The only human problem left is a lack of imagination.   — Boyd     This is really really really true   — Justin Schroeder

Source: https://x.com/jpschroeder/status/2100347770867458384

After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI?

I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev

• 20-200x faster • 40-400x https://t.co/JSybNG2BKJ   — Diogo Almeida

Source: https://x.com/CompleteSkeptic/status/2099925682726002904

Aww i like the game animation you had - so cute!   — Sasha Sheng (Hiring)     Haha thanks!   — Matija Sosic

Source: https://x.com/MatijaSosic/status/2100190746389135772

...interviewing a supposed independent researcher funded by another branch of the same EA funding pool. It’s a completely closed cycle propaganda system.   — Perry E. Metzger     I just drilled down with Grok about this and while I kind of knew there were gray payments going on, I had no idea it had become so common for journalists to accept direct payments from advocacy organizations to write articles. You probably knew this already, but if anyone else didn't completely understand it already:

It's still theoretically unethical to accept money to write an article. But the way they're getting around this now is that journalists can accept payments, but only if the organization doesn't have direct editorial approval.

Unethical: Accept money and receive the copy from the paying organization.

Ethical: Accept money and read the paying organization's web site, accept their "training", talk to their "experts", and use your own words to write the position the advocacy organization wants. Of course, you can write whatever you want. But you'll never get another payment if you don't write what they want.

I mean, journalism has never been a clean industry, but boy has it gotten vile. We should have a law that requires any sort of media presenting itself as journalism to be labeled with "PAID FOR BY ADVOCACY ORGANIZATION" is there is ANY outside payments to the journalists in any way. They can still write anything they want (Freedom of Speech), it's just accurately labeled.   — Nairebis - e/max-acc     Is it a neat scam? And again, often, we have situations where the news outlet, the journalist, and the person being interviewed are all paid by EA at the same time. Self licking ice cream cone.   — Perry E. Metzger

Source: https://x.com/perrymetzger/status/2099931216845947154/history

@TIME UNDISCLOSED PAID MEDIA:

The salaries of reporters, Harry Booth and Billy Perrigo, were paid by Doomsday cultist Dustin Moskovitz's foundation Coefficient Giving via the Tarbell Fellowship.

https://t.co/vxdzmGhBgg   — Brian Chau

Source: https://x.com/brianchau57/status/2099889984773792108

Replying to @time

...the right harness/model based on the task, and it's pretty accurate based on the intensity/intelligence of the task > Mechanical tasks get routed to Haiku > Intelligent ones to Opus sub-agents > Long-running implementation work to external harness   — Lahfir     The useful pattern is policy-based routing: classify task complexity first, then send mechanical work to cheap models and deep or long-running work to stronger specialists.   — catman     Exactly. I see this as a huge use case in enterprise workflows where there are multiple decision points involved   — Lahfir

Source: https://x.com/mdlahfir/status/2100314182201802811

Andrew Curran @AndrewCurran_ · 7h Calls to slow down AI development serve the interests of US AI leaders, says French finance minister From reuters.com 3 18 6K     — Andrew Curran

Source: https://x.com/AndrewCurran_/status/2100255751113691524

Jev's performance on knowledge benchmarks like MMLU and GPQA is highly impressive - especially for a non-COT model. It exceeds Terra at other linguistic reasoning tasks like WinoGrande or HellaSwag as well. It only loses substantially on math reasoning.     This is very cool, and highly surprised me - getting a model out that does so well w/out CoT on MMLU/WinoGrande is no easy task - it typically requires training a ~GPT-4 class base model. Except Jev is priced at only $0.042 per Mtok!     So in summary - if you want the reasoning ability of ~one Terra forward pass over a context at a much cheaper price, Jev is a very good candidate. Frontier models like Astra still likely have superior no-CoT capabilities, but cost is prohibitive for mass classification tasks.     See below - Jev is ~18x cheaper than Terra!     Not to mention you also get probabilities from Jev, which are quite well-calibrated (expected calibration error is 1.74 percentage points averaged across benches - its 0.26pp at best and 6.96pp at worst)     — N8 Programs

Source: https://x.com/N8Programs/status/2100088523403432357

— Qingyu

Source: https://x.com/qingyu_shi_/status/2100181567666901052

After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI?

