Practical AI
Mamba & Jamba
Apr 24, 2024
Yoav Shoham, co-founder and co-CEO of AI21 and a Professor Emeritus at Stanford, dives into the evolution of AI models, discussing the groundbreaking Jamba model. He explains how Jamba combines the best of non-transformer benefits with attention layers, creating a highly efficient open-source model. Yoav also explores advancements in task-specific AI models, particularly their growing role in industries like finance. The conversation highlights the importance of open-source collaboration and the future of reliable, efficient AI in enterprise settings.
41:13
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Quick takeaways
- Jamba model combines non-transformer goodness with attention layers for high performance and efficiency.
- AI21 focuses on enterprise value with AI language models, aiming for true task comprehension and specialized systems.
Deep dives
AI 21's Background and Mission
AI 21's journey began over six years ago with a vision that modern AI requires more than just deep learning. They believe that intelligence, specifically reasoning, goes beyond statistical methods. Starting with Jurassic One, a model exceeding GPT-3's scale, AI 21 evolved into focusing on large language models. Language, intricate and nuanced, became their lens into the human mind, unlocking potential in enterprise data, predominantly text-based.
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