Latest news, beside the leaderboard

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.

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.

Wharton associate finance professor Sylvain Catherine posted on X that his views on AI have "radically shifted": he loves the tools and pays $200/month for Claude, but thinks the industry should be far more regulated and that frontier labs need not race toward superintelligence. The post drew about 48K views and 389 likes and is being shared in AI policy circles.

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.

On October 31, X user @Dylanszn01 posted: "AI is popular because it gives dumb people the illusion they are smart and uncreative people the illusion they are artistic." By November 2 it had about 34K likes, 5,030 reposts and 512K views. On November 1, Louis Anslow, curator of Pessimists Archive, an account that collects historical moral panics about new technology, quoted it with the same all-caps format: "AI is unpopular because it breaks creative professionals' illusion they are special." His post has about 1,852 likes, 103 replies and 35K views. The two posts capture the emotional split between generative AI and creative workers. This is an opinion fight; neither side cites survey data or any institutional finding.

Shopify distinguished engineer Burke Libbey posted on November 1 that moving to a monorepo has been a boon for agents at Shopify; it needs thoughtful tooling and has downsides that take effort to mitigate, but he would not go back. He was replying to Darren Shepherd, who said a day earlier that he hates the idea that monorepos are great for agents. Shopify CEO Tobi Lütke then quoted Burke and recalled Mikhail Parakhin telling him that every engineer hates the idea of moving to a monorepo, yet once it is there no engineer would want to work somewhere without one. Tobi's post drew about 1,115 likes, 454 bookmarks and 89K views and set off a wide debate. These are practitioner opinions, not an official technical announcement.

Microsoft AI CEO Mustafa Suleyman published an X article on November 1 titled "Don't build conscious superintelligence", responding to reactions to his September essay on model welfare. He clarified that his line "AIs are not conscious" was deliberately in the present tense: they are not today, and that is how they must remain. If consciousness started to emerge in training, he would call for everyone to stop AI development until those properties could be designed out. He argued that AI developers have no right to bring a new conscious species into the world and that welfare concerns should focus on humans, animals and the natural environment. He also credited Anthropic for publishing its constitution and research, while saying he disagrees with its approach. The post drew about 353 likes, 251 bookmarks and 290K views, with ethicists and practitioners on both sides. This is a personal opinion piece, not a Microsoft product or policy announcement.

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.

On October 31, Scott Alexander published "Against SURA" on LessWrong. He uses SURA (Stop Unilaterally + Raise Awareness) for the view that AI companies, their employees and countries should halt AI work on their own and focus on raising awareness, and argues it would hand the lead to companies that do not prioritize alignment and cost the US its bargaining chip with China. He cites AI Futures Project members' survival estimates for scenarios without a global pause, mostly in the 25%-50% range, to push back on 90%+ doom estimates. Blogger jessicat quoted it and said parts of AI safety now behave like a mass political movement with bad epistemics (about 359 likes, 63K views); Bloomberg Odd Lots co-host Joe Weisenthal summed it up as people competing to out-doom each other (about 287 likes, 38K views). This is an opinion debate, not a policy announcement from any organization.

Flask creator Armin Ronacher (@mitsuhiko) posted on November 1 that he is convinced an Opus 5.5 agent could now re-implement all of CPython in about two weeks against just the tests, with no human input, possibly with ABI compatibility, no GIL, a JIT, and better numbers on every measurable metric. The post had about 1,637 likes, 98K views and 162 replies. He later added that a rewrite does not strictly need an existing test suite, and that having the agent build its own tests is often better for porting. antirez agreed, while Mario Zechner and Meta engineer Kevin Newton pushed back. This is a personal prediction; no such rewrite has been done.

Indie developer Pieter Levels (@levelsio) posted a roughly 13.5-minute walk-and-talk video on X on November 1, following up his October 11 "software is dead" post. He says AI has finally hit programmers themselves, and the identity and sense of achievement that came from building paid products is fading; his own businesses and many friends' are flat or shrinking, and competition has exploded because anyone can now ship a landing page or app. He sees the remaining moats as community, audience, content and slower-moving enterprise B2B, and has already made Nomad List free as nomads.com. The post had about 2,478 likes and 205K views. These are personal views, not industry data.

Saudi Arabia's Public Investment Fund (PIF) and Aramco announced on November 1 that their deal has closed: Aramco, through a wholly owned subsidiary, takes a 49% stake in Saudi AI company HUMAIN, while PIF keeps 51% control. Besides transferring its own AI, compute and digital assets, Aramco will contribute about SAR 9.9 billion (roughly $2.6 billion) in cash to HUMAIN in 2026. HUMAIN plans to deploy 3 GW of AI data center capacity by 2030 and keeps developing ALLaM, its multimodal Arabic large language model.

