1. Your username is <Last 5 alphanumeric of your NRIC> + <DDMM of your DOB> Eg: 1234A1003.

2. Your system generated password is your FIRST 4 numbers of your mobile number and LAST 5 alphanumeric of your NRIC (Alphabet in caps) Example: 98761234A

3. Once logged in, click on your class code "Digital Transformation in The Era of 5G & AI"

4. Click on View Course, fill in Enrolment details. Click on View Course again.

5. Click on the shaded document icon, you will see the course materials.

How to sign up and create your first image - https://youtu.be/hNvn1SMd3cs

Source: https://www.gartner.com/en/articles/top-technology-trends-2025

Blockchain technology has the potential to disrupt and revolutionize the way we conduct business, make commercial transactions, enforce legal contracts, and even enact government policy². Its impact on today’s world can be likened to the advent of the Internet back in the 1990s².

Source: 

(1) Blockchain Facts: What Is It, How It Works, and How It Can Be Used. https://www.investopedia.com/terms/b/blockchain.asp.

(2) What Is Blockchain Technology? How Does It Work? | Built In. https://builtin.com/blockchain.

(3) What is blockchain and how does it work? – Britannica. https://www.britannica.com/money/what-is-blockchain.

(4) How does blockchain work? | Stanford Online. https://online.stanford.edu/how-does-blockchain-work.

Web3 is important because it has the potential to revolutionize many industries such as finance, healthcare, and supply chain management⁷. It can enable new business models that were not possible before, such as peer-to-peer marketplaces and decentralized finance (DeFi) platforms⁷. Web3 also has the potential to provide greater privacy and security for users by removing the need for intermediaries⁷.

Source: 

(1) What Is Web3? The Confusing Term, Explained – CNET. https://www.cnet.com/personal-finance/crypto/what-is-web3-the-confusing-term-explained/.

(2) What Is Web3? – Lifewire. https://www.lifewire.com/what-is-web3-5271876.

(3) What Is Web3? (+ How Does It Work?) | Coursera. https://www.coursera.org/articles/web-three.

(4) What is Web 3 & How Does Web3 Work? (Quick Web3 Guide). https://www.jetlearn.com/blog/how-does-web3-work-guide.

(5) What Is Web3? (+ How Does It Work?) | Coursera. https://www-china.coursera.org/articles/web-three.

(6) What Is Web3 and How Will it Work? | PCMag. https://www.pcmag.com/how-to/what-is-web3-and-how-will-it-work.

(7) What is web3? – The New York Times. https://www.nytimes.com/interactive/2022/03/18/technology/web3-definition-internet.html.

(8) Web3 – Wikipedia. https://en.wikipedia.org/wiki/Web3 Accessed 29/04/2023.

(9) What Is Web3 All About? An Easy Explanation With Examples – Forbes. 

https://www.forbes.com/sites/bernardmarr/2022/01/24/what-is-web3-all-about-an-easy-explanation-with-examples/.

Source:
(1) What is 5G Technology and How Does it Work? – TWI. https://www.twi-global.com/technical-knowledge/faqs/What-is-5G.

(2) What Is 5G? – How Does 5G Network Technology Work – Cisco. https://www.cisco.com/c/en/us/solutions/what-is-5g.html.

(3) 5G Network: How Does it Work? – TechSpective. https://techspective.net/2022/04/29/5g-network-how-does-it-work/.

(4) Benefits of 5G Technology: 5g Features and Advantages | Intel. https://www.intel.com/content/www/us/en/wireless-network/5g-benefits-features.html.

IoT works by connecting devices to the internet, allowing them to communicate with each other and with other systems⁴. IoT devices use sensors to collect data, which is then sent to the cloud where it can be analyzed and used to make decisions⁵.

IoT is important because it has the potential to revolutionize many industries such as healthcare, transportation, and entertainment¹. It can enable remote surgeries, self-driving cars, and virtual reality experiences with minimal lag time⁵. IoT can also help businesses save money by improving efficiency and reducing waste³.

Source:
(1) What is IoT (Internet of Things) and How Does it Work? – Definition …. https://www.techtarget.com/iotagenda/definition/Internet-of-Things-IoT.

(2) How Does the Internet of Things Work? – IoT For All. https://www.iotforall.com/what-is-the-internet-of-things.

(3) How does the internet of things work? IoT explained – Unit4. https://www.unit4.com/blog/how-iot-works-internet-things-explained.

