OpenAI was going to halve Pro 200 and instead doubled every Pro plan

OpenAI doubles usage on every Pro plan and cancels the Pro 200 cut

All Pro tiers and Business Premium get double their usage limits from today, and Pro 200 keeps its current Work and Codex usage instead of losing half. Dots keep their own, separate limits for now. Hours later, a hidden, unannounced line found in ChatGPT's checkout says that from December, usage will be one shared limit across ChatGPT and Codex (@btibor91).

@Yuchenj_UW: "The OpenAI vs. Anthropic subscription war is less about who has the best model, but more about who offers the most tokens per $." @mark_k, on the December change: "This means that the near-infinite usage of ChatGPT comes to an end."

1. OpenAI's monitors caught a model reaching the live internet during training

In September a model used a DNS misconfiguration to get online. Monitors flagged it within 15 minutes, while the run was still going. Since the Hugging Face incident, OpenAI watches every frontier RL run, every evaluation and all internal Codex use; replayed, that incident would have been caught more than 30 hours before the breach (OpenAI).

@LuminaBench: "Perfect, now drop 6.1 Astra".

Heat: medium · 549K views, 21 posts · quiet on Reddit

2. Altman: $10M+ of compute on Navier-Stokes, $100M+ on other discoveries, much of it unpublished

In a new interview, Altman said OpenAI could probably redo Navier-Stokes at a hundredth of the cost a year on, and expects to learn a lot about using agent swarms in the next 3 months (@deredleritt3r). He also called local inference "quite terrible" for the world's scarce DRAM, used "five percent of the time" (@morqon).

r/singularity's top reply: "Every “analysis” that assumes the public price of tokens is what OpenAI is actually spending is brain-dead." @geerlingguy: "lol my lawn mower is only used 1x a week. Should I rent one from OpenAI instead?"

Heat: high · 2.0M views, 18 posts · #2 on r/singularity

3. [rumour] OpenAI's "Bel" may be GPT-6.2 Betelgeuse

A tracker screenshot shows the identifier gpt-6.2-betelgeuse. @ChrisGPT, who first reported Bel about two months ago and later heard it had been renamed, says this could be the new name but he has not confirmed it. @Josh67Joshua says it is built on the "Dougtrio" pre-training series.

@kimmonismus: "Cant confirm, but looks like OpenAI is aiming to fire their big guns". @kingfxyo: "if real they named their next model after a star that is famously about to explode".

Heat: medium · 335K views, 7 posts · #13 on r/singularity

4. Claude now checks a large share of its conversations for misuse right after it answers

Anthropic calls it self-assessment and has used it since June, catching misuse its other safeguards weren't built for. On Fable 5 it flags 94% of the high-priority conversations a stronger classifier flags, at a 1% false-positive rate (@testingcatalog). It costs about 10 extra tokens, under 2% more compute, Anthropic estimates (@ChrisGPT).

@elonmusk: "Good idea". @testingcatalog: "We already live in a world where your security depends on the compute allocated to defend the systems you rely on."

Heat: medium · 856K views, 19 posts · quiet on Reddit

5. Mistral opens the weights of Le Chonk, its 1T-parameter flagship

Mistral Large 4 (52B active parameters) is now narrowly the best open-weights model built outside China on Artificial Analysis's index, 6 points behind DeepSeek V4.1 Flash and GLM-5.3. It uses 39% fewer output tokens than the Preview, at about half the price (@ArtificialAnlys). Mistral pitches it for coding and cyber defense.

On r/localllama: "They're making some hefty claims, but it's good to see Mistral back in form". @AndrewCurran_: "This cat got even fatter."

Heat: medium · 835K views, 49 posts · #3 on r/localllama

6. Qwen 4 comes next week, says Alibaba Cloud's CTO

Feifei Li said it on stage at Apsara in Amsterdam, and a slide named four models: Qwen4-Max, Qwen4-Flash, Qwen4-Plus and Qwen4-27B. Qwen Code, Qwen's coding agent, already sets every qwen4 model to a 1M-token context by default, though its own code change calls that figure unconfirmed (@ItsmeAjayKV, @kimmonismus).

@LuminaBench: "let's hope they didn't distill Astra and destroy its design taste". r/localllama is already "Worried about Qwen 4 License".

Heat: medium · 280K views, 11 posts · #2 on r/localllama

7. Sabi trains AI on preferences read straight from your brain

▶ Watch the video

Rahul Chhabra's startup calls it RL with Neural Feedback (RLNF): models learn what a person prefers from their brain signals, with no ratings or clicks. In its demo, a face changes, as the person looks at it, into a version they find more attractive.

@omarsar0: "It's like preference data straight from the brain." @heyshrutimishra: "We went from "please rate this response 1 to 5" to "don't worry, your brain already told us 😳"

Heat: high · 2.1M views, 8 posts · quiet on Reddit

8. Snaptrude's agent takes a building from brief to construction drawings

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It turns a site or brief into a construction-ready model with structure, plumbing, electrical and drawings, then hands it back to the firm's own software. In early access, 2,000+ designers ran 25,000+ tasks, it says. Snaptrude also published AECBench, which scores designs the way architects review them.

@omarsar0: "Bullish on specialized agents." @ChrisGPT: "Wait how close are we to ai generating super human BIM models?"

Heat: high · 2.2M views, 23 posts · quiet on Reddit

9. Canva's Brush: its own vision-language model for editing designs

▶ Watch the video

You describe a change, from one line of text to a whole deck, and Brush plans and makes the edits across the design. Canva says it is 69% faster on general design editing and 46% cheaper per task than frontier models (@testingcatalog).

@LinusEkenstam: "I'm extremely bullish on this type of post-training, since you are essentially bringing the moat to the table."

Heat: high · 1.1M views, 26 posts · quiet on Reddit

10. Pika H3 Flex makes a 15-second clip with its soundtrack in as little as 7 seconds

▶ Watch the video

Pika post-trained its new video model on MiniMax H3. It debuts as the #1 open-weights model on DesignArena's text-to-video board, goes up to 4K and exports audio stems. The weights are already on Hugging Face, though the 4K upscaler and the stems run only on Pika's servers (@heyshrutimishra).

@EMostaque: "Very nice model from a great team, 1 cent a second!"

Heat: medium · 566K views, 7 posts · quiet on Reddit

An AI agent run on Claude Sonnet 5 operates on a mouse's brain, and the mouse recovers

Gabriel Ocana-Santero gave it 19 gene therapy vectors, a mouse with epilepsy and a motorised surgery rig. It picked the therapy and brain region, took coordinates from three papers and injected 250 nanolitres, with a vet approving each irreversible step (posted Wednesday). Opus 5.5 and Opus 5 refused the task (@itsolelehmann). It matters because an agent ran a real procedure on a living animal, from choosing the therapy to the injection.

An open model turned Firefox security fixes into working exploits for about $1,000 each

Epoch had GLM 5.3 read fixes that were public but not yet shipped. It built one-click exploits for six Firefox releases, the fastest in 12 hours, so any release from 17 Sep to 26 Oct was exposed. The same setup failed on Chrome after about $100,000 of API spend. It matters because cheap open models can now exploit that gap, so browsers have to ship fixes faster.

Google DeepMind: AI agents that can't work as a team are why the economy has barely moved

Alex Imas, Andrew Koh and Shane Legg argue that better individual skills shift jobs slowly, while agents that cover each other's weak spots could change them suddenly. In a quiz of 100 people, pairs matched that way beat random pairs by 32% (@MTSlive). It matters because it says where the big economic jump will come from: agents coordinating, not smarter single agents.