Every ThursdAI, Alex Volkov hosts a panel of experts, ai engineers, data scientists and prompt spellcasters on twitter spaces, as we discuss everything major and important that happened in the world of AI for the past week.
Topics include LLMs, Open source, New capabilities, OpenAI, competitors in AI space, new LLM models, AI art and diffusion aspects and much more.
What a week this has been, not a huge one in terms of new AI releases, but a very significant one in how the world sees and reacts to AI. During the weekend, my timelines were full of hope, and folks reading the “Commanding Heights“ by Will Manidis, outlining a future were AI = the economy.
Then, the US midterm elections happened, and if you’ve not been following, a lot of the new folks who got elected, are not in favor of AI. Some call for an outright pause on advanced AI training. As far as datacenter concerns go, around 40 ballot measures called for restrictions on data center buildouts, with Ohio leading with 21 of those.
The US capital markets reacted violently, erasing over ~3$ trillion in market value, mostly lead by the tech and chips sectors. So I opened the show today with the question: Is it completely over for AI?
I don’t think so, let’s try and make sense of it.
AI and Society: The US Midterms results - Is it over for AI?
Look we try and stay away from politics on ThursdAI, but when it comes to weeks like this, we pretty much don’t have a choice. The Midterm elections, at least in some sense, put AI, Datacenters and candidates that talk about it, in the spotlight.
I’ve mentioned on the show, that messaging in politics is about Hope and Fear. Unfortunately, the folks who got elected, many have made statements, leaning into the fears regular people have about AI. Job replacement, environmental impacts from datacenters, etc.
This tweet by Congresswoman Yassamin Ansari, had been uplifted by the X algo to 12 million views, and as we all know, the algorithm LOVES controversy and FUD.
But, is it really all that bad? Will the democrats get to work and as she suggested “Ban artificial superintelligence”? What does a ban like this even mean when we have Open Source, when Chinese models are catching up to the frontier?
Honestly, this was the open question I opened with at the show, and it seems, that at least for now, it’s more posturing than anything else. Yes, there were over 40 ballot measures asking for Datacenter buildout restrictions, but over 21 of them were in Ohio only. It doesn’t seem at all like “the country rejects AI buildout”
Additionally, the new Texas Governor, Gina Hinojosa’s position on datacenter is actually very reasonable. She explicitly said that currently permitted datacenter builds in Texas will be allowed to continue, and that the moratoriums on new buildouts will apply only until a few fairly reasonable and sensible conditions will be in place. Note: She’s not saying “NO new buildouts” anywhere.
However, moderate takes and reasonable positions are rarely taking center page in the current media landscape, so the bombastic and populist takes are the ones bubbling to the top.
So is it over?
Highly unlikely, the frontier labs will continue to innovate and push the boundaries of AI forward. Some regulation may come, and as LDJ said, it could be that this mid-term result will actually accelerate innovation, as the labs will potentially try and get more done before the next election cycle.
Wolfram’s take is also an interesting one, pausing AI in the US (which is unlikely to happen, as even the folks who got elected will not cede the most powerful tech in the world to China) will not stop AI from being developed elsewhere. Even at current level of capabilities, we can use AI for so much more things, new medical breakthroughs, new algorithms etc that that’s very unlikely to go away.
An interesting thing is happening also, that the fears about AI are very populist, and are landing with folks who don’t have any benefit from AI themselves. Most of the world still uses AI as a better / smarter alternative to Google. This is very likely to change in the next year or two, so by the time next election cycle comes around, we’ll be in a completely different scenario.
Last second edit: new METR report makes safety folks update their ASI timelines
This goes into the bucket of “it’s so over, we’re so so back” - Many respected folks in the AI Safety space are now updating their timelines, given what’s “really” going on inside Anthropic. A new report from METR (The independent AI safety institute Anthropic let in) shows that the speed of RSI (Recursive Self Improvement) is much faster than folks previous thought (And anthropic has blocked much of the full report from being published)
This is to me a much higher signal about what’s really going on with AI vs the market and the politics hype.
The Commanding Heights - who profits from AI (Essay, X)
This book from a financier Will Manidis, is a very interesting background to whatever is happening in the markets with AI right now.
If you remember Leopolds “Situational Awareness” from 2024 (which to be frank is getting a lot of beating right now in the market), this is the spiritual successor of sorts for the end of 2026.
This book looks into the future where AI is the economy, not just part of it, it’s embedded in everyone’s 401K, it’s no longer just a part of the capital markets, and the Sovereign (the states), both US & China (The only two countries that matter for AI) are taking over.
Fascinating read.
What still excites us about AI
I asked the panel what still gets them excited, despite the doom on the timelines. Wolfram says he basically lives with his agent now, and asked everyone to talk about AI with real people offline, because online discussion is mostly hostile. Peter loves discovering things he did not know he could do, and is waiting for models to do 3D animation through code. He also asked for some sympathy: if all you see is AI slop on Instagram and coworkers pasting Claude output into Slack, the backlash makes sense.
LDJ is most excited about formally verified software, starting with big Lean projects and moving to real infrastructure. Nisten thinks public opinion is improving thanks to game mods and decompilations (there are about 200 million gamers on Steam), and says he doesn’t know a single doctor who doesn’t use an LLM now. His closing line: the dot com bubble did not slow down internet speeds.
For me, it is that most people still have not had their “wait, this thing can do that?” moment. And even if everything stopped today (it won’t), current models give us years of use cases to discover.
Big CO LLMs + APIs
GPT-6 Cyber - breaking news in the middle of the TL;DR (X, Linux research, Blog)
As if on queue, to underline how important AI is going to be to the world, to governments and to the economy, OpenAI announced that a new model, focused on cybersecurity, GPT-6 Cyber, has worked continuously to find over 948 Linux kernel escalation bugs in one run that cost around $1.2 million in API credits. OpenAI is making this new model (they call GPT-6 Cyber) available to customers in the premium tier of their DayBreak program (Daybreak Red)
This is maybe the most direct example of why the posturing about “pausing” is incorrect. OpenAI is essentially showing to the world, that if they got to this level of capability, and found so many severe vulnerabilities, the rest of the world will catch up. And so pausing will effectively mean, opening up the door for hacks and exploits to the most critical infrastructure, sandboxes, for banks and governments. If all of the US companies tell their elected officials, “if you pause AI ,we won’t be able to defent ourselves”, it’s pretty clear what the answer will be (Just look at the united states military budget)
The numbers that blew me away, was that ExploitGym, the eval that famoulsy was being tested on when OpenAI swarms of agents hacked huggingface, is now nearly 50% done! GPT-6 Cyber scores 48% on ExploitGym, up from 32% for GPT 5.6 - Cyber the previous model. And, OpenAI is highlighting how strongly their worked on alignment, with these models ONLY doing what they are being asked to do, this model avoided exploiting 99.93% of unrelated and out of scope services.
Who gets access to Daybreak? Well, OpenAI is saying “Our goal is to dramatically expand Daybreak, brin…
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ThursdAI - Oct 29 - Gemini 4 Carbon is the new #1, Anthropic files to go public & more
Thursday, October 29, 2026 • Duration 02:06:02
Hey, it’s Alex 👋
What a week! Gemini 4 Argon was Google’s best model for exactly two weeks. Then Google shipped Gemini 4 Carbon, and it’s the new number 1 in the world. Google is SO back. (when they actually release, it’s waitlisted so far)
The other big story is Anthropic’s S-1. For the first time, we get real, audited numbers on what a frontier AI lab looks like as a business. Peter Gostev stayed up making 60+ charts, and we walked through them together on the show.
We also had models trying to escape their sandboxes, and Genie 4, which made me think (again) that we live in a simulation.