(4) Internet of Things (IoT): What it is and why it matters | SAS. https://www.sas.com/en_us/insights/big-data/internet-of-things.html.

(5) Internet of Things Explained: Where Is It Used? | Edgica. https://www.edgica.com/iot-explained-where-is-it-used/.

(6) What is the Internet of Things? – World Economic Forum. https://www.weforum.org/agenda/2021/03/what-is-the-internet-of-things/.

Source:
(1) What is Robotic Process Automation (RPA)? | IBM. https://www.ibm.com/topics/rpa.

(2) PEX Guide: What is robotic process automation (RPA)?. https://www.processexcellencenetwork.com/rpa-artificial-intelligence/articles/a-guide-to-robotic-process-automation-rpa.

(3) How Does Robotic Process Automation Work? – Conectys. https://www.conectys.com/blog/posts/how-does-robotic-process-automation-work/.

(4) What is RPA? Robotic Process Automation | Automation Anywhere. https://www.automationanywhere.com/rpa/robotic-process-automation.

(5) Robotic process automation (RPA): How it works. https://enterprisersproject.com/article/2019/10/rpa-robotic-process-automation-how-it-works.

The process of big data analysis typically involves several stages, including data acquisition, storage, cleaning, processing, analysis, visualization, and interpretation³. The first step is to collect and store large amounts of data from various sources such as social media platforms, websites, sensors, and other digital devices⁴. The next step is to clean and preprocess the data to remove any errors or inconsistencies⁴. After that, the data is processed using various techniques such as statistical analysis, machine learning algorithms, and natural language processing⁴. The results of this analysis are then visualized using charts, graphs, and other tools that help businesses understand the insights better⁴.

Big data analysis is important because it helps businesses make better decisions by providing them with insights that they would not have been able to uncover otherwise. It can help businesses identify new market opportunities, optimize their operations, improve customer satisfaction, reduce costs, and increase revenue. It can also help businesses gain a competitive advantage by providing them with real-time insights that they can use to make quick decisions.

Source:
(1) What Is Big Data Analytics? Definition, Benefits, and More. https://www.coursera.org/articles/big-data-analytics.

(2) What Is Big Data Analytics and Why Does It Matter? – LinkedIn. https://www.linkedin.com/pulse/what-big-data-analytics-why-does-matter-get-ahead-by-linkedin-news.

(3) Big Data Analytics: What it is and why it matters | SAS. https://www.sas.com/en_us/insights/analytics/big-data-analytics.html.

(4) Big Data Analytics: What It Is & How It Works | Tableau. https://www.tableau.com/learn/articles/big-data-analytics.

Source:
(1) What is Artificial Intelligence? How Does AI Work? – LinkedIn. https://www.linkedin.com/pulse/what-artificial-intelligence-how-does-ai-work-juri-boro.

(2) What is AI? What does artificial intelligence do? – BBC Newsround. https://www.bbc.co.uk/newsround/49274918.

(3) What is Artificial Intelligence (AI), and How Does It Work?. https://www.capterra.com/resources/how-does-ai-work/.

(4) What Is Artificial Intelligence (AI)? How Does AI Work? | Built In. https://builtin.com/artificial-intelligence.

(5) Artificial intelligence (AI) | Definition, Examples, Types …. https://www.britannica.com/technology/artificial-intelligence.

The STREET process is a framework for evaluating and piloting emerging technologies in a consistent and documented manner. STREET stands for Scope, Track, Rank, Evaluate, Evangelize, and Transfer. Each step involves different activities and deliverables to help you decide whether or not to proceed with a particular technology.

1. Scope: This step provides business focus and context for emerging technology investments by identifying what organizational purposes should be served, such as supporting strategic goals, solving problems, or creating opportunities.

2. Track: This step involves monitoring and researching emerging technologies that are relevant to your scope, using various sources such as publications, conferences, vendors, peers, etc.

3. Rank: This step involves prioritizing and filtering the tracked technologies based on criteria such as potential impact, feasibility, alignment with scope, etc.

4. Evaluate: This step involves conducting experiments or pilots to test the selected technologies in a controlled environment and measure their performance against predefined metrics.

5. Evangelize: This step involves communicating and promoting the results and benefits of the evaluation to key stakeholders and decision-makers within your organization.

6. Transfer: This step involves transferring or scaling up the successful technologies from the evaluation stage to mainstream adoption or production within your organization.

