AI Coding Live News

On November 2 OpenAI published LifeVal, an evaluation of whether AI can actually get everyday tasks done for ordinary people, such as finding childcare, accessing government services, budgeting, ordering groceries and adapting recipes. The task list draws on the American Time Use Survey, the Multinational Time Use Study and a new demographically representative OpenAI survey of 3,995 people. OpenAI says it has used LifeVal for the past year to track and improve its models, and it lists several best recorded GPT-6 Astra task scores, many at 100%. All scores are vendor-reported and have not been independently reproduced.

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At 15:50 UTC on Nov 2, Tibo (@thsottiaux), whose X bio reads "Codex & ChatGPT @OpenAI", posted that OpenAI is working on expanding the family of frontier models that power dots, including GPT-6 Astra and GPT-6.1 Terra, with others to come. He said Terra brings speed and "a nice personality upgrade" and will help bring dots to more people. Dots are the always-on agents in ChatGPT with their own cloud computer, launched on GPT-6 Astra. This is a first-hand post by an OpenAI employee, not a formal company announcement; no timing or plan details have been published.

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Marvell and Lumentum announced on November 2 a definitive agreement for Marvell to acquire Lumentum in an all-stock deal: 4.5 Marvell shares per Lumentum share, an implied enterprise value of $115 billion (about $1,132 per share, a roughly 23.9% premium). Marvell holders will own about 67% of the combined company. The companies say AI clusters are shifting from copper to optics, and the combination will cover connectivity from data center interconnect down to in-package links, targeting a $550 billion market. Closing is expected in the first half of 2028.

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In his 2027 budget address to the National Assembly on November 2, South Korean President Lee Jae Myung proposed a record 820.9 trillion won budget (+12.8%), with 21.3 trillion won (about $16B) for semiconductors, physical AI, AI data centers and AI, nearly double the 10.8 trillion won in 2026. The Ministry of Planning and Budget document allocates 4.7 trillion won to a sovereign AI model aiming for world-leading performance, including the purchase of 10,000 Vera Rubin GPUs. Parliament still has to pass the budget.

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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 November 2, Abu Dhabi Crown Prince Sheikh Khaled met OpenAI CEO Sam Altman and witnessed four agreements: ADNOC, with G42 subsidiary Inception42, will deploy OpenAI frontier technology; the Abu Dhabi Government and OpenAI launched an AI-native Machine-Readable Government initiative whose first food-import compliance pilot is already in production; Mubadala will apply AI to investment analysis; and Inception42 and OpenAI signed a five-year partnership. Inference runs inside the UAE.

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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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On Nov 2, semiconductor and AI research firm SemiAnalysis released GDPx, a benchmark of agentic capability across 11 domains: chip design, cybersecurity, biology, finance, legal, quant trading, recursive self-improvement (RSI), hardware design, materials science, alignment and software engineering. Its 206 tasks were built by 14 specialist data partners, with SemiAnalysis doing final QA. On the official leaderboard Claude Opus 5.5 leads at 12.0%, followed by Gemini 4 Carbon at 10.9% and GPT-6 Astra at 9.6%; nearly every model scores 0 on finance and legal. SemiAnalysis says safety classifiers drag down Opus 5.5 and GPT-6 Astra, and plans a new version every 3–6 months. All scores are as reported by SemiAnalysis.

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On November 1, John Burn-Murdoch, a Financial Times columnist and chief data reporter, posted a long X thread with his FT piece arguing that the productivity rise in AI-adopting US sectors began in 2020, before AI agents existed, shows up only in the US, and comes mainly from tech layoffs and hiring pullbacks rather than AI. The thread opener has about 1,344 likes, 306 reposts and 186K views. Gavin Baker, managing partner and CIO of Atreides Management, quoted the FT charts and said it is hard not to see some evidence of "ROI on AI," citing a16z and EPB Research data; his post has about 793 likes and 102K views. Burn-Murdoch replied that he is "slightly on the fence" and that the data cannot rule out a role for AI. These are two readings of the same data, not a settled finding.

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