Capabilities of LLMs 🤯
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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 – Twitter), GitHub), LinkedIn), Website)

• Chris Benson – Twitter), GitHub), LinkedIn), Website)

• Daniel Whitenack – Twitter), GitHub), Website)

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)

Something missing or broken? PRs welcome!)