AI Coding Live News

On November 5 Google made Gemini Omni 1.2 Flash (gemini-omni-1.2-flash) generally available in AI Studio and the Gemini API: video generate/edit length rises to 15 seconds, vendor pricing cuts video output about 30% (~$12 per 1M tokens, roughly $0.07/s at 720p), with stronger multi-reference consistency and more natural speech. The changelog states that from December 3, 2026, requests to gemini-omni-1.1-flash will automatically route to 1.2 at 1.2 rates.

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Flower Labs, the company behind the Flower federated learning framework, released Endeavor 1.1 on November 3, its third model this year after the UK sovereign 7B model Lizzy in April and Endeavor 1.0 in September. The update adds image input, an optional EU-only GPU inference tier, and Flower-managed, private-cloud or on-premises deployment, and promises readable thinking traces plus ownership of outputs that customers may use to train their own models. Vendor-reported scores are GPQA 94.4, HumanEval 99.9, AIME 2026 99.9 and MMMU-Pro 81.1, but the comparison uses GPT-5.6 Sol and Claude Fable 5 rather than either lab's newest models, and access is request-only for now.

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Indie developer Pieter Levels (@levelsio) said on X on November 2 that he used Claude Code to decompile the engine of the free Battlefield 1942 demo, port it to C, compile it to WebAssembly and host it at bf1942.pieter.com, where it runs in the browser with online co-op on the Tobruk map. He said the job took about 1 million output tokens, roughly $100 at API prices, while he pays for a $100-a-month Claude subscription. His two main posts drew about 2,200 likes and 340,000 views and reached X trending. These are the author's own claims and community discussion, not independently verified.

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Google CEO Sundar Pichai and Google Research announced that the Project Suncatcher prototype satellite, launched on October 1, finished commissioning and ran a prompt on its onboard TPU with the open Gemma 4 model, downlinking a haiku as it passed over Svalbard, Norway. Google calls it the first AI response from a data-center-class TPU in orbit. Next come thermal-stress and radiation tests, then two interconnected satellites in 2027 to test AI computation distributed across satellites.

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On Nov 2 Meituan's LongCat team listed LongCat-2.5 in its API platform change log as the full release of September 25's LongCat-2.5-Preview. The official technical blog says it has 1.6 trillion total parameters with about 48 billion activated per token, builds on LongCat-2.0 with stronger native visual understanding and agentic coding, and was trained and served with W4A4 inference on domestic AI accelerators. Vendor-reported scores include 88.4 on Terminal Bench v2.1, 38.5 on Terminal Bench v4.0, 91.9 on BrowseComp and 83.1 on MCP Atlas. The API speaks both OpenAI and Anthropic formats with a 1M-token context and up to 128K output tokens, at a limited-time price of $0.30 per 1M uncached input tokens, $0.006 cached input and $1.20 output.

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Katelyn Lesse, Anthropic's head of platform engineering, said on the Latent Space podcast (published Oct 27) that a Rust version of the Messages API fully rolled out the previous week. The old system was a CPU-hungry Python monolith, the team started with "not a single Rust developer", humans designed and verified the system, Claude wrote the implementation, and shadow traffic compared outputs between the old and new versions. Her ballpark figures are roughly 40-50% less CPU and 10-20% better time to first token. A clip posted by Somi (@somi_ai) drew 1,000+ likes and about 140K views on X and was quoted by swyx and others, with the debate centered on whether "never do the big rewrite" is now outdated advice. These are X discussion views and spoken estimates; Anthropic has not published a written engineering report.

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On Oct 30 Google CEO Sundar Pichai announced a "hello world" milestone for Project Suncatcher on X: the team sent a command to the prototype satellite in orbit, booted the TPU, ran a prompt and received the first complete response back on Earth, a haiku. TechCrunch reports the reply came from Gemma 4 preloaded on the satellite.

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On Oct 29 Anthropic introduced self-assessment on X: after each response, Claude produces a structured preliminary safety assessment of the whole conversation for offline review. Anthropic's Safeguards blog says that on Claude Fable 5, at a 1% false-positive rate, it flags 78% of the conversations a stronger prompted classifier flags and 94% of high-priority ones. Because the conversation is already in the KV cache, it adds about 10 output tokens on average and an estimated under 2% of inference compute. It has run in production since June, but Anthropic says it is not robust against an attacker who targets it directly and is only one layer of defense in depth.

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On Oct 28, Mixpanel founder Suhail Doshi announced his new company Particle on X, with its first model, Particle-1, live now. Particle's blog says it is a reinforcement-learning post-train of DeepSeek V4.1 Flash that uses 28.4% to 52.2% fewer output tokens and costs 34.4% to 51.6% less per task across four coding and data engineering benchmarks, with pass rates inside the base model's confidence intervals. It is available through the Particle API, OpenRouter and Vercel AI Gateway; Particle's docs list $0.25 input and $1.00 output per million tokens with a 1,048,576-token context window.

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