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63 articles
Richard Sutton, the father of reinforcement learning and 2024 Turing Award winner, is leaving Keen Technologies to start a new AI company, Oak Lab.
Turing Award winner Richard Sutton has founded Oak Lab to develop AI agents that learn autonomously from their environment, challenging current deep learning limitations.
Skyfall AI introduces MORPHEUS, a persistent enterprise simulation benchmark that challenges current continual reinforcement learning methods by simulating non-stationary environments.
This explainer explores how iOS 27's enhanced Siri AI system represents a significant advancement in mobile artificial intelligence, combining transformer architectures, reinforcement learning, and edge computing techniques to create more sophisticated, adaptive voice assistants.
Prime Intellect has released Verifiers v1, a modular platform for agentic reinforcement learning training and evaluations, featuring tasksets, harnesses, and runtimes.
Learn how TRACE, a new AI system from Stanford, helps AI agents learn from their own mistakes to become more capable and efficient.
This explainer explores loop engineering, a cutting-edge AI approach that enables autonomous machine learning research through iterative feedback loops. Learn how autoresearch and bilevel autoresearch allow AI agents to self-improve and discover new methodologies without human intervention.
This article explains how structured memory systems in AI agents can improve efficiency and performance in complex environments like Slay the Spire 2, by replacing traditional unstructured chat logs with modular memory layers.
This article explores the limitations of hybrid thinking in AI models and why researchers like Junyang Lin are now advocating for agentic thinking as a more robust and scalable approach.
This explainer explores agentic finance, a cutting-edge field where AI agents autonomously manage financial tasks. Learn how reinforcement learning, deep learning, and transformer models enable these systems to make intelligent financial decisions.
DeepReinforce has released Ornith-1.0, an open-source coding model that learns its own reinforcement learning scaffolding during training. The 397B parameter flagship model achieved a score of 82.4 on SWE-Bench Verified.
Learn to build a digital world environment for AI agent testing using Python, reinforcement learning, and PyTorch. This tutorial demonstrates how to create a simulated environment where AI agents navigate obstacles and learn optimal behaviors.