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How to Stay Updated in 2024 using Gen AI Agents

Science & Technology


How to Stay Updated in 2024 using Gen AI Agents

Hello everyone and welcome to AI with Soini where we talk about anything and everything in this transcendent and ever-changing world of artificial intelligence. If you are intrigued and excited about understanding what is happening in this world of AI—what are the new models, what are the new tools, how you can stay updated with every single thing, what algorithms are being used, and how to stay ahead—then this is the channel for you.

For those who are joining again and have subscribed to this channel, thank you so much for doing so. I apologize for having been away for the last few months; I had to take care of my parents' health, my own health, and my family's health, and also recharge my dopamine levels so that I can come back invigorated to continue the fabulous research in this realm of artificial intelligence.

Thank you again for joining, subscribing, sharing, liking, and being a part of this community. Today's video will be about how to stay updated in the world of AI.

Staying Apprised in AI

We will be showing you some of the latest and greatest tools for both beginner and intermediate levels. If you are not interested in coding and want free tools at your disposal to stay updated with what's happening in the finance world, corporate world, and data science, then this is the video for you.

Let's get started!

Understanding Information in AI

Typically, large language models (LLMs) or chatbots like ChatGPT store information and retrieve it when queried. Products currently use a methodology called Retrieval Augmented Generation (RAG), which takes relevant information and summarises it for you.

Information typically falls into three buckets:

  1. Information that rarely changes: Facts like the distance between the Earth and the Sun.
  2. Information that changes sometimes: Country GDPs or fluctuating insurance prices.
  3. Information that changes frequently: Weather, humidity, temperature, and live scores.

LLMs usually excel in retrieving information that rarely changes but may struggle with frequently changing information without auxiliary help like a Google search. That’s where AI agents or GenAI agents come in—they use web searches to supplement LLMs and provide accurate, up-to-date information.

Design Your Own GenAI Agent

Let's talk about AI agents. They use a search engine for initial retrieval and summarize the information in a user-friendly format. We will examine three tools:

  1. Poe: This tool empowers Quora and allows interaction with a range of large language models including Claude, Gemini, and GPT-4.
  2. ChatGPT: Incorporating versions like ChatGPT along with GPT-4.
  3. Gemini: Another advanced model for text and image-based queries.

For demonstration, let's ask each tool a tricky question to see how they perform:

Comparing Tools

  1. Poe and Claude:

    Poe offers interaction but lacks real-time web search capabilities. If you ask for the latest cricket scores, for instance, it may provide stale information from August 2023.

  2. ChatGPT:

    ChatGPT, equipped with web search, fetches the most current information, compiling it for the user effectively.

  3. Gemini:

    Gemini also uses web search, supplementing its responses with up-to-date data from relevant sites.

Utilizing AI Agent Models

To design your AI agent, start with an OpenAI API key. You will run provided functions and craft a Persona template, instructing the AI about the formality, audience, and bullet-point summary format.

For instance, changing the Persona to "explaining to a five-year-old" will yield simpler language responses. Similarly, altering it to "explaining to a financial analyst" will gear the vocabulary and context accordingly.

Conclusion

I hope you found this guide useful. Designing your AI agent allows for customizable, accurate responses to queries, making it easier to stay current in an ever-evolving AI landscape.


Keywords

  • AI agent
  • GenAI
  • Large Language Models (LLMs)
  • Retrieval Augmented Generation (RAG)
  • OpenAI API
  • Persona customization
  • Information retrieval

FAQ

Q1: What are AI agents?

  • AI agents are enhanced versions of large language models that first perform web searches to gather updated information and then present it in a user-friendly format.

Q2: How do I create an AI agent using OpenAI?

  • You need an OpenAI API key. Use Google Colab to run specific code functions, set a Persona, and test your queries for accurate responses.

Q3: Which AI tools are best for real-time information?

  • ChatGPT and Gemini are recommended as they incorporate web searches to fetch the latest data, unlike tools like Poe, which may rely solely on pre-stored information.

Q4: What is Retrieval Augmented Generation (RAG)?

  • RAG is a methodology where pertinent information is taken from external sources and summarized by the AI, enhancing traditional LLMs’ capabilities.

Q5: Why is it important to design a custom AI agent?

  • Custom AI agents ensure that the responses you get are tailored to your specific needs, vocabulary, and information requirements, making them more relevant and accurate.

We look forward to bringing you more insights and tools in the next video. Stay tuned!