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주식회사 메이킷올의 첫번째 코딩 교육 솔루션 직관적코딩은 아두이노 실드와 블록코딩 어플을 통해 직관적이고 다양한 컨텐츠를 제공하여 코딩의 진입 장벽을 낮춰 쉽고 재미있는 경험을 선사합니다.

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회원 가입이 필요

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네이버 블로그 | 코딩은 메이크MAKE: 스마트폰 메이커 코딩 솔루션

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안녕하세요,

#프로그래밍 #코딩교육 #창의교육 #코딩수업

이제 어플 하나로 걱정 끝!

스마트폰 메이커 코딩 솔루션 메이크MAKE 입니다.

​

​

블로그로는 오랜만에 인사드려요 :)

14일 직관적코딩 챌린지 소식을 알려드리고자 합니다!

' #직관적코딩 ' 과 ' #메이크 ' 어플이 함께하는

14일 #직코 챌린지 를 소개합니다!

직관적이고 다양한 아두이노 콘텐츠를 배울수 있는

14일간 매일 직코에서 제공하는 미션을 수행 학습하고

단기간동안 메이커에 도전하는 프로젝트입니다.

​

■ 참가 신청서 : https://forms.gle/4YJZrd7Q9RVoUJ2K9

■ 참가비 : 0원

- 참가 신청 기간 : 2020년 7월 15일 수요일 ~ 2020년 7월 29일 수요일 (14일간)

- 챌린지 기간 : 2020년 8월 3일 월요일 ~ 2020년 8월 16일 일요일 (14일간 매일 진행)

- 챌린지 정원 : 50명 (선착순 마감)

- 대상 : 코딩에 관심이 있으신 분 (학생, 부모님, 입문자 상관 없이 모두 가능!!)

(참가신청자에 한해 별도 구매링크를 발송합니다!)

​

직코 카카오톡 채널 로 연락 후

변경된 '직코 보드'와 '스피커', '외관' 구매 시 참여 가능합니다.

(추가 비용 25,000원)

■ 문의 사항 : https://pf.kakao.com/_MyvvT

■ 직코 챌린지 네이버 카페 링크 https://cafe.naver.com/makeitall

​

문의 사항은 '직코' 쪽으로 부탁드릴게요~!

​

자세한 설명은 아래 이미지를 참고해주세요!

* 메이크랩 콘텐츠 구매, 출강, 사용법 등

각종 문의 는 '메이크랩' 플러스친구 에서 부탁드릴게요.

(그 외 채널에서는 응답이 늦거나 힘들 수 있음을 알려드립니다)

​

​ 메이크 더 알아보기(홈페이지) ▶

★ ​ 카카오톡 (단체구매 등 각종 문의) ★

​

메이크(MAKE)어플

▶ ◀️

▶ ◀️

​

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[직관적코딩x메이크MAKE] 메이킷올의 14일 직코 챌린지(메이커 코딩 챌린지)

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안녕하세요, #프로그래밍 #코딩교육 #창의교육 #코딩수업 이제 어플 하나로 걱정 끝! 스마트폰 메이커 코딩 솔루션 메이크MAKE 입니다. ​ ​ 블로그로는 오랜만에 인사드려요 :) 14일 직관적코딩 챌린지 소식을 알려드리고자 합니다! ' #직관적코딩 ' 과 ' #메이크 ' 어플이 함께하는 14일 #직코 챌린지 를 소개합니다!

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Open-source electronic prototyping platform enabling users to create interactive electronic objects.

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마이크로비트(micro:bit)는 영국 BBC에서 출시한 프로그래밍이 가능한 작은 교육용 보드로, 전 세계적으로 코딩 교육에 이용되고 있습니다. 내 손 안의 작은 컴퓨터, 마이크로비트로 코딩을 쉽게 배우고 재미있게 가르칠 수 있습니다.

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웹 디자인 사이트(팅커캐드)

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웹 디자인 사이트(팅커캐드)

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Thingiverse - Digital Designs for Physical Objects

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Download files and build them with your 3D printer, laser cutter, or CNC. Thingiverse is a universe of things.

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유니맷 공작기계 한국 총판

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남성의류/정장/빅사이즈

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분유/기저귀/식품/생리대/임부복

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인터넷쇼핑,오픈마켓,패션/뷰티,디지털,식품/유아,스포츠/자동차,생활용품,도서/DVD,여행/항공권,e쿠폰/티켓,만화/게임,공동구매,경매,중고,글로벌쇼핑,브랜드샵,베스트셀러,방문쇼핑몰,G스탬프,할인쿠폰,동영상,이벤트 등 G마켓

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3D프린터 제조사(큐비콘)

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3D프린터 제조사(큐비콘)

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3D프린터 제조사(신도)

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3D프린터 제조사(신도)

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Copyright © 2012~2021 Sindoh Co., Ltd. All rights reserved.

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Fritzing is devoted to making creative use of electronics accessible to everyone.

The source code of Fritzing is available on our GitHub repository. Everyone is welcome to participate in the development.

We are asking you to pay 8€ (around US$10) for downloading the application. This way we can ensure future releases, bugfixes and features.

Version was released on July 21, 2021.

Read the installation instructions below. If you have any problems with the installation, do not hesitate to contact us via the contact form.

See what's new and the known issues.

This version includes translations for:
Deutsch (German), English, Español (Spanish), Français (French), Italiano (Italian), Nederlands (Dutch), Português (eu) (Portuguese EU), Português (br) (Portuguese BR), 日本語 (Japanese), 中文 (简体) (Chinese Simplified), 正體中文 (繁體) (Chinese Traditional), Русский (Russian), Čeština (Czech), 한국어 (Korean), Ελληνικά (Greek), slovenčina (Slovak), română (Romanian), Türkçe (Turkish), Български (Bulgarian), বাংলা (Bengali).

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Fritzing is devoted to making creative use of electronics accessible to everyone. The source code of Fritzing is available on our GitHub repository. Everyone is welcome to participate in the development. We are asking you to pay 8€ (around US$10) for downloading the application. This way we can ensure future releases, bugfixes and features.

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DIY 메카솔루션 오픈랩 : 네이버 블로그

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코딩 관련 종합물(메카솔루션)

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코딩 관련 종합물(메카솔루션)

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메카솔루션 공식 쇼핑몰

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국내 최대 전자부품 쇼핑몰, 아두이노 키트, 라즈베리파이 등 당일발송, 예제 제공, 쇼핑 그 이상을 제공합니다.

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덕유항공 3D프린터 : 네이버쇼핑 스마트스토어

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Creality CR-10S 3D프린터 대한민국 최초 공식수입사/AS제공

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이들은 식사를 하는 사람에게서 얻은 생물학적 정보를 기반으로 개인 맞춤식으로 완벽하게 영양가 있는 스시를 제공하려고 합니다.

이 식당은 손님이 Sushi Singularity 에 예약을 할 때, 손님에게 건강 체크 키트(Health Test Kit)가 보내질 것으로 보입니다. 이 키트는 타액, 소변 또는 대변을 포함 할 수있는 생물학적 샘플을 수집할 것입니다. 이렇게 수집한 생물학적 자료를 기반으로, 특정 고객에게 부족한 영양소가 들어있는 초밥을 3D프린터로 출력하고, 로봇팔도 이용할 것입니다.

3D프린터로 제작하는 것이니 만큼, 다양한 디자인의 스시도 만들어낼 수 있을 것입니다.

이 회사는 기술적인 혁신에 대해서 3가지를 얘기합니다.

첫번째로 말하는 것은 FFM, Food Fabrication Machine 입니다.

다양한 목적의 FDM방식의 3D프린터들, SLS 3D프린터, 로봇팔, 6축 CNC 장비, 음식재료 카트리지, 영양소 실리더 등 여러 첨단 기술로 이루어진 "미래의 주방"이라 불리는 커다란 장비입니다.

두번째로, FOS, Food Operation System

세계 최초의 디지털로 음식을 디자인하는 Operation System 이라고 합니다. 재밌네요^^ 음식디자인 데이터는 .cude 포맷으로 저장한다고 하네요.

여기에는 SFNS (Social "Food" Network Service) 라는 것도 있는데, 사회 음식 네트워크 서비스라고나 할까요?

전세계 사람들과 음식을 공유하기 위한 디지털 플랫폼이라고 합니다. 음식 데이터를 다운로드 받아서, 3D프린터로 출력한다는 것입니다.

마지막으로, HID, Health Identification

DNA, 소변, 내장 검사 등을 통해서, 사람들은 각각 자신만의 건강 ID(Health IDs)를 가진다는 겁니다. 이 정보를 기반으로 개인맞춤형 음식 등을 알 수 있겠죠.

여러분의 다양한 생체정보(소변, 대변 등)를 이 식당에 제공하고, 나에게 부족한 영양소로 가득찬 예쁜 스시를 드시겠습니까?

내년에 개장한다고 하니 관심있는 분들은 가보시는 것도 좋겠네요^^

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3D프린터로 출력한 개인맞춤형 스시(Sushi), 드셔보시겠어요?

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이들은 식사를 하는 사람에게서 얻은 생물학적 정보를 기반으로 개인 맞춤식으로 완벽하게 영양가 있는 스시를 제공하려고 합니다. 이 식당은 손님이 Sushi Singularity 에 예약을 할 때, 손님에게 건강 체크 키트(Health Test Kit)가 보내질 것으로 보입니다. 이 키트는 타액, 소변 또는 대변을 포함 할 수있는 생물학적 샘플을 수집할 것입니다.

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아이디어를 실현시키는 창조의 공간, 메이커스원에서 당신의 아이디어를 펼쳐보세요.

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IT/가젯/IT월드

사진의 2D 객체를 3D객체로 변환해주는 놀라운 기술

썬도그 2014. 8. 7. 11:03

포토샵은 사진을 수정 또는 보정하는 이미지 변형 프로그램의 대명사입니다. 이 포토샵은 사진을 길게 또는 짧게 하거나 다양한 객체를 합성할 수 있지만 2D의 사진을 이용하기 때문에 피사체를 변형할 수는 있지만 안 보이는 뒷면을 보이게 할 수는 없습니다. 뒷면을 변형 시키리면 뒷면 사진이 있어야죠

그러나 2D 사진을 가지고 3D 객체로 변환 시켜서 사진에 담기지 않는 뒷면이나 밑면까지 볼 수 있게 하는 놀라운 기술이 나왔습니다.
사진의 2D 객체를 3D객체로 변환해주는 놀라운 기술

기술 이름은 참으로 깁니다.3D Object Manipulation in a single Photograph using Stock 3D Models
이름은 길지만 2D 객체를 3D로 변환해주는 프로그램이라서 개념은 어렵지 않습니다.

위 이미지는 사진입니다. 바닥에 빨간 의자가 쓰러져있죠. 이 사진만 가지고 저 의자를 자유자재로 움직일 수 있습니다.

2D 사진에서는 볼 수 없는 의자의 뒷면까지 담을 수 있습니다.

위 의자 같은 경우는 2D 사진에 3D 모델링을 입힌 결과인데 3D 모델링 데이터만 있으면 쉽게 2D를 3D로 변환시킬 수 있습니다. 위 의자는 이케아 제품인데 이케아 홈 플래너라는 프로그램은 집안을 3D로 미리 꾸며볼 수 있는 공개 프로그램입니다. 이걸 이용해서 3D데이터를 입혀서 위와 같이 안 보이는 의자의 밑면을 묘사할 수 있습니다.

오리지럴 2D 사진 이미지와 3D 데이터 그리고 광원을 결합하면 위와 같이 아주 매끄러운 3D 데이터를 만들어내고 이렇게 만들어낸 3D개체를 가지고 자유자재로 가지고 놀 수 있습니다.

2D 바나나가 있습니다. 그런데 이 바나나를 가지고 있는 3D 데이터와 결합 시킵니다.

그러면 위와 같이 바나나를 자유롭데 돌릴 수 있습니다. 바나나 사진에 없던 뒷면까지 볼 수 있죠.
2D 객체 + 3D 모델링 데이터 + 광원 = 3D 객체

애플 노트북 사진만 가지고 노트북을 덮거나 뒷면을 볼 수 도 있습니다

이 한 장의 사진을 가지고

택시를 들어 올릴 수도 있고

들어 올릴 수도 있습니다

종이와 펜 사진을 가지고

종이에 글씨를 쓰는 펜으로 바꿀 수도 있습니다

사실, 이런 기술은 이미 허리우드에서 애용하고 있습니다. 먼저 도시에 있는 자동차와 엑스트라를 모두 스캔한 후에 그걸 하나의 객체로 만들어서 대규모 군중씬과 대규모 자동차 폭파씬을 촬영하죠. 그렇게 만들어진 영화가 어벤져스와 최근의 허리우드 영화입니다. 다만 기존에는 3D 객체를 여러각도로 스캔한 후에 알맞게 다듬어서 넣었는데 이 기술은 사진만 가지고 3D로 만들 수 있다는 것이 놀랍네요.

3D 모델링 데이터 뱅크만 있으면 기존의 사진을 3D로 쉽게 객체화 시켜서 수많은 영상물 특수 효과에 사용할 수 있을 듯 합니다. 좀 더 자세한 내용은 PDF파일로 공개되어 있습니다

http://www.cs.cmu.edu/~om3d/papers/SIGGRAPH2014.pdf

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사진의 2D 객체를 3D객체로 변환해주는 놀라운 기술

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IT/가젯/IT월드 썬도그 2014. 8. 7. 11:03 포토샵은 사진을 수정 또는 보정하는 이미지 변형 프로그램의 대명사입니다. 이 포토샵은 사진을 길게 또는 짧게 하거나 다양한 객체를 합성할 수 있지만 2D의 사진을 이용하기 때문에 피사체를 변형할 수는 있지만 안 보이는 뒷면을 보이게 할 수는 없습니다.

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ks0001A Keyestudio REV3 (Black) Main Control Board

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나도메이커(마이크로비트)

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나도메이커(마이크로비트)

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No.1 전자엔지니어 전문몰 아이씨뱅큐 : 네이버 블로그

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No.1 전자엔지니어 전문몰 아이씨뱅큐 : 네이버 블로그

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♡전자 엔지니어와 메이커 DIY 매니아를 위한 다양한 정보 상시 업데이트!♡ - 마이크로비트/아두이노/라즈베리파이/라떼판다/젯슨나노 등 다양한 오픈소스 하드웨어 정보 가득! - 유튜브 '나도메이커' 채널 , 오픈카톡방, 마이크로비트 사용자 모임 카페/DIY나도메이커카페 운영

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SW코딩에서 인공지능까지 상상을 현실화하는 미래교육공작소 코코아팹입니다. SW코딩, AI, 메이커, STEAM, 사물인터넷, 로보틱스 등

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GPT, AI, ChatGPT, 메타버스 및 AI 융합 콘텐츠 만들기, 오큘러스퀘스트2, 4차산업 진로체험 (VR, AI, 드론, 자율주행, 디지털교과서)

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초보자도 쉽고 간단하게 AI GPT 및 메타버스 콘텐츠를 만들 수 있는 SW 입니다. AI가 통합된 VR 메타버스 SW를 통해 GPT를 비롯한 다양한 AI 융합 및 VR 콘텐츠를 직접 제작하고 실행해 볼 수 있습니다. 4차산업 진로체험 수업 및 과학수업, AI 수업에 활용 가능합니다.

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코딩교육 전문 쇼핑몰 에듀이노, 아두이노, 보드, 쉴드, 센서, 모듈, 키트, 로봇, 드론, 교구, 전자부품 등 판매

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상상대장간 : 네이버 블로그

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안녕하세요~ 아이디어, 개발, 신상품과 관련된 다양한 이야기를 만들어내는 상상대장간입니다.

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에듀이노 오픈랩 : 네이버 블로그

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코딩 전문 교육쇼핑몰 에듀이노 보드, 쉴드, 모듈, 키트, 로봇, 전자부품 등 판매

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종합 코딩 교육 플랫폼

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슈퍼트랙이 만든 상상력을 키우는 코딩 교육 플랫폼, 선생님과 학생이 1:1 소통하는 실습형 코딩 교육, 언제 어디서나 STEAM & 메이커 교육

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Requests from FAB365.net have received numerous requests from customers. Among them, there are the most requests for Star Wars items, and this time we created ATAT, which received the most requests. ATAT stands for All Terrain Armored Transport and first appeared in the Star Wars .

The characteristics of ATAT designed this time are first of all,
1) Almost every detail is described. It has described more detail than any ATAT produced by 3D printing so far.
2) Using the print-in-place and folding structure, almost all movements were implemented with just a few printings.

How to make after printing is as follows.
1. Rotate and attach the neck to the connected lower body.
※ Caution※ If the neck is not attached to the lower body first, the upper body cannot be properly connected later.
2. Put the upper body on the lower body. At this time, use the elasticity to slightly open and fit. Then, attach the side parts to the upper body with adhesive.
3. Push the head and put it on the neck.
4. Fold the ankle and attach it to the leg with adhesive.
5. Push the foot and put it on the leg.
6. Glue the 4 legs prepared in this way to the body.

Since the legs and neck can move in multiple angles, it is possible to create a scene in the movie.

1 : 144 scale

Size, X 70mm, Y 191mm, Z 157mm

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Requests from FAB365.net have received numerous requests from customers. Among them, there are the most requests for Star Wars items, and this time we created ATAT, which received the most requests. ATAT stands for All Terrain Armored Transport and first appeared in the Star Wars .

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3D 모델링에 구멍이 뚫린 예술 작품 보로노이 타입 만들기 + 큐라 cura 꿀팁

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보르노이타잎 변환 사이트

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보르노이타잎 변환 사이트

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Have you ever tried to create a Voronoi effect with your 3D models and become exasperated with this tedious process?
To solve this problem we created this free online Voronoizator. Just upload your model, wait a minute and download your tesselated model.

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Have you ever tried to create a Voronoi effect with your 3D models and become exasperated with this tedious process? To solve this problem we created this free online Voronoizator. Just upload your model, wait a minute and download your tesselated model.

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IT도전자에게 추천하는 도

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IT도전자에게 추천하는 도

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64.(책추천 종합) 개발자가 되기 위한 봐야하는 책

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게임과 그래픽 개발자 , 모바일 앱 개발자 ,프런트엔드 개발자 (웹 개발자) ,백엔드 개발자 ,서버운영과 DevOps 엔지니어가 되기위한 기술과 추천 서적 (요약) 개발자가 되기 위한 봐야하는 책 IT공부 시작으로 좋은 사이트 (요약) 개발자가 되기 위한 봐야하는 책 90.HTML시작으로 좋은책 https://brunch.c

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https://www.playsw.or.kr/artificial/textbook

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인공지능&데이터 : 소프트웨어야 놀자

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AI와 DATA의 개념을 영상으로 경험해보세요.

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AI 및 딥러닝은 다양한 산업 부문에 적용되고 있습니다. 이러한 프로젝트 중 일부는 AI를 통해 생산성을 개선했지만, 실패한 프로젝트도 있습니다. 이와 같은 차이점은 어디에서 비롯되는 것일까요?

AI의 강점 및 약점을 파악한 후 주제를 명확히 설정하고, 이를 기존 작업 프로세스에 구현하는 것이 필수적입니다.

본 eBook에서는 MATLAB ® 을 이용한 딥러닝을 통해 비즈니스에 AI를 성공적으로 구현한 다음 8개 산업의 10가지 고객의 성공 사례를 소개하고, 그러한 딥러닝 프로젝트에 사용된 핵심 기술에 관해 설명합니다.

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AI・딥러닝 8개 산업 부문의 10가지 성공 사례

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AI 및 딥러닝은 다양한 산업 부문에 적용되고 있습니다. 이러한 프로젝트 중 일부는 AI를 통해 생산성을 개선했지만, 실패한 프로젝트도 있습니다. 이와 같은 차이점은 어디에서 비롯되는 것일까요? 본 eBook에서는 MATLAB을 이용한 딥러닝을 통해 비즈니스에 AI를 성공적으로 구현한 고객의 성공 사례를 소개하고, 그러한 딥러닝 프로젝트에 사용된 핵심 기술에 관해 설명합니다.

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수채화 번지기 기법으로 물빛정원만들

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수채화 번지기 기법으로 물빛정원만들

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네이버 블로그 | 따뜻함을 글에 담는 사람

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수채화 번지기를 이용한 물빛정원 만들기

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안녕하세요 열정지니쌤 입니다 :) ​아이들과 수채화 활동의 첫시간은 용구 사용법을 익히고 수채화 번지기...

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안녕하세요
’GEG광주 + 에듀데이 = 광듀데이’가 이번주 토요일 저녁 8시에 열립니다.
시청하실 수 있는 URL 발송드립니다^^
많은 참여 바랍니다!!
# 시청URL:  https://youtu.be/f7i73pJllFU

# 구글이랑~KKE
# 2021년 3월 13일(토) 저녁8시
홍보영상: https://youtu.be/h2boIeXdvqI

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알파고의 1패에 대한 분석

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알파고의 1패에 대한 분석

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유럽 바둑챔피온을 꺾은 AlphaGo가 세계최강 이세돌 9단과의 대결을 앞두고 있다. 많은 전문가들은 AlphaGo가 프로 바둑기사처럼 바둑을 둔다고 분석했다. 그렇다면 "어떻게 사람처럼 바둑을 두는 것이 가능한가?"에 대한 자연스러운 물음을 하게 된다. AlphaGo가 기존 바둑프로그램의 한계를 뛰어 넘은 핵심을 더 깊게 이해할 필요가 있다.

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요청 받은지는 꽤 되었는데 이제서야 

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요청 받은지는 꽤 되었는데 이제서야 강의를 개설하게 되었네요.
강의는 세 가지 종류가 있습니다.

(1) 크롬북 인공지능

크롬북 가진 사람 모두 모여라!!
크롬북으로 진행하는 인공지능 강의입니다.
엔트리와 스크래치 모두 다룹니다.
대상 로봇은 햄스터, 햄스터S, 거북이, 치즈스틱, 알버트스쿨, UO알버트, 알버트AI 입니다.
햄스터 AI 카메라도 사용합니다.

누구나 신청가능합니다.
4월 12일 월요일 오후 7시 ~ 10시 (3시간)
https://forms.gle/jVRJ8VvAam5LFUsKA

(2) 블록코딩 인공지능

그동안 강의했던 것들을 모두 순서대로 정리해서 아주 순한 맛부터 매운 맛까지 4주 동안 매주 "월요일" 진행하는 강의입니다.
저도 정리가 좀 필요해서 이참에 정리하고 자료도 모두 다듬어서 배포할 예정입니다.

각 주차별 강의 내용은 정리해서 미리 알려드릴 예정입니다.
강의 신청하신 후 모든 강의를 수강하셔도 되고, 관심 있는 주제만 수강하셔도 됩니다.

강의는 햄스터S 로봇으로 진행하지만
햄스터, 거북이, 치즈스틱, 알버트스쿨, UO알버트, 알버트AI 에 대한 설명도 같이 진행합니다.
햄스터 AI 카메라도 필요합니다.

누구나 신청가능합니다.
4월 19일 ~ 5월 10일 매주 월요일 오후 7시~10시
https://forms.gle/sYZpcqrjGLTpdCKq7

(3) 파이썬 인공지능

마찬가지로 그동안 강의했던 것들을 모두 순서대로 정리해서 아주 순한 맛부터 매운 맛까지 4주 동안 매주 "화요일" 진행하는 강의입니다.
저도 정리가 좀 필요해서 이참에 정리하고 자료도 모두 다듬어서 배포할 예정입니다.

각 주차별 강의 내용은 정리해서 미리 알려드릴 예정입니다.
강의 신청하신 후 모든 강의를 수강하셔도 되고, 관심 있는 주제만 수강하셔도 됩니다.

