Musk pledges a SpaceX share to every American kid, the biggest allowance in history

Musk pledges one of his SpaceX shares to every American kid next year, "the first of many"

A day after telling Anthropic to give shares straight to the public, Musk made his own pledge. It goes through Trump Accounts, so it covers every American under 18 with a Social Security number (@AndrewCurran_): about 72 million kids, or roughly $10.5B at Friday's close of $146.03 (@GuntherEagleman). The White House thanked him.

Cheered on X as the start of "universal high income", Musk's own correction of a "universal basic income" post (@elonmusk). @altcap: "This will be the largest philanthropic gift in history!" A few were less moved: "sufficiently advanced marketing is indistinguishable from philanthropy" (@schisofrenia).

1. [rumour] Anthropic is readying a model that works out what you actually want

Per The Information's one tester, asked to fix a bug it spots the class of problems behind it and asks whether to fix those too. The same scoop has Google's Gemini 4 Carbon and a new OpenAI Terra model due this month.

r/accelerate expects it within days: "Should likely be released tomorrow according to leaks and polymarket". Another reply: "id rather it be opus 5.6 coz fable is expensive asf". @LuminaBench found GPT-6.1 Terra in a Microsoft PR that updated 18 evaluation configs.

Heat: medium · 880K views, 42 posts · 508 pts on r/accelerate

2. [rumour] Anthropic is in talks for a second $45B compute deal with Nscale

It would add a second building at Nscale's Monarch campus, after their $45B deal in August, and could close in the coming days (@negligible_cap). The same day, Microsoft confirmed it had pulled out of Nscale's planned Essex site, which may not get grid power until the 2030s (@mark_k).

Few takes beyond the headlines. @negligible_cap: "Interesting timing to say the least."

Heat: low · 98K views, 28 posts · quiet on Reddit

3. [rumour] OpenAI races to close a ~$30B round before Anthropic's IPO

Per Reuters, the round could value OpenAI above $1.4T, with SoftBank, MGX and other existing backers in talks, ahead of Anthropic's IPO expected in mid-November (@bayaiuai).

Read as a race for the same money: both labs "are courting the *same* pool of capital within weeks of each other" (@bayaiuai).

Heat: medium · 140K views, 11 posts · quiet on Reddit

4. Aleksander Madry returns to OpenAI to work on the pace of AI progress

Months after leaving, he says AI has entered "a different regime" where safety and security "has to become a central priority". Chief scientist Jakub Pachocki asked him back to work on how the pace of progress should shape OpenAI's strategy (@merettm).

Few takes yet. @EthGoldi: it's "openai admitting the strategy question is now the whole game".

Heat: medium · 303K views, 16 posts · quiet on Reddit

5. MiniMax ships M3.1 Flash, and it was the "Space Bunny" model all along

A 428B-parameter mixture of experts with about 23B active, at $0.15/$0.60 per million tokens, with weights due 23 Oct. Artificial Analysis scores it 42, 13 points above MiniMax-M3 but behind DeepSeek V4.1 Flash 1017 (@ArtificialAnlys).

r/LocalLLaMA wanted the size before the scores, and one reply found the benchmarks "look almost like an ad for DS4.1 flash 1017 😂". @nutlope: "This model is insane at design", and 88x cheaper than Opus 5.5 on a landing-page test.

Heat: high · 2.7M views, 63 posts · 571 pts on r/LocalLLaMA

6. Skyfall's SKY-001 builds CAD parts as well as GPT-6 Astra, for under 1% of the cost

▶ Watch the video

An "engineering world model" from the team behind Maluuba, which Microsoft bought. On Skyfall's own test of 1,000 parts it scored 79.7% IoU to Astra's 79.1%, in 3.9 seconds instead of 199, at $0.005 a part instead of $0.75 (@chetaslua).

r/accelerate hailed "The matter compiler", with a skeptic: "Wheres the demo of a real world manufactured product?" @alifarhat79: "GPT-6 Astra: That'll be $750 and 3 business days. SKY-001: That'll be 5 cents and I'm already done".

Heat: high · 3.3M views, 24 posts (2.8M on the launch) · 238 pts on r/accelerate

7. Inception's Mercury 3 is a diffusion LLM that matches GPT-6 Luna and Haiku 5.5 at 1,000+ tokens a second

▶ Watch the video

Diffusion models write many tokens at once instead of one by one. Inception says it beats both on IFBench, GPQA Diamond and SWE-Bench Atlas, with a 1M context, at $0.10/$0.35 per million tokens at launch (@OpenRouter).

"are diffusion LLMs taking off?" asked @scaling01, who reckons 40x the size of Mercury 1 puts it above 280B. @CoreyNoles: "An hour with Mercury-3 and it's clear this is a significant jump".

Heat: medium · 486K views, 27 posts · 96 pts on r/singularity

8. People keep handing their smart TVs to Claude Code to strip out the bloat

▶ Watch the video

The trend reached Brazil: in the top post, Claude removed the TV's preinstalled apps and ads and rebuilt its interface in an Apple TV style, for ~70% less RAM use and a 3x faster UI. Most run it over ADB on Wi-Fi, with no root, and it can be undone (@wallacex227).

"The TV is now a plane. Thank you, Claude. I love you" (@rafaelpimenta1, 386K, in Portuguese). @mchlhess, on Sunday: "if you hack your parents' TV with claude code, DO NOT explain the process. they own a lot of things with model numbers."

Heat: high · 1.4M views, 4 posts · quiet on Reddit

A Gemini agent finds new rules for eleven unsolved Busy Beaver machines

Google DeepMind and Cambridge ran a Gemini-based agent over 1,094 unresolved six-state Turing machines. It spotted patterns in their runs and proposed shortcut rules, keeping only those proved in Lean. The machines, nicknamed "Cryptids", now have exact descriptions, though whether they halt is still open. It matters because the agent wrote the conjectures itself instead of proving ones humans posed, and Lean checked every rule it kept.

Labs report benchmark scores 6.4% higher than independent testers

The builder of the open leaderboard whatmodel.sh matched 611 lab-versus-independent results across 180 models and 103 benchmarks: the labs' own numbers ran 6.4% higher on average. It matters because the gap sits where the lab picks the setup (agent harness, reasoning budget), so those launch numbers need an independent re-run.