At 02:20 UTC on Nov 1, open-source AI builder Jun Song (@jun_song, who builds Supergemma) posted on X that an anonymous black hat group offered him an "astronomical" sum to post-train open-weight models with reinforcement learning on the exploit data it holds. He said the volume was so large he would have believed it was an undercover FBI dataset, that he turned it down, and that what scares him is that someone else will eventually take the deal. As of 17:10 SGT the post had about 2,029 likes, 222K views and 771 bookmarks, and it has been rewritten as a parody template. This is a personal account; the offer, the data volume and the group cannot be verified, so it is treated here as a discussion.

At 00:43 UTC on Nov 1, Tibo (@thsottiaux), who works on Codex and ChatGPT at OpenAI, posted "Banked 1/2" on X; the post has about 6,860 likes and 660K views. In his day 26 post the day before he had teased that "next two days will be resets… banked…", so this is day 27 of his 28-day run: the first of two Codex usage resets you can save and use when you choose. According to OpenAI's Help Center, a banked reset does not refresh usage on arrival; you redeem it in desktop Settings > Usage & billing, web Usage settings, or /usage in the CLI. Eligible plans and the expiry for this particular offer have not been published.

A topic drawing heavy discussion on X: a new Associated Press feature reports that some AI companies are turning to religion as they work out how to teach chatbots right from wrong. On Nov 1 the market-news account unusual_whales relayed the report, noting that Anthropic says it has met with scholars, clergy, philosophers and ethicists from more than 15 religious and cross-cultural groups to help shape how Claude handles moral questions. The post drew about 880 likes, 162K views and 189 replies, and X listed the story among its trending news topics. The Anthropic effort itself is not new: the company described it in an official post on May 19. This is a write-up of the discussion, with opinions presented as opinions.

On Oct 31 the open-source coding agent Memdoor (GitHub guregodevo/memdoor, Apache 2.0) published its team-solve workflow: using the GVS5H paper authors' exact prompts and loop, five Qwen3.8-27B instances act as planner, two ideators, solver and manager, talk only through files on disk, and a script that runs the tests decides success. Over five passes on the first 10 LiveCodeBench Hard problems from the GVS5H list it averaged 9.8/10, against 9.6 for the authors' own harness and 8.0 for a single Fable 5 call; 49 of 50 runs solved the problem for $35.79 in total, and every request and reply is public. The Hacker News post has about 200 points. This is a community reproduction on only 10 problems, and the author notes that training-data contamination cannot be ruled out.

Over the past day, X has been debating whether GPT-6 Astra can work directly as a robot policy. Former OpenAI researcher Will Depue (whose bio lists Sora 1 and 2 and o3/4o post-training) called Astra beating specialized robotics models "deeply surprising", then described it as "the final death of specialized ML". Investor Freda Duan posted that "Astra IS robotics' GPT-3 moment", drawing about 84K views. Third-party evaluations point both ways: in a RoboDojo paper, Astra averages 22.48% success and ranks above all 40 public policies, while an EBench report puts it at 46.7%, third of nine models. This is a discussion of opinions, not an official OpenAI conclusion.

A widely discussed idea on X: on Oct 31 Stripe CEO Patrick Collison (@patrickc) posted that he is building an "improvements" feature into all of his personal vibecoded applications, a freeform text input hooked up to an agent that implements whatever is submitted. He says another person who uses one of the apps has already implemented 150 improvements in a few days, and he floats the name "liquid software" for the pattern. He is also candid that he does not know whether it scales: whether it becomes unmaintainable, how collaborative software works this way, and whether it can be secure and reliable. The post drew about 2,130 likes, 1,900 bookmarks and 147K views. This is a write-up of a personal opinion and the discussion around it, not an official Stripe product announcement.

On Oct 31 Andrej Karpathy published HackerTube (hackertube.org) on his personal blog: a YouTube-style site that only lists the 6,454 YouTube videos recommended in Hacker News comments from 2007 to 2026, grouped into 150 topics. He says Opus 5.5 in Claude Code did the work: it downloaded every HN comment, ran Sonnet over them in a Workflow to narrow things down to about 40K comments recommending a video, wrapped the result in a YouTube UI, then deployed and hardened it on a VPS, all in about 2 hours. His only manual steps were creating a YouTube API key, booting the VPS and buying the domain. His HN submission reached the front page with about 1,005 points and 308 comments.

a16z's Charts of the Week for Oct 30 (by Moses Sternstein) looks at the "Rack Spread": GPU rental prices are rising while token prices fall. The official a16z X account summed it up on Oct 31: since May, average token prices are down 67% and token spend is up more than 120%. By the article's napkin math, Ramp data gives roughly 122%, and Ornn's blended price multiplied by OpenRouter volume gives roughly 160%. A separate post says that since mid-July B300 rentals are up 106%, B200 up 66% and H100 up 17%. a16z also stresses that these indexes come from small, biased samples and do not show true total demand.