Exploration of the Large Language Model Space and Valuable Lessons

In today's episode, I chat about retrieval-augmented generation (RAG) with Naomi White, Engineering Program Manager at Cohere. Naomi shares her unique journey from starting as an Executive Assistant at DeepMind to becoming a key player in Cohere’s cutting-edge RAG development team.

In this episode, we cover: - Naomi's inspiring journey from DeepMind to Cohere and building a career in AI as a non-technical person; - Strategies for navigating the imposter syndrome; - Beginner-friendly tips for learning LLM concepts and staying up to date with AI advancements; - A behind-the-scenes look at developing LLM tool use with RAG techniques;

Resources:

* Jay Alammar's walkthrough "Building LLM Agents With Tool Use": https://youtu.be/5drn2DO7gNY?feature=shared 

* Notebook On Multi-Step Tool Use With Cohere And LangChain: https://colab.research.google.com/github/cohere-ai/notebooks/blob/main/notebooks/Data_Analyst_Agent_Cohere_and_Langchain.ipynb 

* GitHub repo with open-source chat interface optimized for RAG: https://github.com/cohere-ai/cohere-toolkit 

* Learn more about Command R+, Cohere model optimized for RAG use cases: https://txt.cohere.com/command-r-plus-microsoft-azure/ 

* Try it out: https://cohere.com/coral 

Watch podcast episodes on YouTube: https://youtu.be/CzcfrY1aKho&list=UULFjG6QzmabZrBEeGh3vi-wDQ&ab_channel=SandraKublik 

I'm a co-author of a manual on GPT-3 and OpenAI API (Packt, 2023): https://www.packtpub.com/product/gpt-3/9781805125228 

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Music by: Acid Jazz by Kevin MacLeod is licensed under a Creative Commons Attribution 4.0 license. https://creativecommons.org/licenses/by/4.0/