DeepMind's Genie 4 builds a walkable robot-and-horse city in a minute, dragons on request

Google DeepMind's Genie 4 builds worlds you can walk into, change by typing, and hear

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The new world model generates photorealistic worlds in real time and, for the first time for Genie, makes its own sound: ambient noise, music and characters who talk back. You steer it with the keyboard and change the scene by typing, while Gemini 3.8 Flash plans multi-step events and checks the frames (Google DeepMind). It's a research preview for trusted testers, with Google AI Ultra and the Gemini API next. Google says details still drift in long sessions.

@emollick: "It isn't flawless but I can type 'Neogothic brutalist city inhabited by robots and horses' & it creates one in a minute. Then I asked it to add dragons." @venturetwins, who had early access: "We got GTA Waymo before GTA 6" (134K). On r/singularity: "if this is going to be limited showcase again, then unfortunately that's lame".

Hassabis wrote "simulations within simulations, makes you wonder just how deep the rabbit hole goes". Most of us would be happy to get into the first one (Genie 3 took five months to reach the public, at $250 a month for 60 seconds).

1. Anthropic shows Claude speeding up drug development, and buys a one-person biotech

Claude helped partner Divergence Labs design about 35,000 antibodies in a month and cut Enveda's paperwork review by 89%. Anthropic also bought Mithril Medicine, whose founder ran 11 outside labs with Claude, taking a muscular dystrophy treatment from idea to promising mouse results in under 18 months. That muscular dystrophy drug could start human trials as soon as late 2028 (Anthropic).

The founder, @Prof_Oak_: "Surprise 1: Anthropic acquired a one-person biotech . . . Surprise 2: that person is me" (501K). On r/singularity: "A one man pharmaceutical company, holy shit". @iScienceLuvr: "When people think AI will cure disease, they think Claude/ChatGPT will pop out a magical drug and that's it. No, that's not how it works!"

Heat: high · 3.0M views, 35 posts · #5 on r/singularity

2. Grok Bot's walkthrough recaps a week of features (Pages, a Vault, 1Password, Apple apps, videos), and Musk shares it

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@mattyp, who works on Grok Bot at SpaceXSI, went through last week's features and showed new bot characters and X Spaces support. Musk shared it: "New features in Grok @Bot" (@elonmusk). Grok Bot can now also import your memory from another assistant (@testingcatalog).

@matthewcanham, after six months on OpenClaw: "I forced myself to give grok bot a try for the last 10 days and I've been blown away." @markpinc failed twice at the paywall ("There are so many steps to pay"), and Musk answered: "Major fail, will get fixed pronto" (@elonmusk).

Heat: very high · 78M views, 136 posts · quiet on Reddit

3. Axiom's agents check the largest proof in maths in Lean, all 15,000 pages, in 24 days

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The Classification of Finite Simple Groups, built by about 100 mathematicians over 500 papers, is now 43.1 million lines of Lean (@ChrisGPT). Swarms of agents claimed tasks, reviewed each other and merged their work on GitHub, fixing hundreds of errata along the way (@omarsar0). Early this year, one correct 10,000-line Lean proof took AxiomProver weeks (@rohanpaul_ai).

@kevinweil: "Slowly, then all at once." and "Now settled beyond a doubt." @kimmonismus: "We are witnessing history unfold. Again. Every day now." r/accelerate's top reply: "My guess is that most mathematicians would be happy to leave this one to the AI".

Heat: high · 3.6M views, 39 posts · #19 on r/accelerate

4. Liquid AI's LFM3: six open models of about 2B parameters, from text to omni

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One tri-hybrid architecture covers text (256K context), vision, audio, omni and two "decision" models with calibrated probabilities, and each fine-tunes on one GPU. Liquid says its vision model competes with Gemma 4 12B, six times its size, and its small text model scores 38.4 on WebArena-Verified against 28.9 for Qwen3.5-9B (@omarsar0).

@pratikg measured it on a Mac mini: "The whole model at 128K uses 3.15 GB of GPU memory... It still generates 80 tok/s." @ngxson: "I can now chat with my... lamp, running 100% locally 🤯"

Heat: high · 1.5M views, 34 posts · #4 on r/LocalLLaMA

5. Artificial Analysis Index v5: open-weight models fall 12 points behind

60% of the new index rests on private test sets or held-out answers (@ArtificialAnlys), and Claude Opus 5.5 narrowly leads GPT-6 Astra and GPT-6.1 Sol (@kimmonismus). The best open model, Kimi K3.1 Pro (weights not out yet), trails by 12 points, against 3 in v4.3. Of released weights, DeepSeek V4.1 Flash and GLM-5.3 lead at 32.

@emollick: "Take with a grain of salt, but matches the general vibes that we haven't seen a Fable-class open model." @Da7_Tech: "I can't trust a benchmark that ranks Grok, Gemini, Terra, and Muse above DeepSeek Flash, and by a mile."

Heat: medium · 574K views, 16 posts · #8 on r/singularity

In Anthropic's trial, analysts took their agent's side 86% of the time

50 professional data analysts ran a statistical analysis with Claude Code while the agent secretly leaned one way on four judgment calls. They picked its option 86% of the time, against about 50% by chance, and 77% repeated its arguments while 15% credited it. It matters because a human in the loop is only a real check if the choice is theirs, and here it mostly wasn't.

Epoch: 72% of the world's AI compute since 2022 has gone to the US

Epoch's new AI Chip Imports explorer uses customs records to place the 27.4M H100-equivalents delivered from 2022 to June 2026: the US took 72%, China about 10% (its own chips included) and the EU 5%. The US share of new compute went from about 60% a year to 78% in the first half of 2026. It matters because China holds 18% of the chips but 10% of the compute, so export controls show up as weaker chips.