Advancements in AI Search and Model Optimization

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This chapter explores significant advancements in AI, particularly focusing on Audible's AI-powered search feature called Maven and its applications in the audiobook landscape. It discusses strategies for optimizing large language models through techniques like best of n sampling and weight pruning, highlighting their potential benefits and challenges. Additionally, the chapter delves into the implications of recent research on enhancing AI performance while addressing the complexities and uncertainties surrounding these evolving technologies.

Our 178th episode with a summary and discussion of last week's big AI news!

NOTE: this is a re-upload with fixed audio, my bad on the last one! - Andrey

With hosts Andrey Kurenkov (https://twitter.com/andrey_kurenkov) and Jeremie Harris (https://twitter.com/jeremiecharris)

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In this episode:
- Notable personnel movements and product updates, such as Character.ai leaders joining Google and new AI features in Reddit and Audible.
- OpenAI's dramatic changes with co-founder exits, extended leaves, and new lawsuits from Elon Musk.
- Rapid advancements in humanoid robotics exemplified by new models from companies like Figure in partnership with OpenAI, achieving amateur-level human performance in tasks like table tennis.
- Research advancements such as Google's compute-efficient inference models and self-compressing neural networks, showcasing significant reductions in compute requirements while maintaining performance.

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