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Mamba & Jamba (Practical AI #266)
Apr 24, 2024
Yoav, co-founder of AI21, discusses the groundbreaking Jamba model, a fusion of non-transformer and attention layers for efficient AI. The conversation covers the evolution of language models, Meta's llama 3 release, efficient AI system architecture, and the future of AI focusing on trust and reliability.
41:15
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Quick takeaways
- Jamba combines Mamba's non-transformer goodness with attention layers for a highly performant model.
- AI21 emphasizes the importance of large language models in unlocking the value of text data.
Deep dives
Overview of AI21's History and Mission
AI21 was founded with the vision of integrating deep learning and reasoning to advance AI. They believe that modern AI necessitates a combination of statistics and reasoning. Initially focused on vision, AI21 transitioned to language models, noting the complexity and nuances of language. With a focus on the enterprise, they aim to unlock the value of text data, highlighting the significance of large language models in understanding and processing textual information.
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