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The article discusses the limitations of Large Language Models (LLMs) in planning and self-verification tasks, and proposes an LLM-Modulo framework to leverage their strengths in a more effective manner. The framework combines LLMs with external model-based verifiers to generate, evaluate, and improve plans, ensuring their correctness and efficiency.
"Simply put, we take the stance that LLMs are amazing giant external non-veridical memories that can serve as powerful cognitive orthotics for human or machine agents, if rightly used."
"Simply put, we take the stance that LLMs are amazing giant external non-veridical memories that can serve as powerful cognitive orthotics for human or machine agents, if rightly used."
A new model developed by researchers at MIT and the University of Washington predicts human goals or actions more accurately than previous models. The latent inference budget model identifies patterns in human or machine decision-making and uses this information to forecast behavior.
IBM showcased their big bet on open-source AI at their Think conference. They open-sourced a family of IBM Granite models, released AI assistants, expanded their AI ecosystem, and are making a push to monetize and deploy AI for businesses.
Micro Agent, an agent that aids programmers, helping them write and fix code.
The author tests the new GPT-4o AI from OpenAI on a standard set of coding tests and finds that it delivers good results, but with one surprising issue.