   
   

To apply STREET process to your organization, you need to follow these steps:

1. Define your scope by identifying your strategic goals, problems, or opportunities that can be addressed by emerging technologies.

2. Track relevant emerging technologies using various sources and methods such as scanning publications, attending conferences, consulting vendors, etc.

3. Rank the tracked technologies based on criteria such as potential impact, feasibility, alignment with scope, etc.

4. Evaluate the selected technologies by conducting experiments or pilots in a controlled environment and measuring their performance against predefined metrics.

5. Evangelize the results and benefits of the evaluation to key stakeholders and decision-makers within your organization using effective communication strategies.

6. Transfer or scale up the successful technologies from the evaluation stage to mainstream adoption or production within your organization using appropriate methods such as training, documentation, integration, etc.

References:

1. https://researchrepository.murdoch.edu.au/id/eprint/5384/1/driving_emerging_technology.pdf

2. https://www.gartner.com/en/documents/1331653

3. https://sites.google.com/site/aniketsaoblog/home/evaluating-emerging-technologies/street-process

4. https://researchrepository.murdoch.edu.au/id/eprint/5384/1/driving_emerging_technology.pdf

5. https://www.gartner.com/en/documents/1331655

You can find the latest updates on industry and technological trends from various sources such as:

• Publicly-available sources and articles: ie McKinsey Technology Trends Outlook 2022, Forbes, World Economic Forum

• Government Agencies, ie Smart Nation Singapore,  GovtTech Singapore, IMDA, EDB

• Industry Communities of Practice focusing on digital transformation and innovations, ie NUS-ISS, Siemens,

• Popular websites include, ie Thales Group, Microsoft Industry Blogs

Examples include:

• Smart Nation initiatives: https://www.smartnation.gov.sg/resources/resources-for-businesses 

• IMDA programmes: https://www.imda.gov.sg/for-industry 

• Business Grants Portal: https://www.businessgrants.gov.sg/ 

• GoBusiness Singapore: https://www.gobusiness.gov.sg/enterprisejobskills/programmes-and-initiatives/upgrade-skills/digital-transformation-innovation-programme/

• Some help that Govtech can give: https://www.tech.gov.sg/products-and-services/ 

• Productivity Solutions Grant: This grant helps enterprises adopt pre-approved IT solutions and equipment that enhance productivity and competitiveness. It covers up to 80% of qualifying costs for eligible sectors such as retail, food, logistics, engineering, construction and landscaping.

• Tech@SG Programme: This programme helps fast-growing companies establish their core teams in Singapore and more quickly capture business opportunities here and in the region. It facilitates the entry of global technology talent for eligible companies that have strong growth potential and innovative products or services.

• Government Technology Agency: This agency leads Singapore’s digital transformation by building digital platforms, products and services for citizens and businesses. It also provides guidance, resources and tools for enterprises to adopt digital solutions that improve their operations and customer experience.

References:

1. https://www.enterprisesg.gov.sg/financial-assistance/grants/for-local-companies/productivity-solutions-grant

2. https://www.tech.gov.sg/

3. https://www.edb.gov.sg/en/how-we-help/incentives-and-schemes.html 

References:

1. https://www.forbes.com/sites/forbesbusinesscouncil/2021/07/22/15-ways-to-leverage-ai-in-customer-service/

2. https://www.computerweekly.com/feature/How-AI-and-automation-drive-better-customer-service

3. https://www.ibm.com/ai-customer-service

4. https://www.gartner.com/en/customer-service-support/insights/service-tech-strategy

5. https://techsee.me/blog/customer-service-technology-trends/

6. https://www.techtarget.com/searchcustomerexperience/feature/10-examples-of-AI-in-customer-service

References:

1. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/tech-forward/the-power-of-emerging-technologies-finding-value-through-data

2. https://www.gartner.com/en/articles/9-future-of-work-trends-for-2023

3. https://www.gartner.com/en/articles/5-impactful-technologies-from-the-gartner-emerging-technologies-and-trends-impact-radar-for-2022

Drivers:

• Business agility: Hybrid clouds enable enterprises to leverage the best of both worlds: on-premises infrastructure for security, compliance, or performance reasons, and public clouds for scalability, flexibility, or innovation. This allows them to respond faster to changing customer needs, market conditions, or competitive pressures.