강의는 햄스터S 로봇으로 진행하지만
햄스터, 거북이, 알버트AI 에 대한 설명도 같이 진행합니다.
햄스터 AI 카메라도 필요합니다.

누구나 신청가능합니다.
4월 20일 ~ 5월 11일 매주 화요일 오후 7시~10시
https://forms.gle/jVtBKe93baNaBW1j8

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이 그룹에 예술가들이 많은 것 같아서 이 내용을 올립니다.  GPU기반이 아니라 CPU기반이라 고가의 그래픽 카드가 아닌 일반 노트북으로도 사용이 가능해서 설치 예술이나 interactive 기반이 필요한 분들한테 탁월한 도구가 될 듯 하군요.

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Contribute to ai-coodinator/mediapipe-python development by creating an account on GitHub.

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아두이노로 스트립led조작

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아두이노로 스트립led조작

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모든 전자부품 뱅크! 국내 최대 전자부품 전문 쇼핑몰 - 아이씨뱅큐

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주문 즉시 해외로 발주가 나가는 제품이기 때문에
- 단순 변심 , 혹은 으로 인한 납기 지연 공급처 사정에 따라 납기가 지연될 수 있으나 취소 사유가 되지 않습니다. (제품 자체 불량 제외) 교환이나 반품이 불가합니다.
-

Interactive Installation "Half Naked" made with RGB LED Strip and Driver Shield, i mage courtesy of Lei Ye

A Look into the Interactive Installation "Half Naked", image courtesy of Lei Ye

RGB LED 스트립 실드에는 Arduino와 함께 멋진 RGB (또는 다른 3 채널) LED 프로젝트를 구축하는 데

실드는 펄스 폭 변조 기능을 갖춘 3 개의 출력을 가지고 있습니다.

각각 최대 12V 부하를 3A까지 제어 할 수 있습니다.

쉴드는 IR 리모콘으로 LED 스트립을 제어 할 수있는 IR 수신기가 내장되어 있습니다.

빌트인 퓨즈는 어떠한 이유로 든 과전류 나 부족 현상으로부터 LED 스트립을 보호합니다.

이 차폐막을 사용하면 약 10 미터 길이의 RGB LED 스트립을 Arduino 프로세서로 구동 할 수 있으며,

거의 10Amps (12V) 구동 기능이 필요합니다.

참고 : 12VDC 전원을 RGB 스트립 드라이버 실드의 DC 어댑터에 연결하면

Arduino에 전원을 공급하고 시스템을 퓨즈로 과전류로부터 보호 할 수 있습니다.

Arduino UNO R2 / R3 또는 호환 가능

Arduino 메가 1280/2560

Arduino Uno, Mega, Romeo 등과 호환 가능

12V RGB LED 스트립 (Common Anode)과 호환 가능

작동 전력 권장 : 72W (1 회당 2A)

제한된 운전 능력 : 최대 밝기의 10 미터 RGB LED 스트립

IR 리모컨 지원

RGB LED 스트립 구동 핀 :

D9 -> 청색 출력

D10 -> 적색 출력

D11 -> 녹색 출력

IR 수신기

D4 -> IR 수신기 핀

RGB LED 스트립 드라이버 Sheild x1

입금 계좌 안내

우리은행 1005-801-145943 (예금주 IC뱅큐)

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RGB LED 스트립 드라이버 쉴드 [DFR0274] : 마이크로컨트롤러 > DFRobot > BRAND SHOP > MCU보드/제어모듈

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주문 즉시 해외로 발주가 나가는 제품이기 때문에 - 단순 변심 , 혹은 으로 인한 납기 지연 공급처 사정에 따라 납기가 지연될 수 있으나 취소 사유가 되지 않습니다. (제품 자체 불량 제외) 교환이나 반품이 불가합니다.

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Make a paper octopus that retracts its tentacles.

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3D model community. Search & download free 3D models. Share 3D models

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3D Model Community for 3D model enthusiasts. Use geometric search to find over 1 million free 3D models. Download 3D models & upload models to collaborate.

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국립중앙과학관 3D프린팅 자료실

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국립중앙과학관 3D프린팅 자료실

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괴학관련으로 활용하기 좋을듯

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저작권법 제24조의2(공공저작물의 자유이용)에 따라 e과학기술자료관 홈페이지에서 제공하는 자료는 저작물별로 적용된 이용조건에 따라 저작권 침해의 부담 없이 무료로 자유롭게 이용 가능합니다. OPEN, 출처표시 : 공공누리 공공저작물 자유이용허락 단, 자유이용이 가능한 자료는 "공공저작물 자유이용허락 표시 기준(공공누라, KOGL)"을 부착하여 개방하고 있으므로 공공누리 표시가 부착된 저작물인지를 확인한 이후에 자유럽게 이용하시기 바랍니다.

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직관적코딩(스마트스토어)

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직관적코딩(스마트스토어)

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직관적코딩 : 네이버쇼핑 스마트스토어

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3D 프린터는 2013년 2월 버락 오바마 대통령이 국정 연설에서 제조업의 차세대 기술로 강조하면서 전 세계적으로 관심을 받게 된 기술입니다. 기술이 처음 등장한 지는 30년이 넘었답니다. 3D 프린터가 무엇이길래 제조업의 차세대 기술이라고 극찬하는 것일까요?

이제까지 제조 산업에서는 물건을 만들 때 주로 깎아서 만들어 왔습니다. 제조 회사의 공장에 들어가 보시면 온통 깎아내는 기계 밖에는 없답니다. 물건을 돌리면서 깎고, 공구를 돌리면서 깎고, 물건도 돌리고 공구도 돌리면서 깎지요. 정밀하게 만들려면 깎는 수밖에는 없었어요. 그리고, 하나의 큰 덩어리를 처음부터 깎으면 시간이 너무너무 오래 걸리고 버리는 재료도 너무 많기 때문에, 얼추 비슷한 모양의 틀로 주조하거나 눌러 찍어서 기본 모양을 만든 후, 마지막으로 원하는 모양으로 정밀하게 깎아내는 작업을 하는 것이 일반적인 방식입니다. 그런데, 3D 프린터는 깎는 것이 아니라 한 층 한 층 쌓아 올리는 적층 방식이라는 것이 가장 큰 차이입니다. 쉽게 생각하시면 A4지에 프린트를 하는 것을 한 층이라고 생각하고, 한 장씩 높이를 높여가며 프린트하여 높이 방향으로도 쌓아가는 방식입니다.

이 시점에서 의문이 생기실 겁니다. 깎는 것과 쌓아 올리는 것이 어떤 차이가 있다는 건지 말입니다. 현재 깎는 방식으로 물건을 만드는 공정은 '1. 틀 만들기, 2. 틀로 원하는 모양의 소재 만들기, 3. 깎기(정밀 가공)' 순입니다. 그런데 쌓아 올리는 방식의 공정은 '1. 3D 프린팅'이면 끝입니다. 감이 오시지요? 새로운 제품을 만들 경우에는 3D 프린팅 방식은 틀을 만들 필요가 없으니 초단기간에 제작이 가능합니다. 장비도 3D 프린터만 있으면 되지요. 또 한 가지 장점은 틀을 만들어 주조하거나 찍어낸 후 깎는 방식에서는 불가능한 형상을 적층 방식에서는 제작이 가능하다는 것입니다. 예를 들어 공 안에 공이 들어 있는 물건을 만들고 싶다고 가정해 보죠. 기존의 방식으로는 내부의 공은 한 덩어리로 만들 수 있지만, 외부의 공은 반으로 나누어 만들고 내부 공을 안에 넣고 외부의 반쪽 짜리 공 두 개를 붙여야 합니다. 하지만, 3D 프린팅은 내부의 공이나 외부의 공이나 모두 반으로 나누지 않고도 공 안에 공이 든 형상으로 한 번에 만들 수 있다는 것입니다. 즉, 어떤 형상이든 한 번에 제작이 가능하다는 거예요. 이 정도면 3D 프린터의 장점을 아시겠지요?

그런데 아직도 제조 회사들이 3D 프린터를 적극적으로 도입하지는 않고 있습니다. 아직 해결하지 못한 문제점이 있다는 이야기이지요. 크게 세 가지 문제가 있습니다. 하나는 3D 프린팅을 하는 시간이 너무 오래 걸린다는 것이고, 두 번째는 프린터에서 사용하는 재료의 비용이 너무 비싸다는 것입니다. 사실 비싸도 너무 비쌉니다. 세 번째는 프린팅 할 수 있는 소재의 종류가 제한적이라는 것이죠. 세 가지 문제를 해결하기 위해서 많은 사람들이 열심히 기술 개발을 하고 있어요. 프린팅 속도가 빨라지고, 재료 가격이 낮아지고, 소재가 다양해지면 제조업이 바뀔 것이라는 것은 확실합니다. 단지 언제쯤이면 기존 깎는 방식 대비 시간적, 비용적 경쟁력을 확보하게 될 것인가가 관건이지요.

그렇다면 3D 프린터 기술은 제조 회사만 관련이 있는 것이고 소비자의 입장에서는 변화가 없는 걸까요? 그것은 아닙니다. 소비자 입장에서도 큰 변화가 있을 거예요. 지금은 집집마다 프린터가 있지요. 원하면 언제든지 인쇄물을 만들 수 있어요. 책도 만들 수 있고요. 이처럼 3D 프린터도 미래에는 집집마다 보유할 수 있어요. 즉, 원하는 물건을 바로바로 개인이 직접 프린트해서 만들 수 있다는 것이지요. 품질은 조금 떨어지겠지만요. 또한, 품질이 좋은 제품을 위해 주문 제작을 한다고 해도 내가 원하는 나만의 제품을 주문 제작할 수 있게 됩니다. 지금은 같은 모양의 제품을 대량 생산만 하지만, 3D 프린터가 보편화된다면 다품종 소량 생산도 가능해지기 때문입니다.

현재는 플라스틱 3D 프린터가 가장 보편적이지만, 석고, 금속, 모래, 고무, 심지어는 나무까지도 프린팅 하는 기술이 개발되었답니다. 이제 원하는 가구도 프린팅으로 제작할 수 있다는 이야기입니다. 3D 프린터 자체의 기술 발전은 생각보다 매우 빠르게 진행되고 있습니다. 3D 프린팅 시대가 머지않았습니다. 다양한 소재 개발이 지속적으로 이어질 것으로 보입니다. 음식 프린팅은 이미 많은 분들이 이야기를 들으셨을 겁니다. 예쁜 케이크를 3D 프린터에서 즉석으로 뽑는 날도 오겠지요. 최근에는 생체공학 분야에서도 3D 프린팅을 사용하여 인공 피부, 관절, 뼈, 장기 등을 만드는 데에도 활용하고 있답니다.

3D 프린팅 방식도 다양한 기술들이 개발되어 발전해 가고 있습니다. 재료를 압출하여 노즐을 통해 쌓아 올리는 재료 압출(ME, Material Extrusion) 방식을 포함하여, 광경화성 재료에 레이저를 조사하여 경화시키는 광경화(PP, Photo Polymerization) 방식, 분말 소재를 한층씩 적층하고 형상 부위에 레이저를 조사하여 용융 소결시키는 분말 용융 소결(PBF, Powder Bed Fusion) 방식, 분말 소재를 한층씩 적층하고 형상 부위에 접착제를 잉크젯 프린터와 같이 분사하여 경화시키는 바인더 젯팅(Binder Jetting) 방식 등 많은 기술들이 상용화되어 있습니다. 특히, 그 동안 가장 큰 장애물로 여겨졌던 3D 프린팅 출력물의 정밀도나 소재의 한계 등이 어느정도 해결이 되어가면서, 최근에는 3D 프린터의 출력 속도 및 양산성 확보가 확산 적용을 위해 중요한 요소로 부각되면서, 이를 가장 잘 해결할 수 있는 바인더 젯팅 방식 기술이 빠르게 떠오르고 있습니다.

3D 프린팅 기술의 발전에 따라 적용 분야도 자동차, 기계, 조선, 철도, 방산, 항공우주 등의 제조 산업에서 건축, 문화예술, 조형물, 바이오, 문화재 등 다양한 분야로 빠르게 확대되고 있습니다. 실제로 2020년에는 3D 프린팅 기술이 적용된 비정형 커튼월이 백화점 시공에 적용되었고, 최초로 3D 프린팅 에센스 화장품이 발표되기도 하였습니다.

마지막으로 3D 프린팅 기술도 우려의 목소리가 있습니다. 2013년 미국에서 한 업체가 총기를 3D 프린팅 할 수 있는 3D 도면 파일을 인터넷에 올렸고 순식간에 10만 명 이상이 다운로드를 받는 사건이 있었습니다. 개인이 도면만 있으면 무엇이든지 만들 수 있는 세상이 되기 때문에, 나쁜 의도를 갖는 사람이 이 기술을 이용하면 문제가 커질 수 있다는 것입니다. 하지만, 이것도 3D 프린팅 기술이 무슨 죄가 있나요. 다 사람이 문제지요. 이러한 이슈는 새로운 기술이 등장할 때마다 늘 발생하는 문제입니다. 원자력 기술이 발전소로 인류에 큰 이로움을 주고 있지만, 동시에 핵 미사일로 인류를 공포에 떨게 만든 것도 같은 맥락으로 보시면 됩니다.

#와해성기술 #3D프린터 #3D프린팅 #적층제조

(참고로, 본 글은 제가 이전에 작성했던 ' 미래를 바꿀 요즘 뜨는 기술(1)'의 '3D 프린터' 내용을 업데이트한 글입니다.)

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3D 프린터는 2013년 2월 버락 오바마 대통령이 국정 연설에서 제조업의 차세대 기술로 강조하면서 전 세계적으로 관심을 받게 된 기술입니다. 기술이 처음 등장한 지는 30년이 넘었답니다. 3D 프린터가 무엇이길래 제조업의 차세대 기술이라고 극찬하는 것일까요? 이제까지 제조 산업에서는 물건을 만들 때 주로 깎아서 만들어 왔습니다. 제조 회사의 공장에 들

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종이 3D  모형 만들기

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종이 3D  모형 만들기

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김정식 허명성의 과학사랑

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연역적 탐구 방법으로 접근해 봐도 좋다. 이 실험을 실패한 실험이다. 무엇이 잘 못 되었는지 첫번째 실험에서 오류를 찾아 보자. 만약 내 설명에 수긍한다면 여러분도 뭔가 중요한 것을 놓치고 있는 것이다.

물이 든 컵 입구를 두꺼운 종이로 막고 뒤집어 놓아도 대기압 때문에 물이 쏟아지지 않는다 .

한때는 컵 안에 공기가 들어가지 않게 물을 가득채워야 한다고 생각했다 . 그래서 컵을 뒤집으면 컵 안쪽은 진공이 되고 , 그럼 토리첼리 실험에서 대기압은 물을 약 10m 높이 까지 밀어올리니까 물이 쏟아지지 않는 것이라고 생각했다 .

그런데 컵속에 물을 절반만 채우고 실험을 해도 물이 쏟아지지 않는다 .

그래서 좀 더 깊이 생각해 보기로 했다 . 우선 동영상 실험을 먼저 보자.

물이 든 컵을 뒤집었을 때 아래로 내려오려는 힘들을 모두 찾아 보자 .

③ 컵 표면에 붙여 놓은 종이의 무게에 의해 생긴 힘

그렇다면 위로 밀어올리는 힘이 아래로 내려오 려는 힘보다 커야지 물이 쏟아지지 않을 것이다 .

위로 밀어올리는 힘들을 모두 찾아보면

이때 컵속의 물이 쏟아지지 않으려면 최소한

그리고 표면장력이 생각보다 강하다는 것을 다른 실험을 통해 알 수 있다 .

그렇다면 대기압 보다는 표면장력 때문이라고 해야 하지 않을까 ?

어떠경우에 실험이 실패하고 물이 쏟아지게 될까 ?

촬영한 동영상에서는 종이 대신 스타이로폼 접시를 사용했더니 가벼워서 그런지 너무 실험이 잘된다 . 일부러 막 흔들어도 잘 쏟아지지 않는다 .

만약 높이가 높은 컵을 이용해서 물을 높게 넣어서 표면장력보다 크게 만든다면 절대 이 실험을 성공시킬 수 없을 것이다 .

간단한 호기심에서 시작했지만 재미있는 실험들을 해 볼 수 있었다 .

실험을 하는 동안 컵속의 압력변화가 얼마나 일어나는지 측정해 보았다 .

컵속의 압력변화는 스마트폰 기압계를 이용해서 측정해 볼 수 있었다 . 컵을 뒤집어 놓으면 컵속 공기의 압력은 아주 조금 작아진다 . 아마 컵 입구를 막고 있는 스타이로폼 접시가 아래로 약간 밀려 내려 오면서 컵속 부피가 커져 공기의 압력이 조금 작아진 것으로 보인다 . 접시는 표면장력 때문에 떨어지지 않고 붙어 있다 . ( 주사기 피스톤을 살짝 잡아 당기는 것처럼 생각하면 된다 .)

하지만 아주 작은 변화이기 때문에 실험에는 거의 영향을 미치지 않을 것으로 보인다 .

결국 표면장력에 의한 힘이 실험의 성공을 결정하는 것으로 보인다 .

그런데 한가지 표면장력으로 설명할 수 없는 문제가 생겼다 .

대기압 차이가 거의 영향을 미치지 않는다면 , 컵에 구멍을 열어도 표면장력이 잡아 주고 있으니까 물은 안 쏟아져야 할텐데 ...

그렇다면 결국 기압의 차이가 결정적인 영향을 미치는 걸까 ?

이 실험에서 몇가지 문제점과 , 내가 추가 실험을 통해서 내린 이 실험의 해답은 두 번째 실험을 통해 확인해 보도록 하겠다 .

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컵을 뒤집어도 쏟아지지 않는 물(대기압) - 첫번째 실험

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연역적 탐구 방법으로 접근해 봐도 좋다. 이 실험을 실패한 실험이다. 무엇이 잘 못 되었는지 첫번째 실험에서 오류를 찾아 보자. 만약 내 설명에 수긍한다면 여러분도 뭔가 중요한 것을 놓치고 있는 것이다. 물이 든 컵 입구를 두꺼운 종이로 막고 뒤집어 놓아도 대기압 때문에 물이 쏟아지지 않는다 .

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학교에도 있어요
사용하세요
위의 디자인 프로그램과 함께!

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실루엣 공식 한국 총판 코스테크, 실루엣코리아의 공식 홈페이지입니다.

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3D 융합산업 10년의 기록

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3D 융합산업 10년의 기록

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3D융합산업10년의기록

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3D융합산업10년의기록

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3D펜으로 갓과 활 만들기

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3D펜으로 갓과 활 만들기

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3D펜으로 조선시대 갓 만들기 (feat.넷플릭스 킹덤)

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45도 (기)술 인가?! 신비한 3D 프린터 무한 세계로~ Cr 30 인트로

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갓쌤TV - AI미래교육연구회

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3D프린터가 희귀암을 일으킨다고? | 3D프린터 안전하게 사용하는 방법

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[수업 꿀팁] 컴퓨터 PC 화면에서 메이크 모바일어플 연동하는 3가지 방법(블루스택, 미러링, 미러로이드)

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안드로이드 앱을 pc에서...

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안드로이드 앱을 pc에서...

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네이버 블로그 | 코딩은 메이크MAKE: 스마트폰 메이커 코딩 솔루션

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[수업 꿀팁] 컴퓨터 PC 화면에서 메이크 모바일어플 연동하는 3가지 방법(블루스택, 미러링, 미러로이드)

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안녕하세요, 초.간.단 아두이노 메이커코딩 어플, 메이크입니다. 아직 PC버전이 없는 메이크 앱을 많은 ...

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https://zdnet.co.kr/view/?no=20200923134208

비전문가가 노코드 도구로 만든 앱 속속 등장

프로그래밍 교육을 별도로 받지 않은 사람이 노코드(no code) 도구로 직접 앱을 만들어 서비스하는 사례가 속속 등장하고 있다.23일 관련 업계에 따르면 교육, 미용, 건...

zdnet.co.kr

(추가)

추가로, 코딩없이 웹이나 앱을 만들 수 있는 서비스를 제공하는 곳이 많습니다.

이와 관련된 링크는 하기와 같습니다.

=> open-support.tistory.com/entry/%EB%A1%9C%EC%BD%94%EB%93%9C-or-%EB%85%B8%EC%BD%94%EB%93%9C-%EA%B0%9C%EB%B0%9C%EC%9D%84-%EC%9C%84%ED%95%9C-%EB%B9%8C%EB%8D%94-10%EC%84%A0

위의 링크에서 일부를 가져오면,

"""

무료로 사용해볼 수 있는 것은 "모바일 크롬 키트"와 "앱셀러레이트" , "앱아키텍트"입니다.

모바일 크롬 키트의 특징은,

=>아파치 코르도바(Apache Cordova)에 기반한 개발자 프리뷰(Developer Preview) 툴 체인으로, iOS, 안드로이드, 크롬 앱에 대한 하이브리드 앱 전략을 취하고 있다. 사용자 인터페이스는 안드로이드와 iOS 네이티브 툴킷이 통합된 CSS과 표준 HTML이다. 모바일 크롬 개발 키트는 엄밀히 말해, '노코드'(no-code) 툴은 아니지만, 비주얼 HTML 페이지 디자이너 누구나 쉽게 사용할 수 있다. 모바일 코드를 추가해야 할 경우에는 플랫폼에 따라 바뀌는 네이티브 코드를 사용할 필요 없이, 자바스크립트에서 앱을 보완하는 크롬 API와 코르도바 API를 원하는대로 사용하면 됩니다.

앱셀러레이트의 특징은,

=>IDE, SDK, 다수의 프레임워크, 백 엔드 클라우드 서비스를 모바일 개발을 위한 기업 단위 시스템으로 통합한다. 티타늄 SDK(Titanium SDK)를 이용하면 단일 코드로 네이티브, 하이브리드, 모바일 웹 앱을 모두 개발할 수 있다. 티타늄 스튜디오(Titanium Studio)는 확장성이 뛰어난 이클립스(Eclipse) 기반 IDE이고, 앱셀러레이터 클라우드 서비스(Appcelerator Cloud Services)는 앱에 강력한 네트워크 기능과 데이터 객체 배열 등을 지원한다. 알로이(Alloy) 프레임워크는 MVC 아키텍처에 기반한 티타늄 애플리케이션을 더 빨리 개발하기 위해 만들어진 앱셀러레이터 프레임워크로, 백본.js와 언더스코어.js를 지원한다. 앱셀러레이터는 노코드 솔루션이 아니지만, iOS, 안드로이드, 타이젠, 블랙베리, 모바일 웹 앱용 자바스크립트 툴을 한 번에 제공하는 장점이 있다.

매출 또는 자금이 미화 1,000만달러 미만인 모든 인디 개발자 및 조직 대상은 평생 무료라고 합니다.

국내 한국의 개발자 커뮤니티를 한데 모아볼 수 있는 앱이 있습니다.

'데브모아' 라는 앱인데 하기에서 다운로드 가능합니다.

:=> https://play.google.com/store/apps/details?id=com.opensupport.DevMoa

그럼,

공유합니다.

