A research team from MIT, IBM, and the University of Washington has released TOUCAN, the largest open dataset to date for training AI agents. The dataset contains 1.5 million real tool interactions, aiming to help open models handle external tools more effectively.<br /> The article TOUCAN is the largest open training dataset for AI agents appeared first on THE DECODER. [...]
Baseten, the AI infrastructure company recently valued at $2.15 billion, is making its most significant product pivot yet: a full-scale push into model training that could reshape how enterprises wean [...]
AI engineers often chase performance by scaling up LLM parameters and data, but the trend toward smaller, more efficient, and better-focused models has accelerated. The Phi-4 fine-tuning methodology [...]
Jensen Huang walked onto the GTC stage Monday wearing his trademark leather jacket and carrying, as it turned out, the blueprints for a new kind of monopoly.The Nvidia CEO unveiled the Agent Toolkit, [...]
Mistral AI on Monday launched Forge, an enterprise model training platform that allows organizations to build, customize, and continuously improve AI models using their own proprietary data — a move [...]
AI models are only as good as the data they're trained on. That data generally needs to be labeled, curated and organized before models can learn from it in an effective way.One of the big missin [...]
Microsoft today announced the general availability of Agent 365 and Microsoft 365 Enterprise 7, two products designed to bring security and governance to the rapidly growing population of AI agents op [...]
OpenAI introduced a new paradigm and product today that is likely to have huge implications for enterprises seeking to adopt and control fleets of AI agent workers.Called "Workspace Agents," [...]
Patronus AI, the artificial intelligence evaluation startup backed by $20 million from investors including Lightspeed Venture Partners and Datadog, unveiled a new training architecture Tuesday that it [...]
Researchers at Meta, the University of Chicago, and UC Berkeley have developed a new framework that addresses the high costs, infrastructure complexity, and unreliable feedback associated with using r [...]