Wolfram and I hosted from the same room for once (meatspace!). Peter, Nisten and LDJ joined remotely. Mert Gulsun from Artificial Analysis joined to talk about their new index, and for From the Forge we had the CoreWeave engineers who are “forward deployed” inside the Aston Martin F1 team! What does that mean? We dive into FDE
Google is SO back
Gemini 4 Carbon - #1 on Artificial Analysis, 2 weeks after Argon (X, X, Sundar)
Gemini 4 Carbon scores 59 on the Artificial Analysis Intelligence Index. That makes it the top model in the world on their brand new index, 1 point ahead of Claude Opus 5.5. It also debuts at #1 on Text Arena and #2 on Agent Arena.
Two big models back to back is unusual for Google, after a long stretch of Flash models. There’s no version number either. It’s not Gemini 4.1, it’s just... Carbon. I have no idea why 😅
I haven’t seen a Gemini eval chart like this in a long time. Google is finally competing with the full frontier (GPT-6 Astra, Opus 5.5, Fable 5.1), and on most rows it wins.
My favorite eval here is Vending Bench from Andon Labs, where the model runs a real vending machine business. Carbon finished with $16,484 in the bank. Opus 5.5 finished with about 9K. LDJ was most impressed by RiemannBench, a very hard math benchmark, where Carbon beats Opus 5.5 by 10 points. Math was supposed to be OpenAI’s turf!
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ThursdAI - Oct 22 - AI finds all the vulnerabilities, Claude Duet, DeepSeek drops Infer & more AI news
Friday, October 23, 2026 • Duration 01:55:57
Hey %%first_name%%,
Welcome to what cybersecurity experts are calling “Black October” - after a series of critical vulnerabilities that allow remote execution were found in PHP and Node.js, several companies were hacked, and a new supply chain attack on the very popular LiteLLM library was acknowledged.
The internet is freaking out, and we’ve tried to make sense of it all, with a security expert Josh Long on the show.
Also this week, Anthropic stepped into the personal agent category with Claude Duet, their direct competitor to Dots from OpenAI, Muse from Meta etc’. Duet is proactive and always on, and can do work while you’re asleep! I got access this morning so this isn’t the full review yet.
Also DeepSeek is back with a new model and their inference engine!
Let’s dive in:
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Claude Duet - a personal agent powered by Opus 5.5 and doesn’t wait for you (X, Product, Blog)
To me this is the most exciting announcement of the week (which otherwise was full of doom and gloom). Anthropic finally stepped into the personal agent category! Shipping Claude Duet, as a separate mobile app, and its own online UI (claude.ai/messages) which is what I was missing from OpenAI’s Dots!
Duet is built around Opus 5.5, brings over your existing memory, skills and connected apps, and reaches into 6,000+ connectors and plugins on their platform. Every few hours it checks your accounts, surfaces what needs you, and does the task from its own cloud computer, laptop closed.
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Claude now leads 26% of Anthropic’s R&D, Meta drops an 816B open model & Gemini 4 Argon
Friday, October 16, 2026 • Duration 01:58:04
Hey, it’s Alex 👋
What a freaking week! I spent 3 days at AI Engineer in New York, and we did the show from a real studio in Manhattan (the internet did NOT cooperate at first, but we got there 😅). And while I was running around the Sheraton, the labs kept shipping.
Meta became a frontier lab, for real this time. Muse Wonder is #2 on Arena, and then, in the last minutes of the show, Meta ALSO dropped Muse Spark Open, an 816B open weights model. Google’s big Gemini is finally back with Gemini 4 Argon, and Omar Sanseviero and Geneviève Huskens from Google DeepMind came on to show it off. Anthropic gave us 4 stories plus a rumor, and Nathan Benaich came by to talk State of AI 2026.
My theme this week: AI engineers are sleeping on personal agents. More on that below, including how my Muse found this studio and got me coffee on the way here.
With me: Wolfram Ravenwolf, Peter Gostev (Arena), Nisten, Yam Peleg and LDJ (who brought the breaking news, as always). Let’s dive in (all links at the end as always!)
Meta is BACK at the frontier
Muse Wonder - Meta’s first frontier model is #2 on Arena, and it smells BIG (X, X, Arena, Blog)
Folks, we told you after Llama 4 was a disaster, we told you when Zuck started hiring people with soup: do not, under any circumstances, bet against Zuck (and now Alex Wang). Muse Wonder is #2 on Arena Text at 1513, 12 points behind Argon, and it definitely smells like a big model.
There are 2 of them. Muse Wonder is in the API at $4 in / $20 out per million tokens, basically Opus 5.5 pricing. Muse Wonder Full, the better one, is only for Muse Code subscribers at $50 or $200 a month. Did you see what they did there? Everybody calls their top setting “Max”, Meta called it Full, so it’s... Wonder Full. Wonderful 😂 No open weights for either, Meta says they’re too big and maybe too risky.
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Chen Goldberg (CoreWeave) on the AI loop, Forge and infrastructure for agents
Monday, October 12, 2026 • Duration 25:34
Hey folks, a quick bonus episode!
At CoreWeave's Fully Connected in San Francisco, a few minutes after she walked off the keynote stage, I sat down with Chen Goldberg, EVP of Product & Engineering at CoreWeave.
We talked about Forge, the loop every AI engineer is running now (run, observe, curate, improve, evaluate), what carries over from the Kubernetes days to agents, and what breaks first when agents hit your infrastructure.
Video below, and the audio is right here in your podcast feed. Enjoy!
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ThursdAI - Oct 8 - OpenAI drops 722 math papers, Haiku 5.5 hits 10 cents & more
Friday, October 9, 2026 • Duration 02:02:36
Hey %%first_name%%, another banger AI week, let me catch you up!
We say this often but this week we all felt the acceleration! Just look at one Tuesday. OpenAI dropped 722 math manuscripts. Meta( With Stripe, Shopify and Walmart) announced a new agent protocol. OpenAI opened up the Decisions API. Mistral came back with Le Chonk (Mistral 4), Claude moved into Google Docs, and we at CoreWeave shipped RL Rollouts. That was ONE day. Then the rest of the week happened 😂 Haiku 5.5, D1, and tons more!
I had 48 topics on my list, so I asked Claude to build me a Tinder for AI news: I swipe on each story, and it stack-ranks what makes the show this week. I hope we did good (lmk in comments if we missed a major news story)
With me: LDJ, Peter, Yam, Nisten and friend of the pod Maxime Labonne from Liquid AI joined us to talk decision models. Let’s dive in, all links at the end as always!
Remember when ONE Navier-Stokes result was the whole show? On Tuesday night, OpenAI quietly pushed 722 math manuscripts to GitHub, grouped into 372 families of results. No hype video, no exploding-head emojis, just a very thin blog post. My favorite new term for this is a “slop grenade”: somebody throws a mountain of output at you, and now you have to shovel through it.
An internal model nobody outside OpenAI can use was pointed at about 4,000 open problems, at about 3 hours of ChatGPT Pro-level thinking per result. Will Depue asked Fable to measure the drop in Navier-Stokes units. The answer: roughly 5. Roughly 5 “Navier Stokes” size solutions dropped all at once!
The math is so advanced that a mathematician in one family of results often can’t follow the family next door without an LLM explaining it. I find that fascinating and scary at the same time.
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ThursdAI - Oct 1 - OpenAI joins the assistant race, CoreWeave drops serverless GPUs & more
Friday, October 2, 2026 • Duration 01:57:29
Hey %%first_name%%, it’s Alex 👋 What a freaking week!
This one was special. We came to you LIVE from the middle of the show floor at Moscone, from CoreWeave’s Fully Connected, with robots walking behind us and a Vera Rubin rack a few feet away. ThursdAI is only possible because of CoreWeave, and this is their biggest event of the year, so we packed up the mics and did the show right there (at 11am, which confused a bunch of you, sorry!).