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비전문가가 노코드 도구로 만든 앱 속속 등장

# data[].attributes.attachment_link.description
https://zdnet.co.kr/view/?no=20200923134208 (추가) 추가로, 코딩없이 웹이나 앱을 만들 수 있는 서비스를 제공하는 곳이 많습니다. 이와 관련된 링크는 하기와 같습니다. => open-support.tistory.com/entry/%EB%A1%9C%EC%BD%94%EB%93%9C-or-%EB%85%B8%EC%BD%94%EB%93%9C-%EA%B0%9C%EB%B0%9C%EC%9D%84-%EC%9C%84%ED%95%9C-%EB%B9%8C%EB%8D%94-10%EC%84%A0 위의 링크에서 일부를 가져오면, """ 무료로 사용해볼 수 있는 것은 "모바일 크롬 키트"와 "앱셀러레이트" , "앱아키텍트"입니다. 모바일 크롬 키트의 특징은, =>아파치 코르도바(Apache Cordova)에 기반한 개발자 프리뷰(Developer Preview) 툴 체인으로, iOS, 안드로이드, 크롬 앱에 대한 하이브리드 앱 전략을 취하고 있다.

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3D 프린터 멀티컬러 DIY 키트 : 이지팜스토어

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이지팜스토어] 3D프린터의 멀티컬러를 연구하고 제품을 개발하는 업체 입니다.

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편의점 도전 / 티머니 반지도 만들어 봤어요 / 티머니네일 / 아크릴 기초 / 에어브러쉬 / T MONEY RING

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강의 동영상
https://www.youtube.com/playlist?list=PL3tES2o5VicLRG3u3_MiwLUVK7Ve8zfse

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엔닷캐드 - 나만의 커스텀 메이킹 툴

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엔닷캐드는 상상하는 것을 누구나 쉽게 만들 수 있는 국산 3D 디자인 소프트웨어입니다.

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앱 코딩 온라인 프로그램 비교

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앱 코딩 온라인 프로그램 비교

# data[].attributes.attachment_link.readable_text
블록코딩으로 안드로이드 앱을 만들 수 있는 EPL로서

앱인벤터 와 썬커블 그리고 코듈라 가 있습니다.

참고로,

썬커블은 iOS앱도 만드는게 가능하다.

그런데 개인적으로

이 세가지 블록코딩 서비스 중에 코듈라가 가장 좋은 것 같습니다.

참고로 이 세가지 비교를 하기와 같이 해봤습니다.

정리해서 비교하면 위 표와 같습니다.

(추가3)

코듈라 관련 강좌 유튜브 영상이 있어 하기와 같이 공유합니다.

:=> https://www.youtube.com/watch?v=B1FEfetue5g&list=PL1G-op7bJz9AKlxnDSQTWIFa0vAM7XYc5

(추가1)

사람들의 일상에서 발견되는 생활의 꿀팁들을 모아 보고 검색할 수 도 있는 앱이있습니다.

'모두의팀' 이라는 앱인데 하기에서 다운로드 가능합니다.

:=> https://play.google.com/store/apps/details?id=com.opensupport.ModuTip

(추가2)

사람들의 일상에서 체득되는 각종 사용 후기들을 모아 보고 검색할 수 있는 앱이 있습니다.

'모두의사용기' 라는 앱인데 하기에서 다운로드 가능합니다.

:=> https://play.google.com/store/apps/details?id=com.opensupport.ModuReview

그럼,

공유합니다.

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앱인벤터 vs 썬커블 vs 코듈라

# data[].attributes.attachment_link.description
블록코딩으로 안드로이드 앱을 만들 수 있는 EPL로서 앱인벤터 와 썬커블 그리고 코듈라 가 있습니다. 참고로, 썬커블은 iOS앱도 만드는게 가능하다. 그런데 개인적으로 이 세가지 블록코딩 서비스 중에 코듈라가 가장 좋은 것 같습니다. 참고로 이 세가지 비교를 하기와 같이 해봤습니다. 정리해서 비교하면 위 표와 같습니다. (추가3) 코듈라 관련 강좌 유튜브 영상이 있어 하기와 같이 공유합니다.

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인공지능(AI) 교육 자료

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Our ten-year plan to make Britain a global AI superpower

Over the next ten years, the impact of AI on businesses across the UK and the wider world will be profound - and UK universities and startups are already leading the world in building the tools for the new economy. New discoveries and methods for harnessing the capacity of machines to learn, aid and assist us in new ways emerge every day from our universities and businesses.

AI gives us new opportunities to grow and transform businesses of all sizes, and capture the benefits of innovation right across the UK. As we build back better from the challenges of the global pandemic, and prepare for new challenges ahead, we are presented with the opportunity to supercharge our already admirable starting position on AI and to make these technologies central to our development as a global science and innovation superpower.

With the help of our thriving AI ecosystem and world leading R&D system, this National AI Strategy will translate the tremendous potential of AI into better growth, prosperity and social benefits for the UK, and to lead the charge in applying AI to the greatest challenges of the 21st Century.

The Rt Hon Kwasi Kwarteng MP
Secretary of State for Business, Energy and Industrial Strategy

This is the age of artificial intelligence. Whether we know it or not, we all interact with AI every day - whether it's in our social media feeds and smart speakers, or on our online banking. AI, and the data that fuels our algorithms, help protect us from fraud and diagnose serious illness. And this technology is evolving every day.

We've got to make sure we keep up with the pace of change. The UK is already a world leader in AI, as the home of trailblazing pioneers like Alan Turing and Ada Lovelace and with our strong history of research excellence. This Strategy outlines our vision for how the UK can maintain and build on its position as other countries also race to deliver their own economic and technological transformations.

The challenge now for the UK is to fully unlock the power of AI and data-driven technologies, to build on our early leadership and legacy, and to look forward to the opportunities of this coming decade.

This National AI Strategy will signal to the world our intention to build the most pro-innovation regulatory environment in the world; to drive prosperity across the UK and ensure everyone can benefit from AI; and to apply AI to help solve global challenges like climate change.

AI will be central to how we drive growth and enrich lives, and the vision set out in our strategy will help us achieve both of those vital goals.

Nadine Dorries MP
Secretary of State for Digital, Culture, Media and Sport

Executive summary

Artificial Intelligence (AI) is the fastest growing deep technology in the world, with huge potential to rewrite the rules of entire industries, drive substantial economic growth and transform all areas of life. The UK is a global superpower in AI and is well placed to lead the world over the next decade as a genuine research and innovation powerhouse, a hive of global talent and a progressive regulatory and business environment.

Many of the UK's successes in AI were supported by the 2017 Industrial Strategy, which set out the government's vision to make the UK a global centre for AI innovation. In April 2018, the government and the UK's AI ecosystem agreed a near £1 billion AI Sector Deal to boost the UK's global position as a leader in developing AI technologies. This new National AI Strategy builds on the UK's strengths but also represents the start of a step-change for AI in the UK, recognising the power of AI to increase resilience, productivity, growth and innovation across the private and public sectors. This is how we will prepare the UK for the next ten years, and is built on three assumptions about the coming decade:

The key drivers of progress, discovery and strategic advantage in AI are access to people, data, compute and finance - all of which face huge global competition;

AI will become mainstream in much of the economy and action will be required to ensure every sector and region of the UK benefit from this transition;

Our governance and regulatory regimes will need to keep pace with the fast-changing demands of AI, maximising growth and competition, driving UK excellence in innovation, and protecting the safety, security, choices and rights of our citizens.

The UK's National AI Strategy therefore aims to:

1. Invest and plan for the long-term needs of the AI ecosystem to continue our leadership as a science and AI superpower;

2. Support the transition to an AI-enabled economy, capturing the benefits of innovation in the UK, and ensuring AI benefits all sectors and regions;

3. Ensure the UK gets the national and international governance of AI technologies righ t to encourage innovation, investment, and protect the public and our fundamental values.

This will be best achieved through broad public trust and support, and by the involvement of the diverse talents and views of society.

Summary of key actions

Investing in the long-term needs of the AI ecosystem

Ensuring AI benefits all sectors and regions

Governing AI effectively

Short term (next 3 months):

* Publish a framework for government's role in enabling better data availability in the wider economy

* Consult on the role and options for a National Cyber-Physical Infrastructure Framework

* Support the development of AI, data science and digital skills through the Department for Education's Skills Bootcamps

* Begin engagement on the Draft National Strategy for AI-driven technologies in Health and Social Care, through the NHS AI Lab

* Publish the Defence AI Strategy, through the Ministry of Defence

* Launch a consultation on copyright and patents for AI through the IPO

* Publish the CDEI assurance roadmap

* Determine the role of data protection in wider AI governance following the Data: A new direction consultation

* Publish details of the approaches the Ministry of Defence will use when adopting and using AI

* Develop an all-of-government approach to international AI activity

Medium term (next 6-12 months):

* Publish research into what skills are needed to enable employees to use AI in a business setting and identify how national skills provision can meet those needs

* Evaluate the private funding needs and challenges of AI scaleups

* Support the National Centre for Computing Education to ensure AI programmes for schools are accessible

* Support a broader range of people to enter AI-related jobs by ensuring career pathways highlight opportunities to work with or develop AI

* Implement the US UK Declaration on Cooperation in AI R&D

* Publish a review into the UK's compute capacity needs to support AI innovation, commercialisation and deployment

* Roll out new visa regimes to attract the world's best AI talent to the UK

* Publish research into opportunities to encourage diffusion of AI across the economy

* Consider how Innovation Missions include AI capabilities, such as in energy

* Extend UK aid to support local innovation in developing countries

* Build an open repository of AI challenges with real-world applications

* Publish White Paper on a pro-innovation national position on governing and regulating AI

* Complete an in-depth analysis on algorithmic transparency, with a view to develop a cross-government standard

* Pilot an AI Standards Hub to coordinate UK engagement in AI standardisation globally

* Establish medium and long term horizon scanning functions to increase government's awareness of AI safety

Long term (next 12 months and beyond):

* Undertake a review of our international and domestic approach to semiconductor supply chains

* Consider what open and machine-readable government datasets can be published for AI models

* Launch a new National AI Research and Innovation Programme that will align funding programmes across UKRI and support the wider ecosystem

* Back diversity in AI by continuing existing interventions across top talent, PhDs, AI and Data Science Conversion Courses and Industrial Funded Masters

* Monitor and use National Security and Investment Act to protect national security while keeping the UK open for business

* Include trade deal provisions in emerging technologies, including AI

* Launch joint Office for AI / UKRI programme to stimulate the development and adoption of AI technologies in high potential, lower-AI-maturity sectors

* Continue supporting the development of capabilities around trustworthiness, adoptability, and transparency of AI technologies through the National AI Research and Innovation Programme

* Join up across government to identify where using AI can provide a catalytic contribution to strategic challenges

* Explore with stakeholders the development of an AI technical standards engagement toolkit to support the AI ecosystem to engage in the global AI standardisation landscape

* Work with global partners on shared R&D challenges, leveraging Overseas Development Assistance to put AI at the heart of partnerships worldwide

* Work with The Alan Turing Institute to update guidance on AI ethics and safety in the public sector

* Work with national security, defence, and leading researchers to understand what public sector actions can safely advance AI and mitigate catastrophic risks

Introduction

Artificial Intelligence technologies (AI) offer the potential to transform the UK's economic landscape and improve people's lives across the country, transforming industries and delivering first-class public services.

AI may be one of the most important innovations in human history, and the government believes it is critical to both our economic and national security that the UK prepares for the opportunities AI brings, and that the country is at the forefront of solving the complex challenges posed by an increased use of AI.

This country has a long and exceptional history in AI - from Alan Turing's early work through to DeepMind's recent pioneering discoveries. In terms of AI startups and scaleups, private capital invested and conference papers submitted, the UK sits in the top tier of AI nations globally. The UK ranked third in the world for private investment into AI companies in 2020, behind only the USA and China.

The National AI Strategy builds on the UK's current strengths and represents the start of a step-change for AI in the UK, recognising that maximising the potential of AI will increase resilience, productivity, growth and innovation across the private and public sectors. Building on our strengths in AI will take a whole-of-society effort that will span the next decade. This is a top-level economic, security, health and wellbeing priority. The UK government sees being competitive in AI as vital to our national ambitions on regional prosperity and for shared global challenges such as net zero, health resilience and environmental sustainability. AI capability is therefore vital for the UK's international influence as a global science superpower.

The National AI Strategy for the United Kingdom will prepare the UK for the next ten years, and is built on three assumptions about the coming decade:

The key drivers of progress, discovery and strategic advantage in AI are access to people, data, compute and finance - all of which face huge global competition;

AI will become mainstream in much of the economy and action will be required to ensure every sector and region of the UK benefit from this transition;

Our governance and regulatory regimes will need to keep pace with the fast-changing demands of AI, maximising growth and competition, driving UK excellence in innovation, and protecting the safety, security, choices and rights of our citizens.

This document sets out the UK's strategic intent at a level intended to guide action over the next ten years, recognising that AI is a fast moving and dynamic area. Detailed and measurable plans for the execution of the first stage of this strategy will be published later this year.
The UK's National Artificial Intelligence Strategy will:

1. Invest and plan for the long term needs of the AI ecosystem to continue our leadership as a science and AI superpower;

2. Support the transition to an AI-enabled economy, capturing the benefits of innovation in the UK, and ensuring AI benefits all sectors and regions;

3. Ensure the UK gets the national and international governance of AI technologies right to encourage innovation, investment, and protect the public and our fundamental values.

This will be best achieved through broad public trust and support, and by the involvement of the diverse talents and views of society.
10-Year Vision

Over the next decade, as transformative technologies continue to reshape our economy and society, the world is likely to see a shift in the nature and distribution of global power. We are seeing how, in the case of AI, rapid technological change seeks to rebalance the science and technology dominance of existing superpowers like the US and China, and wider transnational challenges demand greater collective action in the face of continued global security and prosperity.

With this in mind, the UK has an opportunity over the next ten years to position itself as the best place to live and work with AI; with clear rules, applied ethical principles and a pro-innovation regulatory environment. With the right ingredients in place, we will be both a genuine innovation powerhouse and the most supportive business environment in the world, where we cooperate on using AI for good, advocate for international standards that reflect our values, and defend against the malign use of AI.

Whether it is making the decision to study AI, work at the cutting edge of research or spin up an AI business, our investments in skills, data and infrastructure will make it easier than ever to succeed. Our world-leading R&D system will step up its support of innovators at every step of their journey, from deep research to building and shipping products. If you are a talented AI researcher from abroad, coming to the UK will be easier than ever through the array of visa routes which are available.

If you run a business - whether it is a startup, SME or a large corporate - the government wants you to have access to the people, knowledge and infrastructure you need to get your business ahead of the transformational change AI will bring, making the UK a globally-competitive, AI-first economy which benefits every region and sector.

By leading with our democratic values, the UK will work with partners around the world to make sure international agreements embed our ethical values, making clear that progress in AI must be achieved responsibly, according to democratic norms and the rule of law.

And by increasing the number and diversity of people working with and developing AI, by putting clear rules of the road in place and by investing across the entire country, we will ensure the real-world benefits of AI are felt by every member of society. Whether that is more accurate AI-enabled diagnostics in the NHS, the promise of driverless cars to make our roads safer and smarter, or the hundreds of unforeseen benefits that AI could bring to improve everyday life.

The goals of this Strategy are that the UK:

1. Experiences a significant growth in both the number and type of discoveries that happen in the UK, and are commercialised and exploited here;

2. Benefits from the highest amount of economic and productivity growth due to AI; and

3. Establishes the most trusted and pro-innovation system for AI governance in the world.

This vision can be achieved if we build on three pillars fundamental to the development of AI:

1. Investing in the needs of the ecosystem to see more people working with AI, more access to data and compute resources to train and deliver AI systems, and access to finance and customers to grow sectors;

2. Supporting the diffusion of AI across the whole economy to ensure all regions, nations, businesses and sectors can benefit from AI; and

3. Developing a pro-innovation regulatory and governance framework that protects the public.

The National AI Strategy does not stand alone. It purposefully supports and amplifies the other, interconnected work of government including:

The Plan for Growth and recent Innovation Strategy, which recognise the need to develop a diverse and inclusive pipeline of AI professionals with the capacity to supercharge innovation;

The Integrated Review , to find new paths for UK excellence in AI to deliver prosperity and security at home and abroad, and shape the open international order of the future;

The National Data Strategy, published in September 2020, sets out our vision to harness the power of responsible data use to boost productivity, create new businesses and jobs, improve public services, support a fairer society, and drive scientific discovery, positioning the UK as the forerunner of the next wave of innovation;

The Plan for Digital Regulation , which sets out our pro-innovation approach to regulating digital technologies in a way that drives prosperity and builds trust in their use;

The upcoming National Cyber Strategy to continue the drive for securing emerging technologies, including building security into the development of AI;

The forthcoming Digital Strategy, which will build on DCMS's Ten Tech Priorities to further set out the government's ambitions in the digital sector;

A new Defence AI centre as a keystone piece of the modernisation of Defence;

The National Security Technology Innovation exchange (NSTIx), a data science & AI co-creation space that brings together National Security stakeholders, industry and academic partners to build better national security capabilities; and

The upcoming National Resilience Strategy, which will in part focus on how the UK will stay on top of technological threats.

The government's AI Council has played a central role in gathering evidence to inform the development of this strategy, including through its roadmap published at the beginning of the year, which represents a valuable set of recommendations reflecting much of the wider AI community in the UK. The wider ecosystem also fed in through a survey run by the AI Council in collaboration with The Alan Turing Institute. The government remains grateful to the AI Council for its continued leadership of the AI ecosystem, and would like to thank those from across the United Kingdom who shared their views during the course of developing this strategy.

The AI Council

The AI Council was established in 2019 to provide expert advice to the government and high-level leadership of the AI ecosystem. The AI Council demonstrates a key commitment made in the AI Sector Deal, bringing together respected leaders in their fields from across industry, academia and the public sector. Members meet quarterly to advise the Office for AI and broader government on its current priorities, opportunities and challenges for AI policy.

In January 2021, the AI Council published its 'AI Roadmap' providing 16 recommendations to the government on the strategic direction for AI. Its central call was for the government to develop a National AI Strategy, building on the success of investments made through the AI Sector Deal whilst remaining adaptable to future technological disruption. Since then, the Council has led a programme of engagement with the wider AI community to inform the development of the National AI Strategy.

To guide the delivery and implementation of this strategy the government will renew and strengthen the role of the AI Council, ensuring it continues to provide expert advice to government and high-level leadership of the AI ecosystem.

AI presents unique opportunities and challenges

'Artificial Intelligence' as a term can mean a lot of things, and the government recognises that no single definition is going to be suitable for every scenario. In general, the following definition is sufficient for our purposes: "Machines that perform tasks normally performed by human intelligence, especially when the machines learn from data how to do those tasks." The UK government has also set out a legal definition of AI in the National Security and Investment Act.

Much like James Watt's 1776 steam engine, AI is a 'general purpose technology' (or more accurately, technologies) that have many possible applications, and we expect them to have a transformational impact on the whole economy. Already, AI is used in everyday contexts like email spam filtering, media recommendation systems, navigation apps, payment transaction validation and verification, and many more. AI technologies will impact the whole economy, all of society and us as individuals.

Many of the themes in AI policy are similar to tech and digital policy more widely: the commercialisation journeys; the reliance on internationally mobile talent; the importance of data; and consolidation of economic functions onto platforms. However there are some key examples of differences derived from the above definition which differentiate AI and require a unique policy response from the government.

In regulatory matters, a system's autonomy raises unique questions around liability, assurance, and fairness as well as risk and safety - and even ownership of creative content - in a way which is distinct to AI, and these questions increase with the relative complexity of the algorithm. There are also questions of transparency and bias which arise from decisions made by AI systems.

There are often greater infrastructure requirements for AI services than in cloud/Software as a Service systems. In building and deploying some models, access to expensive high performance computing and/or large data sets is needed.

Multiple skills are required to develop, validate and deploy AI systems, and the commercialisation and product journey can be longer and more expensive because so much starts with fundamental R&D.

Reflecting and protecting society

AI makes predictions and decisions, and fulfils tasks normally undertaken by humans. While diverse opinions, skills, backgrounds and experience are hugely important in designing any service - digital or otherwise - it is particularly important in AI because of the executive function of the systems. As AI increasingly becomes an enabler for transforming the economy and our personal lives, there are at least three reasons we should care about diversity in our AI ecosystem:

Moral: As AI becomes an organising principle which creates new opportunities and changes the shape of industries and the dynamics of competition across the economy, there is a moral imperative to ensure people from all backgrounds and parts of the UK are able to participate and thrive in this new AI economy.

Social: AI systems make decisions based on the data they have been trained on. If that data - or the system it is embedded in - is not representative, it risks perpetuating or even cementing new forms of bias in society. It is therefore important that people from diverse backgrounds are included in the development and deployment of AI systems.

Economic: There are big economic benefits to a diverse AI ecosystem. These include increasing the UK's human capital from a diverse labour supply, creating a wider range of AI services that stimulate demand, and ensuring the best talent is discovered from the most diverse talent pool.

The longer term

Making specific predictions about the future impact of a technology - as opposed to the needs of those developing and using it today - has a long history in AI. Since the 1950s various hype cycles have given way to so-called 'AI winters' as the promises made have perpetually remained 'about 20 years away'.

While the emergence of Artificial General Intelligence (AGI) may seem like a science fiction concept, concern about AI safety and non-human-aligned systems is by no means restricted to the fringes of the field. The government's first focus is on the economic and social outcomes of autonomous and adaptive systems that exist today. However, we take the firm stance that it is critical to watch the evolution of the technology, to take seriously the possibility of AGI and 'more general AI', and to actively direct the technology in a peaceful, human-aligned direction.

The emergence of full AGI would have a transformational impact on almost every aspect of life, but there are many challenges which could be presented by AI which could emerge much sooner than this. As a general purpose technology AI will have economic and social impacts comparable to the combustion engine, the car, the computer and the internet. As each of these has disrupted and changed the shape of the world we live in - so too could AI, long before any system 'wakes up.'

The choices that are made in the here and now to develop AI will shape the future of humanity and the course of international affairs. For example, whether AI is used to enhance peace, or a cause for war; whether AI is used to strengthen our democracies, or embolden authoritarian regimes. As such we have a responsibility to not only look at the extreme risks that could be made real with AGI, but also to consider the dual-use threats we are already faced with today.

From Sector Deal to AI Strategy

The UK is an AI superpower, with particular strengths in research, investment and innovation. The UK's academic and commercial institutions are well known for conducting world-leading AI research, and the UK ranks 3rd in the world for AI publication citations per capita. This research strength was most recently demonstrated in November 2020 when DeepMind, a UK-based AI company, used AlphaFold to find a solution to a 50-year-old grand challenge in biology.

The UK has the 3rd highest number of AI companies in the world after the US and China. Alongside DeepMind, the UK is home to Graphcore, a Bristol-based machine learning semiconductor company; Darktrace, a world-leading AI company for cybersecurity; and BenevolentAI, a company changing the way we treat disease. The UK also attracts some of the best AI talent from around the world - the UK was the second most likely global destination for mobile AI researchers after the USA.

AlphaFold and AlphaFold 2

In November 2020, London-based DeepMind announced that they had solved one of the longest running modern challenges in biology: predicting how proteins - the building blocks of life which underpin every biological process in every living thing - take shape, or 'fold'.

Improvements in the median accuracy of predictions in the free modelling category for the best team in each CASP, measured as best-of-5 GDT. Source: DeepMind

AlphaFold, DeepMind's deep learning AI system, broke all previous accuracy levels dating back over 50 years, and in July 2021 the organisation open sourced the code for AlphaFold together with over 350,000 protein structure predictions, including the entire human proteome, via the AlphaFold database in partnership with EMBL-EBI.

DeepMind's decision to share this knowledge openly with the world, demonstrates both the opportunity that AI presents, as well as what this strategy seeks to support: bleeding-edge research happening in the UK and with partners around the world, solving big global challenges.

AlphaFold opens up a multitude of new avenues in research - helping to further our understanding of biology and the nature of the world around us. It also has a multitude of potential real-world applications, such as deepening our understanding of how bacteria and viruses attack the body in order to develop more effective prevention and treatment, or support the identification of proteins and enzymes that can break down industrial or plastic waste.

