In this episode we talk about the paper "Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer" by Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc Le, Geoffrey Hinton, Jeff Dean.

We talk about Low Rank Approximation for fine tuning Transformers. We are also on YouTube now! Check out the video here: https://youtu.be/lLzHr0VFi3Y

In this episode we discuss the paper "Training language models to follow instructions with human feedback" by Ouyang et al (2022). We discuss the RLHF paradigm and how important RL is to tuning GPT.

This week we talk about Whisper. It is a weakly supervised speech recognition model.

We talk about AlphaTensor, and how researchers were able to find a new algorithm for matrix multiplication.