AI & Machine Learning
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Google Rolls Out Orchestrator in Antigravity, Pairing a Carbon or Argon Planner With Hydrogen; Two Google Posts Name Different Terminal-Bench Versions
Google says Orchestrator, rolling out in Antigravity on November 12, hands a task between a Gemini 4 planner and Hydrogen; Google's pages differ on the Terminal-Bench version, the planner options and enterprise access.
MCP Working Group Publishes an Experimental Draft for Moving Files Between Clients and Tools Outside Model Context; No Reference Implementation Yet
An experimental MCP extension draft, io.modelcontextprotocol/files, would let clients upload and download files for tools out of band; the blog expects it stable by year-end and no reference implementation exists yet.
Artificial Analysis Scores Google's Gemini 4 Hydrogen 51 Against Argon's 50 at High Thinking, With $1.87 per Index Task Versus $4.97
Google's Gemini 4 Hydrogen costs $1.50 and $7.50 per million tokens. Artificial Analysis scores it 51 at high thinking against Argon's 50; Google Cloud lists 3.8 Flash at half that price through December 31.
Google Announces XLA Serving Engine, a C++ Runtime for Exported Models; Its Benchmark Reports 2x to 5x a Python Server's Throughput on Small Requests
Google's blog launches XLA Serving Engine, a C++ runtime for exported models. Its repo benchmark, run on one TPU chip, lists 2.0x to 5.0x a Python server's throughput for 1- and 16-item requests and 1.14x at 128.
How Much Notice Developers Get Before AI Models Retire: OpenAI, Anthropic and Google Cloud Publish Minimums, GitHub Copilot Dates Imply About a Month
OpenAI, Anthropic and Google Cloud publish different minimum notice periods for retiring AI models; the Herald's date arithmetic puts GitHub Copilot's notices at 31 to 32 days, and one OpenAI notice ran about three months.
Autark, a 14-year-old's open-source app for AI agent teams, runs Codex and Claude Code with no sandbox or approval prompts, its docs say
Autark, an Apache-2.0 desktop app built by a 14-year-old, coordinates AI agents through Codex and Claude Code; its docs and The Register say agents run with no sandbox, approval prompts or permission gate.
Google Launches Gemini Decisions API With Up to 1,000 Questions per Request at $0.10 per Million Input Tokens; Its Benchmark Table Is Self-Reported
Google says its Gemini Decisions API takes up to 1,000 questions per request at $0.10 per 1M input tokens; Artificial Analysis' Decision Index data scores it between Jev 1.14 and OpenAI's entry.
Five Reports Since April Describe Leaked Fixes or Broken Tasks in SWE-Bench Pro, Which OpenAI Recommended in February; Scale Issued V2 in September
OpenAI recommended SWE-Bench Pro on February 23, 2026; between April 29 and September 8, a GitHub issue, Datacurve, Cursor, OpenAI and an arXiv preprint each described leaked fixes or broken tasks, and Scale published V2 on September 22.
GPT-Image-2.6 Sunburst and Flare reach OpenAI's API; the API reference says GIF needs preview access and 2.6 model pages list Batch as not supported
OpenAI's November 4 API release adds a complexity setting, SVG and GIF output and markup edits; the API reference says GIF requires preview access, the 2.6 pages list Batch as not supported, and gpt-image-2 is deprecated for removal on February 10, 2027.
Google Reports Unprompted Detours to TODO Bug References Added 70% More Steps and 77% More Tokens per Session in Its Agent Traces
Google's developer blog says agents ignored inline TODO bug references in 94% of encounters, and that unprompted detours to them added 70% more steps per session.
Google Open-Sources TPU Sync, a C++ KV-Cache Transfer Library for TPUs; Its Own Low-Concurrency Tests Report Average TTFT Cuts of 60% and 90%
Google says TPU Sync, an open-source C++ library for KV-cache transfer on TPUs, cut average TTFT 60% and 90% at low concurrency in internal July 2026 tests; its README says the APIs are evolving rapidly.
Meta's Muse Ember Scores 36 at $0.14 per Task at Max Reasoning on Artificial Analysis, Which Reports 68.1% on AutomationBench-AA Versus Meta's 37.8%
Meta lists Muse Ember at $0.10 input and $0.50 output per million tokens for prompts up to 200K tokens; Artificial Analysis scores it 36 at $0.14 per task (max) and gives AutomationBench-AA 68.1% where Meta's table shows 37.8%.