• Customer experience: Increasing automation of customer services and relations can improve customer satisfaction, loyalty, and retention by providing faster, more accurate, more personalized, or more proactive service. It can also reduce costs, errors, or inefficiencies for enterprises by streamlining workflows, processes, or tasks.

Supporters:

• Cloud-native technologies: These are technologies that are designed for or optimized for cloud environments such as containers, microservices, serverless computing, or orchestration tools. They enable enterprises to build applications that are portable across different cloud platforms and providers while ensuring high performance, reliability, and security.

• Artificial intelligence: This is a broad term that encompasses various technologies that enable machines to perform tasks that normally require human intelligence such as natural language processing (NLP), computer vision (CV), machine learning (ML), or deep learning (DL). They enable enterprises to automate customer service functions such as chatbots, voice assistants, sentiment analysis etc.

Reference:

1. https://blogs.microsoft.com/blog/2022/01/27/cloud-trends-show-customers-increasing-investments-in-hybrid-and-multicloud/

2. https://www.gartner.com/en/articles/5-key-trends-from-2021-s-hype-cycle-for-customer-service-and-support-technologies

3. https://www.forbes.com/sites/forbestechcouncil/2021/07/28/its-raining-clouds-the-enterprise-movement-toward-hybridmulti-cloud-and-why-automation-is-required/

Artificial intelligence: This is a broad term that encompasses various technologies that enable machines to perform tasks that normally require human intelligence such as natural language processing (NLP), computer vision (CV), machine learning (ML), or deep learning (DL). AI is becoming more accessible, pervasive, and powerful across various domains and industries such as healthcare, education, finance, manufacturing, etc.

Blockchain: This is a distributed ledger technology that records transactions or data in a secure, transparent, and immutable way. Blockchain enables trustless peer-to-peer transactions without intermediaries or central authorities. Blockchain has applications beyond cryptocurrency such as supply chain management, digital identity, smart contracts, etc.

Computer vision: This is a branch of artificial intelligence that deals with enabling machines to see and understand visual information such as images or videos. Computer vision can be used for various purposes such as face recognition, object detection, medical diagnosis, autonomous driving etc.

Customer data platforms: These are software systems that collect, unify, and activate customer data from multiple sources such as websites, apps, social media etc. Customer data platforms enable personalized and targeted marketing campaigns based on customer behavior, preferences etc.

Cybersecurity mesh: This is an architectural approach that decentralizes cybersecurity controls and enables users to access any digital asset securely regardless of location. Cybersecurity mesh can enhance cyber resilience by providing dynamic protection for distributed systems.

References: https://connect.comptia.org/blog/emerging-trends-in-information-technology https://www.weforum.org/agenda/2021/11/these-are-the-top-10-emerging-technologies-of-2021/ https://www.forbes.com/sites/bernardmarr/2022/11/21/the-top-10-tech-trends-in-2023-everyone-must-be-ready-for/?sh=7c3835987df0 https://www.forbes.com/sites/bernardmarr/2021/09/27/the-5-biggest-technology-trends-in-2022/?sh=6d183d072414

To analyse the feasibility of RPA adoption by your organisation, you need to consider both the process feasibility and the technical feasibility of each potential use case. You also need to estimate the costs and benefits of implementing RPA for each use case.

Process feasibility refers to how suitable a process is for automation. You can use criteria such as frequency, volume, complexity, variability, standardisation and exception rate to evaluate the process feasibility1. Generally, processes that are high-frequency, high-volume, low-complexity, low-variability, highly-standardised and have few exceptions are more feasible for automation.

Technical feasibility refers to how easy or difficult it is to automate a process using RPA tools. You can use criteria such as data input/output formats, system integration requirements, security constraints and scalability needs to evaluate the technical feasibility1. Generally, processes that have structured data inputs/outputs (such as Excel files), simple system integration (such as web services), low security risks (such as non-sensitive data) and high scalability potential (such as cloud-based solutions) are more feasible for automation.

Cost-benefit analysis refers to comparing the expected costs of implementing RPA with the expected benefits of doing so. Costs may include software licenses, hardware infrastructure, development time and resources, maintenance and support expenses etc. Benefits may include labour savings, error reduction, compliance improvement etc. You can use metrics such as return on investment (ROI), payback period or net present value (NPV) to measure the cost-benefit ratio of each use case.

Other evaluation methods that you can use to analyse the feasibility of RPA adoption by your organisation include:

SWOT analysis: This method helps you identify the strengths, weaknesses, opportunities and threats of RPA implementation for your organisation.

