Self improving ai

Evolution of agentic surfaces — Gagan Bhat & Isabella Kai He, Anthropic

Evolution of agentic surfaces — Gagan Bhat & Isabella Kai He, Anthropic

Anthropic's Gagan Bhat and Isabella Kai He discuss how agent harnesses must evolve rapidly to keep pace with fast-improving LLMs. They introduce Claude Managed Agents, an architecture that decouples the agent's 'brain' (reasoning) from its 'hands' (tool execution) to address issues like stale assumptions, latency, and reliability. This approach enables dynamic adaptation, secure tool execution, and features like 'dreaming' for self-improving agents and 'outcomes' for goal-oriented task completion, ultimately aiming to close the gap between model capabilities and product offerings.

Morgan Stanley's ALPHALAB: Multi-Agent Research Across Optimization Domains — Brendan Rappazzo

Morgan Stanley's ALPHALAB: Multi-Agent Research Across Optimization Domains — Brendan Rappazzo

Morgan Stanley's AlphaLab is an open-sourced multi-agent system designed to automate quantitative research. Initially, AlphaLab 1.0 automated code generation, backtesting, and experimentation. Facing challenges, AlphaLab 2.0 evolves to prioritize building robust, verifiable environments, which serve as reinforcement learning signals, enabling the system to meta-optimize itself. This shift redefines the human role from performing research to designing these critical environments.

No Priors Ep. 120 | With Google DeepMind’s Pushmeet Kohli and Matej Balog

No Priors Ep. 120 | With Google DeepMind’s Pushmeet Kohli and Matej Balog

Push Kohli and Máté Balog from Google DeepMind discuss AlphaDev, an AI agent that uses large language models and evolutionary search to discover novel, more efficient algorithms for fundamental computer science problems, marking a significant step in AI's ability to generate creative and practical solutions.