Edge 414: Inside Meta AI's HUSKY: A New Agent Optimized for Multi-Step Reasoning
Was this email forwarded to you? Sign up here Edge 414: Inside Meta AI's HUSKY: A New Agent Optimized for Multi-Step ReasoningNew research from Meta AI, Allen AI, and the University of Washington tackles one of the most important problems in LLM reasoning.
Reasoning is highly acknowledged as the next frontier in generative AI. By reasoning, we refer to the ability to decompose a task into smaller subsets and solve those individually. Chain-of-Thought, Tree-of-Tought, Skeleton-of-Thought, and Reflexion are some of the recent techniques that have tackled reasoning capabilities in LLMs. Reasoning also involves peripherical capabilities such as accessing external data or tools. In the last couple of years, we have seen models to perform extremely well in specific reasoning techniques, but they failed to generalize across domains. This is not a surprise if we consider that reasoning is a very computationally expensive task. This is precisely the challenge that researchers from Meta AI, Allen Institute of AI and the University of Washington address in a recent paper. HUSKY is an open-source language agent designed to handle a variety of complex tasks involving numerical, tabular, and knowledge-based reasoning. Unlike other agents that focus on specific tasks or use proprietary models, HUSKY operates within a unified framework to manage diverse challenges. It works in two stages: first, it generates the next action needed to solve a task; second, it executes this action using expert models, updating the solution as it progresses... Subscribe to TheSequence to unlock 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 413: Autonomous Agents and Semantic Memory
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Can agents capture memory that encodes actual knowledge? ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
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Data is crucial for AI/ML systems but often becomes a bottleneck in development. Data scientists and engineers grapple with the complexity of building and maintaining feature pipelines, ensuring
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FlashAttention has a new version. Plus some important research milestones and major funding activity in AI. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
Edge 411: Learn About Microsoft's Impressive 4 New AI Compilers
Thursday, July 11, 2024
Parallelism, computation, memory, hardware acceleration and control flow are some of the capabilities addressed by the new compilers. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
Edge 411: Autonomous Agents with Episodic Memory
Tuesday, July 9, 2024
Capturing memories of important events in the lifecycle of an agent. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
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