Microsoft

Microsoft researchers' Fork-and-Flush method lifts agent results up to 66%: Microsoft researchers found autonomous AI agents get trapped in "idea basins" as chat context grows, local solution regions they cannot escape. Their Fork-and-Flush method clears chat history while keeping the workspace, achieving up to 66% better results on the same compute budget.

AI Research • The Decoder

Microsoft plans to scale in-house Maia chips to multi-gigawatt AI inference by 2027: Microsoft plans to make its in-house Azure Maia chips the main AI inference system starting in 2027, at multi-gigawatt scale. The upcoming Maia 300 is expected to deliver 40% more tokens per megawatt than leading GPU systems. CEO Nadella called it Microsoft's biggest bet on its own silicon.

AI Infrastructure • The Decoder

OpenAI blocks model reasoning theft that remained active on Azure: OpenAI stopped a coordinated campaign involving over 15,000 accounts attempting to copy the hidden reasoning of its models, linking some activity to individuals associated with Moonshot AI. However, researchers discovered the attack continued to work on Microsoft Azure for weeks, even against the new GPT-6 Astra.

Security • The Decoder

OpenAI launches Dots always-on agents to automate background tasks: OpenAI has launched Dots, always-on agents that run on their own cloud computers to perform tasks like fixing bugs or sending invoices. Users can access them via ChatGPT, Slack, and Microsoft Teams. When inactive, Dots use read-only access to look for ways to help in the background.

Artificial Intelligence • The Decoder

Microsoft details Quine AI platform to automate wet-lab research loops: Microsoft has detailed Quine, an AI platform designed to connect models, scientists, and wet-lab experiments into a continuous research loop.

AI Applications • The Neuron