758: The Mamba Architecture: Superior to Transformers in LLMs — with Jon Krohn (@JonKrohnLearns)
Super Data Science: ML & AI Podcast with Jon Krohn
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The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on Super Data Science, the most listened-to podcast in the industry. In lighthearted conversation with renowned guests, Jon cuts through hype to fuel your professional impact. Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy. We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.
Video Description
Jon Krohn explores the groundbreaking Mamba architecture, the latest challenger to the Transformer model's dominance in the AI landscape, going through the key insights from the "Mamba: Linear-Time Sequence Modeling with Selective State Spaces" paper, authored by leading researchers at Carnegie Mellon and Princeton. Learn why the tech community is buzzing about Mamba's ability to efficiently handle long input sequences - a task that has traditionally bogged down Transformer models with computational inefficiencies. Jon also explores how Mamba's selective information processing and linear scalability could revolutionize fields from natural language understanding to genomics, setting new benchmarks in AI's capabilities. Additional materials: https://www.superdatascience.com/758 Interested in sponsoring a SuperDataScience Podcast episode? Visit https://passionfroot.me/superdatascience for sponsorship information.
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