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Microsoft Corporation, Microsoft Way, Redmond, WA, USA

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Microsoft Corporation, Microsoft Way, Redmond, WA, USA

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Microsoft Corporation, Microsoft Way, Redmond, WA, USA

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Netflix, Sunset Boulevard, Los Angeles, CA, USA

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Netflix, Sunset Boulevard, Los Angeles, CA, USA

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Netflix, Sunset Boulevard, Los Angeles, CA, USA

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Company Name: Netflix
Company Location: Los Gatos, California, U.S.
Case: Generic ML use cases at Netflix. For example, Movie-Streaming Services.

Name: Felix Wong Jing Jie

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IBM Campus Tecnológico Guadalajara, El Salto, Jalisco, Mexico

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IBM Campus Tecnológico Guadalajara, El Salto, Jalisco, Mexico

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IBM Campus Tecnológico Guadalajara, El Salto, Jalisco, Mexico

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Baidu
https://www.youtube.com/watch?v=wL3ybtoIp4k&ab_channel=CyrusJanssen

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Baidu: How China became the World Champion in AI

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Spotify, Greenwich Street, New York, NY, USA

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Spotify, Greenwich Street, New York, NY, USA

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Spotify, Greenwich Street, New York, NY, USA

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ByteDance (TikTok)

https://www.forbes.com/sites/roomykhan/2020/09/19/tiktok-why-is-everyone-in-a-tizzy/?sh=3e0ef34b33d5

Carmen

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Pinterest :
https://vimeo.com/575090744

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D&I in shopping; How Pinterest is building a more representative shopping experience through AI & AR

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Using the guiding principle of, you can't be inspired if you don't feel represented, Pinterest set out to build a more inclusive product, starting with a way to filter beauty searches and products by skin tone range. Pinterest's SVP of Technology Jeremy King will discuss the latest in building a more inclusive platform and the company's work to make the service diverse by default, and how it has resulted in the evolution of Pinterest as a place to shop. By working with a more diverse data set to build inclusive products — from skin tone ranges to AR Try on— to help in the discovery and purchasing of beauty products, Pinterest has found Pinners are more likely to buy. For example, Pinners are 5x more likely to show purchase intent on Pins with AR than standard Pins. And the user base continues to grow, with +450 million global monthly users, representing 37% year over year growth. Jeremy will dive into the company's work to diminish bias in AI, build more compassionate algorithms, and how Pinterest is using machine learning to match the best products to the best people.

Speakers

Jeremy King: Head of Engineering - Pinterest
Matt Marshall: CEO - VentureBeat

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Salesforce Tower, Mission Street, San Francisco, CA, USA

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Salesforce Tower, Mission Street, San Francisco, CA, USA

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Salesforce Tower, Mission Street, San Francisco, CA, USA

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Name: Sook-Fun Lau

Salesforce Smart Money - URL:
https://www.salesforce.com/products/platform/best-practices/ai-and-machine-learning-technology/

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Smart Money: AI and Machine Learning Are Changing Business Forever

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investments in AI technology and machine learning will give businesses the ability to more efficiently capture and manipulate important data, and to forecast events with unparalleled accuracy.

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Company name: Amazon
Company location: Arlington County, Virginia, USA
URL Link: https://www.youtube.com/watch?v=NZBBkaJqBd8&t=116s

Name: Wong Quan Ming

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Google San Francisco, Spear Street, San Francisco, CA, USA

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Google San Francisco, Spear Street, San Francisco, CA, USA

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Google San Francisco, Spear Street, San Francisco, CA, USA

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Company Name: Google
Company Location: US
Link: The Amazing Ways Google Uses Deep Learning AI (forbes.com)

Name: Ang Wen Kai

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Deep learning is the area of artificial intelligence where the real magic is happening right now. Traditionally computers, while being very fast, have not been very smart - they have no ability to learn from their mistakes and have to be given precise instructions in order to carry out any task.

Deep learning involves building artificial neural networks which attempt to mimic the way organic(living) brains sort and process information. The "deep" in deep learning signifies the use of many layers of neural networks all stacked on top of each other. This data processing configuration is known as a deep neural network, and its complexity means it is able to process data to a more thorough and refined degree than other AI technologies which have come before it.

Deep learning is already driving innovation at the cutting edge of artificial intelligence and it can be seen in many applications today. However, as data volumes continue to increase and processing technology becomes more affordable, many more sectors of society are likely to be impacted. Here's a look at how one of the pioneers - Google - is already using it across many of its products and services.
Why is Google interested in deep learning?
Google has been a powerful force in championing the use of deep learning - a technology now so prevalent in cutting edge applications that its name is pretty much synonymous with artificial intelligence. There's a simple reason for this - it works. Putting deep learning to work has enabled data scientists to crack a number of difficult cases which had proved challenging for decades, such as speech and image recognition, and natural language generation.

It's first publicly-discussed explorations of the possibilities of deep learning began with the Google Brain project in 2011. The following year, Google announced that it had built a neural network, designed to simulate human cognitive processes, running on 16,000 computers and which was capable, after studying around 10 million images, of identifying cats.