It’s October. The last quarter of 2026. And nobody’s pacing! There’s no pacing the frontier. Three big models this week (GPT-6.1 Sol, Claude Sonnet 5.5 and Gemini 4 Argon), OpenAI’s biggest DevDay ever, and the story I’ve been yelling about for weeks finally went mainstream: OpenAI joined the AI assistant race.
With me: Wolfram Ravenwolf in person on the floor, Peter Gostev from Arena (who was at DevDay with me), Nisten and LDJ remote. In hour two we interviewed four folks from CoreWeave, on physical AI, Forge, sandboxes, and one piece of breaking news I’m still excited about. Let’s dive in (all links at the end as always!)
OpenAI DevDay 2026 - 20 launches and a new assistant
Dots - OpenAI joins the AI assistant race (X, Blog)
Meta has Muse. Grok has Grokbot. Anthropic has Claude, but it’s not really an assistant. And this week OpenAI stepped in with something called Dots. I was in the room at Fort Mason when Sam talked about it, and it was the headline of their fourth DevDay, which honestly felt like OpenAI’s WWDC: 20 releases, the biggest DevDay ever.
Funny thing, the original ChatGPT system prompt was literally “you are an AI assistant.” But it wasn’t proactive, it never pinged you, it just sat there. So OpenAI looked at their competitors, looked at Peter Steinberger from OpenClaw (who they hired like 8 months ago), and built this. A dot is an always-on agent in ChatGPT, powered by GPT-6 Astra, with its own computer and its own browser in the cloud, connected to 4,000+ apps people already built for ChatGPT. It works 24/7, you can talk to it in Slack or Teams, and there’s an interface that looks like a phone call. I think that’s going to be great for my mom.
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Opus 5.5 is your new workhorse! OpenAI ships GPT 6 Sol and Luna before DevDay and Meta goes all in on Muse! Your friday read is here
Friday, September 25, 2026 • Duration 01:40:53
Hey, it’s Alex 👋
What a freaking week! A week after every lab head agreed to “pace the frontier”, Anthropic and OpenAI shipped big new models within hours of each other, and both of them are CHEAPER. So much for pacing 😂
Visit https://thursdai.news/ep/2026-09-24 for all the links in this podcast
And we had a new producer on the show today! Opus 5.5 listened to us live, put up the chyrons, kept me on time (mostly) and even fact-checked Nisten on air. If the stream died, you knew who to blame. You can re-watch it work on thursdai.live if you want to experience being there with us!
3 huge themes this week: pacing the frontier does not mean stopping, Assistants not just agents (Meta went all in on Muse at Connect), and voice, where Google now says it has the best TTS in the world... and it clones voices.
With me: Peter Gostev (Arena), Nisten, Yam Peleg, and Wolfram Ravenwolf live from AI Engineer Paris (thanks Mazi for the tether!), plus JevBench creator Florian S. Let’s dive in (all links at the end as always!)
Frontier AI - not pacing yet!
Claude Opus 5.5 - Opus is BACK, Fable-level smarts for 40% less (X, Blog, System card)
Folks. FOLKS. Opus 5.5 is the highlight of my week, and it’s not even close. It’s like Opus 4.6 is back, with Fable-level abilities, and it talks like a normal person again - no more Jargon Douche Claude!
My week started with burning through my quotas on Fable, and I was like, oh no, I need Claude for production on Thursday! Then Opus 5.5 dropped and... I just couldn’t get to the end of my quota. I ran workflows, agents, Claude Code for hours with no end in sight. Remember the “limitless Codex” days when you never thought about quotas? Then Astra came out and I burned my entire weekly quota in half a day (ps. this was partly due to a bad config, so if Astra is burning your tokens, keep reading for a fix). Now it’s flipped, and Claude is the seemingly limitless one. And it’s fast!
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ThursdAI - Sep 17 - TypeSafe's Jev is a ChatGPT moment for decisions, Pace the Frontier splits the labs & more
Friday, September 18, 2026 • Duration 02:15:30
Hey yall, Alex here, writing this VERY late because, well, not every day a new type of “ChatGPT” moment drops. I really hope I’m not overhyping this, but a new model (that’s NOT an LLM!) called Jev (a wink to Jevons paradox) just came out and if what I see early on materializes, this is another ChatGPT moment (or another reasoning models moment). I am completely blown away by the implications of the speed/accuracy/cost (the holy grail of all models) of this model. Please if you read one thing in this newsletter, read this. (or listen, I’ve interviewed Allie, a Devrel on the TypeSafe team for 30 minutes and it wasn’t clear who was more excited about Jev!)
The other huge theme of this week is... pacing. Pacing the frontier. Dario Amodei of Anthropic penned an essay saying that the models are getting to a point where it’s important to pace the development of new and super capable AI, and outlines 3 ways to do so, one is about letting independent evaluators inside the labs, second is collaborating with other frontier labs (they are asking for an exception to anti-trust laws for this) and third is to try and have global cooperation with “authoritative gov” (he means china). Trumps answer: This is all a hoax. Lovely times to be alive. Also we outlined Jensen and Zucks positions on this topic ,read more below.
And the third huge theme is the rise of the AI assistant. I’ve told you about Grok and Muse last week, Instinct (a new invite only AI Assistant that VCs are going crazy about is raising at a $10B valuation) and we interviewed the guy who evaluates them all on assistant bench. + Muse released a mac app today!
Tons of other stuff happened but it’s getting near impossible to cover everything so we’re switching to themes and notable mentions. read on (and do listen to the pod, it was edited by heavily using Jev and Fable, so might be a bit rough while I smooth the edges, but do LMK in comments if you like this faster format)
TypeSafe AI debuts Jev, a non-LLM ‘System One’ decision model from ex-OpenAI RLHF lead that’s 200x faster and 400x cheaper than LLMs (X, X, , , , )
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OpenAI solves Navier-Stokes, Meta’s Muse a free AI agent that’s really good, DeepSeek V4.1 shrinks KV cache, and one doomer post causes OpenAI to consider pausing training + more AI news
Friday, September 11, 2026 • Duration 01:43:31
Hey yall, welcome back to ThursdAI, this is Alex, let me catch you up!
Today on the show, we covered 1 week with Astra (hint, it’s not quite AGI yet despite what we were told), DeepSeek V4.1 catches up to the frontier at a fraction of the cost, and Meta launches a free AI agent with it’s own computer, that will take over the OpenClaw/Hermeses of the world for most people. Also huge this week, OpenAI claimed that a swarm of 10K agents of their unreleased model solved the Navier-Stokes, one of the millennium problems!
I was stoked to have Chris Alexiuk from Nvidia on the show to cover the innovations DeepSeek put into this latest model!
Oh, and the guy who quit Anthropic this week, and wrote an essay about “AI is going to kill all of us” somehow got 130M views on X, a mirriad of TV interviews and rekindled the doomerism movement, we talk about that too!
Also, I already told about FullyConnected, CoreWeave’s premier conference that’s coming up, but they told me about a new announcement today, and you’re not going to believe who it’s about (not AI related). As a reminder, ThursdAI subscribers get a free ticket!
Ok, let’s dive in!
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OpenAI claims a Navier-Stokes solution from a 10,000 agent swarm from an unreleased model - with some drama (X, Blog, Paper)
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Google is pitching Carbon for agentic coding and cybersecurity. The launch price is $2 per million input tokens and $10 per million output, which already includes a 50% launch discount. Wolfram loved this. Models are finding security holes that have been there for years, and fixing them takes a LOT of tokens. In his words: “the cheaper the model that can do this, the better for everybody.”
The catch is access. Right now only selected cyber defenders get it, and everyone else gets it “soon”. I got early access the night before the show but barely used it, so I don’t have a hands-on verdict yet.
