S1-E4: From ChatGPT to AI agents and applications

In this episode we discuss the limitations of ChatGPT such as its lack of up-to-date knowledge, lack of private / domain specific knowledge, and lack of tool use abilities. We then discuss innovative new solutions to these problems such as vector database retrieval, ChatGPT plugins, and AI agents with access to external tools that can orchestrate complex tasks and workflows autonomously. What are the implications for business and society? We also touch upon some criticisms of OpenAI’s convoluted governance structure and lack of transparency into their model training and data sources.

🎧 Listen to the episode

Watch or listen to the episode on YouTube, Spotify, Apple Podcasts, Substack (right on top of this page), or copy the RSS link into your favorite podcast player!

⏰ Chapters

00:00: Preview and intro

00:57: OpenAI controversies and limitations of ChatGPT

09:17: Connecting ChatGPT with external data

18:49: AI Agents

🧠 Key concepts

• Obtaining training data for AI LLMs is ethically and legally complicated

• LLMs like ChatGPT don’t have up to date knowledge or domain specific knowledge

• To give ChatGPT specific knowledge, you can connect it to vector databases

• The next evolution in AI is AI agents which can use a variety of tools and models to perform complex real world tasks

🔗 References

• Nikhil Maddirala: https://www.linkedin.com/in/nikhilmaddirala/

• Piyush Agarwal: https://www.linkedin.com/in/piyush5/

• "Building a system around LLMs for private data" by Vikash Rungta

📓 Detailed notes

1. OpenAI controversies and AI Training Data: The conversation delves into the sources and controversies surrounding the training data for AI models like GPT, highlighting the complexities and ethical considerations of using vast amounts of internet data without explicit permission for the content creators.

2. Limitations of ChatGPT and the role of vector Databases: We explain how vector databases like Pinecone store are crucial to enhance ChatGPT with external knowledge, enabling efficient retrieval of information such as private documents for AI models.

3. Innovations in AI: Chat GPT Plugins: Introduction to Chat GPT plugins and their role in connecting AI models to external databases and knowledge bases, allowing for more personalized and relevant interactions, and illustrating the growing sophistication of AI applications.

4. The Future of AI: Agent GPT and External Tools: Exploration of the next evolution in AI, where Agent GPTs can autonomously manage and execute complex tasks by orchestrating multiple specialized models and tools, pointing towards a future where AI significantly enhances productivity and decision-making.

💬 Keywords

#AI #ArtificialIntelligence #GenerativeAI #GenAI #LLM #MachineLearning #ML #VectorDB #AIAgents #Pinecone #tech #podcast