Not Just Transformers: Jamba is New LLM that Brings the Best of SSMs, Transformers, and MoEs in a Single Architect…
Was this email forwarded to you? Sign up here Not Just Transformers: Jamba is New LLM that Brings the Best of SSMs, Transformers, and MoEs in a Single ArchitectureJamba addresses some of the limitations of transformers with a novel architecture paradigms.
Transformer architectures have been the dominant paradigm in LLMs leading to exceptional advancements in research and development. The question of whether transformers will be the final architecture to reach AGI versus the real possibility of new architecture paradigm has been a passionate topic of debate in the AI community. Recently, researchers from Princeton University and Carnegie Mellon proposed the Mamba architecture based on state space models(SSMs) which has become the most viable alternative to transformers. Instead of thinking about SSMs vs. transformers, could we try to combine the two? This is the thesis behind a new model called Jamba released by the ambitious team at AI21 Labs. Jamba combines transformers and SSMs in a single architecture that could open new avenues for the future of LLMs. The ProblemUntil this point, the creation of LLMs has largely hinged on the use of traditional Transformer structures, known for their robust capabilities. However, these structures have two significant limitations:... Subscribe to TheSequence to read the rest.Become a paying subscriber of TheSequence to get access to this post and other subscriber-only content. A subscription gets you:
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Edge 393: Understanding Planning Techniques in Autonomous Agents
Tuesday, May 7, 2024
A taxonomy of planning in autonomous agents, the ADaPT planning method and the XLANG framework. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
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Maybe Two Big Research Breakthroughs or Maybe Nothing
Sunday, May 5, 2024
Multi-token prediction and a multi-layer perceptron alternative. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
Edge 392: Meet RAFT: UC Berkeley's New Method to Improve RAG Patterns in LLMs
Thursday, May 2, 2024
The method brings the best of RAG and supervised fine tuning. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
Edge 391: Autonomous Agents and LLM Function Calling
Tuesday, April 30, 2024
LLMs that invoke external functions, UC Berkeley's LLM Compiler and the Phidata framework. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
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