Peter tested it until 1am. On Agent Arena it jumped from Argon’s #7 to #2, at a fraction of Opus 5.5’s cost per task. He also made the best point of the segment: if Google had skipped Argon and shipped Carbon with no waitlist, we’d all be saying “oh my God, Google is back.” Instead, people are confused about why they shipped two models in two weeks.
He’s right. But if you missed the Argon drama, Carbon is a great release. Congrats to the team, and please let us actually use it! Until then, you can try it on Arena.
Anthropic filed its S-1 and lists on Nasdaq this Monday under the ticker ANT. This matters because Google, Meta and the others keep their AI numbers buried inside a bigger business. For Anthropic, AI is the whole business, so now we can actually see the numbers. In Q2 2026 they made $974 million in operating profit, with an 85% gross margin.
Peter picked the S-1 as his highlight of the week, over any model release. His reason: even if you don’t care how rich Anthropic gets, this proves there is real money in AI, and that money pays for the next models and the infrastructure. The numbers are good, and nobody credible is saying otherwise.
Adding 5 billion in a quarter is insane
Here’s the growth. In 2025, Anthropic made a billion or two per quarter. In Q1 2026 they made about $4.7B. In Q2 they made $11.55B, more than double in a single quarter. As Peter said, “that does not happen.”
And that was before Opus 5.5 came out. The S-1 stops at Q2, but later reporting puts Q3 around $16.8B, so they added another 5 billion. Peter’s reaction: “Adding 5 billion in a quarter extra is insane.”
We say “insane” a lot on this show, but this time it’s literally true. Claude Code started as a side project inside Anthropic. Around Opus 4.6 it turned into a general agent that can actually do things, and this chart is what happened next.
A common worry was that the revenue depends on a few huge customers, like Cursor. It doesn’t. In 2023, about 20 customers paid Anthropic more than $100K a year. By December 2025 it was 1,500. Now it’s almost 12,000. Enterprises are slow to adopt, but once they do, it looks like this.
Where the compute goes
The S-1 also shows how efficient their compute spending got. Through 2025, Anthropic spent more on compute than it made in revenue. In Q1 2026, each dollar of compute brought in $1.40 of revenue. In Q2, it brought in over $2.
LDJ added something most people miss. People assume research compute means training the big final models like Opus. But Epoch and others estimate the final training run is at most about 30% of it. Most of it goes to thousands of small experiments looking for better algorithms. Peter estimates that about 70% of Anthropic’s compute in the first half of 2026 went to R&D and internal use, not to serving customers.
The risk factors
Every S-1 has a list of risk factors, and most of them are boring. "We face intense competition." Interest rates could change. But this one has a line no other IPO has ever had: sufficiently advanced AI systems "could... pose catastrophic or existential risks to humanity." Such a Dario move 😂
The timeline turned that into "risk factor #4: our core product may end humanity", plus a bonus #5, "our models may refuse to help with this filing." That one is a joke, it's not in the filing. But the existential risk line is real.
Peter’s investor take was great. If the product doesn’t end humanity, you made a lot of money. If it does, you won’t care. (Not financial advice, folks.) Wolfram took it more seriously. If it’s a real risk, and they’re making this much money from models trained on everything humanity wrote, they should share that value. To be fair, the co-founders have pledged up to 80% of their funds to public benefit.
This is a huge moment for anyone who’s followed AI for years. Go browse all of Peter’s charts, they’re incredible.
World models
Genie 4 - a real-time world model with sound (X, Blog)
Genie 4 was my personal highlight of the week. Every time world models level up, I say we’re probably living in a simulation, and I’m saying it again. First you could walk around in these worlds. Then you could interact with them. Now you can HEAR them. Genie 4 generates sound along with the picture: ambient noise, music, even dialogue.
The other big jump is consistency. Older world models felt like a dream, where you turn around and things have changed. Genie 4 keeps things where you left them. Peter asked if the demos are cherry-picked, and honestly, a little. You roll the dice a few times to get a great one. But the sound makes it SO much more immersive.
So we tried it live. I created a sunlit Italian piazza cafe, with people walking by and steam rising from a coffee cup. Then I edited the scene while it was running. I turned the coffee into wine and added an explosion in the street behind the camera. You could hear the explosion, and people shouting in Italian 🤯 It’s not perfect (the wine came out looking more like a cup), but I haven’t heard audio like this from any other world model.
After From the Forge, I built an F1 world on the fly. You steer with WASD and move the camera with the mouse (thanks to Genevieve from DeepMind for the tip in the comments!). I added a rival cutting in and explosions on the track, and the sound effects were perfect. You could even see cars in the mirr…
The rest is pretty much the same, similar UI, similar features to others, just with Claude taste and intelligence. It can somehow interact with Claude Code but not fully, so it can’t be used as a chief of staff. This seems like a weak link given just how much folks are using Claude Code.
Claude Duet is also not personal at all, I didn’t find a way to rename it or make it “mine”, it doesn’t seem to do any phone calls. So for now, it’s a great start, but definitely not replacing Muse for me.
Hot take: Anthropic is following in this category, not leading. OpenClaw and Hermes worked best with Anthropic models, then Anthropic cut off subscription access for them, and now we finally see why. Every lab has a personal agent now: Dots, Muse (still leading for me), Grok Bot, and Google’s Spark, which most people don’t even know exists. Nisten says Dots “feels like that government employee that tries to avoid all responsibility”, while Muse is “so energetic”. LDJ finds Dots a net positive.
My big realization: switching personal agents is WAY harder than switching coding harnesses. Once your assistant knows everything about you, moving takes a lot of effort for the human. If you only copy over the memories/context, then you have two/three AI assistants doing the same work, sending you the same notifications and all updating you about the same emails.
Black October: the densest and scariest security week I can remember
Some folks are calling this month Black October, and it’s one of the worst I can remember. Some bugs were found by AI, some attacks are run by AI (Microsoft says a China state-aligned group used an agentic pentest framework called ARTEX against hundreds of organizations), and some attackers are just going after your AI keys. Security expert Josh Long joined to keep us sane, with an attempt of positivity though it wasn’t easy!
PHP2Shell - AI helped find holes in the language that runs 70% of websites (Wiz, OpenAI, Blog, Calif, CISA, Checker)
This was one of the hugest things that shook the industry this week!
PHP runs an estimated 70% of websites, and two bugs in the language engine itself let an attacker send one request, no login, and potentially take over the server with code execution ability. CVSS 9.2, every release back to 5.4. It is really important that if you are running anything on a PHP server, that you patch it right away. Ask your agents to do a security audit.
This vulnerability was present in the PHP code for 14 years! Calif found the first bug in an audit funded through OpenAI’s Patch the Planet initiative. Josh says several groups finding the same bugs independently is rare, his advice was refreshingly calm: if you run a PHP server, you should have patched yesterday, no excuses. Cloudflare invented a new form of WAF to block it for all websites that are protected by Cloudflare and the big cloud companies patched right away, so regular folks browsing the web can go about their daily business.
Still, a lot of websites that are run on PHP and aren’t able to patch, their IT guy quit, or they lost the keys to their servers, and your information can be at risk of getting stolen. Personal security actions like locking down your credit (if you’re in US), rotating passwords, having a password manager is always a good idea.
OpenAI Daybreak - the defenders got the good models (X, Infosecurity)
Back in August, post the HuggingFace hack, Greg Brockman penned “the defenders window“, where he outlined that Defenders need access to the best models, with lower safeguards to get ahead of the attackers. It seems that this defenders window was starting to close this week, given the hacks that happened in addition to the PHP2Shell vulnerability disclosure, which for the record, wasn’t a hack!
OpenAI’s Daybreak blue gave vetted researchers GPT-5.6 Sol with loosened safeguards (and GPT-5.6-Cyber on the Red tier), and Hacktron’s s1r1us credits it for a run of finds: a HEIF heist, a KVM escape, PHP2Shell, GitLab RCEs, a full Chrome chain and a WordPress RCE. Greg Brockman calls this the Defender’s Window, and it does feel like it’s closing.
