AI progress — 26 October 2026

Kimi K3.1 Pro is the main release of the weekend: it is live on Moonshot’s API, with open weights promised by 4 November. Until the weights ship, it is an API-only model. Elsewhere, Ollama added speech output on macOS, and Apollo published a sceptical note on AI returns outside the tech sector. Releases were otherwise light.

New models and papers

• Kimi K3.1 Pro and K3.1 Pro Highspeed — Moonshot’s new model is on the Kimi API, with a faster “Highspeed” variant. Why it matters: weights are not open yet, but Moonshot promises a release by 4 November 2026, so self-hosting is a date to plan around, not an option today.
• RynnUnify: Towards Unified Embodied Brain — a 16B model that combines embodied understanding with long-horizon visual planning through interleaved video–language reasoning. Why it matters: it is one model for both perception and planning in robotics, where those are often separate; the results are the authors’ own and unreplicated.
• HoloBoxing: A Simple Recipe for Humanoid Boxing — the authors build on a pretrained whole-body controller and separate reusable motor skills from the task, reporting 7 minutes of single-GPU training. Why it matters: if the claim holds, new humanoid tasks can be added on top of an existing controller at very low training cost.

New tools and software

• Ollama v0.40.11 — adds speech generation on macOS; ollama run plays text or a chat model’s reply aloud as audio is generated. Why it matters: local models can now talk back without a separate TTS stack, at least on Mac.
• Claude Code v2.1.310 — the Monitor tool and plugin monitors now work on Bedrock, Vertex and Foundry, and when nonessential traffic is disabled. Why it matters: teams on those cloud providers or locked-down networks get the same monitoring workflow as direct users.
• Copilot usage metrics API adds tools like OpenCode — the API now reports model usage from more tools developers use with Copilot. Why it matters: admins measuring Copilot usage get a fuller count than before.

Overall digest

• No signs of AI payoff outside the tech sector — an Apollo note arguing that most companies outside tech see no financial return from AI; TechCrunch reports the economist’s phrase as “zero financial payoff”. Why it matters: this is one firm’s view, but it is a concrete claim to test against your own deployment’s numbers.
• Pennsylvania will require labels on AI-generated ads — Governor Shapiro signed the Artificial Intelligence Deceptive Advertising Act, requiring disclosures on AI-generated ads. Why it matters: anyone producing ad content for Pennsylvania audiences now has a disclosure obligation to build into their workflow.
• Securing our frontier model training environment — OpenAI describes stronger containment for training and evaluation, including offline environments and high-compute red-teaming. Why it matters: it is a primary-source look at how a frontier lab isolates training runs, useful as a reference for your own controls.