The government has invested more than £2.3 billion into Artificial Intelligence across a range of initiatives since 2014.[footnote 10] This portfolio of investment includes, but is not limited to:

£250 million to develop the NHS AI Lab at NHSX to accelerate the safe adoption of Artificial Intelligence in health and care;

£250 million into Connected and Autonomous Mobility (CAM) technology through the Centre for Connected and Autonomous Vehicles (CCAV) to develop the future of mobility in the UK;

16 new AI Centres for Doctoral Training at universities across the country, backed by up to £100 million and delivering 1,000 new PhDs over five years;

A new industry-funded AI Masters programme and up to 2,500 places for AI and data science conversion courses. This includes up to 1,000 government-funded scholarships;

Investment into The Alan Turing Institute and over £46 million to support the Turing AI Fellowships to develop the next generation of top AI talent;

Over £372 million of investment into UK AI companies through the British Business Bank for the growing AI sector;

£172 million of investment through the UKRI into the Hartree National Centre for Digital Innovation, leveraging an additional £38 million of private investment into High Performance Computing.

Further investments have been made into the Tech Nation Applied AI programme - now in its third iteration; establishing the Office for National Statistics Data Science Campus; the Crown Commercial Service's public sector AI procurement portal; and support for the Department for International Trade attracting AI related Foreign Direct Investment into the UK.

As part of the AI Sector Deal, the government established the AI Council to bring together respected leaders to strengthen the conversation between academia, industry, and the public sector. The Office for Artificial Intelligence was created as a new team within government to take responsibility for overarching AI policy across government and to be a focal point for the AI ecosystem through its secretariat of the AI Council. The Centre for Data Ethics and Innovation (CDEI) was established as a government expert body focused on the trustworthy use of data and AI in the public and private sector.

This strategy builds on the recent history of government support for AI and considers the next key steps to harness its potential in the UK for the coming decade. In doing so, the National AI Strategy leads on from the ambitions outlined in the government's Innovation Strategy to enable UK businesses and innovators to respond to economic opportunities and real-world problems through our national innovation prowess. AI was identified in the Innovation Strategy as one of the seven technology families where the UK has a globally competitive R&D and industrial strength[footnote 11] and has been widely cited as a set of technologies in which the UK must maintain a leading edge to guarantee our continued security and prosperity in an intensifying geopolitical landscape.

Pillar 1: Investing in the long-term needs of the AI ecosystem

Investing in and planning for the long term needs of the AI ecosystem to remain a science and AI superpower

To maintain the UK's position amongst the global AI superpowers and ensure the UK continues to lead in the research, development, commercialisation and deployment of AI, we need to invest in, plan for, secure and unlock the critical inputs that underpin AI innovation.

Government's aim is to greatly increase the type, frequency and scale of AI discoveries which are developed and exploited in the UK. This will be achieved by:

Making sure the UK's research, development and innovation system continues to be world leading, providing the support to allow researchers and entrepreneurs to forge new frontiers in AI;

Guaranteeing that the UK has access to a diverse range of people with the skills needed to develop the AI of the future and to deploy it to meet the demands of the new economy;

Ensuring innovators have access to the data and computing resources necessary to develop and deliver the systems that will drive the UK economy for the next decade;

Supporting growth for AI through a pro-innovation business environment and capital market, and attracting the best people and firms to set up shop in the UK;

Ensuring UK AI developers can access markets around the world.

Increasing diversity and closing the skills gap through postgraduate conversion courses in data science and artificial

Autumn 2020 student admissions data shows a diverse range of students have enrolled on AI and data science postgraduate conversion courses funded by the Office for Students. The data shows that 40% of the total students are women, one quarter are Black students and 15% are students that are disabled. Source:_ Office for Students

As a result of the growing skills gap in AI and data science, 2,500 new Masters conversion courses in AI and data science are now being delivered across universities in England. The conversion course programme included up to 1,000 scholarships to increase the number of people from underrepresented groups and to encourage graduates from diverse backgrounds to consider a future in AI and Data Science.

In the first year over 1,200 students enrolled, with 22% awarded scholarships. Over 40% of the total students are women, one quarter are black students and 15% of students are disabled. 70% of the total students are studying on courses based outside of London and the South East.

These conversion courses are providing the opportunity to develop new digital skills or retrain to help find new employment in the UK's cutting-edge AI and data science sectors, ensuring that industry and the public sector can access the greatest supply of talent across the whole country.

Skills and talent
Continuing to develop, attract and train the best people to build and use AI is at the core of maintaining the UK's world-leading position. By inspiring all with the possibilities AI presents, the UK will continue to develop the brightest, most diverse workforce.
Building a tech-savvy nation by supporting skills for the future is one of the government's ten tech priorities. The gap between demand and supply of AI skills remains significant and growing,[footnote 12],[footnote 13] despite a number of new AI skills initiatives since the 2018 AI Sector Deal. In order to meet demand, the UK needs a larger workforce with AI expertise. Last year there was a 16% increase for online AI and Data Science job vacancies and research found that 69% of vacancies were hard to fill.[footnote 14] Data from an ecosystem survey conducted by the AI Council and The Alan Turing Institute showed that 81% of respondents agreed there were significant barriers in recruiting and retaining top AI talent in their domain within the UK.

Research into the AI Labour Market showed that technical AI skill gaps are a concern for many firms, with 35% of firms revealing that a lack of technical AI skills from existing employees had prevented them from meeting their business goals, and 49% saying that a lack of required AI skills from job applicants also affected their business outcomes.[footnote 15] To support the adoption of AI we need to ensure that non-technical employees understand the opportunities, limitations and ethics of using AI in a business setting, rather than these being the exclusive domain of technical practitioners.

Understanding the UK AI Labour Market Understanding the UK AI Labour Market ' research

In 2021, the Office for AI published research to investigate Artificial Intelligence and Data science skills in the UK labour market in 2020. Some key findings from the research:

Half of surveyed firms' business plans had been impacted by a lack of suitable candidates with the appropriate AI knowledge and skills.

Two thirds of firms (67%) expected that the demand for AI skills in their organisation was likely to increase in the next 12 months.

Diversity in the AI sector was generally low. Over half of firms (53%) said none of their AI employees were female, and 40% said none were from ethnic minority backgrounds.

There were over 110,000 UK job vacancies in 2020 for AI and Data Science roles.

The findings from this research will help the Office for AI address the AI skills challenge and ensure UK businesses can take advantage of the potential of AI and Data Science.

We need to inspire a diverse set of people across the UK to ensure the AI that is built and used in the UK reflects the needs and make-up of society. To close the skills gap, the government will focus on three areas to attract and train the best people: those who build AI, those who use AI, and those we want to be inspired by AI.

Build: Train and attract the brightest and best people at developing AI

To meet the demand seen in industry and academia, the government will continue supporting existing interventions across top talent, PhDs and Masters levels. This includes Turing Fellowships, Centres for Doctoral Training and Postgraduate Industrial-Funded Masters and AI Conversion Courses.

Government will seek to build upon the £46 million Turing AI Fellowships investment to attract, recruit, and retain a substantial cohort of leading researchers and innovators at all career stages. Our approach will enable Fellows to work flexibly between academia and other sectors, creating an environment for them to discover and develop cutting edge AI technologies and drive the use of AI to address societal, economic and environmental challenges in the UK. We note that recently, research breakthroughs in the field of AI have been disproportionately driven by a small number of luminary talents and their trainees. In line with the Innovation Strategy, the government affirms our commitment to empowering distinguished academics.

Research[footnote 16] and industry engagement has demonstrated the need for graduates with business experience, indicating a need to continue supporting industry/academic partnerships to ensure graduates leave education with business-ready experience. Our particular focus will be on software engineers, data scientists, data engineers, machine learning engineers and scientists, product managers, and related roles.

We recognise that global AI talent is scarce, and the topic of fierce competition internationally. As announced in the Innovation Strategy, the government is revitalising and introducing new visa routes that encourage innovators and entrepreneurs to the UK. Support for diverse and inclusive researchers and innovators across sectors, and new environments for collaboratively developing AI, will be key to ensuring the UK's success in developing AI and investing in the long term health of our AI ecosystem.
Attracting the best AI talent from around the world
The UK is already the top global destination for AI graduates in the United States and we punch above our weight globally in attracting talent. The UK nearly leads the world in its proportion of top-skilled AI researchers. Government wants to take this to the next level and make the UK the global home for AI researchers, entrepreneurs, businesses and investors.

As well as ensuring the UK produces the next generation of AI talent we need, the government is broadening the routes that talented AI researchers and individuals can work in the UK, through the recently announced Innovation Strategy.

The Global Talent visa route is open to those who are leaders or potential leaders in AI - and those who have won prestigious global prizes automatically qualify. Government is currently looking at how to broaden this list of prizes.

A new High Potential Individual route will make it as simple as possible for internationally mobile individuals who demonstrate high potential to come to the UK. Eligibility will be open to applicants who have graduated from a top global university, with no job offer requirement. This gives individuals the flexibility to work, switch jobs or employers - keeping pace with the UK's fast-moving AI sector.

A new scale-up route will support UK scale-ups by allowing talented individuals with a high-skilled job offer from a qualifying scale-up at the required salary level to come to the UK. Scaleups will be able to apply through a fast-track verification process to use the route, so long as they can demonstrate an annual average revenue or employment growth rate over a three-year period greater than 20%, and a minimum of 10 employees at the start of the three-year period.

A revitalised Innovator route will allow talented innovators and entrepreneurs from overseas to start and operate a business in the UK that is venture-backed or harnesses innovative technologies, creating jobs for UK workers and boosting growth. We have reviewed the Innovator route to make it even more open to:

Simplifying and streamlining the business eligibility criteria. Applicants will need to demonstrate that their business venture has a high potential to grow and add value to the UK and is innovative.

Fast-tracking applications. The UK government is exploring a fast-track, lighter touch endorsement process for applicants whose business ideas are particularly advanced to match the best-in-class international offers. Applicants that have been accepted on to the government's Global Entrepreneur Programme will be automatically eligible.

Building flexibility. Applicants will no longer be required to have at least £50,000 in investment funds to apply for an Innovator visa, provided that the endorsing body is satisfied the applicant has sufficient funds to grow their business. We will also remove the restriction on doing work outside of the applicant's primary business.

The new Global Business Mobility visa will also allow overseas AI businesses greater flexibility in transferring workers to the UK, in order to establish and expand their business here.

These reforms will sit alongside the UK government's Global Entrepreneur Programme (GEP) which has a track record of success in attracting high skilled migrant tech founders with IP-rich businesses to the UK. The programme will focus on attracting more international talent to support the growth of technology clusters including through working with academic institutions from overseas to access innovative spinouts and overseas talent.

Through the Graduate Route we are also granting international students with UK degrees 2 years, 3 years for those with PhDs, to work in the UK post-graduation. This will help ensure that we can attract the best and brightest from across the world while also giving students time to work on the most challenging AI problems. These are all in addition to our existing skills visa schemes for those with UK job offers.

Use: Empower employers and employees to upskill and understand the opportunities for using AI in a business setting_

The AI Council ecosystem survey found that only 18% agreed there was sufficient provision of training and development in AI skills available to the current UK workforce. As the possibilities to develop and use AI grow, so will people's need to understand and apply AI in their jobs. This will range from people working adjacent to the technical aspects such as product managers and compliance, through to those who are applying AI within their business, such as in advertising and HR. Below degree level, there is a need to clearly articulate the skills employers and employees need to use AI effectively in the workplace. For example, industries have expressed their willingness to fund employees to undertake training but have not found training that suits their needs: including training that is business-focused, modular and flexible.
Skills for Jobs White Paper
The Skills for Jobs: Lifelong Learning for Opportunity and Growth White Paper was published in January 2021 and is focused on giving people the skills they need, in a way that suits them, so they can get great jobs in sectors the economy needs and boost the country's productivity.

These reforms aim to ensure that people can access training and learning flexibly throughout their lives and that they are well-informed about what is on offer, including opportunities in valuable growth sectors. This will also involve reconfiguring the skills system to give employers a leading role in delivering the reforms and influencing the system to generate the skills they need to grow.

To more effectively use AI in a business setting, employees, including those who would not have traditionally engaged with AI, will require a clear articulation of the different skills required, so they can identify what training already exists and understand if there is still a gap.

Using the Skills Value Chain approach piloted by the Department for Education,[footnote 17] the government will help industry and providers to identify what skills are needed. Lessons learned from this pilot will support this work to help businesses adopt the skills needed to get the best from AI. The Office for AI will then work with the Department for Education to explore how these needs can be met and mainstreamed through national skills provision.

The government will also support people to develop skills in AI, machine learning, data science and digital through the Department for Education's Skills Bootcamps. The Bootcamps are free, flexible courses of up to 16 weeks, giving adults aged 19 and over the opportunity to build up in-demand, sector-specific skills and fast-track to an interview with a local employer; improving their job prospects and supporting the economy.

Inspire: Support all to be excited by the possibilities of AI

The AI Council's Roadmap makes clear that inspiring those who are not currently using AI, and allowing children to explore and be amazed by the potential of AI, will be integral to ensuring we continue to have a growing and diverse AI-literate workforce.

Through supporting the National Centre for Computing Education(NCCE) the government will continue to ensure programmes that engage children with AI concepts are accessible and reach the widest demographic.

The Office for AI will also work with the Department for Education to ensure career pathways for those working with or developing AI are clearly articulated on career guidance platforms, including the National Careers Service, demonstrating role models and opportunities to those exploring AI. This will support a broader range of people to consider careers in AI. The government will ensure that leaders within the National AI Research and Innovation Programme will play a key role in engaging with the public and inspiring the leaders of the future.

Research, development and innovation

Our vision is that the UK builds on our excellence in research and innovation in the next generation of AI technologies.

The UK has been a leader in AI research since it developed as a field, thanks to our strengths in computational and mathematical sciences.[footnote 18] The UK's AI base has been built upon this foundation,[footnote 19] and the recently announced Advanced Research and Invention Agency (ARIA) will complement our efforts to cement our status as a global science superpower. The UK also has globally recognised institutes such as The Alan Turing Institute and the high-performing universities which are core to research in AI.[footnote 20]

Currently, AI research undertaken in the UK is world class, and investments in AI R&D contribute to the Government's target of increasing overall public and private sector R&D expenditure to 2.4% of GDP by 2027. But generating economic and societal impact through adoption and diffusion of AI technologies is behind where it could be.[footnote 21] There is a real opportunity to build on our existing strengths in fundamental AI research to ensure they translate into productive processes throughout the economy.

At the same time, the field of AI is advancing rapidly, with breakthrough innovations being generated by a diverse set of institutions and countries. The past decade has seen the rise of deep learning, compute-intensive models, routine deployment of vision, speech, and language modelling in the real world, the emergence of responsible AI and AI safety, among other advances. These are being developed by new types of research labs in private companies and public institutions around the world. We expect that the next decade will bring equally transformative breakthroughs. Our goal is to make the UK the starting point for a large proportion of them, and to be the fastest at turning them into benefits for all.

To do this, UKRI will support the transformation of the UK's capability in AI by launching a National AI Research and Innovation (R&I) Programme. The programme will shift us from a rich but siloed and discipline-focused national AI landscape to an inclusive, interconnected, collaborative, and interdisciplinary research and innovation ecosystem. It will work across all the Councils of UKRI and will be fully-joined up with business of all sizes and government departments. It will translate fundamental scientific discoveries into real-world AI applications, address some limitations in the ability of current AI to be effectively used in numerous real world contexts, such as tackling complex and undefined problems, and explore using legacy data such as non-digital public records.

The National AI Research and Innovation (R&I) Programme has five main aims:

Discovering and developing transformative new AI technologies, leading the world in the development of frontier AI and the key technical capabilities to develop responsible and trustworthy AI.The programme will support:

foundational research to develop novel next generation AI technologies and approaches which could address current limitations of AI, focusing on low power and sustainable AI, and AI which can work differently with a diverse range of challenging data sets, human-AI interaction, reasoning, and the maths underpinning the theoretical foundations of AI.

technical and socio-technical capability development to overcome current limitations around the responsible trustworthy nature of AI.

Maximising the creativity and adventure of researchers and innovators, building on UK strengths and developing strategic advantage through a diverse range of AI technologies. The programme will support:

Building new research and innovation capacity to deliver the ideas, technologies, and workforce of the future, recruiting and retaining AI leaders, supporting the development of new collaborative AI ecosystems, and developing collaborative, multidisciplinary, multi-partner teams. The programme will support:

the recruitment, retention, training and development of current and future leaders in AI, and flexible working across sectoral and organisational interfaces using tools such as fellowships, and building on the success of the Turing AI Fellowships scheme;

enhanced UK capacity in key AI professional skills for research and innovation, such as data scientists and software engineers.

Connecting across the UK AI Research and Innovation ecosystem, building on the success of The Alan Turing Institute as the National Centre for AI and Data Science, and building collaborative partnerships nationally and regionally between and across sectors, diverse AI research and innovation stakeholders. The programme will support:

the development of a number of nationally distributed AI ecosystems which enable researchers and innovators to collaborate in new environments and integrate basic research through application and innovation. These ecosystems will be networked into a national AI effort with the Alan Turing Institute as its hub, convening and coordinating the national research and innovation programme and enabling business and government departments to access the UK's AI expertise and skills capability e.g. the catapult network and compute capability.

Supporting the UK's AI Sector and the adoption of AI, connecting research and innovation and supporting AI adoption and innovation in the private sector. The programme will support:

challenge-driven AI research and innovation programmes in key UK priorities, such as health and the transition to net zero;

collaborative work with the public sector and government organisations to facilitate leading researchers and innovators engaging with the AI transformation of the public sector;

innovation activities in the private sector, both in terms of supporting the development of the UK's burgeoning AI sector and the adoption of AI across sectors.

International collaboration on research and innovation

As well as better coordination at home, the UK will work with friends and partners around the world on shared challenges in research and development and lead the global conversation on AI.

The UK will participate in Horizon Europe, enabling collaboration with other European researchers, and will build a strong and varied network of international science and technology partnerships to support R&I collaboration. By shaping the responsible use of technology, we will put science and technology, including AI, at the heart of our alliances and partnerships worldwide. We will continue to use Official Development Assistance to support R&D partnerships with developing countries.

We are also deepening our collaboration with the United States, implementing the US UK Declaration on Cooperation in AI Research and Development This declaration outlines a shared vision for driving technological breakthroughs in AI between the US and the UK. As we build materially on this partnership, we will seek to enable UK partnership with other key global actors in AI, to grow influential R&I collaborations.

Access to data

The National Data Strategy sets out the government's approach to unlocking the power of data. Access to good quality, representative data from which AI can learn is critical to the development and application of robust and effective AI systems.

The AI Sector Deal recognised this and since then the government has established evidence on which to make policies to harness the positive economic and social benefit of increased availability of data. This includes the Open Data Institute's original research into data trusts as a model of data stewardship to realise the value of data for AI. The research established a repeatable model for data trusts which others have begun to apply.

Mission 1 of the National Data Strategy seeks to unlock the value of data across the economy, and is a vital enabler for AI. This mission explores how the government can apply six evidenced levers to tackle barriers to data availability. The government will publish a policy framework in Autumn 2021 informed by the outcomes of Mission 1, setting out its role in enabling better data availability in the wider economy. The policy framework includes supporting the activities of intermediaries, including data trusts, and providing stewardship services between those sharing and accessing data.

The AI Council and the Ada Lovelace Institute recently explored three legal mechanisms that could help facilitate responsible data stewardship - data trusts, data cooperatives and corporate and contractual mechanisms. The ongoing Data: A new direction consultation asks what role the government should have in enabling and engendering confidence in responsible data intermediary activity. The government is also exploring how privacy enhancing technologies can remove barriers to data sharing by more effectively managing the risks associated with sharing commercially sensitive and personal data.

Data foundations and use in AI systems

Data foundations refer to various characteristics of data that contribute to its overall condition, whether it is fit for purpose, recorded in standardised formats on modern, future-proof systems and held in a condition that means it is findable, accessible, interoperable and reusable (FAIR). A recent EY study delivered on behalf of DCMS has found that organisations that report higher AI adoption levels also have a higher level of data foundations.

The government is considering how to improve data foundations in the private and third sectors. Through the National AI R&I Programme and ambitions to lead best practices in FAIR data, we will grow our capacity in professional AI, software and data skills, and support the development of key new data infrastructure capabilities. Technical professionals such as data engineers have a key role to play in opening up access to the most critical data and compute infrastructures on FAIR data principles, and in accelerating the pathway to using AI technologies to make best use of the UK's healthy data ecosystem.

Data foundations are crucial to the effective use of AI and it is estimated that, on average, 80% of the time spent on an AI project is cleaning, standardising and making the data fit for purpose. Furthermore, when the source data needed to power AI or machine learning is not fit for purpose, it leads to poor or inaccurate results, and to delays in realising the benefits of innovation.[footnote 22] Poor quality datasets can also be un-representative, especially when it comes to minority groups, and this can propagate existing biases and exclusions when they are used for AI.

The government is looking to support action to mitigate the effects of quality issues and underrepresentation in AI systems. Subject to the outcomes of the Data: A new direction consultation, the government will more explicitly permit the collection and processing of sensitive and protected characteristics data to monitor and mitigate bias in AI systems.

An important outcome for increasing access to data and improving data foundations is in how technology will be better able to use that data. Technological convergence - the tendency for technologies that were originally unrelated to become more closely integrated (or even unified) as they advance - means that AI will increasingly be deployed together with many other technologies of the future, unlocking new technological, economic and social opportunities. For example, AI is a necessary driver of the development of robotics and smart machines, and will be a crucial enabling technology for digital twins. These digital replicas of real-world assets, processes or systems, with a two-way link to sensors in the physical world, will help make sense of and create insights and value from vast quantities of data in increasingly sophisticated ways. And in the future, some types of AI will rely on the step-change in processing power that quantum computing is expected to unlock.

Government will consult later this year on the potential value of and options for a UK capability in digital twinning and wider 'cyber-physical infrastructure.'[footnote 23] This consultation will help identify how common, interoperable digital tools and platforms, as well as physical testing and innovation spaces can be brought together to form a digital and physical shared infrastructure for innovators (e.g. digital twins, test beds and living labs). Supporting and enabling this shared infrastructure will help remove time, cost and risk from the process of bringing innovation to market, enabling accelerated AI development and applications.

Public sector data

Work is underway within the government to fix its own data foundations as part of Mission 3 of the National Data Strategy, which focuses on transforming the government's use of data to drive efficiency and improve public services. The Central Digital and Data Office (CDDO) has been created within the Cabinet Office to consolidate the core policy and strategy responsibilities for data foundations, and will work with expert cross-sector partners to improve government's use and reuse of data to support data-driven innovation across the public sector.

The CDDO also leads on the Open Government policy area, a wide-ranging and open engagement programme that entails ongoing work with Civil Society groups and government departments to target new kinds of data highlighted as having 'high potential impact' for release as open data. The UK's ongoing investment in open data will serve to further bolster the use of AI and machine learning within government, the private sector, and the third sector. The application of standards and improvements to the quality of data collected, processed, and ultimately released publicly under the Open Government License will create further value when used by organisations looking to train and optimise AI systems utilising large amounts of information.

The Office for National Statistics(ONS) is leading the Integrated Data Programme in collaboration with partners across government, providing real-time evidence, underpinning policy decisions and delivering better outcomes for citizens while maintaining privacy. The 2021 Declaration on Government Reform sets out a focus on strengthening data skills across government including senior leaders.