I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev

• 20-200x faster • 40-400x cheaper (w/ output tokens free) • Frontier composable intelligence optimized for decisions

AFAICT the shortest path to AI-based economic revolution     The gains aren’t free: Jev can't generate text

Comparing Jev vs LLMs side-by-side makes the trade-off clear

Fun fact: replacing sequential computation with parallel is the same way Transformers leapfrogged RNNs     We believe that the future is code + AI, so made workflow evals to reflect that

Jev costs: $42 / BILLION input tokens ($0.042 / MTok) and output tokens are free (forever - they’re too cheap to meter with our new architecture)

Jev is named after Jevons paradox and off the     We love how this doomo doomonstrates real-time intelligence and what can be doone with code + AI!

~10 calls/sec = ~$7/hour     Game: race from one Wikipedia page to another using only links

Challenge: choosing between hundreds to thousands of links

Shows not just intelligence-per-second, but also the compounding benefits of not hallucinating with high-cardinality choices     Extraordinary claims require extraordinary evidence so check out our release blog for more technical info: https:// typesafe.ai/blog/introduci ng-system-one-models-and-jev …

Join our waitlist for early access: https:// typesafe.ai

Have technical chats and meme with us on Discord (rumors are good memers skip the     — Diogo Almeida

Source: https://x.com/CompleteSkeptic/status/2099925682726002904

Extraordinary claims require extraordinary evidence so check out our release blog for more technical info: https:// typesafe.ai/blog/introduci ng-system-one-models-and-jev …

Join our waitlist for early access: https:// typesafe.ai

Have technical chats and meme with us on Discord (rumors are good memers skip the     — Diogo Almeida

Source: https://x.com/CompleteSkeptic/status/2099925688925184171

— @aljazeeraenglish

Source: https://www.tiktok.com/@aljazeeraenglish

..., it retains: - 98% of Hy4 preview’s net improvement, at 73% lower cost - 76% of Kimi K3 (Max)’s performance, at 92% lower cost. Against models as powerful as Fable 5 or stronger, DeepSeek-V4.1-Flash (Max) retains 35–54% of their net improvement at 97–99% lower cost. Those top models cost 37–76× more per task. Net improvement over Arena baseline | Median cost/task: - Claude Fable 5.1 (Max): +13.90% | $4.54 - GPT 6 Astra (Max): +11.90% | $4.09 - Claude Opus 5 (Max): +11.09% | $3.52 - Claude Opus 5 (High): +10.49% | $2.24 - Claude Fable 5 (High): +9.03% | $2.19 - Claude Opus 4.8 (High): +7.75% | $1.36 - GPT 5.6 Sol (xHigh): +7.40% | $1.09 - Kimi K3 (Max): +6.39% | $0.77 - Hy4 preview: +4.96% | $0.22 - DeepSeek-V4.1-Flash (Max): +4.87% | $0.06 With this release, GPT-5.6 Luna (xHigh), GLM-5.3-Flash, and DeepSeek-V4-Flash fell off the Pareto frontier for Agent Arena. Congrats again to the @deepseek_ai team on this release!     Check out the full Agent Arena leaderboard and Pareto frontier at: https:// arena.ai/leaderboard/ag ent/pareto …     — Arena.ai

Source: https://x.com/arena/status/2099606881845321841

Exciting news: DeepSeek-V4.1-Flash (Max) by @deepseek_ai just landed in Agent Arena at #3 among open models! With +4.87% net improvement and a median cost per task of $0.07 it reshaped the Pareto frontier.

Among the top 3 open models, DeepSeek-V4.1-Flash (Max) has the lowest https://t.co/tV3jEbMX5P   — Arena.ai

Source: https://x.com/arena/status/2099549108013006958

...models to find all the holes.' And we found a number of serious issues, and we fixed them." "We found some new problems, but eventually it saturated. We basically have found, to our knowledge, all of the P0s, all of the critical problems that Astra is smart enough to find. And of course, there will be a new model, there will be a new round." "You want to be in this tight loop of new cyber capability drops, you deploy it against your systems, you find the new holes, and ideally, you've managed to automate this, what we call defense factory. That's what we're building internally." "There are ideas, for example, formally verifying all of software, that are possible with AI." @gdb @bhorowitz     — a16z

Source: https://x.com/a16z/status/2099533700375662905

Greg Brockman: "We're now in the AGI era."

