AI systems began a major shift in 2025 from content creators and chatbots to agents capable of using other software tools and ...
Use any model and build agents in pure Python. Full control. Zero magic. LitAI is an LLM router (OpenAI format) and minimal agent framework. Chat with any model (ChatGPT, Anthropic, etc) in one line ...
Overview: Reinforcement learning in 2025 is more practical than ever, with Python libraries evolving to support real-world simulations, robotics, and deci ...
Abstract: This research investigates the problem of exponential tracking consensus for nonlinear switched multi-agent systems (NSMASs) under limited communication resources. To alleviate the ...
We present Agent Lightning (opens in new tab), a flexible and extensible framework that enables seamless agent optimization for any existing agent framework. Here agent optimization includes various ...
Abstract: This paper presents an agent-based simulation model with cognitive elements, developed to explore strategies for managing complex projects under uncertainty. The model was implemented using ...
U.S.-listed cryptocurrency exchange Coinbase (COIN) has unleashed the latest version of its stablecoin-based payments protocol for AI agents, making it easier to extend and plug in the autonomous ...
Google released on Thursday a “reimagined” version of its research agent Gemini Deep Research based on its much-ballyhooed state-of-the-art foundation model, Gemini 3 Pro. This new agent isn’t just ...
AI agents are being sold as the solution for planning trips, answering business questions, and solving problems of all kinds, but getting them to work with tools and data outside their chat interfaces ...
On Tuesday, French AI startup Mistral AI released Devstral 2, a 123 billion parameter open-weights coding model designed to work as part of an autonomous software engineering agent. The model achieves ...
Currently all the metrics events are defined and handled (also hard-coded) in observability.py and I am not sure if there is a better way to emit OT events/metrics thru MAF rather than re-inventing ...
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