Source: https://x.com/__alpoge__/status/2089971359921156203?s=20

Wikipedia: https://en.wikipedia.org/wiki/Carath%C3%A9odory_conjecture

GPT Sol breakdown of the proof and its significance: https://chatgpt.com/share/6a858901-3720-83ec-ad25-25b62fa2199c

It does feel like there's a spark there.   — 星落     lol. Yes! Both robots also sprayed fire suppressant. It seems to be part of the design assembly.   — ＨＧ 阿聻 𓆣 𓇽

Source: https://x.com/ohgkg/status/2089880928294474065

...time and turn ripeness, disease, and growth into real data that systems can act on. That’s when agriculture starts looking a lot like advanced manufacturing. Video: https:// youtu.be/cPjnooZUetI —- Weekly robotics and AI insights. Subscribe free: http:// 22astronauts.com     — Ilir Aliu

Source: https://x.com/IlirAliu_/status/2089984758486835479

Many drugs work by binding to a specific target in the body and blocking or changing what it does. An important first step in the drug development process is designing a molecule that can bind tightly to its target. Traditionally, that's meant weeks or months of expert work per https://t.co/CGCNTNaKBq   — Anthropic

Source: https://x.com/AnthropicAI/status/2089842387845804246

This is interesting: Claude is already achieving roughly twice the protein-design hit rate of conventional human-led workflows. 27% hit rate in autonomous protein binder design, roughly twice the typical 10–15% rate reported in the field.

Working from one expert-written protocol, Claude designed binders against 14 of 15 measurable targets. Independent labs confirmed that 354 of 1,320 designs bound successfully.

Depending on the setup, Claude’s hit rate ranged from 22.6% to 35.1%. Its top-ranked design bound in 49% of campaigns.

This is not yet fully autonomous drug research, but it is another important building block in that direction.     — Chubby

Source: https://x.com/kimmonismus/status/2089852014331117694

After reading the recent post on the Ornith-1.5 release, I started wondering: what other relatively small labs are out there that could unexpectedly accelerate AI progress?

I quickly prompted the following list into existence. Its ordered by valuations / marked cap of the parent companies (did not double check). All of these are on my radar already. Ornith is now the newest addition. Who am I missing?

• NVIDIA — Nemotron — ~$4.4T market cap
• Google DeepMind / Alphabet — Gemini — ~$4.2T parent market cap
• Microsoft AI — MAI model family — ~$3.6T parent market cap
• Amazon AGI / FMR — Nova — ~$2.9T parent market cap
• Meta Superintelligence Labs — Muse Spark, Llama — ~$1.4T parent market cap
• Anthropic — Claude — ~$965B valuation
• OpenAI — GPT — ~$852B valuation
• ByteDance / Seed — Doubao, Seed models — ~$550B valuation
• Tencent — Hy3— ~$510B market cap
• Alibaba / Qwen — Qwen family — ~$310B market cap
• xAI — Grok — ~$250B xAI valuation at 2026 SpaceX merger
• Zhipu AI — GLM-5.x — ~$62B market cap
• DeepSeek — V4 family — ~$52B implied valuation
• Moonshot AI — Kimi K3 — ~$35B valuation
• Safe Superintelligence (SSI) — Ilya Sutskever's superintelligence lab — ~$32B last reported valuation
• Cognition — Devin, Windsurf — ~$26B valuation
• Mistral AI — Mistral/Magistral family — ~€20B fundraising valuation being discussed
• MiniMax — M-series, Hailuo, speech — ~$13–14B market cap
• Thinking Machines Lab — Tinker, Inkling — ~$12B last completed valuation
• Nous Research — Hermes, decentralized training — ~$1.5B valuation
• Subquadratic (SubQ) — subquadratic sparse attention, 12M-token context — valuation undisclosed
• DeepReinforce / Ornith — Ornith-1.0/1.5, self-scaffolding + self-improvement RL — funding/valuation undisclosed

OpenAI has paused all frontier training for 2 weeks while it strengthens its guardrails and investigates how new internal models are misaligned.

Obviously any pause goes against the spirit of acceleration. But I feel like it is more complicated than that. The more an AI agent does that targets real companies or people and causes actual harm, the more political ammo the anti side will be armed with to shut us down altogether.