Railway and OpenCode: someone is always hunting your AI keys (Railway, OpenCode)
OpenCode got hacked about a week ago, and now Railway too, and what the attackers seem to be after is your LLM API keys. The main reason is, API keys can be immediately sold on the black market and used for distillation. They are immediately and immensely valuable.
Think about it. Your personal data is probably on the dark web already, I’m not sure how much your SSN is even worth right now. But an OpenAI or Anthropic key without a limit on it is basically direct access to your credit card, and there are people buying those keys on the black market for distillation. If you had keys on either service, invalidate, rotate them and make sure to have separate keys for each service despite how much pain in the A it is. Also always add a limit!
If only there was a more secure way to make machines talk to other machines!? Turns out, there is, it’s called OIDC, it just wasn’t implemented yet by anyone besides the big companies. It’s more complex than just minting a simple API key and pasting it into a file, but it’s definitely the right way to go!
eMudhra - root certificates with a private key of... 4? (X, Cloudflare)
The other big one this week has nothing to do with AI, it’s just plain human negligence. eMudhra is one of the certificate authorities your browser trusts to sign HTTPS certificates, and it turns out some of their root certificates were created with a trivial private key (Cloudflare’s Matthew Prince says it was literally the number 4!). Anyone who figures that out can mint a “valid” certificate for any website, and your browser would happily trust it.
Josh (who wrote about DigiNotar back in 2011, a very similar mess) walked us through what this means in practice, and it’s less scary than the timeline makes it sound. To abuse this, an attacker has to sit in the middle of your connection, think sketchy coffee shop Wi-Fi, and only then can they pretend to be Google.com and read traffic you thought was encrypted. Chrome, Brave, Edge and Firefox have already removed eMudhra’s roots, and Safari is lagging behind because Apple takes its time with patches. So update your browser and your OS, and you’re good.
Nisten has a theory that the key was changed by hand during …
Meta’s own table beats Opus, Astra and Fable on a bunch of evals... but Personal Superintelligence Index, GDP.pdf, JobBench, MemoryBench (which Meta built, and then won)? I’ve never seen most of these. Every launch now is the iPhone 18 moment: numbers bigger, best one yet.
On evals we know, Artificial Analysis has Wonder Full at 56 and Wonder at 52, Opus 5.5 on top at 58. And on OSWorld, the Wonder we can use sits below Fable and Opus, and computer use is the number one thing I need from an assistant.
Peter’s Arena view: #2 on text means people like talking to it, but it’s 12th on Agent Arena, and he tried building websites with it, “it was kind of awful.” His theory: Theo loved Wonder Full and thought the API Wonder was bad, so maybe Meta is talking about a different model than the one we got. Not ideal. He also found the half-life of a benchmark quoted in a launch is about ONE release: quote it once because the number looks good, never see it again.
Wolfram says it’s excellent in German. Nisten joined not knowing what Muse Wonder was (”No idea”), sometimes our co-hosts come to get their news from the show.
My Muse got upgraded with a click
Here’s where I disagree with the timeline. “It can’t do 3D scenes, so it sucks” misses the point. Meta is tuning Wonder for Muse, the personal agent. Officially, Wonder will “soon” power more of Muse, subscribers first. I’m on the paid plan, and my Muse (Wilfred) flipped to Wonder the moment I subscribed. Matrix moment: “I know kung fu.”
Then I kept shoving tasks at it. Muse found the podcast studio I recorded from in NY and emailed Ezra at Virgo Studios with my requirements, got me coffee on the way here, and designed and ordered the wristbands for our AIE sauna meetup. The failures weren’t logic, they were the real world: a site that’s blank because Cloudflare doesn’t like agents, a Stripe link that wouldn’t connect, and businesses that hung up because they didn’t want to talk to a personal assistant 😂 Peter’s read: that’s the harness, not the model, and it’s exactly why this stuff is so hard to benchmark.
Muse Spark Open - Llama is SO back (X, X, Blog, HF)
In the last minutes of the show, LDJ hit us with breaking news: Meta released Muse Spark Open 20 minutes earlier. 816B total, 42B active, 1M context, multimodal in, text out. Meta calls it the most capable US open-weight model to date. I wish I had my air horn button!
LDJ’s framing: about 3x smaller than Kimi K3, and the fair comparison is GLM 5.3 (753B, 40B active). You’ll need about 700GB of VRAM for NVFP4, or, per Zuck, two new M5 Ultra Mac Studios.
Peter found the coding asterisk: Terminal-Bench 2.1 is 76.4 vs 83.9 for GLM 5.3 and 85 for Kimi K3. Better than the US open models, not yet at the top Chinese ones. Nisten read the license live: show “built with Muse Spark Open” in your product, and there’s a $20M annual revenue cap. His take: great for generating data, and “probably one of the best computer use ones.”
Post-show breaking: Peter put Spark Open next to the earlier Spark releases, and on coding it lands closer to Spark 1.1/1.2 than 1.3 (Terminal-Bench 2.1: 76.4 vs 84.3). So it’s not the latest Spark with the weights flipped open. Still, every lab that ships weights gets our applause 👏
Can I just say... it’s about time! Peter pointed out we hadn’t seen a full Pro-class Google model in 8 to 10 months. Gemini 4 Argon (I called it a “novel gas” on air, it’s a noble gas, sorry chemistry teachers 😅) is GA in the Gemini API, AI Studio, the Gemini app for Pro and Ultra, and Antigravity for Ultra. #1 on Arena Text, #1 on Roboflow’s vision evals.
It’s $2 in / $10 out until November 30, then $4 / $20 (what comes after? Omar: “breaking news for next month”). Omar’s TL;DR: go try it, you’ll be pleasantly surprised. Geneviève says it’s their biggest training run ever, and Argon, an early checkpoint, is already helping train the next generation.
Artificial Analysis has Argon tied with GPT-6 Astra at 53, at about 60% of Astra’s cost per task (at the discount price), with Opus 5.5 still on top at 58. I haven’t been able to test it myself yet, so the demos did the talking.
Geneviève’s Desk Racer is a racing game built on top of her actual desk. She gave Argon reference photos (the mic, a cute cat figurine), it planned the track around the objects, and it even prompted Google’s Omni video model to pull engine sounds from race cars and loop them. Play it in the AI Studio gallery.
Her process is the tip of the week. Reference images, let it grill you with planning questions, then one big goal: spawn sub-agents, work as long as you need. The secret sauce is an adversarial sub-agent that grades the output out of 10 and sends it back until the score is high. For 3D, render something rough, ask Nano Banana to “make this look real”, and hand that image back to Argon: “make it look like this.” The neon in Desk Racer was designed by Nano Banana. Use visual references, folks!
On the million-token outputs, both were honest: day to day you don’t need them, they’re for long scientific work. And the RSI-flavored one: Argon optimized vLLM so Gemma 4 E2B passed 100K tokens per second on one A100, “AI for AI” as Omar put it. Geneviève’s ask: give Argon a creative shot, “it’s the start of a new era.” Google is back!
Anthropic’s very big week
Distillation defenses cut harvesting by up to 99% (X, Blog)
Wolfram caught the one I missed: after clamoring for regulation on distillation, Anthropic just did it themselves. They say what distillers can harvest is down 90 to 99%, mostly by locking down Claude’s reasoning traces, with a classifier and tens of thousands of banned accounts.