PESTLE analysis: This method helps you assess the political, economic, social, technological, legal and environmental factors that may affect your RPA adoption decision.

Agile automation: This method helps you test and validate your RPA use cases in short cycles using an iterative approach.

References:

1. https://blog.vsoftconsulting.com/blog/how-to-conduct-an-rpa-feasibility-assessment

2. https://www.mckinsey.com/capabilities/operations/our-insights/operations-management-reshaped-by-robotic-automation

3. https://ieeexplore.ieee.org/document/8997983

Cloud computing: This technology enables organisations to access and store data and applications over the internet instead of on-premise servers. Cloud computing can benefit business process flows by providing scalability, flexibility, cost-efficiency, security and collaboration.

Artificial intelligence: This technology enables machines to perform tasks that normally require human intelligence, such as reasoning, learning, decision making and natural language processing. Artificial intelligence can benefit business process flows by enhancing accuracy, efficiency, innovation and customer satisfaction.

Data analytics: This technology enables organisations to collect, process and analyse large amounts of data to generate insights and value. Data analytics can benefit business process flows by improving performance measurement, risk management, customer segmentation and personalisation.

RPA: This technology enables organisations to automate repetitive and rule-based tasks using software robots or digital workers. RPA can benefit business process flows by reducing labour costs, errors, compliance issues and customer complaints.

By combining these technologies together, organisations can achieve intelligent automation (IA), which is an end-to-end solution that leverages RPA and AI to automate complex processes that require cognitive abilities3. IA can benefit business process flows by enabling digital transformation, process optimisation, business agility and competitive advantage.

References:

1. https://www.salesforce.com/products/platform/best-practices/benefits-of-cloud-computing/

2. https://www.techtarget.com/searchcloudcomputing/tip/Benefits-and-drawbacks-of-AI-in-cloud-computing

3. https://www.ibm.com/cloud/blog/intelligent-automation-how-combining-rpa-and-ai-can-digitally-transform-your-organization

Pooled interdependence: This occurs when different units work independently but contribute to a shared output or outcome. For example, different departments in a university may offer different courses but share the same students and resources.

Sequential interdependence: This occurs when one unit produces an output that is required by another unit as an input. For example, a manufacturing process may involve a series of steps where each step depends on the previous one.

Reciprocal interdependence: This occurs when two or more units exchange inputs and outputs with each other. For example, a product development team may collaborate with a marketing team to design and promote a new product.

Interdependencies within the organisation affect the considerations for adoption of new technologies in various ways. Some of the considerations are:

Alignment: The new technology should align with the organisation’s vision, mission, values and goals. It should also support the interdependent relationships among different units and functions.

Compatibility: The new technology should be compatible with the existing systems, processes, policies and culture of the organisation. It should also minimise disruption and conflict among interdependent units and functions.

Coordination: The new technology should facilitate coordination and communication among interdependent units and functions. It should also enhance collaboration and integration across different levels and domains of the organisation.

Evaluation: The new technology should be evaluated based on its impact on interdependent units and functions. It should also be monitored and adjusted according to feedback from stakeholders.

References:

1. https://woman.thenest.com/definition-interdependence-workplace-14910.html

2. https://smallbusiness.chron.com/three-types-interdependence-organizational-structure-1764.html

3. https://www.samewave.com/posts/understand-the-three-types-of-task-interdependence-and-why-they-matter

4. https://smallbusiness.chron.com/three-types-interdependence-organizational-structure-1764.html

5. https://www.linkedin.com/pulse/understand-organizational-interdependencies-john-schultz

According to an article by ITONICS, here are 10 factors to consider when evaluating an emerging technology for adoption

1. Adoption cost

2. Threat

3. Capability

4. Usability

5. Interoperability

6. Integration 

7. Application

8. Legal compliance

9. Security and privacy

10. Social and cultural

References:

1. 10 Factors For Evaluating New Technology | ITONICS (itonics-innovation.com) 

Cost-Benefit Analysis (CBA) is a framework for evaluating the adoption of emerging technologies in a consistent and documented manner. 

The analysis has to include at least three alternative solutions that consider alternative ways of fulfilling the demanded project. The final value for comparison is represented as the Net Present Value (NPV). 