We need to strengthen the way that public authorities can engage with private sector data providers to make better use of data through FAIR data and open standards, including making government data more easily available through application programming interfaces (APIs), and encouraging businesses to offer their data through APIs. Government will continue to publish authoritative open and machine-readable data on which AI models for both public and commercial benefit can depend. The Office for AI will also work with teams across government to consider what valuable datasets government should purposefully incentivise or curate that will accelerate the development of valuable AI applications.

Compute

The total amount of compute shows two distinct eras of compute usage in training AI systems. A petaflop/s-day consists of performing 10615 neural net operations per second for one day, or a total of about 10620 operations. Starting from ~2012 we see a 3.4-month doubling time for the compute seen in historical results, compared to a ~2-year doubling time (Moore's Law) before then. Shown on a logarithmic scale. Source: OpenAI

Access to computing power is essential to the development and use of AI, and has been a dominant trend in AI breakthroughs of the past decade. The computing power underpinning AI in the UK comes from a range of sources. The government's recent report on large-scale computing[footnote 24] recognises its importance in AI innovation, but suggests that the UK's infrastructure is lagging behind other major economies around the world such as the US, China, Japan and Germany. We also recognise the growing compute gap between large-scale enterprises and researchers. Access to compute is both a competitiveness and a security issue. It is also not a one-size-fits-all approach - different AI technologies need different capabilities.
Digital Catapult's Machine Intelligence Garage
For more than three years, Digital Catapult's Machine Intelligence Garage (MI Garage) has helped startups accelerate the development of their industry-leading AI solutions by addressing their need for computational power.

Some AI solutions being developed require greater computing capacity in the form of High Performance Computers (HPC) for unusually large workloads (such as weather simulation, protein folding and simulation of molecular interactions) or access to AI focussed hardware like Graphcore's Intelligence Processing Unit (IPU), a new processor specifically designed for developing AI. MI Garage provides a channel through which startups can connect with HPC centres and access specialised hardware. HPC partners include the Hartree National Centre for Digital Innovation, the Edinburgh Parallel Computing Centre, and the Earlham Institute. MI Garage has also worked with NVIDIA, Graphcore and LightOn to facilitate access to special trials to lower the barrier to entry to AI specialised hardware.

Sustained public and private investment in a range of facilities from cloud, laboratory and academic department scale, through to supercomputing, will be necessary to ensure that accessing computing power is not a barrier to future AI research and innovation, commercialisation and deployment of AI. In June 2021, the government announced joint funding with IBM for the Hartree National Centre for Digital Innovation to stimulate high performance computing enabled innovation in industry and make cutting-edge technologies like AI more accessible to businesses and public sector organisations.

Understanding our domestic AI computing capacity needs and their relationship to energy use is increasingly important[footnote 25] if we are to achieve our ambitions. To better understand the UK's future AI computing requirements, the Office for AI and UKRI will evaluate the UK's computing capacity needs to support AI innovation, commercialisation and deployment. This study will look at the hardware and broader needs of researchers and organisations, large and small, developing AI technologies, alongside organisations adopting AI products and services. The study will also consider the possible wider impact of future computing requirements for AI as it relates to areas of proportional concern, such as the environment. The report will feed into UKRI's wider work on Digital Research Infrastructure.[footnote 26]

Alongside access to necessary compute capacity, the competitiveness of the AI hardware will be critical to the UK's overall research and commercial competitiveness in the sector. The UK is a world leader in chip and systems design, underpinned by processor innovation hubs in Cambridge and Bristol. We have world-leading companies supporting both general purpose AI - Graphcore has built the world's most complex AI chip,[footnote 27] and for specific applications - XMOS is a leader in AI for IOT. The government is currently undertaking a wider review of its international and domestic approach to the semiconductor sector. Given commercial and innovation priorities in AI, further support for the chip design community will be considered.

Finance and VC

AI innovation is thriving in the UK, backed by our world-leading financial services industry. In 2020, UK firms that were adopting or creating AI-based technologies received £1.78bn in funding, compared to £525m raised by French companies and £386m raised in Germany.[footnote 28] More broadly, investment in UK deep tech companies has increased by 291% over the past five years, though deal sizes remain considerably smaller compared to the US.[footnote 29]

The government will continue to evaluate the state of funding specifically for innovative firms developing AI technologies across every region of the UK. This work will explore if there are any significant investment gaps or barriers to accessing funding that AI innovative companies are facing that are not being addressed. Government commits to reporting on this work in Autumn 2022.

Accessing the right finance at the right time is critical for AI innovators to be able to develop their idea into a commercially viable product and grow their business, but this is complicated by the long timelines often needed for AI research and development work.[footnote 30][footnote 31] The AI Council's Roadmap suggests a funding gap at series B+, meaning that AI companies are struggling to scale and stay under UK ownership.
Tech Nation
Tech Nation is a predominantly government-funded programme, built to deliver its own initiatives that grow and support the UK's burgeoning digital tech sector. This includes growth initiatives aiming to help businesses successfully navigate the transition from start-up to scale-up and beyond, network initiatives to connect the UK digital ecosystem, and the Tech Nation Visa scheme, which offers a route into the UK for exceptionally talented individuals from overseas.

Recent growth programmes include Applied AI, their first to help the UK's most promising founders who are applying AI in practical areas and creating real-world impact; Net Zero, a six-month free growth programme for tech companies that are creating a more sustainable future; and Libra, which is focused on supporting Black founders and addressing racial inequality in UK tech.

While the UK's funding ecosystem is robust, the government is committed to ensuring the system is easy for businesses and innovators to navigate, and that any existing gaps are addressed. The recent Innovation Strategy signalled the Government's efforts to support innovators by bringing together effective private markets with well-targeted public investment. In it, the government set out plans to upskill lenders to assess risk when lending to innovative businesses and outlined work across Innovate UK and the British Business Bank to investigate how businesses interact with the public support landscape, to maximise accessibility for qualifying businesses. A good example of this is the Future Fund: Breakthrough, a new £375 million UK-wide programme launched in July 2021, will encourage private investors to co-invest with the government in high-growth innovative businesses to accelerate the deployment of breakthrough technologies.

Our economy's success and our citizens' safety rely on the government's ability to protect national security while keeping the UK open for business with the rest of the world. Within this context, we will ensure we protect the growth of welcome investment into the UK's AI ecosystem. The government has introduced the National Security and Investment Act that will provide new powers to screen investments effectively and efficiently now and into the future. It will give businesses and investors the reassurance that the UK continues to welcome the right talent, investment and collaboration that underpins our wider economic security.

Trade

AI is a key part of the UK's digital goods and services exports, which totalled £69.3bn in 2019.[footnote 32] Trade can support the UK's objectives to sustain the mature, competitive and innovative AI developer base the UK needs to access customers around the world.

As part of its free trade agenda, the government is committed to pursuing ambitious digital trade chapters to help place the UK as a global leader. As the UK secures new trade deals, the government will include provisions on emerging digital technologies, including AI, and champion international data flows, preventing unjustified barriers to data crossing borders while maintaining the UK's high standards for personal data protection.

In doing so, the UK aims to deliver digital trade chapters in agreements that: 1) provide legal certainty; 2) support data flows; 3) protect consumers; 4) minimise non-tarriff barriers to digital trade; 5) prevent discrimination against trade by electronic means; and 6) promote international cooperation and global AI governance. All of these aims support a pro -innovation agenda.
Pillar 1 - Investing in the Long Term Needs of the AI Ecosystem Actions:
1. Launch a new National AI Research and Innovation Programme, that will align funding programmes across UKRI Research Councils and Innovate UK, stimulating new investment in fundamental AI research while making critical mass investments in particular applications of AI.

2. Lead the global conversation on AI R&D and put AI at the heart of our science and technology alliances and partnerships worldwide through:

Work with partners around the world on shared AI challenges, including participation in Horizon Europe to enable collaboration with other European researchers.

Use of Overseas Development Assistance to support partnerships with developing AI nations.

Delivering new initiatives through the US UK Declaration on Cooperation in AI R&D.

3. Develop a diverse and talented workforce which is at the core of maintaining the UK's world leading position through:

Supporting existing interventions across top talent, PhDs and Masters levels and developing world leading teams and collaborations, the government will continue to attract and develop the brightest and best people to build AI.

Scoping what is required to upskill employees to use AI in a business setting. Then, working with the Department for Education, explore how skills provision can meet these needs through the Skills Value Chain and build out AI and data science skills through Skills Bootcamps.

Inspiring all to be excited by the possibilities of AI, by supporting the National Centre for Computing Education (NCCE) to ensure AI programmes for children are accessible and reach the widest demographic and that career pathways for those working with or developing AI are clearly articulated on career guidance platforms.

Promoting the revitalised and new visa routes that encourage innovators and entrepreneurs to the UK, making attractive propositions for prospective and leading AI talent.

4. Publish a policy framework setting the government's role in enabling better data availability in the wider economy. The government is already consulting on the opportunity for data intermediaries to support responsible data sharing and data stewardship in the economy and the interplay of AI technologies with the UK's data rights regime.

5. Consult on the potential role and options for a future national 'cyber-physical infrastructure' framework, to help identify how common interoperable digital tools and platforms and cyber-physical or living labs could come together to form a digital and physical 'commons' for innovators, enabling accelerated AI development and applications.

6. Publish a report on the UK's compute capacity needs to support AI innovation, commercialisation and deployment. The report will feed into UKRI's wider work on infrastructure.

7. Continue to publish open and machine-readable data on which AI models for both public and commercial benefit can depend.

8. Consider what valuable datasets the government should purposefully incentivise or curate that will accelerate the development of valuable AI applications.

9. Undertake a wider review of our international and domestic approach to the semiconductor sector. Given commercial and innovation priorities in AI, further support for the chip design community will be considered.

10. Evaluate the state of funding specifically for innovative firms developing AI technologies in the UK, and report on this work in Autumn 2022.

11. Protect national security through the National Security & Investment Act while keeping the UK open for business with the rest of the world, as our economy's success and our citizens' safety rely on the government's ability to take swift and decisive action against potentially hostile foreign investment.

12. Include provisions on emerging digital technologies, including AI, in future trade deals alongside championing international data flows, preventing unjustified barriers to data crossing borders and maintaining the UK's high standards for personal data protection.

Pillar 2: Ensuring AI benefits all sectors and regions

Supporting the transition to an AI-enabled economy, capturing the benefits of AI innovation in the UK, and ensuring AI technologies benefit all sectors and regions

To ensure that all sectors and regions of the UK economy can benefit from the positive transformation that AI will bring, the government will back the domestic design and development of the next generation of AI systems, and support British business to adopt them, grow and become more productive. The UK has historically been excellent at developing new technologies but less so at commercialising them into products and services.

As well as smart action to support both suppliers, developers and adopters, government also has a role to play when it comes to the use of AI, both as a significant market pull in terms of public procurement, such as the NHS and the defence sector, with a dedicated Defence AI Strategy and AI Centre, but also in terms of using the technology to solve big public policy challenges, such as in health and achieving net zero. Finally, it requires being bold and experimental, and supporting the use of AI in the service of mission-led policymaking.

Government's aim is to diffuse AI across the whole economy to drive the highest amount of economic and productivity growth due to AI.
This will be achieved by:

Supporting AI businesses on their commercial journey, understanding the unique challenges they face and helping them get to market and supporting innovation in high potential sectors and locations where the market currently doesn't reach;

Understanding better the factors that influence the decisions to adopt AI into organisations - which includes an understanding of when not to;

Ensuring AI is harnessed to support outcomes across the government's Innovation Strategy, including by purposefully leveraging our leading AI capabilities to tackle real-world problems facing the UK and world through our Innovation Missions,[footnote 33] while driving forward discovery;

Leveraging the whole public sector's capacity to create demand for AI and markets for new services.

Commercialisation

Developing a commercial AI product or service is more than just bringing an idea to market or accessing the right funding. Recent analysis from Innovate UK suggests that obtaining private funding is only one among many other obstacles to successful commercial outcomes in AI-related projects. As well as the well known barriers such as access to data, labour market supply and access to relevant skills discussed above, other challenges reported by businesses are the lack of engagement with end users, limiting adoption and commercialisation. Commercialisation outcomes are also often constrained by business models rather than technical issues and a lack of understanding of AI-related projects' return on investment.

AI deployment - understanding new dynamics

To grow the market and spread AI to more areas of our economy, the government aims to support the demand side as well as the means for commercialising AI - understanding what, why, when and how companies choose to incorporate AI into their business planning is a prerequisite to any attempt to encourage wider adoption and diffusion across the UK.

EY research delivered on behalf of DCMS shows that AI remains an emerging technology for private sector and third sector organisations in the UK. 27% of UK organisations have implemented AI technologies in business processes; 38% of organisations are planning and piloting AI technology; and 33% of organisations have not adopted AI and are not planning to. Consistent with studies of AI adoption,[footnote 34] the size of an organisation was found to be a large contributing factor to the decision to adopt AI, with large organisations far more likely to have already done so. Recognising that for many sectors this is the cutting edge of industrial transformation, and the need for more evidence, the Office for AI will publish research later this year into the drivers of AI adoption and diffusion.

To stimulate the development and adoption of AI technologies in high-potential, low-AI maturity sectors the Office for AI and UKRI will launch a programme that will :

Support the identification and creation of opportunities for businesses, whether SMEs or larger firms, to use AI and for AI developers to build new products and services that address these needs;

Create a pathway for AI developers to start companies around new products and services or to extend and diversify their product offering if they are looking to grow and scale;

Facilitate close engagement between businesses and AI developers to ensure products and services developed address business needs, are responsibly developed and implemented, and designed and deployed so that businesses and developers alike are prepped and primed for AI implementation; and

Incentivise investors to learn about these new market opportunities, products, and services, so that, where equity finance is needed, the right financing is made available to AI developers.

Creating and protecting Intellectual Property

Intellectual Property (IP) plays a significant part in building a successful business by rewarding people for inventiveness and creativity and enabling innovation. IP supports business growth by incentivising investment, safe-guarding assets and enabling the sharing of know-how. The Intellectual Property Office (IPO) recognises that AI researchers and developers need the right support to commercialise their IP, and helps them to understand and identify their intellectual assets, providing them with the skills to protect, exploit and enforce their rights to improve their chances of survival and growth.
AI and Intellectual Property (IP): Call for Views and Government Response
An effective Intellectual Property (IP) system is fundamental to the Government's ambition for the UK to be a 'science superpower' and the best place in the world for scientists, researchers and entrepreneurs to innovate. To ensure that IP incentivises innovation, our aspiration is that the UK's domestic IP framework gives the UK a competitive edge.

In support of this ambition, the IPO published its AI and IP call for views to put the UK at the forefront of emerging technological opportunities, by considering how AI impacts on the existing UK intellectual property framework and what impacts it might have for AI in the near to medium term.

In March this year, the government published its response to the call for views, which committed to the following next steps:

To consult on the extent to which copyright and patents should protect AI generated inventions and creative works;

To consult on measures to make it easier to use copyright protected material in AI development;

An economic study to enhance understanding of the role the IP framework plays in incentivising investment in AI.

The consultation, on copyright areas of computer generated works and text and data mining, and on patents for AI devised inventions, will be launched before the end of the year so that the UK can harness the opportunities of AI to further support innovation and creativity.

Using AI for the public benefit

AI can contribute to solving the greatest challenges we face. AI has contributed to tackling COVID-19, demonstrating how these technologies can be brought to bear alongside other approaches to create effective, efficient and context-specific solutions.
AI and COVID-19
When the pandemic began it created a unique environment where AI technologies were developed to identify the virus more quickly, to help with starting treatments earlier and to reduce the likelihood that people will need intensive care. Working with Faculty, NHS England and NHS Improvement developed the COVID-19 Early Warning System (EWS). A first-of-its-kind toolkit that forecasts vital metrics such as COVID-19 hospital admissions and required bed capacity up to three weeks in advance, based on a wide range of data from the NHS COVID-19 Data Store. This gave national, regional and local NHS teams the confidence to plan services for patients amid any potential upticks in COVID-related hospital activity.

At the same time over the past year, the NHS AI Lab has collected more than 40,000 X-ray, CT and MRI chest images of over 13,000 patients from 21 NHS trusts through the National COVID-19 Chest Imaging Database (NCCID), one of the largest centralised collections of medical images in the UK. The NCCID is being used to study and understand the COVID-19 illness and to improve the care for patients hospitalised with severe infection. The database has enabled 13 projects to research new AI technologies to help speed up the identification, severity assessment and monitoring of COVID-19.

UK AI companies have also shown how AI can help accelerate the search for potential drug candidates, streamline triage and contribute to global research efforts. BenevolentAI, a world-leading AI company focused on drug discovery and medicine development, used their biomedical knowledge graph to identify a potential coronavirus treatment from already approved drugs that could be repurposed to defeat the virus. This was later validated through experimental testing from AstraZeneca. UK AI company DeepMind have adapted their AI-enabled protein folding breakthrough to better understand the virus' structure, contributing to a wider understanding of how the virus can function.

There are many areas of AI development that have matured to the point that industry and third sector organisations are investing significantly in AI tools, techniques and processes. These investments are helping to move AI from the lab and into commercial products and services. But there remain more complex, cross-sector challenges that industry is unlikely to solve on its own. These challenges will require public sector leadership, identifying strategic priorities that can maximise the potential of AI for the betterment of the UK.

The government has a clear role to play. In stimulating and applying AI innovation to priority applications and wider strategic goals, the government can help incentivise a group of different actors to harness innovation for improving lives, simultaneously reinforcing the innovation cycle that can drive wider economic benefits - from creating and invigorating markets, to the role of open source in the public, private and third sectors, to raising productivity. Over the next six to twelve months, the Office for AI will work closely with the Office for Science and Technology Strategy and government departments to understand the government's strategic goals and where AI can provide a catalytic contribution,[footnote 35] including through Innovation Missions and the Integrated Review's 'Own-Collaborate-Access' framework.

The COVID-19 pandemic has shown that global challenges need global solutions. The UK's international science and technology partnerships, global network of science and innovation officers, and research and innovation hubs, are working alongside UK universities, research institutes and investors to foster new collaborations to tackle the global challenges we all share, including in innovations on global health and to achieve net zero emissions around the globe.

Missions

The Innovation Strategy set out the government's plans to stimulate innovation to tackle major challenges facing the UK and the world, and drive capability in key technologies. This will be achieved through Innovation Missions,[footnote 36] which will draw on multiple technologies and research disciplines towards clear and measurable outcomes. They will be supported by Innovation Technologies,[footnote 37] including AI, supporting their capability to tackle pressing global and national challenges while supporting their adoption in novel areas, boosting growth and helping to consolidate our position as a science and AI superpower.

Some of these challenges have been articulated and revolve around the future health, wellbeing, prosperity and security of people, the economy, and our environment - in the UK and globally. These challenges are worthwhile and therefore difficult, and will require harnessing the combined intellect and diversity of the AI ecosystem and the whole nation, and will consider a full range of possible impacts of a given solution. The pace of AI development is often fast, parallel and non-linear, and finding the right answer to these challenges will require a collection of actors beyond just government departments, agencies and bodies to consider the technical and social implications of certain solutions and increase the creativity of problem solving. In doing so, the UK will be able to find new paths for AI to deliver on our security and prosperity objectives at home and abroad.

At the same time, well-specified challenges have also led to some of the most impactful moments of progress in AI. Whether through Imagenet, CIFAR-10, MNIST, GLUE, SquAD, Kaggle, or more, challenge-related datasets and benchmarks have generated breakthroughs in vision, language, recommender systems, and other subfields.[footnote 38]. The government believes that challenges could be created that simultaneously incentivise significant progress in Innovation Missions while rapidly progressing the development in the technology along desirable lines.

To this end, the government will develop a repository of short, medium and long term AI challenges to motivate industry and society to identify and implement real-world solutions to the strategic priorities. These priorities will be identified through the Missions Programme, and guided by the National AI R&I Programme.

Climate change and global health threats are examples of shared international challenges, and science progresses through open international collaboration. This is particularly the case when AI development is able to take advantage of publicly available coding platforms to produce new algorithms. The UK will extend its science partnerships and its work investing UK aid to support local innovation ecosystems in developing countries. Through our leadership in international development and diplomacy, we will work to ensure international collaboration can unlock the enormous potential of AI to accelerate progress on global challenges, from climate change to poverty.

Net zero

The Prime Minister's Ten Point Plan for a Green Industrial Revolution highlights the development of disruptive technologies such as AI for energy as a key priority, and in concert with the government's Ten Tech Priorities to use digital innovations to reach net zero, the UK has the opportunity to lead the world in climate technologies, supporting us to deliver our ambitious net zero targets. This will be key to meet our stated ambition in the Sixth Carbon Budget, and with it a need to consider how to achieve the maximum possible level of emissions reductions.
AI and net zero
AI works best when presented with specific problem areas with clear system boundaries and where there are large datasets being produced. In these scenarios, AI has the capability to identify complex patterns, unlock new insights, and advise on how best to optimise system inputs in order to best achieve defined objectives. There are a range of climate change mitigation and adaptation challenges that fit this description. These include:

using machine vision to monitor the environment;

using machine learning to forecast electricity generation and demand and control its distribution around the network;

using data analysis to find inefficiencies in emission-heavy industries; and

using AI to model complex systems, like Earth's own climate, so we can better prepare for future changes.

AI applications for energy and climate challenges are already being developed, but they are predominantly outliers and there are many applications across sectors that are not yet attempted. A study by Microsoft and PwC estimated that AI can help deliver a global reduction in emissions of up to 4% by 2030 compared to business as usual, with a concurrent uplift of 4.4% to global GDP. Such estimates are likely to become more accurate over time as the potential of AI becomes more apparent.

Over the last ten years there have been a series of advances in AI. These advances offer opportunities to rapidly increase the efficiency of energy systems and help reduce emissions across a wide array of climate change challenges. The AI Council's AI Roadmap advocates for AI technologies to play a role in innovating towards solutions to climate change, and literature is emerging that shows how 'exponential technologies' such as AI can increase the pace of decarbonisation across the most impactful sectors. AI is increasingly seen as a critical technology to scale and enable these significant emissions cuts by 2030.[footnote 39],[footnote 40],[footnote 41]

In the UK we have previously used mission-driven innovation policy to promote a range of technologies towards the delivery of social, economic and environmental goals. Government will continue this through the National AI R&I Programme, which will make critical mass investments in particular applications of AI technology that will generate new solutions to tackle our net zero objective.

Missions will also be continued through the Innovation Strategy's Missions Programme, which will form the heart of the government's approach to respond to these priorities, and we will develop these missions in a way that considers the promise of AI technologies, particularly in areas of specific advantage such as energy. Government will ensure that, in key areas of international collaboration such as the US UK Declaration on Cooperation in AI Research and Development and the Global Partnership on AI, we will pursue technological developments in world-leading areas of expertise in the energy sector to maximise our strategic advantage.

Health

In August 2019, the Health Secretary announced a £250 million investment[footnote 42] to create the NHS AI Lab in HSX to accelerate the safe, ethical and effective development and use of AI-driven technologies to help tackle some of the toughest challenges in health and social care, including earlier cancer detection, addressing priorities in the NHS Long Term Plan, and relieving pressure on the workforce.

AI-driven technologies have the potential to improve health outcomes for patients and service users, and to free up staff time for care.[footnote 43] The NHS AI Lab along with partners, such as the Accelerated Access Collaborative, the National Institute of Health and Care Excellenceand the Medicines and Healthcare products Regulatory Agency, are working to provide a facilitative environment to enable the health and social care system to confidently adopt safe, effective and ethical AI-driven technologies at pace and scale.

The NHS AI Lab is creating a National Strategy for AI in Health and Social Care in line with the National AI Strategy. The strategy, which will begin engagement on a draft this year and is expected to launch in early 2022, will consolidate the system transformation achieved by the Lab to date and will set the direction for AI in health and social care up to 2030.

