
Tencent Cloud has open-sourced TencentDB Agent Memory v2.0, a team-level memory hub for AI agents. The idea is super simple: if project context was already explained once, a new session should not need it repeated. The system turns conversations, documents and code into four reusable memory assets — Chat Memory, Skill, LLM-Wiki and Code-Graph — that are versioned, permissioned and equipped to specific agents. Single-agent memory is not new. What is new here is the governance layer, which lets a
Tencent Cloud has released TencentDB Agent Memory v2.0, a system that allows AI coding agents to share and reuse information learned from conversations, documents, and code across team members. The core innovation is a governance layer that lets one agent's memory be accessible to teammates' agents while keeping privately marked information hidden, solving the problem of repeatedly explaining the same project context. The system converts work into four reusable memory types (Chat Memory, Skill, Wiki, and CodeGraph) and uses layered retrieval with permission controls rather than simple search. The software is open-source under MIT license, self-hosted via Docker, and designed primarily for solo developers and small engineering teams building software.

Long-running agents accumulate state that no transcript captures. A coding agent at step 10 holds edited files, a running dev server, installed packages, and a warm prompt cache. When it misreads a traceback and rewrites a file that was already correct, neither available recovery path is cheap: patching forward grows the context and the token bill, and restarting from step one re-pays every model and tool call while reproducing nothing exactly, because runs are non-deterministic. Jumping back t

New AI toolbars and prompts are showing up in Google Docs and Gmail. If you don’t want Gemini’s help in writing documents and emails, here’s how to turn that stuff off.

In October 2025, a storm brewed over the Caribbean Sea. Weather models differed on its trajectory. Would it remain weak and end up in Haiti, or would it intensify and head to Jamaica? Artificial intelligence model WeatherNext, developed by Google’s DeepMind and Google Research, went with the latter. Five days before landfall, it predicted with 80 percent confidence that the storm system would hit Jamaica as a Category 5 hurricane. Hurricane Melissa was catastrophic, causing flooding and landslid
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