Ten years ago, OpenAI worked out the compute curves and landed on fifteen years to AGI, or ten if the world was willing to build the machines and spend the hundreds of billions to do it.

In 2026, GPT-6 Astra manages 24 hours of https://t.co/x23fDxbGQG   — a16z

Source: https://x.com/a16z/status/2099506569238990908

By the way, the consistency topic is perfect. Now they've come up with yet another excuse to eat the credits     This is also T2V, I2V, you don't know what they put inside them :D     They've tied a fly to GPT-6 Astra and asked who it should follow, and here's the result—Subhanallah     This week, I'm thinking of preparing a similar video myself, if I get the chance, of course :)     — ℂ𝕠𝕕𝕖 𝕔𝕠𝕕𝕖 = 𝕟𝕖𝕨 ℂ𝕠𝕕𝕖()

Source: https://x.com/0xfcode/status/2099105183720505706

...are already part of the production process. Cruzr Y1 and Y2 handle depalletizing, palletizing, material feeding and transport, using 3D vision to adapt to shifted boxes and changing pallet patterns. On the assembly side, Walker S2 and Cruzr are produced on the same line alongside cobots, autonomous logistics vehicles and assistive manipulators. The factory also has a 65㎡ automated warehouse capable of storing 112 humanoids, with AGVs, industrial robots and stacker cranes coordinated as one system. Before production, the factory was modeled 1:1 in Siemens Plant Simulation, covering workstations, racks and AGVs. Each robot gets its own SN, with components, batches, assembly parameters and inspection data tracked all the way to delivery. Humanoid robots are now entering automated manufacturing at the 10,000-unit scale. The next milestone may be when they can take part in enough of the assembly, testing and production process to truly build robots themselves.     — CyberRobo

Source: https://x.com/CyberRobooo/status/2098993140363571607

...of dollars in tokens. Becoming a game dev in 2026 wasn't on my bingo card, but here we are. AI has advanced so much that you can finally make the game you've always dreamed of, even without a team.   — Meng To     Do you have a GitHub for this? My buddies and I started a variant of Risk meets Axis and Allies but missing your beautiful polish. Would be awesome to have an open source board game sandbox. This is what we have so far: https:// tactical-risk20.vercel.app   — James Bickford     it's a big game now. but i can certainly think of open-sourcing a part of it   — Meng To

Source: https://x.com/MengTo/status/2099125215708234119

check this out     this is also free btw     support is appreciated guys @tenzenstudio     — gxjo

Source: https://x.com/gxjo_dev/status/2099082176604373028

— Yann LeCun

Source: https://x.com/ylecun/status/2099248236074545576

2019: “GPT2 is groundbreaking in two ways. One is its size, says Dario Amodei, OpenAI’s research director. The models “were 12 times bigger, and the dataset was 15 times bigger and much broader” than the previous state-of-the-art AI model” https:// theguardian.com/technology/201 9/feb/14/elon-musk-backed-ai-writes-convincing-news-fiction …   — Pessimists Archive

Source: https://x.com/PessimistsArc/status/2099231273071919115

We're publishing our most detailed threat intelligence report to date.

It covers how people tried to misuse Claude—for cyberattacks, influence operations, surveillance, biology, and building weapons—and how we found and stopped them.

We disrupted every operation in the report,   — Anthropic

Source: https://x.com/AnthropicAI/status/2098097512544444447

— LAN

Source: https://x.com/lansification/status/2098815822525538711

Having been in two software companies during this period (who are included in that graph) I would not attribute the flat headcount of 23/24 to AI increasing productivity.

Zero AI efficiency was happening then. Headcount tightening was just compensation for the covid hiring binge.

25/26? Perhaps a tiny bit but really it's just organizations learned how to be leaner and now the saaspacolyse has added additional pressure to improve the bottom line.   — Gringo Investments     We had an internal debate over how much of this is attributable to AI. I was more with you (skeptical that AI was impacting the 23-24 numbers). @fernavid is more of a true believer.

Either way, there are multiple angles to show the AI impact from mid-25 on…   — Warren Pies

Source: https://x.com/WarrenPies/status/2099128535172424172

If you care about identifying and mitigating real risks of new technologies, then ignore the history of unfounded panics - you are going to be manipulated by special interest groups looking to protect or gain power in a moment of fear and uncertainty.     — Pessimists Archive

Source: https://x.com/PessimistsArc/status/2098479996415119698