The public sector as a buyer

To build a world-leading strategic advantage in AI and build an ecosystem that harnesses innovation for the public good, the UK will need to take a number of approaches. As the government, we can also work with industry leaders to develop a shared understanding and vision for the emerging AI ecosystem, creating longer-term certainty that enables new supply chains and markets to form.

This requires leveraging public procurement and pre-commercial procurement to be more in line with the development of deep and transformative technologies such as AI. The recent AI Council ecosystem survey revealed that 72% agreed the government should take steps to increase buyer confidence and AI capability. The Innovation Strategy and forthcoming National Procurement Policy Statement have recently articulated how we can further refine public procurement processes around public sector culture, expertise and incentive structures. This complements previous work across government to inform and empower buyers in the public sector, helping them to evaluate suppliers, then confidently and responsibly procure AI technologies for the benefit of citizens.[footnote 44]

The government has outlined how it plans to rapidly modernise our Armed Forces[footnote 45][footnote 46] and how investments will be guided.[footnote 47][footnote 48] The Ministry of Defence will soon be publishing its AI strategy which will contribute to how we will achieve and sustain technological advantage, and be a great science power in defence. This will include the establishment of the new Defence AI Centre which will champion AI development and use, and enable rapid development of AI projects. Defence should be a natural partner for the UK AI sector and the defence strategy will outline how to galvanise a stronger relationship between industry and defence.
Ministry of Defence using AI to reduce costs and meet climate goals
The MOD is trialling a US startups' Software Defined Electricity (SDE) system, which uses AI to optimise electricity in real time, to help meet its climate goals and reduce costs. Initial tests suggest it could reduce energy draw by at least 25% which, given the annual electricity bill for MOD's non-PFI sites in FY 2018/19 was £203.6M, would equate to savings of £50.9M every year and significant reductions in CO2 emissions.
Crown Commercial Service
The Crown Commercial Service worked closely with colleagues in the Office for AI and across government during drafting of guidelines for AI procurement. This was used to design their AI Dynamic Purchasing System (DPS) agreement to align with these guidelines, and included a baselines ethics assessment so that suppliers commit only to bidding where they are capable and willing to deliver both the ethical and technical dimensions of a tender.

The Crown Commercial Service is piloting a training workshop to help improve the public sector's capability to buy AI products and services, and will continue to work closely with the Office for AI and others across government to ensure we are addressing the key drivers set out in the National AI Strategy.

Pillar 2 - Ensuring AI Benefits all Sectors and Regions

Actions:

1. Launch a programme as part of UKRI's National AI R&I Programme, designed to stimulate the development and adoption of AI technologies in high-potential, lower-AI maturity sectors. The programme will be primed to exploit commercialisation interventions, enabling early innovators to access potential market opportunities where their products and services are relevant.

2. Launch a draft National Strategy for AI in Health and Social Care in line with the National AI Strategy. This will set the direction for AI in health and social care up to 2030, and is expected to launch in early 2022.

3. Ensure that AI policy supports the government's ambition to secure strategic advantage through science and technology.

4. Consider how the development of Innovation Missions also incorporates the potential of AI solutions to tackling big, real-world problems such as net zero. This will also be complemented by pursuing ambitious bilateral and multilateral agreements that advance our strategic advantages in net zero sectors such as energy, and through the extension of UK aid to to support local innovation ecosystems in developing AI nations.

5. Build an open repository of AI challenges with real-world applications, to empower wider civil society to identify and implement real-world solutions to the strategic priorities identified through the Missions Programme and guided by the National AI Research and Innovation Programme.

6. Publish research into the determinants impacting the diffusion of AI across the economy.

7. Publish the Ministry of Defence AI Strategy, which will explain how we can achieve and sustain technological advantage and be a science superpower in defence, including detail on the establishment of a new Defence AI Centre.

Pillar 3: Governing AI effectively

An effective governance regime that supports scientists, researchers and entrepreneurs to innovate while ensuring consumer and citizen confidence in AI technologies is fundamental to the government's vision over the next decade.

In a world where systematic international competition will have significant impacts on security and prosperity around the world, the government wants the UK to be the most trustworthy jurisdiction for the development and use of AI, one that protects the public and the consumer while increasing confidence and investment in AI technologies in the UK.

Effective, pro-innovation governance of AI means that (i) the UK has a clear, proportionate and effective framework for regulating AI that supports innovation while addressing actual risks and harms, (ii) UK regulators have the flexibility and capabilities to respond effectively to the challenges of AI, and (iii) organisations can confidently innovate and adopt AI technologies with the right tools and infrastructure to address AI risks and harms. The UK public sector will lead the way by setting an example for the safe and ethical deployment of AI through how it governs its own use of the technology.

We will collaborate with key actors and partners on the global stage to promote the responsible development and deployment of AI. The UK will act to protect against efforts to adopt and apply these technologies in the service of authoritarianism and repression. Through our science partnerships and wider development and diplomacy work, we will seek to engage early with countries on AI governance, to promote open society values and defend human rights.
Government's aim is to build the most trusted and pro-innovation system for AI governance in the world.
This will be achieved by: - Establishing an AI governance framework that addresses the unique challenges and opportunities of AI, while being flexible, proportionate and without creating unnecessary burdens;

Enabling AI products and services to be trustworthy, by supporting the development of an ecosystem of AI assurance tools and services to provide meaningful information about AI systems to users and regulators;

Growing the UK's contribution to the development of global AI technical standards, to translate UK R&D for trustworthy AI into robust, technical specifications and processes that can support our AI governance model, ensure global interoperability and minimise the costs of regulatory compliance;

Building UK regulators' capacities to use and assess AI, ensuring that they can deliver on their responsibilities as new AI-based products and services come to market;

Setting an example in the safe and ethical deployment of AI, with the government leading from the front;

Working with our partners around the world to promote international agreements and standards that deliver for our prosperity and security, and promote innovation that harnesses the benefits of AI as we embed our values such as fairness, openness, liberty, security, democracy, rule of law and respect for human rights.

Supporting innovation and adoption while protecting the public and building trust

The UK has a strong international reputation for the rule of law and technological breakthroughs. To build on this the government set out its pro-innovation approach through its Plan for Digital Regulation. The Plan recognises that well-designed regulation can have a powerful effect on driving growth and shaping a thriving digital economy and society, whereas poorly-designed or restrictive regulation can dampen innovation. The Plan also acknowledges that digital businesses, which include those developing and using AI technologies, are currently operating in some instances without appropriate guardrails. The existing rules and norms, which have so far guided business activity, were in many cases not designed for these modern technologies and business models. In addition, these technologies are themselves disrupting these established rules and norms.

This is especially the case for AI which, with its powerful data processing and analytical capabilities, is disrupting traditional business models and processes.[footnote 49] There is growing awareness in industry and by citizens of the potential risks and harms associated with AI technologies. These include concerns around fairness, bias and accountability of AI systems. For example, the report from the Commission on Race and Ethnic Disparities raised concerns around the potential for novel ways for bias to be introduced through AI. Other concerns include the ability of AI to undermine privacy and human agency; and physical, economic and financial harms being enabled or exacerbated by AI technologies. For example, cyber security should be considered early in the development and deployment of AI systems to prevent such harms from arising, by adopting a 'secure by design' approach to mitigate against cyber security becoming an afterthought.

This is not to say that AI is currently unregulated. The UK already regulates many aspects of the development and use of AI through 'cross-sector' legislation and different regulators. For example, there is coverage in areas like data protection ( Information Commissioner's Office), competition ( Competition & Markets Authority), human rights and equality (Equality & Human Rights Commission). As well as through 'sector-specific' legislation and regulators, for example financial services ( Financial Conduct Authority) and medical products ( Medicines and Healthcare products Regulatory Agency).

As the use of AI increases, the UK has responded by reviewing and adapting the regulatory environment. For example, the Data: A new direction consultation, published earlier this month, invites views on the role of the data protection framework within the broader context of AI governance. Specifically, the consultation examines the role of sensitive personal data in bias detection and mitigation in AI systems, and the use of the term 'fairness' in a data protection context.

Data Protection Framework and AI: Data: A new direction consultation

The UK data protection framework (UK General Data Protection Regulations and Data Protection Act 2018) is technology neutral and was not intended to comprehensively govern AI systems, or any other specific technologies. Many AI systems do not use personal data at all.

Navigating and applying relevant data protection provisions can be perceived as a complex or confusing exercise for an organisation looking to develop or deploy AI systems, possibly impeding uptake of AI technologies.

DCMS is currently running a consultation on potential reforms to the data protection framework, closing on the 19th November 2021. The consultation calls for views on specific data protection provisions that are currently triggered in the process of developing and deploying AI. In particular, the consultation covers:

Clarifying the use and reuse of personal data for research (including AI development) (Ch 1);

Clarifying the use and reuse of personal data under the legitimate interests test, including bias detection and mitigation anonymisation (Ch 1);

Explicitly authorising the use of sensitive personal data (special category data) for bias detection and mitigation in AI systems (Ch 1);

Clarifying the use of the term 'fairness' in a data protection context (Ch 1);

Assessing the challenges with the current data protection framework in developing and deploying AI responsibly (Ch 1);

Assessing the general suitability and operation of UK GDPR Article 22 (rights relating to automated decision-making and profiling) (Ch 1);

Mandatory transparency requirements for the use of algorithmic decision-making in the public sector (Ch 5).

In 2018, the government agreed with the House of Lords' view that " blanket AI-specific regulation, at this stage, would be inappropriate... [and] that existing sector-specific regulators are best placed to consider the impact on their sector of any subsequent regulation which may be needed."

There are some strong reasons why our sector-led approach makes sense:

1. The boundaries of AI risks and harms are grey, because the harms raised by these technologies are often non-AI, or extensions of non-AI, issues, and also because AI is rapidly developing and therefore what counts as the AI part of a system is constantly changing.

2. Use cases for AI, and their wider impacts, can be highly complex in their own right. There is a big limitation in what can be covered in cross-cutting legislation on AI, and regardless of the overall regulatory approach, the detail will always need to be dealt with at the level of individual harms and use cases.

3. Individual regulators and industries are already starting to respond to the risks of AI, and to work with innovators in their sectors to guide on interpretation of existing regulations, and on what further regulatory responses are appropriate. Enabling and empowering individual bodies to respond is a much quicker response to individual harms than agreeing to an AI regulatory regime that makes sense across all sectors.

4. AI is not the only ongoing technology change, and its impacts are often interlinked with other innovations and behaviour changes, including increased connectivity, the move to mobile working, the dominant role of major platforms etc. It is often hard to unpick the specific impact of AI; focusing regulation on the particular use cases where there is risk allows risks to be addressed holistically, and simplifies things for innovators.

Having embraced a strong sector-based approach to date, now is the time to decide whether our existing approach remains the right one.

As the UK's regulators have begun to respond to the emergence of AI, challenges have emerged. These include:

Inconsistent or contradictory approaches across sectors. While a sector-led approach allows responsiveness to sector specific challenges, it could create barriers to adoption across sectors by creating confusing or contradictory compliance requirements;

Overlap between regulatory mandates, creating uncertainty about responsibility, the potential for issues to fall between the gaps, and increased need for coordination;

AI regulation could become framed narrowly around prominent, existing cross-cutting frameworks, e.g. the data protection framework, while the range of AI risks and harms is much broader;

The growing activity in multilateral and multi stakeholder fora internationally, and global standards development organisations that addresses AI across sectors could overtake a national effort to build a consistent approach.

These challenges raise the question of whether the UK's current approach is adequate, and whether there is a case for greater cross-cutting AI regulation or greater consistency across regulated sectors.

At the same time, alternative methods and approaches to governing AI have emerged from multilateral and multi stakeholder fora, at international and regional levels, including global standards development organisations, academia, thought leaders, and businesses. This has raised awareness about the importance of AI governance, but also potentially confusion for the consumer about what good AI governance looks like and where responsibility lies.

Working with the AI ecosystem the Office for AI will develop our national position on governing and regulating AI, which will be set out in a White Paper in early 2022. The White Paper will set out the government's position on the potential risks and harms posed by AI technologies and our proposal to address them.

Alternative options

The UK's 2018 policy position that "existing sector-specific regulators are best placed to consider the impact on their sector of any subsequent regulation which may be needed" will be tested in our work towards the development of a White Paper, along with potential alternatives. The main alternative options are:

1. Removing some existing regulatory burdens where there is evidence they are creating unnecessary barriers to innovation.

2. Retaining the existing sector-based approach, ensuring that individual regulators are empowered to work flexibly within their own remits to ensure AI delivers the right outcomes.

3. Introducing additional cross-sector principles or rules, specific to AI, to supplement the role of individual regulators to enable more consistency across existing regimes.

For any of these options, it will be necessary to ensure that regulators and other relevant bodies are equipped to tackle the challenges raised by AI. This may require additional capabilities, capacity, and better coordination among existing regulators; new guidance; or standards to better enable consistency across existing regulatory regimes.

In developing our White Paper position, the Office for AI will consider all of these, and potentially other, options for governing AI technologies. Having exited the EU, we have the opportunity to build on our world-leading regulatory regime by setting out a pro-innovation approach, one that drives prosperity and builds trust in the use of AI. We will consider what outcomes we want to achieve and how best to realise them, across existing regulators' remits and consider the role that standards, assurance, and international engagement plays.

Regulators' coordination and capacity

While some regulators are leading the way in understanding the implications of AI for their sector or activity, we need all regulators to be able to do this. The cross-sector and disruptive nature of AI also raises new challenges in terms of regulatory overlap. For example, concerns around fairness relate to algorithmic bias and discrimination issues under the Equality Act, the use of personal data (including sensitive personal data) and sector-specific notions of fairness such as the Financial Conduct Authority's Fair Treatment of Customers guidance.

The government is working with The Alan Turing Institute and regulators to examine regulators' existing AI capacities. In particular, this work is exploring monitoring and assessing products and services using AI and dealing with complexities arising from cross-sectoral AI systems.[footnote 50]

Greater cooperation is also being enabled through initiatives such as through the Digital Regulation Cooperation Forum, a recently formed voluntary forum comprising the Competition & Markets Authority (CMA), Financial Conduct Authority (FCA), Information Commissioner's Office (ICO) and Office of Communications (Ofcom) to deliver a joined up approach to digital regulation.

International governance and collaboration

The UK will work with partners to support the international development of AI governance in line with our values. We will do this by working with partners around the world to shape approaches to AI governance under development, such as the proposed EU AI Act and potential Council of Europe legal framework. We will work to reflect the UK's views on international AI governance and prevent divergence and friction between partners, and guard against abuse of this critical technology.

The UK is already working with like-minded partners to ensure that shared values on human rights, democratic principles and the rule of law shape AI regulation and governance frameworks, whether binding or non-binding, and that an inclusive multi-stakeholder approach is taken throughout these processes. As the international debate on these frameworks has gained momentum, the UK has proactively engaged on AI at the OECD[footnote 51], Council of Europe and UNESCO, and helped found the Global Partnership on AI (GPAI), providing significant support for evidence underpinning these initiatives, such as the recently announced £1m investment in GPAI's data trust research by BEIS.

The UK will act to protect against efforts to adopt and apply these technologies in the service of authoritarianism and repression and through our science partnerships and wider development and diplomacy work seek to engage early with countries on AI governance, including when existing technology governance is less developed, to promote open society values and defend human rights.

UK Defence has a strong record of collaboration with international partners and allies. Key collaborations include engagement with NATO allies to lead AI integration and interoperability across the Alliance, and supporting the AI Partnership for Defence, a 14-nation coalition providing values based global leadership for defence AI.

The government will continue to work with our partners around the world to shape international norms and standards relating to AI, including those developed by multilateral and multistakeholder bodies at global and regional level. This will support our vision for a global ecosystem that promotes innovation and responsible development and use of technology, underpinned by our shared values of freedom, fairness, and democracy.

AI and global digital technical standards

The UK's Plan for Digital Regulation sets out our ambition to use digital technical standards to provide an agile and pro-innovation way to regulate AI technologies and build consistency in technical approaches, as part of a wider suite of governance tools complementing 'traditional' regulation.

The integration of standards in our model for AI governance and regulation is crucial for unlocking the benefits of AI for the economy and society, and will play a key role in ensuring that the principles of trustworthy AI are translated into robust technical specifications and processes that are globally-recognised and interoperable.
What are technical standards and how do they benefit the UK?
Global technical standards set out good practice that can be consistently applied to ensure that products, processes and services perform as intended - safely and efficiently. They are generally voluntary and developed through an industry-led process in global standards developing organisations, based on the principles of consensus, openness, and transparency, and benefiting from global technical expertise and best practice. For example, technical standards are referenced alongside regulatory tools in the UK's digital identity and attributes trust framework (2021), which represents a cohesive set of rules for digital identity services.

We want global technical standards for AI to benefit UK citizens, businesses, and the economy by:

Supporting R&D and Innovation. Technical standards should provide clear definitions and processes for innovators and businesses, lowering costs and project complexity and improving product consistency and interoperability, supporting market uptake.

Supporting trade. Technical standards should facilitate digital trade by minimising regulatory requirements and technical barriers to trade.

Giving UK businesses more opportunities. Standardisation is a co-creation process that spans different roles and sectors, providing businesses with access to market knowledge, new customers, and commercial and research partnerships.

Delivering on safety, security and trust. The Integrated Review set out the role of technical standards in embedding transparency and accountability in the design and deployment of technologies. AI technical standards (e.g. for accuracy, explainability and reliability) should ensure that safety, trust and security are at the heart of AI products and services.

Supporting conformity assessments and regulatory compliance. Technical standards should support testing and certification to ensure the quality, performance, reliability of products before they enter the market. This includes providing a means of compliance with requirements set out in legislation.

The UK is taking a global approach to shaping technical standards for AI trustworthiness, seeking to embed accuracy, reliability, security, and other facets of trust in AI technologies from the outset. The government's work to date on AI technical standards with international partners, industry, and other stakeholders provides a potential foundation to complement our governance and regulatory approach.

Domestically, the government has established a strategic coordination initiative with the British Standards Institution (BSI) and the National Physical Laboratory to explore ways to step up the UK's engagement in global standards developing organisations.[footnote 52] The government is also exploring with stakeholders to:

Pilot an AI Standards Hub to expand the UK's international engagement and thought leadership; and

Develop an AI standards engagement toolkit to guide multidisciplinary UK stakeholders to engage in the global AI standardisation landscape.

Internationally, the government is:

Increasing bilateral engagement with partners, including strengthening coordination and information sharing.

Bringing together conversations at standards developing organisations and multilateral fora. BSI and the government are members of the Open Community for Ethics in Autonomous and Intelligent Systems (OCEANIS), which unites global SDOs, businesses, and research institutes.

Engaging in the OECD's Network of Experts Group on Implementing Trustworthy AI, collaborating with governments, academics, and experts to build guidance.

Promoting the 2021 Carbis Bay G7 Leaders' Communiqué, on supporting inclusive, multi-stakeholder approaches to standards development, by ensuring our UK approach to AI standards is multidisciplinary, and encourages a wide set of stakeholders in standards developing organisations.

The UK is leading the way on AI technical standards internationally
The UK's global approach to AI standardisation is exemplified by our leadership in the International Organisation for Standardisation and International Electrotechnical Commission (ISO/IEC) on four active AI projects, as well as the UK's initiation of and strong engagement in the Industry Specification Group on Securing AI at the European Telecommunications Standards Institute (ETSI).

At ISO/IEC, the UK, through BSI, is leading the development of AI international standards in concepts and terminology; data; bias; governance implications; and data life cycles. At ETSI we have published, among other documents, ETSI GR SAI 002 on Data Supply Chain Security, which was led by the UK's National Cyber Security Centre.

The ISO/IEC work programme includes the development of an AI Management System Standard (MSS), which intends to help solve some of the implementation challenges of AI. This standard will be known as ISO/IEC 42001 and will help an organisation develop or use artificial intelligence responsibly in pursuing its objectives, and deliver its expected obligations related to interested parties.

AI Assurance

Understanding whether AI systems are safe, fair or are otherwise trustworthy requires measuring, evaluating and communicating a variety of information, including how these systems perform, how they are governed and managed, whether they are compliant with standards and regulations, and whether they will reliably operate as intended. AI assurance will play an important enabling role, unlocking economic and social benefits of AI systems.
What is Assurance?
Assurance covers a number of governance mechanisms for third parties to develop trust in the compliance and risk of a system or organisation.Assurance as a service draws originally from the accounting profession, but has since been adapted to cover many areas such as cyber security, product safety, quality and risk management.

In these areas, mature ecosystems of assurance products and services enable people to understand whether systems are trustworthy and direct their trust or distrust appropriately. These products and services include: process and technical standards; repeatable audits; impact assessments; certification schemes; advisory and training services.

An AI assurance ecosystem is emerging within both the public and private sectors, with a range of companies including established accountancy firms and specialised start-ups, beginning to offer assurance services. A number of possible assurance techniques[footnote 53] have been proposed and regulators are beginning to set out how AI might be assured (for example, the ICO's Auditing Framework for AI).

However, the assurance ecosystem is currently fragmented and there have been several calls for better coordination, including from the Committee on Standards in Public Life and the Office for Statistics Regulation. The CDEI's recently published review into bias in algorithmic decision-making also points to the need for an ecosystem of industry standards and professional services to help organisations address algorithmic bias in the UK and beyond.

Playing this crucial role in the development and deployment of AI, assurance is likely to become a significant economic activity in its own right and is an area in which the UK, with particular strengths in legal and professional services, has the potential to excel.

To support the development of a mature AI assurance ecosystem, the CDEI is publishing an AI assurance roadmap. This roadmap clarifies the set of activities needed to build a mature assurance ecosystem and identifies the roles and responsibilities of different stakeholders across these activities.

Public sector as an exemplar

The government must lead from the front and set an example in the safe and ethical deployment of AI. The Office for AI and the Government Digital Service worked with The Alan Turing Institute to produce guidance on AI ethics and safety in the public sector in 2019. This guidance identifies the potential harms caused by AI systems and proposes measures to counteract them. The government is working with The Alan Turing Institute to update this guidance in order to provide public servants with the most current information about the state of the art in responsible AI innovation. This update incorporates the delivery of interactive workbooks aimed to equip public sector stakeholders with the practical tools and skills needed to bring the content of the original guidance to life.[footnote 54]

The Ministry of Defence is moving quickly against a fast-evolving threat picture to secure the benefits of these transformative technologies. The Ministry of Defence has rigorous codes of conduct and regulation which uphold responsible AI use, and is working closely with the wider government on approaches to ensure clear alignment with the values and norms of the society we represent.

As the CDEI conducts its ongoing work to address bias in algorithmic decision-making, the Commission on Race and Ethnic Disparities recommended that a mandatory transparency obligation be placed on all public sector organisations applying algorithms that have an impact on significant decisions affecting individuals, highlighting the importance of stewarding AI systems in a responsible manner to increase overall trust in their use.

To ensure that citizens have confidence and trust in how data is being processed and analysed to derive insights, the Central Digital and Data Office (CDDO) is conducting research with a view to developing a cross-government standard for algorithmic transparency in line with the commitment in the National Data Strategy.

The CDDO work is being conducted collaboratively with leading organisations in AI and data ethics and it has been informed by a range of public engagement processes. To date, no other country has developed a standard for algorithmic transparency at a national level. Proactive transparency in this field will be an extension of the UK's long standing open data and data ethics leadership.

AI risk, safety, and long-term development

The government takes the long term risk of non-aligned Artificial General Intelligence, and the unforeseeable changes that it would mean for the UK and the world, seriously.