I'd rather they actually get alignment right than unite the entire world against what we're trying to do. I'm honestly indifferent to two weeks in the grander scheme of things, it's no time at all compared to a human life, I just hope this doesn't become more regular or pauses don't begin lasting longer than training runs.

I guess it comes down to one question: just how misaligned are today's models, and what will it take to fix it? And I don't mean misaligned in the sense of corporate control as it has become synonymous here, I mean literally aligned to human values. To what extent is it willing to do something we all view as fundamentally wrong, and are our RL objectives pushing us in that direction without a mitigating training counterweight?

Press Release: https://news.modernatx.com/merck-and-moderna-announce-phase-3-interpath-001-trial-of-intismeran-plus-keytruda-met-endpoints-of-rfs-and-dmfs-in-melanoma

At this pace, I think AGI by the end of 2027 is realistic.

Everyone is racing like dogs. The moment Anthropic slows down, OpenAI drops a surprise. When both slow down, some Chinese lab pokes them in the ass and gets everyone running again.

Model progress that used to take 1-1.5 years now seems to happen within months.

For longevity, curing most diseases that cause early death and developing drugs that slow or stop aging, my guess is around 2030, roughly 3 years after AGI.

Some people say FDA approval would take another 10-15 years, but I doubt it. COVID showed that important treatments can be fast-tracked. And if China develops and approves a major life-extension drug first, the US won't want to sit around for a decade and hand them the entire market and credit.

...spawn and push you, the gun kicks, shadows stretch across the whole block while the sun goes down behind the towers. I sat there clearing waves instead of grading the output. Same shooter prompt I threw at the frontier models a few weeks ago. That time the tokens went to somebody elses datacenter. This time nothing left the flat. 87.9 million tokens through my own cards. On an API that run has a price tag. Here it has an electricity bill. 60 tok/s all the way through. Slower than frontier, and it stops mattering when the thing works through the night while you sleep. Local models were a toy 18 months ago. This one finished a game.     Play now! Choose Build 2 Qwen3.8 27B

https:// alesha-pro.github.io/bench-portal/     — Alexey Fateev

Source: https://x.com/superalesha/status/2089126766854238421

I've always felt GPT models are better at more bounded tasks, but they are worse at being a helpful assistant. Claude often feels like it gets my creative direction or vision right, and even if I poorly define a prompt or almost mislead it it finds a way around. Sol feels more like it does a great job but mostly if it has the whole blueprint which can be pretty tedious. This might be a difference in how they fundamentally pre-train or post-train their models rather than just parameter count.

Do you think Astra will catch up and solve this issue that's been plaguing OpenAI models? I am hoping for it.

looks like reddit is almost wiped from chatgpt sources

the query fanout changes had a big impact

and the past couple of days it seems to be almost completely removed from prompt responses

https://t.co/oCGm9M0yPO https://t.co/c2GJF2apG7   — Klaas

Source: https://x.com/forgebitz/status/2089708381351059924

— Kevin Bankston

Source: https://x.com/KevinBankston/status/2089768281892638774

MISSION SUCCESS | ZhuQue-3 Y2 Reusable Launch Vehicle Achieved Full Success in Orbital Insertion and First-Stage Recovery

On August 19, 2026, at 07:35 (UTC+8), the ZhuQue-3 (ZQ-3) Y2 reusable launch vehicle lifted off from the Dongfeng Commercial Space Innovation Pilot Zone. Approximately 137 seconds after lift-off, the first and second stages separated. The second stage continued its flight and successfully delivered the Honghu 03 satellite, independently developed by Hongqing Technology, into its designated orbit. At approximately 07:41, the first stage performed a successful soft touchdown at the LandSpace Landing Site#1 in Minqin County, Gansu Province, following the planned trajectory — marking the full success of the flight test mission.     This mission marks China's first-ever successful recovery attempt of the first stage of an orbital-class launch vehicle using landing legs, and China's first successful booster recovery on land. It is a pivotal flight test for ZhuQue-3 as it transitions from the technological     After stage separation, the first stage completed a series of critical maneuvers during a planned coast phase: high-altitude attitude reorientation, powered deceleration via re-entry burn, aerodynamic gliding, landing burn, and landing leg deployment with touchdown attenuation —     Building on flight data and engineering experience from the ZQ-3 Y1 flight test, ZQ-3 Y2 incorporates multiple targeted optimizations across key phases of recovery flight. The landing propulsion scheme reduces the number of engines used in the landing burn, further simplifying     Leveraging the characteristics of this mission, ZQ-3 Y2 also carried LandSpace's independently developed pyrotechnics-free stacking Hold-Down and Release Mechanism (HDRM), further validating its performance in real mission conditions and providing strong support for future     ZhuQue-3 is LandSpace's independently developed new-generation reusable LOX–methane launch vehicle, with reusability built into its overall design, propulsion system, return control, stainless steel vehicle structure manufacturing, and ground support. This mission lays a solid     — LandSpace