I know the effect on ME: not a day goes by that my Claudes don’t disconnect and ask me to re-login. I don’t know if that’s the security work, but Anthropic, please, please let me use my Claudes wherever I am. This is getting old 🤦♂️ Nisten noticed that if you even mention “reasoning” while working on LLM code, Claude Code now trips and stops. His verdict anyway: “you can’t beat Opus”, try everything on Opus Low, “it is ju…
Peter’s tried this before! For weeks he threw GPT-6, Fable and Opus at one problem, Hadwiger-Nelson. He thinks he burned 300 to 400 BILLION tokens, and in his words, “I did not discover a single bloody thing.” And this new OpenAI’s model spent about 3 hours on it and narrowed the bounds from 5-to-7 down to 6-or-7 😅
Then LDJ dropped a stat that I made him repeat slowly. Fable and Astra had put together a list of the 500 most important open problems in math ever. On Tuesday, OpenAI dropped solutions to 92 of them. There’s also a list of the 100 most significant problems from the last 12 months, and over 80% of those got solutions in this drop. Absolutely insane, folks. Yam’s reaction was a very loud “F***ing go.”
Yam’s favorite is the Riemann one. It doesn’t prove the hypothesis, it bounds a region for the zeros, which “was never done before, and many, many, many people have tried.” And to the “it’s just brute force” crowd, Yam says: “Let’s brute force everything.” Yes please, room temperature superconductors next! LDJ’s mathematician friends think that on some of these, the model used fewer tokens and less time than a human would. So who’s brute forcing whom? 🤔
The missing crypto results (speculation!)
If you hold any crypto, this part is for you.
The manuscripts are numbered, and some numbers are missing. There’s a #44 and a #46, but no #45, and LDJ counted 4 or 5 gaps like that. He also looked at which topics made it in, and cryptography is almost absent.
So here’s the theory going around. Maybe OpenAI found something big in cryptography and held it back, either by its own choice or because someone asked them to. LDJ said it himself: it sounds conspiratorial. But the US government really can stop cryptography research from being published on national security grounds.
To be clear, this is SPECULATION. Nobody outside OpenAI knows what’s in #45. But Bitcoin’s security rests on elliptic curve math. Imagine a paper that shows a way into the 25,000 old Satoshi wallets, each holding 50 BTC. Not great for the price, not great for the world, and not great for encryption in general.
“Are you saying your field is useless?”
Not everyone is celebrating. Not every result is verified in Lean, and nobody outside OpenAI can reproduce any of it.
Kevin Buzzard (thanks Ksenia from Turing Post) says many mathematicians are going through the stages of grief. I get it. Imagine spending decades on one problem and watching 3 hours of compute knock it down. When I wrote code in the 2000s, I didn’t consider it my life’s work. For a lot of mathematicians, that one problem IS their life’s work.
Then came a letter from the Association for Human Mathematics: “Mathematicians did not ask for this work to be done.” Peter’s take: imagine doctors saying “please stop curing diseases, we’ve got a good thing going.” So, “are you saying that your field is useless?” You can’t say your field is really useful and also ask everyone not to solve any of it.
I don’t understand the please-don’t-solve crowd. Get on board. This is in OpenAI’s hands today, and in a year it’ll be in everyone’s hands. That’s the pace we’ve been on. Figure out how you can place yourself so when you get access to these level of capabilities, you can make the world a better place!
Frontier for everyone
Claude Haiku 5.5 - 10 cents, and Luna has catching up to do (X, Blog, Sonnet cache cut)
Haiku is BACK after a whole year, and this is one hell of a model. It costs 10 cents per million input tokens and 50 cents per million output (under 100K tokens), and cache reads are 1 cent. Haiku 4.5 was a dollar. So it’s TEN times cheaper, and significantly better. I’ve missed Haiku for all the stuff where you want Claude-level intelligence, but really fast and really cheap.
Just a week ago, GPT-6 Luna was THE fast, cheap reasoning model. According to Anthropic, Haiku 5.5 scores 72.4% on OSWorld, versus 48.9% for Luna, and 39.2% on Terminal-Bench 4.0, versus 16.4%. GPT used to be the computer-use king! These are Anthropic’s numbers, so let’s wait for independent evals.
Quiet bonus: Sonnet 5.5 cache reads are now half price, which Anthropic says makes most agent work about 20% cheaper. Peter: “For agentic work that’s the biggest thing.”
Yam called it “the obvious choice for swarms,” and “Anthropic is on fire, and we are the ones getting stuff because of it.”
And Nisten? He’s “running 10 Haiku agents right now,” because he already burned through 97% of his Max 20 plan. He also used Haiku to research his rice cooker ratios. Nisten. Bro. It’s 1 to 1 and a half, my grandma knows this 😂 His actual verdict: it’s better than Qwen 3.8 27B, and “it kind of feels like Sonnet, actually.” Folks, use Haiku. All three of the Claude brothers are great right now.
The same day, GPT-6 became the default in ChatGPT for everyone, free users included. It’s just “GPT-6,” no Sol, no Luna, no Astra. (Terra is dead. RIP Terra.) Most of ChatGPT’s 1.2 billion weekly users are on the free tier, so with one release OpenAI just upgraded the intelligence of a huge chunk of the world. If you’re on the free tier, congrats, your intelligence has been upgraded.
It also comes with something OpenAI calls Intelligent UI. Instead of a wall of text, answers can come back as charts, forms and small working tools. I asked it to visualize OpenAI’s math drop, and it built me a little app right in the chat. The search inside it didn’t work, but it did show 719 manuscripts instead of 722. OpenAI had quietly pulled a few back since I did my research.
Peter’s point: anyone listening to this show is “very not normal” (said with love!). Your hairdresser isn’t listening to ThursdAI, and for most people this free upgrade matters way more than a new 500-a-month model.
Claude in Google Docs, Sheets and Slides (X, Blog)
Small thing, huge thing. Our Claude producer keeps a Google Doc for the show, and every time I asked it to add a story, it had to spin up a whole computer. Now Claude lives in a sidebar in Docs, Sheets and Slides, and asks before every edit. Beta, paid plans.
Sam literally said he uses dots to run OpenAI. And my favorite DevDay moment: Romain Huet’s live voice demo didn’t work, because somebody was deploying in the middle. But Thibault’s dot had already pinged him that the demo might break. The dot knew before the humans did 😂
Wolfram (him and Amy are a known duo) loved that Sam uses it for actual work. Peter was more honest: underwhelmed at onboarding (”you connect and it’s like... then what?”), but once you’re past that you’re talking to Astra, and it’s great at juggling threads through one bot. Same shape as Muse. Wolfram’s version: one executive assistant, and a lot of sub-agent employees working for you.
Dots is Pro only for now (including the $100 plan), while Meta gives Muse away free. With 1.2 billion weekly ChatGPT users, this goes to everyone eventually. This is the race now.
We covered GPT-6 Sol on this show LAST week. Five days later it’s already replaced. GPT-6.1 Sol is the same price, $2 in and $10 out, but cached input is now 95% off, 10 cents a million tokens. OpenAI’s pitch is near-Astra intelligence for a fifth of the price.
And the independent numbers kind of back that up. Artificial Analysis has it 1 point below Astra at 72 cents a task vs over 3 dollars. On Deep SWE it actually beats Astra at about a sixth of the cost. It’s the default in Codex now, and folks are calling it the workhorse.
LDJ said it has “less of the big model smell” but loves the token efficiency, Sonnet and Opus 5.5 burn a LOT of tokens. Peter has it 4th on Code Arena, above Fable, and says it’s a bit “artistic,” it goes into its hole and comes back with the thing. And his verdict is the one I had to repeat straight to the camera:
It does not make sense to use Fable or Astra as your daily driver right now. Opus 5.5 is enough. GPT-6.1 Sol is enough. For Navier-Stokes level problems, sure, reach for the big ones. Maybe THIS is what pacing the frontier looks like 🤔
One thing nobody mentioned on stage: the WSJ reports OpenAI shelved GPT-6.1 Astra, the big one, after safety tests showed it being more deceptive. OpenAI hasn’t confirmed it. But the model they felt good shipping this week is the cheap one.