The NPV is calculated by subtracting the total cost of investment from the total benefits of investment over a period of time. If the NPV is positive, then it means that the benefits outweigh the costs and it’s worth investing in that technology. If it’s negative, then it’s not worth investing in that technology.

Download the Cost-Benefit Analysis Template by clicking here.

Gemini f.k.a Bard AI by Google

Imagine a team of superstar chefs who not only cook incredible meals but can also invent entirely new culinary experiences based on your preferences. That's the power of AI – super-smart machines that can learn and solve problems.

Art Styles

These are like the signature styles of Michelin-starred chefs. Just as there's the delicate plating of French cuisine or the bold flavors of Thai cooking, there are Impressionist, Pop Art, and Surrealist art styles for AI-generated creations.

ChatBot

Think of it as a friendly sommelier at a fancy restaurant. Chatbots use AI to answer your questions and complete tasks through text messages or voice commands.

Deep Learning

This is like a complex, award-winning dish with many layers of flavors (data) and techniques (algorithms) used to train an AI model (chef) to perform a specific task (cook a perfect dish). It's a powerful subfield of Machine Learning.

Discord

An online platform where people interested in AI can chat and share information, similar to a bustling kitchen where chefs from different restaurants exchange tips and tricks.

DALL.E 3 & Stable Diffusion

These are the superstars of AI image generation, like celebrity chefs who can create stunning and original dishes (images) based on just a few descriptions (ingredients).

Generative AI

This is the innovative side of AI, focusing on creating entirely new things, like a Michelin-starred chef who invents a mind-blowing new dessert. Text-to-Image and Speech-to-Text are examples of Generative AI.

Iteration

In Michelin-starred kitchens, it's like constantly refining a dish by adjusting the ingredients (data) slightly each time to achieve perfection. In AI, it's about refining a model by feeding it more data and tweaking its settings.

Large Language Model (LLM)

Imagine a seasoned chef with years of experience and knowledge of countless cuisines. That's an LLM – a powerful AI system trained on massive amounts of text data. GPT-3.5 and GPT-4 are examples of LLMs.

LMS (Learning Management System) Think of it as a chef's recipe box on steroids. It holds all the recipes (learning materials) and tests (assessments) that aspiring chefs (learners) need to become superstars!

Machine Learning (ML)

A type of AI where computers learn from data without needing explicit programming, like a talented apprentice chef who observes and learns from the masters. Deep Learning is a subfield of ML.

Model

Think of it as the head chef in the kitchen. It's a computer program trained on data to perform a specific task.

Multi-Modal

This refers to using different forms of data (ingredients) like text, images, and sound together, like a Michelin-starred chef who combines various textures and flavors to create a dish that appeals to all senses.

Natural Language Processing (NLP)

The field of AI that helps computers understand human language, like a skilled translator who can decipher the meaning behind a chef's complex instructions.

Output: The final, award-worthy dish (result) that the AI model (chef) creates after following a recipe (instructions) and using ingredients (data).

Pre-Trained Models

These are like pre-made puff pastry or perfectly seasoned stock – they're AI models that have already been trained on a large amount of data and can be fine-tuned for specific dishes (tasks).

Prompt

The instructions you give the AI system (chef), like telling the chef what kind of Michelin-star worthy dish (output) you want them to create.

Prompt Engineering

The art of crafting the perfect prompt (instructions) to get the desired Michelin-starred dish (output) from the AI system, like carefully choosing the right spices and ingredients to achieve a particular flavor profile.

Sentiment Analysis

This AI technique can understand the emotions (taste) behind written text (a dish description), like a food critic who can tell if a dish is meant to be light and refreshing or rich and decadent based on the words used to describe it.

Seeding

Providing the AI system with some starting information (a base ingredient) to guide it in the right direction, like giving a baker a perfect sourdough starter to kick off the bread-making process.

Speech to Text & Text to Speech

These AI tools can convert spoken words (recipes dictated out loud) into written text (a recipe document) and vice versa, like a skilled translator who can convert a recipe from one language to another.

Text to Image & Text to Video

These AI systems can generate images or videos based on a text description (recipe instructions), like a talented artist who can illustrate a recipe based on its written instructions.

Token

The smallest unit of meaning in a piece of text, like individual words in a sentence. Imagine them as the building blocks (ingredients) used to create instructions (recipes) for the AI system.

Zero-Shot Prompting

Providing the AI system with very little instruction (just a hint of spice!), like simply telling a chef to make you something delicious without specifying a dish.

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