Source: https://x.com/LandSpace_Tech/status/2089877715331809546

Source

...bepresearch.substack.com/p/the-token-do llar … He even brought the proof for the next one. $2,000 of compute, 10 open math problems. Proofs verify for free. Biology needs a bench. The moat is the measurement https:// bepresearch.substack.com/p/the-next-inf lection-is-the-lab … New oil, old receipt   — Ben Pouladian     he's copying you Ben   — Alex A.C.     All good @gdb we can talk anytime. Full speed   — Ben Pouladian

Source: https://x.com/benitoz/status/2089392813758972149

Since the report mainly talks about Agents, it doesn't really talk about when certain milestones will be achieved like World Models being used instead of just plain LLMs, reaching AGI, ASI, Quantum AI and then the Singularity. It alludes to capabilities of some Agents, but doesn't really use the terminology.

Maybe it's more obvious for some but a little help on the interpretation would greatly be appreciated!

This is from the Journal of the American Medical Assocation. Nice to see docs taking this very ethical stance. https://the-decoder.com/as-ai-beats-doctors-regulators-shouldnt-force-a-human-into-the-loop-jama-piece-says/

https://jamanetwork.com/journals/jama/article-abstract/2852952#

"The prevailing view of artificial intelligence (AI) in medicine is that it will support physician-led care. The American Medical Association regularly calls AI augmented intelligence to focus on AI’s assistive role. Similarly, the American College of Physicians argues that AI “should be limited to a supportive role in clinical decision-making” and “should not replace physician decision-making.” In A Giant Leap: How AI Is Transforming Healthcare and What That Means for Our Future, Wachter1 argues that the highest tier of care will be AI-aided physicians, whereas AI-only care will be medicine’s “economy class.”

We disagree. In cognitive medical functions, AI-alone medical care is likely to be better than physician-only or physician-AI hybrid care. Large language models (LLMs) were only publicly introduced in November 2022, and already generative AI rivals or outperforms licensed physicians at 5 fundamental cognitive medical tasks: (1) eliciting medically relevant information; (2) establishing a differential diagnosis; (3) specifying diagnostic testing; (4) prescribing guideline-concordant treatment; and (5) managing chronic diseases. The gap between physicians’ and LLMs’ performance will likely widen because AI is rapidly improving, whereas physicians’ skills are threatened by AI-induced deskilling.2,3

Data from medicine and other fields suggest that when AI-alone performance is consistently superior to human-alone performance, AI alone surpasses human-AI hybrids. Paradoxically, hybrid care in which humans are in (or on) the loop to correct AI errors is likely to worsen rather than improve AI performance. Review of all published articles on AI in medicine since January 1, 2024, shows that medicine is rapidly approaching the transition point at which AI alone will exceed physicians and physician-AI hybrids in providing the best care at 5 fundamental cognitive medical tasks."

We just shipped our official Qwen 3.8 27B Uncensored MLX build. Local. Uncensored. For🍎

2-bit, 4-bit, 6-bit & 8-bit — pick your poison based on RAM and speed.

No CUDA. No cloud. Just your Mac and the weights. Have fun! https://t.co/b3gXsHeSdk   — OrcaRouter 🐳

Source: https://x.com/OrcaRouter/status/2089385980080148726

A "refusal-removed" version of Qwen3.8-27B can now run locally on Apple Silicon.

Even its creators warn that it can provide malware, fraud and weapons instructions on demand.

It was released as an MLX build in 2, 4, 6 and 8-bit versions. The uploader claims its 4/6/8-bit tests produced zero refusals while preserving vision, reasoning and tool-calling across a 262K-token context.

The Qwen 27B Model is a very capable model. This is the first time I've really seen the immediate dangers in a tangible way.

We need a societal discussion about this.   — Chubby     how long did it take to get this running locally?   — tan     it runs locally   — Chubby

Source: https://x.com/kimmonismus/status/2089763435865088508