If you’re a billionaire, there’s another option: a $500 Pro tier with UltraFast mode, their models on Cerebras. Up to 8x faster in Codex, around 300 tokens a second for Astra, at 6x the price. Sam said it’s so fast he never wants to go back.
And quietly, the $200 Pro plan is back... with half the usage. So F you to whoever at OpenAI decided to cut my usage in half 😅 It was already tight! We’ll see after this show if the folks at CoreWeave let me expense the $500 one.
The Codex harness now runs fully in the cloud. Close your laptop, turn it off, steer it from your phone, and it keeps going. And there’s an Agents API in public beta with hosted computer use, basically the stuff that runs dots, as an API.
My call: local environments make no sense anymore. The more I run Fable and Codex on my machine, the less memory I have. All the cloud needs is my logins... and that’s what dots are for.
This one made me smile. You give it a question and a fixed set of answers, and it gives you back one answer, fast. It runs on Luna, it’s multimodal, and it’s waitlisted, so we can’t benchmark it yet. If you’ve listened the last few weeks, that’s exactly what Jev from TypeSafe does.
Wolfram and Peter both liked the same thing: these models are so cheap you end up classifying ALL your data, so keeping it with the provider you already use matters.
Did OpenAI just react to Jev? I asked Sam at the Q&A. Diogo told Swyx on Latent Space that he pitched this idea to Sam 2.5 years ago and Sam said “it’s a crazy idea, you should work on it.” Now decision models are popping up everywhere like mushrooms after rain. TypeSafe proved the category exists.
For the FOURTH time, OpenAI launched the App Store at DevDay. GPTs, then plugins, then the app store, and now... plugins again 😂 This time on MCP Apps (shout out Liad and Ido who created this category).
The bigger play is Sign in with ChatGPT. Remember “sign in with Facebook”? Now it’s sign in with your tokens, so apps can use the plan you already pay for. 1.2 billion people is a lot more than Apple had when it launched the App Store.
Wolfram also brought up Google’s new family assistant, CC, and I have to say it. Google’s Spark is awful. Sorry if you work on it. Spark is connected to Gmail, Drive, everything Google, it should be the BEST assistant in the world, and what I use assistants for most is my email! Google, why are you not building the best assistant for my email?
Big CO LLMs + APIs
Claude Sonnet 5.5 - faster, cheaper, beats Opus on Terminal-Bench (X, Benchmarks)
Anthropic did not want to give OpenAI any time to rest on their DevDay laurels, so on Monday they shipped Sonnet 5.5, a week after Opus 5.5. Over 30% faster than Sonnet 5, up to 30% cheaper for most work, same $2 / $10 as GPT-6.1 Sol, and on Terminal-Bench 4.0 it scores 70.6, which beats last week’s Opus (66.4).
Peter put it best: if we’d had access to these models 6 to 8 months ago, we’d be losing our minds. All the Anthropic models are jumping over each other and crowding up against the frontier. Opus still feels a little smarter, Sonnet is totally ok to use, and Fable doesn’t quite make sense anymore.
LDJ thinks it’s the new best FREE model for friends and family (it’s on the free tier, even at high reasoning). Nisten made it his default for agentic tasks because “it talks a lot nicer,” but never for coding: “nothing beats Opus 5.5 on a large code base.”
The numbers back it up. It beats Anthropic’s own Fable 5.1 on GDPval-AA (1846 vs 1735), 66.4% on Terminal-Bench 4.0 vs 57.9% for GPT-6 Astra, and it’s 40% cheaper than Opus 5. Output goes from $25 to $20 /1Mtok and cached reads from 50 cents to 20 cents, and for agentic coding the cache reads are most of your bill, so you really feel it. Basically the smaller, overachieving brother of Fable. Sonnet and Haiku 5.5 are coming in the next few weeks too.
Peter came in hot with Arena news: Opus 5.5 is #1 on Code Arena, above Astra, and the HTML and 3D stuff it generates is “completely insane.” His one caveat: on his hardest max-effort prompts, a single generation cost $60 to $80 in API terms, so the long tail can still get pricey.
And then Nisten, who (like all of us) has specific opinions about Anthropic’s politics, said it writes the best code he’s seen, it’s crazy good at WebGPU and kernels, and it’s “an absolute banger.” It’s his default now. Folks, do you understand what it takes for Nisten’s default to NOT be some obscure open source model he runs himself on 17 GPUs?! Anthropic won over Nisten. I don’t think you guys get what just happened here.
Wolfram is the holdout, he left Anthropic over the OpenClaw bans and hasn’t touched it since. Wolfram, how do I say this gently... you’re an evaluator, this is not allowed 😂
An Anthropic employee basically said “sorry for Opus 5, we hope this makes up for it”, and honestly it does. Opus 5 was slow, incoherent and full of Claude-isms. Nobody wanted to talk to it. The Claude-isms are gone, the jargon is gone, this model talks like a human. I used to love Opus back in the Opus 3 days, and it feels like that again.
Want to squeeze even more out of it? Read the great Addy Osmani’s guide to Opus 5.5 (@addyosmani). 2 things blew my mind: stop writing “think carefully” in your prompts (”You don’t need to ask it to think”, it picks its own depth, and replies start sooner without it), and one early tester found Opus 5.5 on its LOWEST effort caught more bugs than Opus 5 on high, with fewer false alarms. Try low effort before you go max!
Tip from me to you: if it ever gives you something confusing, the pstack “bro” skill (/bro) makes it say it again in human words. I use it all the time.
(Full disclosure: Opus 5.5 produced the show AND helped with this writeup, so it might be a tiny bit biased 😅 but the quota thing is 100% me.) Anthropic, please, please don’t nerf this one.
GPT-6 Sol and Luna - half the price, and honestly better than Astra for me (X, Blog, Caching)
Hours later, OpenAI answered with GPT-6 Sol ($2 in / $10 out) and Luna (10 cents in / 50 cents out, that’s basically free!), at half the GPT-5.6 price. The lineup is now Astra, Sol and Luna (bye Terra). On DeepSWE, Sol gets 68.8 and Luna 66.6. The sneaky big one for builders: 90% off cached input, and changing reasoning effort or tools no longer busts your cache 👏
Ok, hot take... Astra has been kind of dumb for me day to day, burning tokens for crappy results. Sol is great, and Luna is even better! Peter agrees, Sol is his daily driver and he only flips to Astra when Sol can’t do it. Wolfram misses the humor and personality 5.6 had, so “keep 5.6” is officially the new “keep 4o.” Reddit says the news is the price, not the performance, and... they’re not wrong.
PSA if Codex is eating your account: I had previously set my context window to 1 million tokens via the se, which kills OpenAI’s cache and rips through your quota. Removed it, moved sub-agents to a cheaper model, and usage went right back to normal. Check your codex.toml! if you don’t know how, just so just ask your codex to diagnose itself.
Also from OpenAI this week, a 4-area plan for independent safety audits. No auditors, dates or funding yet, but hey, it’s the pacing idea on paper. (Blog)
Assistants are not agents
Meta Muse gets an inbox, your Mac, and a place on your face and becomes a Tamagochi!? (X, My Connect supercut)
Muse is #1 in the App Store (to be precise, it got there faster than ChatGPT did, not more users... yet). Zuck says Muse is now the center of everything Meta builds, and they shipped a LOT: it controls your Mac, gets its own email you can CC, does real-time voice and video with a face you design, and keeps working while you talk to it. It’s coming to the glasses with a custom wake word, so yes, I get to say “Hey Wolfred” 😂
If you don’t have an hour to watch the whole keynote (it was a good one!), I cut a 2.5 minute supercut of the most important announcements for you 👇
On the hardware side: new Ray-Ban Meta Gen 3 (I already ordered, will report next week), audio-only glasses with no camera that are also FDA-certificed hearing-aid! (maybe the most important launch for a lot of people!), VR Glasses that look like normal glasses, and the Muse Charm, a Tamagotchi-like keychain shipping in December.