In 2014, Google acquired UK based deep learning startup Deep Mind.

Deep Mind pioneered work in connecting existing machine learning techniques to cutting edge research in neuroscience, leading to systems which more accurately resembled "real" intelligence (I.e brains). Deep Mind was responsible for the creation of Alpha Go, which used video games, and later the boardgame Go, to demonstrate the ability of their algorithm to learn how to carry out a task and become increasingly good at it.
What does Google use deep learning for across its mail services?
While proving the concept in laboratories and games contests, it was also quietly rolled out across many of Google's services.

It's first practical use was in image recognition, where it was put to work sorting through the millions of images uploaded to the parts of the internet which Google indexes. It does this in order to more accurately classify them, and in turn give users more accurate search results. Google's latest breakthrough involving deep learning in the field of image analytics is in image enhancement. This involves restoring or filling in detail missing from images, by extrapolating for data that is present, as well as using what it knows about other similar images.

Another platform, Google Cloud Video Intelligence focuses on opening up video analytics to new audiences. Video stored on Google's servers can be segmented and analyzed for content and context, allowing automated summaries to be generated, or even security alerts if the AI thinks something suspicious is going on.

Language processing is another area of their services where the tech has been implemented. It's Google Assistant speech recognition AI uses deep neural networks to learn how to better understand spoken commands and questions. Techniques developed by Google Brain were rolled into this project. More recently, Google's translation service was also put under the umbrella of Google Brain. The system was rewritten to run on a new platform called Google Neural Machine Translation, moving everything to a deep learning environment.

The third primary way Google uses deep learning today on its core services is to provide more useful recommendations on Youtube. Again, Google Brain is behind the technology used here, which monitors and records our viewing habits as we stream content from their servers. Data already showed that suggesting videos that viewers will want to watch next is key to keeping them hooked to the platform, and the ad bucks rolling in. Deep neural networks were put to work studying and learning everything they could about viewers' habits and preferences, and working out what would keep them glued to their screens.
What else does Google use deep learning for?
Of course, given the success they have had with it, it is inevitable that Google would be keen to implement this technology in its more ambitious, specialist or future-oriented projects.

In 2015, it open sourced its TensorFlow machine learning and deep learning-focused programming platform, to allow anyone to develop neural network-based solutions using the same technology they use themselves.

Through its Cloud Machine Learning Engine, it also offers storage and processing power to third parties which want to put the technology to use without investing upfront in hugely powerful computer infrastructure.

Google's self-driving car division, Waymo, has incorporated deep learning algorithms into their autonomous systems, in order to make self-driving cars more efficient at analyzing and reacting to what is going on around them.

And Deep Mind is currently working on healthcare-focused projects involving detecting early signs of eye damage, and cancerous tissue growth.
What's next?
Google has been an effective force in pioneering, championing and bringing deep learning to the masses. Thanks to their research and investment anyone can benefit from these technologies. And increasingly, we will be able to put them to work ourselves on our own data. A great deal of people are pinning their hopes on deep learning providing some great leaps forward in coming years, in every field from medicine to exploring space - and the groundwork done by Google will play a big part in that.

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The Amazing Ways Google Uses Deep Learning AI

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Google is one of the pioneers of artificial intelligence (AI). In this article we look at the amazing ways Google is using the most cutting edge AI - deep learning - in many of its operations and how this is boosting their customer offerings and business performance.

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Tesla
USA
https://www.youtube.com/watch?v=UZNDNYR-s1A
Goh Xue Mei

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How Tesla Uses Machine Learning |  The Age of A.I. | Tech Series

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Huawei
https://consumer.huawei.com/en/

by YikMing

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Explore the latest technologies in smartphones, laptops, tablets, accessories, and smart home devices with HUAWEI, check out HUAWEI P50 series and Mate 40 series.

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Company Name: Google
Company Location: US
URL: https://economictimes.indiatimes.com/tech/software/how-google-maps-is-using-ai-and-machine-learning-to-understand-post-covid-traffic/ai-meets-ml/slideshow/77927574.cms

Name: Tan Chee Beng

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How Google Maps is using AI and Machine Learning to understand post-COVID traffic - ​AI meets ML

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As people traverse over 1 billion kms with help from Google Maps in more than 220 countries, the company is using artificial intelligence (AI) machine learning (ML) models to predict whether the traffic along your route is heavy or light, an estimated travel time, and an estimated time of arrival (ETA), reports IANS.

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Facebook Headquarters, Hacker Way, Menlo Park, CA, USA

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Facebook Headquarters, Hacker Way, Menlo Park, CA, USA

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Facebook Headquarters, Hacker Way, Menlo Park, CA, USA

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https://research.fb.com/category/facebook-ai-research-/
YP

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We're connecting people to what they care about, powering new, meaningful experiences, and advancing the state-of-the-art through open research and accessible tooling.

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Starbucks: https://www.youtube.com/watch?v=7_GpgSpaKTg
by Fadra

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DHL: https://www.youtube.com/watch?v=00wOf3xEQD4
by Fadra

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ZARA: https://www.youtube.com/watch?v=bkcAmCqIaao

by Fadra