There are also risks, safety and national security concerns that must be considered here and now - from deepfakes and targeted misinformation from authoritarian regimes, to sophisticated attacks on consumers or critical infrastructure. As AI becomes increasingly ubiquitous, it has the potential to bring risks into everyday life, into businesses and into national security and defence. So as AI becomes more general and is simply used in more domains, we must maintain a broad perspective on implications and threats, with the tools to understand its most subtle impacts, and ensure the UK is protected from bad actors using AI, as well as risks inherent in unsafe future versions of the technology itself. The Office for AI will coordinate cross-government processes to accurately assess long term AI safety and risks, which will include activities such as evaluating technical expertise in government and the value of research infrastructure. Given the speed at which AI developments are impacting our world, it is also critical that the government takes a more precise and timely approach to monitoring progress on AI, and the government will work to do so.

The government will support the safe and ethical development of these technologies as well as using powers through the National Security & Investment Act to mitigate risks arising from a small number of potentially concerning actors. At a strategic level, the National Resilience Strategy will review our approach to emerging technologies; the Ministry of Defence will set out the details of the approaches by which Defence AI is developed and used; the National AI R&I Programme's emphasis on AI theory will support safety; and central government will work with the national security apparatus to consider narrow and more general AI as a top-level security issue.

Pillar 3 - Governing AI Effectively

Actions:

1. Develop a pro-innovation national position on governing and regulating AI, which will be set out in a White Paper, to be published in early 2022.

2. Publish the CDEI AI assurance roadmap and use this to continue work to develop a mature AI assurance ecosystem in the UK.

3. Pilot an AI Standards Hub to coordinate UK engagement in AI standardisation globally, and explore with stakeholders the development of an AI standards engagement toolkit to support the AI ecosystem to engage in the global AI standardisation landscape.

4. Continue our engagement to help shape international frameworks, and international norms and standards for governing AI, to reflect human rights, democratic principles, and the rule of law on the international stage.

5. Support the continuing development of new capabilities around trustworthiness, acceptability, adoptability, and transparency of AI technologies via the national AI Research and Innovation Programme.

6. Publish details of the approaches which the Ministry of Defence will use when adopting and using AI.

7. Develop a cross-government standard for algorithmic transparency.

8. Work with The Alan Turing Institute to update the guidance on AI ethics and safety in the public sector.

9. Coordinate cross-government processes to accurately assess long term AI safety and risks, which will include activities such as evaluating technical expertise in government and the value of research infrastructure.

10. Work with national security, defence, and leading researchers to understand how to anticipate and prevent catastrophic risks.

Next steps

The National AI Strategy proposes three core pillars which, taken together, are areas the UK can make the biggest impact to set the country on its way to being an AI and science superpower fit for the coming decade.

By their nature, strategies are a response to the moment in which they exist - further actions will also be required to elaborate on the paths set out in this document in a way that responds to the fast-changing landscape in the years to come. A plan to execute against the vision set out in this strategy will be published in the near future. Alongside this, we will put mechanisms in place to monitor and assess progress.

We will publish a set of quantitative indicators, given the far-ranging and hard-to-define impacts AI will have on the economy and society. We will publish these indicators separately to this document and at regular intervals to provide transparency on our progress and to hold ourselves to account. Given the cross-cutting nature of AI, collaboration across a wide range of sectors and stakeholders will be paramount. The Office for AI will be responsible for overall delivery of the strategy, monitoring progress and enabling its implementation across government, industry, academia and civil society.

We will also continue talking with the wider community to get their feedback on AI in the UK. Taken together, this quantitative analysis and qualitative intelligence will enable us to track progress and course-correct if we are at risk of falling short in any particular area.

The government's AI Council, an independent expert group formed to represent high-level leadership of the UK's AI ecosystem, has played a key role in reaching a National AI Strategy and informing its direction. As we move into an implementation phase, the AI Council will continue to help galvanise action from across the ecosystem in fulfilling our objectives and holding the government to account on the actions contained in the strategy. The recently established Office for Science and Technology Strategy, National Science and Technology Council and National Technology Adviser will work with the rest of government to drive forward Whitehall's science and technology priorities from the centre. As a part of this, we will collectively identify the technological capabilities required in the UK and in the government to deliver the Prime Minister's global science superpower ambitions through AI.

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Over the next ten years, the impact of AI on businesses across the UK and the wider world will be profound - and UK universities and startups are already leading the world in building the tools for the new economy.

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무선 충전 마우스 만들기

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근자에 방 정리하면서 안쓰던 무선 마우스를 찾았습니다. 전 무선 마우스가 유선 마우스보다 모든 점에서 좋습니다만... 단 한 가지, 배터리 바꾸는게 너무 귀찮았습니다. 꼭 필요할 때 집에 남는 배터리가 없다던지, 충전지는 어딨는지 보이질 않고... 그래서 언제부턴가 집에서는 유선 마우스만 사용했습니다.

문득 예전에 구매한 무선충전 모듈이 생각났습니다. 아래 사진에 있는 모듈인데 송신부에 5~12V 입력해주면 수신부에 무선으로 5V가 유도됩니다. 이걸 이용하면 무선 마우스를 무선 충전으로 사용할 수 있을 것 같더군요. 그래서 한 번 만들어 봤습니다. 고급스런 무선 충전 마우스 DIY.

동작방식

마우스에 1.5V 건전지 2개가 들어가니까 3V로 동작할테고, 그러면 리튬폴리머 LiPo 배터리를 달아서 전원을 공급하면 되겠네요. 그리고 LiPo 배터리를 충전하기 위해 충전 모듈을 달고, 무선 충전 모듈의 수신부를 연결해주면 되겠습니다.

평소 배터리가 충전되어 있는 상태에서는 원하는 대로 사용하다가, PC 사용을 마쳤을 때 무선 충전 송신부가 있는 패드 - 마우스 파킹 패드에 올려두기만 하면 자동으로 내장된 LiPo 배터리가 충전되도록 만드는게 목표입니다.

준비물

무선 마우스, 무선 충전 모듈 (송신부, 수신부), LiPo 충전 모듈, LiPo 배터리, 5~12V 전원을 준비합니다. 추가로 납땜을 위한 도구와 점퍼선, 니퍼, 커터칼, 절연용 테이프 등을 준비해 둡니다.

아래 사진의 부품들이 실제 마우스에 탑재될 부품들 입니다.

조립

1. 마우스 분해

먼저 무선 마우스를 분해합니다. 대개 아래 사진과 비슷한 모양으로 되어 있습니다. 1.5V 건전지 삽입하는 부분을 떼어내고 여기에 부품들을 탑재하면 되겠습니다. 그리고 빨간색, 검은색 라인으로 +, - 전원을 공급해주면 됩니다. DIY 하실 마우스 상태를 보고 부품이 들어갈 공간을 적당히 확보하시면 되겠습니다.

2. 부품 연결 방법

LiPo 배터리를 충전하기 위해서 충전 모듈을 사용합니다. 아래 모듈인데, 충전과 동시에 전원도 빼 쓸 수 있는 모듈을 선택해야 합니다. LiPo 충전 모듈에 대한 자세한 내용은 링크를 참고하세요. 이 모듈은 충전 뿐 아니라 과충전과 과방전으로부터 배터리를 보호해 줍니다.

왼쪽의 +, - 패드가 충전을 위한 외부 전원(5V) 입력용 입니다. 여기에 무선 충전 모듈 수신부를 연결해주면 됩니다.

오른쪽의 B+, B- 패드가 LiPo 배터리 연결용입니다. 여기에 LiPo 배터리의 +, - 라인을 연결해주면 됩니다.

오른쪽의 OUT+, OUT- 패드가 LiPo 배터리에서 전원을 빼내는 곳입니다. 여기에 마우스의 건전지 연결 라인을 연결해주면 됩니다.

3. 부품 연결

납땜 작업으로 부품들을 연결합니다. 전 배터리 쪽에 스위치도 하나 연결해 뒀습니다.

이제 실제 무선으로 충전이 되는지 테스트 할 차례입니다. 아래와 같이 무선 충전 모듈의 송신부를 준비합니다. 전 파워 서플라이를 12V로 맞춰 사용했습니다만, 안쓰는 충전기를 찾아서 활용하셔도 좋겠습니다.

이제 송신부와 수신부를 가깝게 위치시켜서 배터리가 충전되는지 (충전 모듈에 붉은색 LED 켜짐, 완충시 파란색 LED 켜짐), 이 상태에서 마우스 포인터가 동작하는지 확인합니다.

동작이 잘 된다면 이제 마무리만 하면 됩니다!!

(위 사진에서 나온 마우스가 고장난 마우스란 사실을 뒤늦게 알고 다른 마우스로 교체했습니다. 그래서 아래서부터는 검은색 마우스가 등장합니다;;)

4. 조립 및 마무리

이제 부품들을 마우스 내부에 수납해야 합니다.

먼저 마우스 내부 건전지가 탑재되는 부분을 없애서 공간을 확보합니다. LiPo 배터리와 모듈들이 절연되도록 테이프로 감싸고 우겨 넣습니다. 무선 충전 모듈 수신부가 바닥에 위치하도록 합니다. 송신부와 거리가 가까워야 충전 효율이 좋아지니까요. 위치를 잡고나면 글루건으로 고정시켜줍니다.

다시 한번 무선 충전이 잘 되는지 확인!!

뚜껑을 덮어서 마무리!!

5. 파킹 패드 제작

이제 무선 충전을 위해 마우스를 올려둘 파킹 패드를 만듭니다. 무선 충전 모듈 송신부를 마우스 패드 밑에 깔아두면 됩니다!

완성!!

이 글은 무선 충전 마우스를 이용해서 작성되었습니다. :)
참고자료

# data[].attributes.attachment_link.title
무선 충전 마우스 만들기

# data[].attributes.attachment_link.description
근자에 방 정리하면서 안쓰던 무선 마우스를 찾았습니다. 전 무선 마우스가 유선 마우스보다 모든 점에서 좋습니다만... 단 한 가지, 배터리 바꾸는게 너무 귀찮았습니다. 꼭 필요할 때 집에 남는 배터리가 없다던지, 충전지는 어딨는지 보이질 않고... 그래서 언제부턴가 집에서는 유선 마우스만 사용했습니다. 문득 예전에 구매한 무선충전 모듈이 생각났습니다.

# data[].attributes.attachment_link.readable_text
푸로젝트 대신 음식점 코로나 방지 칸막이를

만들어 보기로 했습니다.

제가 자주가는 음식점에 칸막이가 없어 하나 만들어 기부하기로...

제가 개발하는 일이 있어 작업실이 있는

포천 작업장에 못 가고 다른곳에서 일을하고 있어

디자인만 진행하고 화요일 자를 겁니다.

일단 아크릴로 그 크기를 대략 정하기로 하였습니다.

음식점 식탁크기를 메모한 노트북을 참조로

이러한 현장의 데이터를 이용하여 그려 나갑니다.

이 크기는 음식점 테이블의 크기를 고려해서 만들었습니다.

일단 요정도롤 대략적인 스케치가 끝났으면 다음 단계 디자인으로 넘어갈까 하는데

일단 dxf파일 올립니다.

# data[].attributes.attachment_link.description
푸로젝트 대신 음식점 코로나 방지 칸막이를 만들어 보기로 했습니다. 제가 자주가는 음식점에 칸막이가 없어 하나 만들어 기부하기로... 제가 개발하는 일이 있어 작업실이 있는 포천 작업장에 못 가고 다른곳에서 일을하고 있어 디자인만 진행하고 화요일 자를 겁니다. 일단 아크릴로 그 크기를 대략 정하기로 하였습니다. 음식점 식탁크기를 메모한 노트북을 참조로 이러한 현장의 데이터를 이용하여 그려 나갑니다.

# data[].attributes.attachment_caption
집 하루에 뚝딱, 이산화탄소는 2t 감축... ESG에 '3D프린터' 부활

# data[].attributes.attachment_link.title
집 하루에 뚝딱, 이산화탄소는 2t 감축... ESG에 '3D프린터' 부활

# data[].attributes.attachment_link.description
집 하루에 뚝딱, 이산화탄소는 2t 감축 ESG에 3D프린터 부활 기존보다 산업폐기물 대폭 줄고 이산화탄소 줄이는 효과도 커 자동차 엔진의 볼트 총무게 5㎏을 3D프린터 이용해 절반으로 줄여 바이오잉크로 신약 개발에 쓰이는 인공장기를 만드는 기술도 개발중 미국 건설회사

# data[].attributes.attachment_caption
라즈베리파이 프로젝트 - 스마트미러 만들기

# data[].attributes.attachment_link.readable_text
라즈베리파이 3B+ 보드 기반의 스마트미러 만들기 관련한

유용한 유튜브 강좌가 있어 링크를 남깁니다.

:=> https://www.youtube.com/watch?v=JUaybGZuPPg&list=PLgkpDfSY2BezVKrDcCP-yaJJt_xdUlica&index=2

강의 내용을 요약하면 하기와 같습니다.

총 13강의 강의인데 각 강의에서 사용된 명령을 남겨봅니다.
#1 MagicMirror 설치/ 자동실행 설정
1. 매직미러 설치 (04:53) 1.1 curl -sL https://deb.nodesource.com/setup_10.x | sudo -E bash - ★1.1의 내용을 바로 복사하면 터미널에서 이상하게 인식이 되니, 메모장에 한번 복사 후, 그것을 다시 복사해서 터미널에 붙여주세요^^ 1.2 sudo apt install -y nodejs 1.3 git clone https://github.com/MichMich/MagicMirror 1.4 cd MagicMirror/ 1.5 npm install (상당히 오래걸립니다) 1.6 cp config/config.js.sample config/config.js 1.7 npm run start 1.8 Ctrl + Q 누르면 빠져나옴 1.9 cd .. 으로 이전폴더로 2. 매직미러 자동실행 설정 (07:38) 2.1 sudo npm install -g pm2 2.2 pm2 startup 2.3 sudo env PATH=$PATH:/usr/bin /usr/lib/node_modules/pm2/bin/pm2 startup systemd -u pi --hp /home/pi 2.4 cd ~ 2.5 sudo nano mm.sh 2.6 mm.sh에 추가 cd ./MagicMirror DISPLAY=:0 npm run start 2.7 sudo chmod +x mm.sh 2.8 pm2 start mm.sh 2.9 pm2 save 2.10 자동실행을 해제하려면 원격(ssh, xrdp)으로 들어가서 pm2 stop mm pm2 save 를 각각 입력하면 됨
#2 스마트미러를 위한 라즈베리파이 설정
1. 화면설정 1.1 OpenGL driver 설정 (라즈베리파이 3만) (01:05) 1.1.1 터미널에서 sudo raspi-config 입력 (01:19) 1.1.2 Advanced options - GL Driver - GL (Full KMS) OpenGL desktop driver with full KMS 선택 1.1.3 sudo reboot으로 재부팅 1.2 화면 회전 (직접 모니터 연결해서 해야 함) (03:28) 1.2.1 시작버튼 - 기본설정 - Screen Configuration (03:33) 1.2.2 Configure - Screens - HDMI-1 - 방향 - 원하는 방향 선택 (03:50) 1.2.3 Configure - 적용 1.2.4 재부팅해도 적용이 유지 2. 화면보호기 끄기 2.1 터미널에서 sudo apt-get install xscreensaver (05:38) 2.2 시작버튼 - 기본설정 - 화면보호기 (06:23) 2.3 disable (06:50) 3. wifi 절전모드 해제(07:37) 3.1 iwconfig 입력해서 power management: off인지 확인 3.2 sudo nano /etc/rc.local 3.3 exit 0 바로 윗줄에 /sbin/iwconfig wlan0 power off 추가 3.4 sudo reboot으로 재부팅 3.5 iwconfig 입력해서 power management: off인지 확인
#3 한글설정 / 지역별 날씨 설정
1. 한글 설정 1.1 터미널에서 geany MagicMirror/config/config.js (02:04) 1.2 화면 바로 중간의 "en"을 "ko"로 바꿈 (02:46) 1.3 cd ~, cd MagicMirror, npm start를 입력하여 잘 나오나 확인(확인 후 cd .. 필수) (03:10) 2. 날씨 2.1 https://openweathermap.org/ 에 가입 (03:52) 2.2 로그인 후 계정 - My API Keys 에서 API Key를 복사 (05:29) 2.3 https://drive.google.com/file/d/1k5VJ... 를 다운받아 지역 검색 (05:48) 2.4 터미널에서 geany MagicMirror/config/config.js (07:04) 2.5 중간쯤 Current weather에 지역 ID(숫자)와 appid(API KEY) 입력 (08:02) 2.6 config 윗줄에 header: "현재 날씨", 추가 2.7 바로 아래 weatherforecast에 지역 ID(숫자)와 appid(API KEY) 입력 2.8 header를 header: "날씨 예보", 로 수정 2.9 cd ~, cd MagicMirror, npm start를 입력하여 잘 나오나 확인(확인 후 cd .. 필수) (10:34) 2.10 잘 안될때 geany MagicMirror/config/config.js 의 module 부분부터 (11:32) modules: [ { module: "alert", }, { module: "updatenotification", position: "top_bar" }, { module: "clock", position: "top_left" }, { module: "calendar", header: "US Holidays", position: "top_left", config: { calendars: [ { symbol: "calendar-check", url: "webcal://www.calendarlabs.com/ical-calendar/ics/76/US_Holidays.ics" } ] } }, { module: "compliments", position: "lower_third" }, { module: "currentweather", position: "top_right", header: "현재 날씨", config: { location: "Seoul", locationID: "1835847", //ID from http://bulk.openweathermap.org/sample... unzip the gz file and find your city appid: "여러분의 API ID" } }, { module: "weatherforecast", position: "top_right", header: "날씨 예보", config: { location: "Seoul", locationID: "1835847", //ID from http://bulk.openweathermap.org/sample... unzip the gz file and find your city appid: "여러분의 API ID" } }, { module: "newsfeed", position: "bottom_bar", config: { feeds: [ { title: "New York Times", url: "https://rss.nytimes.com/services/xml/..." } ], showSourceTitle: true, showPublishDate: true, broadcastNewsFeeds: true, broadcastNewsUpdates: true } }, ]
#4 구글 캘린더 연동 / 뉴스 설정
1. 구글캘린더 연동 1.1 크롬을 열어서 오른쪽 위 ::: 클릭 - 캘린더 선택 (00:51) 1.2 왼쪽 내 캘린더 아래에 이름 오른쪽 : 클릭 후 설정 및 공유 선택 (01:10) 1.3 맨 밑의 비공개 형식 주소 복사해서 기록해둠 (01:23) 1.4 라즈베리파이 터미널에서 geany MagicMirror/config/config.js (02:24) 1.5 calander 부분에서 header를 header: "나의 일정", 로 수정 (02:50) 1.6 url에는 아까 복사해둔 달력주소를 붙여넣음 (03:07) 2. 뉴스 설정 2.1 구글에서 '뉴스 RSS 주소 모음' 검색 후 원하는 뉴스의 RSS 주소 복사해둠 (05:28) 2.1.1 구글뉴스 RSS 주소: "https://news.google.com/news/rss/?ned..." 2.2 라즈베리파이 터미널에서 geany MagicMirror/config/config.js (06:06) 2.3 module newfeed에서 title을 원하는 이름으로 해둠 (06:23) 2.4 url은 아까 복사해둔 RSS주소를 붙여넣음
#5 미세먼지 모듈 설치/설정
1. 미세먼지 모듈 설치 1.1 터미널에서 cd ~/MagicMirror/modules 1.2 git clone https://github.com/CFenner/MMM-AirQuality 2. 미세먼지 모듈 배치 2.1 https://aqicn.org/search 에 방문해서 도시이름 검색 2.2 주소 중 city/ 뒷부분을 복사해둠 2.3 cd MMM-AirQuality 2.4 npm install 2.5 터미널에서 geany MagicMirror/config/config.js 2.6 하단에서 첫번째 윗줄에 커서를 대고 { module: 'MMM-AirQuality', position: 'top_left', config: { location: 'seoul', lang: "kr" } }, 를 복사해서 붙임
#6 모듈 위치변경/삭제, 원하는 주제로 뉴스RSS 주소 만들기
1. 모듈 위치 바꾸기 (01:06) 1.1 터미널에서 geany MagicMirror/config/config.js 1.2 module: "모듈이름" 바로 아랫줄의 position: "위치"를 바꿈 1.3 바꿀 위치는 https://drive.google.com/file/d/1GFVL... 을 참조 2. 모듈 삭제하기 (03:43) 2.1 터미널에서 geany MagicMirror/config/config.js 2.2 삭제할 모듈을 드래그하여 삭제, 또는 주석처리 3. 나만의 뉴스 RSS 주소 만들기 (05:59) 3.1 https://www.google.co.kr/alerts (구글에서 구글알리미 검색)으로 접속 3.2 검색창에 원하는 검색어 입력 후 옵션 더보기 3.3 수신 위치를 RSS 피드로 설정 3.4 부채모양 오른클릭 - 링크 복사 3.5 터미널에서 geany MagicMirror/config/config.js (07:18) 3.6 newsfeed 의 title, url 추가 3.7 여러개를 쓰고싶으면 {} 로 구분
#7 마이크/스피커 연결 및 설정
1. (02:00) 이 과정은 복사/붙여넣기를 해야 편하므로 ssh로 원격연결하여 하는 것이 편함. 라즈베리파이에 모니터를 직접 연결하여 터미널에서 작업해도 상관없음 2. (02:28) 현재 xrdp 원격 터미널에서 ifconfig 입력하여 내부아이피(192.168.xxx)를 기록해둠 3. (03:03) 시작메뉴 - 기본설정 - raspberrypi configuration 선택 4. (03:13) interfaces - ssh 활성화 후 끔 5. (03:41) 윈도우로 돌아와서 putty 다운로드 후 설치 6. (04:27) putty를 실행해서 라즈베리파이 내부아이피를 입력하여 ssh 접속 7. (06:49) aplay -l 로 스피커의 카드번호, 디바이스 번호 적어둠 (카드 3, 디바이스 0) 8. (07:48) arecord -l 로 마이크의 카드번호, 디바이스 번호 적어둠 (카드 3, 디바이스 0) 9. (08:57) sudo nano .asoundrc 를 입력. 빈화면이 나오면 정상 10.1 (09:22) USB 마이크 + 3.5mm 스피커의 경우 pcm.!default{ type asym playback.pcm{ type hw card 0 } capture.pcm{ type plug slave.pcm "hw:1, 0" } } ctl.!default{ type hw card 0 } 를 입력, 이때 hw:1, 0 부분을 마이크의 카드번호와 디바이스번호로 수정 후 저장 10.2 (10:26) USB 마이크 + 스피커 동시연결인 경우 pcm.!default { type asym capture.pcm "mic" playback.pcm "speaker" } pcm.mic { type plug slave { pcm "hw:1,0" } } pcm.speaker { type plug slave { pcm "hw:1,0" } } 를 입력, 이때 hw:1, 0 부분을 mic(마이크), speaker(스피커)의 카드번호, 디바이스번호로 수정 후 저장 11. (11:16) speaker-test -t wav 를 입력하여 스피커가 잘 나오는지 확인 12. (11:50) arecord --format=S16_LE --duration=5 --rate=16000 --file-type=raw test.raw 를 입력하고 5초간 마이크에 대고 소리를 냄 13. (12:14) aplay --format=S16_LE --rate=16000 test.raw 를 입력하여 녹음된 소리가 잘 나오는지 확인 14. (12:34) 소리가 작거나 크다면 alsamixer로 조절
#8.5 구글 어시스턴트 모듈 업데이트/알림 끄기
1. (01:17) ssh에서 작업 1.1 (01:30) cd ~/MagicMirror/modules 1.2 (01:40 git clone https://github.com/bugsounet/MMM-GoogleAssistant 1.3 (02:08) cd MMM-GoogleAssistant 1.4 (02:16) npm install 1.5 뭔가 물으면 y를 눌러줌 1.6 (03:02) 스피커, 마이크를 테스트할때, 마이크의 plughw 번호는 꼭 기록해둬야 함 2. (04:34) 윈도우에서 작업 2.1 (04:38) https://console.actions.google.com/ 에 접속 2.2 (05:08) new project 선택 2.3 (05:56) 맨 하단 Device registration 선택 2.4 (06:18) 내용 입력 후, type은 스피커로 선택 2.5 (06:48) OAuth 2.0 credentials 파일을 다운받아 라즈베리파이에 복사(xrdp 혹은 USB 메모리 이용) 2.6 (07:42) 파일을 MMM-GoogleAssistant 폴더에 옮겨주고 이름을 credentials.json 으로 바꿔줌 2.7 (08:38) 다음단계는 skip을 눌러줌 2.8 (08:46) https://console.cloud.google.com/ 에 접속 2.9 (09:12)프로젝트 검색에 프로젝트 이름을 넣어서 찾아 선택 2.10 (09:31) 좌측 탐색메뉴 - API 및 서비스 - 라이브러리 2.11 (09:40) google assistant API 검색 - 사용 2.12 (10:04) 좌측 사용자 인증 정보 - 동의 화면 구성 2.13 (10:15) 외부 - 만들기 2.14 (10:25) 중, 하단 지원 email과 개발자 연락처 정보에 email 적고 저장 후 계속 2.15 (10:45) 저장 - 저장 - 저장 눌러서 대시보드로 돌아가기 2.16 (10:56) 대시보드에서 테스트 사용자 +ADD USERS 누름 2.17 (11:03) 사용중인 email 등록 후 저장 3. (11:21) xrdp 에서 작업 3.1 (11:27) 터미널에서 cd MagicMirror/modules/MMM-GoogleAssistant 3.2 (11:48) node auth_and_test.js 입력 3.3 (12:01) 인터넷 창이 뜨면 로그인해줌 3.4 (12:22)계속 - 허용 - 허용 눌러줌 3.5 (12:37) 코드를 복사해서 Ctrl + Shift + v 로 붙여줌 3.6 (12:51) 아무 말이나 써줌 대답이 오면 성공! 3.7 (13:15) cd ~ 로 홈폴더로 이동 3.8 (13:19) geany MagicMirror/config/config.js 3.9 (13:47) 모듈리스트 맨 하단에 { module: "MMM-GoogleAssistant", position: "fullscreen_above", config: { assistantConfig: { lang: "ko-KR", latitude: 37.33, longitude: 126.59, }, micConfig: { // put there configuration generated by auto-installer recorder: "arecord", device: "plughw:3", // 아까 기록해둔 plughw 번호로 수정 }, snowboy: { audioGain: 2.0, Frontend: true, Model: "jarvis", Sensitivity: null }, } }, 붙여줌

cd ~/MagicMirror/modules/MMM-GoogleAssistant

하면 코드를 입력하기를 기다리는 상태가 된다. 웹브라우저가 자동으로 열리면서 인증과정을 거친다.

