The chapter delves into a new hybrid architecture named Samba that merges Mamba and sliding video Window attention for enhanced performance over pure transformers. It highlights the benefits of incorporating recurrences in Mamba-style models and contrasts this with full attention in transformer models, showcasing the ability of Samba to effectively handle long sequences and combine advantages of state-space and attention-based models. The discussion encompasses the future of AI architectures, challenges with incorporating recurrence, recent developments in tech field along with the introduction of Omega PRM for improved mathematical reasoning in language models.
Our 171st episode with a summary and discussion of last week's big AI news!
With hosts Andrey Kurenkov (https://twitter.com/andrey_kurenkov) and Jeremie Harris (https://twitter.com/jeremiecharris)
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