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Good morning, aspiring leaders of the next-gen! ☀️

🚀 Here’s what’s going on today in the AI space…

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📔#1 Insights Today on AI. Click the Links to Read

Virginia "Ginni" Rometty is an American business executive who was executive chairman of IBM after stepping down as CEO on April 1, 2020. She was previously chairman, president, and CEO of IBM, becoming the first woman to head the company.

⬆️ ️ Trends: How Businesses Implement AI

UNESCO leads global efforts to ensure ethical development of Artificial Intelligence (AI). In 2021, UNESCO produced the first global standard on AI ethics, adopted by all 193 Member States.

The Recommendation on the Ethics of AI is built on four core values:

1. Human rights and dignity

2. Peaceful, just, interconnected societies

3. Diversity and inclusiveness

4. Environmental flourishing

Ten principles guide a human rights-centered approach, including:

• Proportionality and do no harm

• Privacy and data protection

• Transparency and explainability

• Human oversight

• Sustainability

UNESCO emphasizes practical implementation through:

• Readiness Assessment Methodology (RAM)

• Ethical Impact Assessment (EIA)

• Women4Ethical AI expert platform

• Business Council for Ethics of AI

The organization addresses various ethical dilemmas, such as AI bias, use in judicial systems, and AI-created art. UNESCO also provides resources including publications, multimedia content, and hosts events like the Global Forum on the Ethics of AI.

By setting standards, offering tools, and fostering collaboration, UNESCO aims to maximize AI's benefits while minimizing risks, ensuring it contributes to a more inclusive, sustainable, and peaceful world.

🛸Let’s Teleport in The Future

Learn Anything with AI and the Feynman Technique

Study any concept in four easy steps, by applying AI and a Noble Prize winner approach

Feynman’s technique for learning a topic can be broken down into these four simple steps:

1. Teach the concept: The most effective method to understand something is by teaching it. Whether you want to imagine teaching the concept to someone else, yourself, or an imaginary child, you must assume the other person knows nothing about the subject. So don’t hide behind and from big words.

2. Identify gaps: Go through what you have been teaching. From the other person’s point of view, try to identify parts of your explanation that are missing, need more work, or are simply not understandable enough.

3. Refine: Using the feedback of the last step, iteratively refine your explanation until you are happy with it.

4. Tell a Story: Now that you have the foundation, fortify it with examples, illustrations, and diagrams. Make your explanation so fluent that you can convey it through a story that is easy to the ears and entertaining to follow.

AI + Feynman Technique = 🔥

You're falling behind if you’re not using AI to enhance your learning process. In this section, I will introduce a very simple method to couple AI with the Feynman Technique by prompting ChatGPT. As an example, I will use “vector database” as a machine learning concept I would like to learn.

Step 1: I will read about the topic and study a basic understanding of it. Then, I developed a simplified explanation of what a vector database is. Let’s say I come up with the following explanation:

Imagine having a library of books. You can add books to the library 
and retrieve them quickly by using their name or any other indexing method.
A vector database is also a library, but instead of books, stores vectors.
A vector can be thought of, as a list of numbers that represent an image,
audio, or any sort of data. Once we convert the data into vectors, by using
various machine learning techniques, we can store the vectors and retrieve 
them efficiently using some indexing method.

Alternatively, we could ask ChatGPT to provide us with an explanation of the concept if we have trouble writing it ourselves. We can use this prompt to ask ChatGPT:

Step 2: Once we have an initial definition of our concept, it’s time to identify how we can improve upon it. We can ask ChatGPT to act as our audience and give us feedback. The prompt for this:

By using this prompt and my explanation of vector database, I get a list of suggestions on which parts of it could have knowledge gaps or more clarification:

Expand on Vectors: Explain how vectors are derived from data, 
using a specific example to illustrate the concept.

Detail Conversion Techniques: Mention specific machine learning techniques,
like neural networks or NLP, used to convert data into vectors.

Clarify Indexing and Retrieval: Discuss specialized algorithms used in 
vector databases, such as approximate nearest neighbor search, and how 
they differ from traditional indexing methods.

Include Use Cases: Add examples of practical applications like multimedia 
retrieval and real-time recommendation systems to show the benefits of 
vector databases.

Discuss Scalability and Performance: Mention how vector databases are 
optimized for handling large datasets and high-performance needs.

Enhance Comparison with Traditional Databases: Extend your library analogy
to compare the search processes in vector and traditional databases, 
emphasizing efficiency and accuracy in finding similar items.

Step 3: Repeat the previous steps until you reach a concise and complete definition of your concept that you are happy with.

Step 4: Expand your explanation by adding analogies and diagrams. Using gpt-4o you can also retrieve diagrams and images to help you get a visual understanding.

I will use two separate prompts, one for analogies:

Another prompt for drawing a diagram of the concept:

ChatGPT will continue to create a diagram for a full understanding of vector databases:

☢️WARNING: It is crucial to have in mind that AI hallucinates! This means that it tends to make up information that doesn’t exist. To make matters worse, AI sounds confident in making up these mistakes, so unless you already have some prior knowledge about a topic, fully handing the steering wheel to AI needs caution!

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⚡ Prompting with Claude.ai or ChatGPT

14. Your Global Culture Expert

When you go to a museum, exhibition, or art gallery, I’m sure you have lots of questions about the installations you see, right? 2 weeks ago, I was at Ocean Park, and they had this scene, but I couldn’t recall the exact name of the book from where it comes from.

Until ChatGPT, of course! You can now ask GPT-4o any questions that come to your mind regarding what you see in an art museum or exhibition.

This is a great example of the contextual awareness of GPT-4o, as its reasoning gives the user the exact answer that they are looking for.

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Work smarter, not harder!

Introduction to DataRobot:

DataRobot is a leader in data science and machine learning platforms, empowering organizations to accelerate AI adoption from idea to impact. It offers a unified platform for generative and predictive AI, enabling enterprises to build, operate, and govern AI models with confidence.

Steps to Harness the Power of DataRobot:

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I hope you find these resources helpful.Let me know if you have any questions, if there's anything else I can do to assist you, or what you would like to learn more about in AI.

Have an amazing day!

No more playing catch-up. It's time to GET AHEAD!!! 🚀🚀🚀

🙌🏼

Elena

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