다시 구글 클라우드 플랫폼으로 가보자,

앱게시 버튼 을 누르자. 공개를 해야 동작이 되도록 한 모양이다. 이게 싫으면 아래 테스트 사용자를 추가해서 테스트 버전으로 사용도 가능한듯 하다. 다시 토큰 생성을 시도해 본다.

두번의 권한 승인에 허용으로 해주면 마지막에 코드가 출력된다. 이값을 복사해서 터미널에 코드 넣어 라고 기다리는 곳에 붙여 넣기 해주면 된다.

새로 추가된 기능 같은데 기타 유튜브나 구글 포토에 관한 토큰을 생성할지 물어 온다. 필요하면 하고 아니면 n 하면 된다. 이렇게 하면 모든 설치가 완료 된다.

(추가3)

Wake word 나 콜사인/Call sign 을 구글어시스턴트나 알렉사에서

"자비스" 나 "Ok, Google" 등으로 설정하기 위해

최신 MagicMirror 모듈에서 MMM-Detector를 사용하는 것으로 변경되었습니다.

하기 링크 참고하세요.

:=> http://wiki.bugsounet.fr/en/MMM-Detector

:=> https://github.com/bugsounet/MMM-Detector
#9 인체감지센서 연동
1. (01:22) 인체감지센서 연결 1.1 인체감지센서는 HC-SR501 사용(2,000원) 1.2 센서의 감도조절 나사는 모두 최소한도로 시작 후 변경 권장 1.3 인체감지센서의 5V는 라즈베리파이의 위쪽 왼쪽 1번째, GND는 아래쪽 왼쪽에서 5번째 1.4 인체감지센서의 OUT은 라즈베리파이의 아래쪽 왼쪽에서 8번째에 연결 2. (05:16) 인체감지센서 모듈 설치 2.1 (05:21) 터미널에서 cd MagicMirror/modules 2.2 (05:33) git clone https://github.com/paviro/MMM-PIR-Sen... ★ 2.2번은 본문에서 바로 복사하면 이상하게 복사되니 메모장에 한번 복사 후 다시 복사해주세요 ★ 텍스트파일로 보시는 경우에는 그냥 복사하셔도 됩니다 2.3 (05:40) cd MMM-PIR-Sensor 2.4 (05:49) npm install 2.5 (06:00) sudo usermod -a -G gpio pi 2.6 (06:06) sudo chmod u+s /opt/vc/bin/tvservice && sudo chmod u+s /bin/chvt 2.7 (06:18) sudo reboot 으로 재부팅 2.8 (06:26) geany MagicMirror/config/config.js 2.9 (06:41) 모듈리스트에 다음을 추가 { module: 'MMM-PIR-Sensor', position: "top_center", // 빨간점이 보기 싫으시면 이줄을 지워주세요 config: { sensorPin: 22, powerSavingDelay: 60, // 60초간 움직임이 없으면 화면이 꺼집니다 preventHDMITimeout: 4, // 4분마다 모니터를 한번씩 켜서 절전모드를 방지합니다 } }
#10 구글포토 연동으로 전자액자 만들기
1. 프로젝트 생성 1.1 (02:07) https://console.actions.google.com/ 에 접속 1.2 (02:16) new project 선택 1.3 (02:47) 맨 하단 Device registration 선택 1.4 (02:55) 내용 입력 후, type은 scene으로 선택 1.5 (03:19) OAuth 2.0 credentials 파일을 다운받아 라즈베리파이에 복사(xrdp 혹은 USB 메모리 이용) 1.6 (03:53) 다음단계는 skip을 눌러줌 1.7 (03:58) https://console.cloud.google.com/ 에 접속 1.8 (04:09) 프로젝트 검색에 프로젝트 이름을 넣어서 찾아 선택 1.9 (04:27) 좌측 탐색메뉴 - API 및 서비스 - 라이브러리 1.10 (04:34) photos library API 검색 - 사용 1.11 (04:50) 좌측 사용자 인증 정보 - 동의 화면 구성 1.12 (05:06) 외부 - 만들기 1.13 (05:11) 하단 중단 지원 email과 개발자 연락처 정보에 email 적고 저장 후 계속 1.14 (05:30) 저장 - 저장 - 저장 눌러서 대시보드로 돌아가기 1.15 (05:41) 대시보드에서 테스트 사용자 +ADD USERS 누름 1.16 사용중인 email 등록 후 저장 2. 전자액자 모듈 설치 2.1 (06:14) 터미널에서 cd MagicMirror/modules 2.2 (06:21) git clone https://github.com/eouia/MMM-GooglePhotos.git 2.3 (06:31) cd MMM-GooglePhotos 2.4 (06:40) npm install 2.5 (06:54) 다운받은 파일을 MMM-GooglePhotos 폴더에 옮겨주고 이름을 credentials.json 으로 바꿔줌 2.6 (08:30) cd ~/MagicMirror/modules/MMM-GooglePhotos 2.7 (08:39) node generate_token.js 2.8 (08:49) 인터넷 창이 뜨면 로그인해줌 2.9 (08:58) 계속 - 허용 - 허용 눌러줌 2.10 (09:13) 코드를 복사해서 Ctrl + Shift + v 로 붙여줌 2.11 (09:32) geany MagicMirror/config/config.js 2.12 (09:37) 모듈리스트에 { module: "MMM-GooglePhotos", position: "fullscreen_below", config: { albums: ["다람쥐"], // 앨범이름을 정확히 써주세요. 예시: ["My wedding", "family share", "Travle to Paris"] updateInterval: 20, // 사진 바꿔주는 시간(최소 10초) sort: "random", // "old", "random" 보여주는 순서 uploadAlbum: null, // Only album created by `create_uploadable_album.js`. condition: { fromDate: null, // Or "2018-03", RFC ... format available toDate: null, // Or "2019-12-25", minWidth: null, // Or 400 maxWidth: null, // Or 8000 minHeight: null, // Or 400 maxHeight: null, // Or 8000 minWHRatio: null, maxWHRatio: null, // WHRatio = Width/Height ratio ( ==1 : Squared Photo, < 1 : Portraited Photo, > 1 : Landscaped Photo) }, showWidth: 1080, // These values will be used for quality of downloaded photos to show. real size to show in your MagicMirror region is recommended. showHeight: 1920, timeFormat: "YYYY/MM/DD HH:mm", // Or `relative` can be used. } }, 2.13 (12:49) cd MagicMirror/css 2.14 (12:57) geany custom.css 2.15 (13:11) 다음을 추가 /* 우측 하단 사진정보를 없애려면 바로 아래 주석 해제 */ /* #GPHOTO_INFO { display:none; } */ /* 배경을 검게하려면 바로 아래 주석 해제 */ /* #GPHOTO_BACK { display:none; } */ /* 시계를 잘보이게 하려면 바로 아래 주석 해제 */ /* .clock { padding: 10px; background-color: rgba(0, 0, 0, 0.5); } */
#11 하프미러 만들기
하프미러(원웨이미러, 매직미러)는 뒷면이 밝으면 뒷면의 모습을 보여주고, 뒷면이 어두우면 거울처럼보이는 것으로 다양한 곳에 많이 활용되고 있습니다.
#12(完) 최종 조립하기/후기
요번편에선 액자틀에 라즈베리파이와 스크린을 조립해보는 방법을 배워보겠습니다.
(추가1) 총12강의 강좌인데 중요한 명령어 부분만 따로 복붙해 보았습니다. 매번 강의를 보면서 확인하기가 불편해서 따로 박제헤 놓습니당~
(추가2)

하기 링크도 매직미러에 구글 Assistant SDK를 적용하고

Wake word를 설정하기 위해 MMM-Detector를 설정하기에 유용한 링크입니다.

:=> https://blog.naver.com/cosmosjs/222394379523

그럼,

공유합니다.

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50 Stem Activities To Help Kids Think Outside the Box

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These days, STEM learning is more important than ever. Science, technology, engineering, and math are the keys to many modern careers, so a good grounding in them from an early age is a must. The best STEM activities are hands-on, leading kids to cool innovations and real-world applications. Here are some of our favorites, with challenges that will really get kids thinking about how STEM plays a part in their everyday lives.

1. Participate in the St. Jude EPIC Challenge

St. Jude's EPIC Challenge gives students a chance to create real-world impact for other kids currently facing cancer. EPIC stands for Experimenting, Prototyping, Inventing, and Creating. Participants come up with innovative ways to help St. Jude kids, following through from concept to creation. Past winners have created comfortable pillows, buddy blankets, and more. Learn about the EPIC Challenge and find out how to join here.

Plus, get a free copy of our engineering and design poster we created together with St. Jude right here.

2. Add STEM bins to your classroom

You can use STEM activities in a wide variety of ways with these cool bins. Incorporate them into literacy centers, create a makerspace, and offer early finishers fun enrichment ideas. Learn how to create and use STEM bins.

3. Conduct an egg drop

This is one of those classic STEM activities every kid should try at least once. Kids can do it at any age, with different materials and heights to mix it up.

Learn more: Buggy and Buddy

4. Engineer a drinking straw roller coaster

This is such a fun way to encourage engineering skills! All you need are basic supplies like drinking straws, tape, and scissors.

Learn more: Straw Roller Coaster/Frugal Fun For Boys and Girls

5. Simulate an earthquake

The ground under our feet may feel solid, but an earthquake changes that pretty quickly. Use Jello to simulate the earth's crust, then see if you can build an earthquake-proof structure.

Learn more: Teaching Science

6. Stand up to a hurricane

In a hurricane zone, houses must be able to stand up to strong winds and possible flooding. Can your students design houses that make it safer to live in these dangerous areas?

Learn more: Carly and Adam

7. Create a new plant or animal

Kids will really get into this project, indulging their creativity as they invent a plant or animal that's never been seen before. They'll need to be able to explain the biology behind it all, though, making this an in-depth project you can tailor to any class.

Learn more: I Love 2 Teach

8. Design a helping hand

This is a great group science project. Students hone their design and engineering skills to make a working model of a hand.

Learn more: Model Hand/Science Buddies

9. Understand the impact of non-renewable resources

Discuss the differences between renewable and non-renewable resources, then have your class form "companies" to "mine" non-renewable resources. As they compete, they'll see how quickly the resources are used. It's a great tie-in to energy conservation discussions.

Learn more: The Owl Teacher

10. Devise an amazing marble maze

Marble mazes are one of students' favorite STEM activities! You can provide supplies like straws and paper plates for their project. Or let them use their imaginations and create marble mazes from any materials they can think of.

Learn more: Marble Maze/Raising Lifelong Learners

11. Fly clothespin airplanes

Ask students what they think the airplane of the future might look like. Then, provide them with clothespins and wood craft sticks, and challenge them to build a new kind of airplane. Bonus points if it can actually fly!

Learn more: STEAMsational/Clothespin Airplane

12. Play catch with a catapult

This take on a classic science project challenges young engineers to build a catapult from basic materials. The twist? They also must create a "receiver" to catch the soaring object on the other end.

Learn more: Catapult Challenge/Science Buddies

13. Bounce on a trampoline

Kids love bouncing on trampolines, but can they build one themselves? Find out with this totally fun STEM challenge.

Learn more: Teach Student Savvy

14. Build a solar oven

Learn about the value of solar energy by building an oven that cooks food without electricity. Enjoy your tasty treats while discussing ways we can harness the energy of the sun and why alternative energy sources are important.

Learn more: Desert Chica

15. Build a snack machine

Incorporate everything students learn about simple machines into one project when you challenge them to build a snack machine! Using basic supplies, they'll need to design and construct a machine that delivers snacks from one location to another.

Learn more: Snack Machine/Left Brain Craft Brain

16. Recycle newspaper into an engineering challenge

It's amazing how a stack of newspapers can spark such creative engineering. Challenge students to build the tallest tower, support a book, or even build a chair using only newspaper and tape!

Learn more: STEM Activities for Kids

17. Design a biosphere

This project really brings out kids' creativity and helps them understand that everything in a biosphere is really part of one big whole. You'll be overwhelmed by what they come up with!

Learn more: Laney Lee

18. See the effects of an oil spill

Learn why an oil spill is so devastating for wildlife and the ecosystem with this hands-on activity. Kids experiment to find the best way to clean up oil floating on water and rescue the animals affected by the spill.

Learn more: Kitchen Counter Chronicles

19. Assemble a steady-hand game

This is such a fun way to learn about circuits! It also brings in a bit of creativity, adding the "A" to STEAM.

Learn more: Steady Hand Game/Left Brain Craft Brain

20. Craft a cell phone stand

Your science students will be thrilled when you let them use their phones in class! Challenge them to use their engineering skills and a small selection of items to design and build a cell phone stand.

Learn more: Science Buddies/Engineer Cell Phone Stand

21. Engineer a craft stick bridge

Here's another one of those classic STEM activities that really challenge kids to use their skills. Build a bridge with popsicle sticks and push pins, and find out which design can bear the most weight.

Learn more: Build a Bridge/Scholastic

22. Forage and build a bird nest

Birds build incredibly intricate nests from materials they find in the wild. Take a nature walk to gather materials, then see if you can build a sturdy, comfy nest of your own!

Learn more: Kids Craft Room

23. Drop parachutes to test air resistance

Use the scientific method to test different types of material and see which makes the most effective parachute. Your students also learn more about the physics behind air resistance.

Learn more: Education.com

24. Find the most waterproof roof

Calling all future engineers! Build a house from LEGO, then experiment to see what type of roof prevents water from leaking inside.

Learn more: Waterproof Roof/Science Sparks

25. Build a better umbrella

Challenge students to engineer the best possible umbrella from various household supplies. Encourage them to plan, draw blueprints, and test their creations using the scientific method.

Learn more: Better Umbrella/Raising Lifelong Learners

26. Go green with recycled paper

We talk a lot about recycling and sustainability these days, so show kids how it's done! Recycle old worksheets or other papers using screen and picture frames. Then, ask kids to brainstorm ways to use the recycled paper.

Learn more: Undercover Classroom

27. Brew up your own slime

Chances are good your students already love making and playing with slime. Turn the fun into an experiment by changing the ingredients to create slime with a variety of properties-from magnetic to glow-in-the-dark!

Learn more: Slime Design/Science Buddies

28. Create a taxonomy system

Students can step into Linnaeus' shoes by creating their own system of taxonomy using a handful of different dried beans. This is a fun science project to do in groups, so students can see the differences between each group's system.

Learn more: Our Journey Westward

29. Find out which liquid is best for growing seeds

As you learn about the life cycle of plants, explore how water supports plants' growth. Plant seeds and water them with a variety of liquids to see which sprout first and grow best.

Learn more: Lessons 4 Little Ones

30. Find the best soap bubble solution

It's easy to mix your own soap bubble solution with just a few ingredients. Let kids experiment to find the best proportion of ingredients to blow the longest-lasting bubbles with this fun outside science activity.

Learn more: Soap Bubbles/Science Buddies

31. Blow the biggest bubbles you can

Add a few simple ingredients to dish soap solution to create the largest bubbles you've ever seen! Kids learn about surface tension as they engineer these bubble-blowing wands.

Learn more: Scholastic/Dish Soap Bubbles

32. Help monarch butterflies

You may have heard that monarch butterflies are struggling to keep their population alive. Join the fight to save these beautiful bugs by planting your own butterfly garden, monitoring monarch populations, and more. Get all the info you need at the link.

Learn more: Monarch Watch

33. See water pollution in action

Learn about the challenges of cleaning up polluted water sources like rivers and lakes with this interesting outdoor science activity. Pair it with a visit to a local water treatment plant to expand the lesson.

Learn more: Water Pollution/JDaniel4's Mom

34. Test your local water quality

Once you've "cleaned up" your water, try testing it to see how clean it really is! Then head out to test other types of water. Kids will be fascinated to discover what's in the water in their local streams, ponds, and puddles. Student water testing kits are readily available online.

Learn more: The Homeschool Scientist

35. Explore with an edible Mars Rover

Learn about the conditions on Mars and the tasks the Mars Rover will need to complete. Then, give kids supplies to build their own. (Add to the challenge by making them "buy" the supplies and stick to a budget, just like NASA!).

Learn more: Library Makers

36. Baked potato science

This edible science project is a nutritious way to explore the scientific method in action. Experiment with a variety of methods for baking potatoes-microwaving, using a traditional oven, wrapping them in foil, using baking pins, etc.-testing hypotheses to discover which works best.

Learn more: Potato Science/Left Brain Craft Brain

37. Waterproof a boot

Ask kids to select various materials and tape them over the free boot printable. Then, test their hypotheses to see which ones work best.

Learn more: Waterproof a Boot/Science Sparks

38. Determine the best way to melt ice

Conventional wisdom says we sprinkle salt on ice to melt it faster. But why? Is that really the best method? Try this science experiment and find out.

Learn more: The Chaos and the Clutter

39. Don't melt the ice

We spend a lot of time in winter trying to get rid of ice, but what about when you don't want the ice to melt? Experiment with different forms of insulation to see which keeps ice frozen the longest.

Learn more: Ice Insulation/Frugal Fun for Boys and Girls

40. Build a straw house

Grab a box of straws and a package of pipe cleaners. Then task kids with designing and building their dream house, using only those two items.

Learn more: Deceptively Educational

41. Design a balloon-powered car

Explore the laws of motion and encourage creativity when you challenge students to design, build, and test their own balloon-powered cars. Bonus: Use only recycled materials to make this project green!

Learn more: Balloon-Powered Cars/Science Buddies

42. Learn map skills by designing an amusement park

For this cross-curricular activity, students investigate the parts of a map by creating an amusement park. After they create their map, they do a detailed drawing and write about one of their ride designs. Then they design an all-access park pass. So many STEM activities in one! Find out more about it here.

43. Reach for the ceiling

Round up all your building blocks and try this whole-class project. What will students need to do to be able to construct a tower that reaches all the way to the ceiling?

Learn more: Mama Smiles

44. Cast a tall shadow

Here's another tower-building challenge, but this one's all about shadows! Kids will experiment with the height of their tower and the angle of their flashlight to see how tall of a shadow they're able to cast.

Learn more: No Time for Flashcards

45. Devise a recycled toy bot

These adorable toy bots are made from pool noodles and recycled electric toothbrushes. So clever! Kids will have fun designing their own, plus they can tweak this idea to make other fun wiggling toys.

Learn more: Artsy Momma

46. Link up the longest paper chain

This incredibly simple STEM activity really gets kids thinking. The challenge? Create the longest possible paper chain using a single piece of paper. So simple and so effective.

Learn more: Paper Chain Challenge/Frugal Fun For Boys and Girls

47. Find out what you can make from a plastic bag

Plastic bags are one of the most ubiquitous items on the planet these days, and they're difficult to recycle. Give each student a plastic bag and ask them to create something new and useful. ( These ideas from Artsy Craftsy Mom offer some inspiration.)

48. Start a school robotics team

Coding is one of the most valuable STEM activities you can include in your classroom plans. Set up a school robotics club and inspire kids to embrace their newfound skills! Learn how to set up your own club here.

49. Embrace the Hour of Code

The Hour of Code program was designed as a way to get all teachers to try just one hour of teaching and learning coding with their students. Originally, the Hour of Code event was held in December, but you can organize yours any time. Then, continue to learn using the huge amount of resources on Hour of Code's website.

50. Give kids a Maker Cart and a pile of cardboard

You don't need a whole lot of fancy supplies to create a STEM Cart or makerspace. Scissors, tape, glue, wood craft sticks, straws-basic items like these combined with a stack of cardboard can inspire kids to all sorts of amazing creations! See how these STEM activities work here.

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50 Stem Activities To Help Kids Think Outside the Box

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Hands-on science is one of the best ways to get kids thinking creatively. These STEM activities are perfect for upper elementary students.

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[코드위즈] AI자율주행 전기차 '위즈오토' 소개영상

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You can write and upload sketches on Chrome OS with the Web Editor in Arduino Cloud. The Web Editor has an extensive feature set similar to the desktop IDE. While many popular boards are compatible, you should check the list of compatible boards here.

Install the Chrome app

1. Go to the Chrome web store page.

2. Click Add to Chrome.

3. Click Add app to confirm.

4. Click Launch app to start the Web Editor or go to create.arduino.cc/editor.

Use the Web Editor

1. Go to create.arduino.cc/editor.

2. If you're not signed into an Arduino account, you will be asked to do so.

3. Connect a compatible board to a USB port on your computer.

4. Select your board in the Boards Dropdown.

5. Start writing a new sketch in the editor, or use a sketch from the Examples sidebar.

Learn more about the Web Editor:

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You can write and upload sketches on Chrome OS with the Web Editor in Arduino Cloud. The Web Editor has an extensive feature set similar to the desktop IDE. While many popular boards are compatible, you should check the list of compatible boards here. Go to the Chrome web store page.