Large Language Model (LLM) capabilities have reached new heights and are nothing short of mind-blowing! However, with so many advancements happening at once, it can be overwhelming to keep up with all the latest developments. To help us navigate through this complex terrain, we’ve invited Raj - one of the most adept at explaining State-of-the-Art (SOTA) AI in practical terms - to join us on the podcast.

Raj discusses several intriguing topics such as in-context learning, reasoning, LLM options, and related tooling. But that’s not all! We also hear from Raj about the rapidly growing data science and AI community on TikTok.

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Featuring:

Rajiv Shah – Website, GitHub, LinkedIn, X
Chris Benson – Website, GitHub, LinkedIn, X
Daniel Whitenack – Website, GitHub, X

Show Notes:

Solving AI Tasks with ChatGPT and its Friends in HuggingFace | GitHub
Generative Agents: Interactive Simulacra of Human Behavior
Wolfram ChatGPT
Comparing LLMs
LangChain
Learn about LLMs:
- Emergence and reasoning in large language models (Jason Wei)
- Sparks of Artificial General Intelligence
Learning Prompting
Getting Started with Transformers:
- Transformers course (free)
- Tasks at Hugging Face
Training your own LLM Models:
- Efficient Large Language Model training with LoRA and Hugging Face
- PEFT (Parameter-Efficient Fine-Tuning)
Dolly blog post
Illustrating Reinforcement Learning from Human Feedback

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