Capabilities of LLMs 🤯

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 • | GitHubGenerative Agents: Interactive Simulacra of Human BehaviorWolfram ChatGPTComparing LLMsLangChain • Learn about LLMs: Emergence and reasoning in large language models (Jason Wei)Sparks of Artificial General IntelligenceLearning 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 FacePEFT (Parameter-Efficient Fine-Tuning)Dolly blog postIllustrating Reinforcement Learning from Human Feedback Something missing or broken? PRs welcome!

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