But the part that got me? Every Muse comes with a real cloud VM (root, 8GB RAM, 100GB disk). Nisten has been living in it, Tailscaled into it, and when it hit a CAPTCHA he tapped it on his phone and it just kept going. 100 million tokens a week plus a computer in the cloud, free, for everyone! Peter’s take: it’s the only big consumer app that doesn’t treat people like idiots. Meta’s pitch is no ads (they are going for a novel “we’ll get a take from the transactions you do with muse and our partners like Shopify, BestBuy, Walmart and a bunch more they announced) and a private VM co-designed with Moxie Marlinspike, though Peter doubts anyone’s parents care.
Assistant tip: connect your email, go on a walk, hit record and just talk about your life. Assistants are only as good as what they know about you. Mine now checks our weekend plans for activities cancellations after I woke up too damn early to drive kids to a karate class to find out it’s closed that week & searches local events every Thursday! Weekend plans solved - proactively!
Grok 4.7 disappoints... but Grok in your Tesla is the real news (X, Blog, Tesla)
Sorry Cursor folks. Grok 4.7 gets 46.3 on CursorBench (up from 40.4), $2 per million with 500K context, but it’s still behind even GPT-5.6 on where it matters, and they compared 4.7 on xHigh against 4.6 on High 🤨 Everyone on the panel agreed, disappointing. Peter won’t write them off yet, my read is it’s a talent and data problem, not compute.
But here’s what I AM excited about: Grok Connectors in Tesla. One guy asked his car for his usual Starbucks, Grok placed the order, set the destination, and it was paid and waiting when he got there. My car already drives itself, and soon it’ll do my email. Your car has MCP now, folks! (SuperGrok Heavy only, and I don’t have it in my car yet 😭)
Fun moment: our Opus 5.5 AI producer fact-checked Nisten live on how many Teslas are on the road. About 10 million (9.2M delivered by Q1 plus ~480K in Q2). Nisten was right! He wants the same thing for politicians.
This Week’s Buzz 🐝
Next week ThursdAI is LIVE from Fully Connected at Moscone South in SF (Sep 29 to Oct 1, the day after OpenAI DevDay), with Fei-Fei Li, BattleBots and... yes, Pitbull! We start at 11am Pacific. Come hang, listeners get in free with code THURSDAIFC2026 (Register)
Also huge news for us, CoreWeave got Platinum on SemiAnalysis ClusterMAX again, 3 reports in a row, the only provider to do it 💪 (SemiAnalysis)
And W\&B Hive Mind saves every agent conversation across harnesses and machines, and lets you fork them. I fork Codex sessions into Claude for a review all the time. Plus, it’s completely free! (Try it)
Last week I said open source would copy Jev fast. It took less than a week! The clones speak Jev’s format, so you point the TypeSafe SDK at a different URL and it just works. jeff is MIT and ~6x cheaper to self-host, and Laya went viral as the “Jev killer” (its own model card is a lot more modest).
Laya’s real trick is running locally. Nisten’s WebGPU demo loaded ~600MB into my browser and classified Hugging Face model cards at 132ms per decision, on MY machine, for free 🤯 The clones still make about 1% errors where Jev barely makes any, and Yam says wait for more benchmarks. But my take: System 1 models are fast and cheap enough to sit inside your code and make the same call every time. They’re the microprocessor of the next era of software.
We also had Florian S ont the show, he built JevBench (@airesearch12, Benchmark Heaven), and has barely slept since Jev dropped. He started the benchmark that same day, it has 70+ entrants now, and people have literally tried to hack his machine to steal the test set! Laya briefly hit #2 and is now around #36: super fast, runs on CPU, but not as smart as Jev on the hard questions.
Post-show breaking: a few hours after we signed off, Florian shipped JevBench v1.4.2 and... a 4B open model, decider-4b v2, took #1 (64.13 vs Jev’s 63.29)! His own asterisk: Jev is still smarter (53.1 vs 49.4 on intelligence), decider wins on speed (5x faster) and cost (~half). Told you open source would catch up fast 😅 (X)
Voice & Audio
Gemini 3.8 Flash TTS is #1... and it clones voices (X, Blog)
Google is BACK in voice. Gemini 3.8 Flash TTS and Flash-Lite TTS are #1 and #2 on Hume’s quality index, cheaper than before, with 2 speakers per request. The big one: clone a voice from 30 seconds of audio (adults only, recorded consent, SynthID watermark and C2PA credentials). We played the designed voices live, and the meditation guide in headphones was 🤌. I didn’t clone my own on air though, recording my consent on a live stream is exactly the thing that gets faked!
Years ago we said nothing would break when voice cloning went mainstream, and nothing did, just like with GPT-2 and Stable Diffusion. Nobody knows where this goes, and that’s why we cover it with optimism.
Lightning round
ACTx486 - interrupt a podcast, and it answers back (X, Site)
This one is wild. Karina Nguyen’s research demo turns a Joe Rogan episode with Elon into a video you can talk to. Tap Elon, ask a question, and he answers while a model draws the explainer: a flamethrower diagram, a Starship you can open up, then both of them on Mars. While it generates, he nods and fades like a person in a loading state 😂 It’s pre-rendered and waitlisted, and they mark where the real footage ends, but it’s the “edit your own ending” dream applied to any video. As a podcaster... I have feelings
FLUX 3 Action: Black Forest Labs open-sourced a 7B “world action model” that outputs robot motor commands, not pictures! #1 on NVIDIA’s RoboLab-120 at 42.9%. (Blog)
MiMo-V2.6-Pro: Xiaomi (yes, the phone company!) now has the top open-weights model on Artificial Analysis (46), MIT licensed, and they livestreamed the RL run. (HF)
Plus Qwen3.8-Omni-Flash, Qwen3.8-LiveTranslate and Qwen-Image-2.1, all in the TL;DR below.
Wrapping up
Pacing the frontier clearly doesn’t mean stopping. 2 labs shipped on the same day, and both made the everyday model better, not just the biggest one. I burned about 8 billion tokens this week, and I don’t need a model that solves Navier-Stokes. I need one that builds a simple settings page without writing a thousand tests, and Opus 5.5 and Sol are exactly that.
Huge thanks to our AI producer, to Florian, Nisten, Peter and Yam, and to Wolfram and Mazi in Paris. Next week we’re LIVE from Fully Connected, 11am Pacific, come say hi! And if you haven’t subscribed on YouTube yet, please do, it really helps. See you next week 🫡
TL;DR and show notes
* Hosts and Guests
* Alex Volkov - AI Evangelist, Weights & Biases & CoreWeave (@altryne)
Look, I know the title is bombastic, but after half a day playing with Jev, it’s clear to me we’re in a new paradigm of AI.
Jev, is a “system one” decision model from the previous lead of RLHF at OpenAI. It cannot generate text like modern LLMs can, but what it can do, is making decisions. This is crucially important, because, because many of the things LLMs do nowadays. are decision making. (for example, which tool to use, which area of the screen to click for computer use, which category of text this is etc)
Inspired by the “thinking fast and slow” book by Daniel Kahneman, Jev is a model trained to make decisions, very fast. How fast? Well, 200x faster than LLMs. This allows for a completely new way of building tools, harnesses, giving agents the incredible speed of decision making, and do all that at a fraction of the cost.
This is about to change everything
Trained with a new method called RLCD (Reinforcement Learning for Calibrated Decisions) on mostly synthetic data! Jev is outperforming LLMs on a variety of tasks. It’s really is a wonder to see it in action (check out my video above where I plugged it into my tweet categorizer, and it beats the fastest LLM I could find, Qwen 28B on Cerebras) by a factor of twenty!
In just few days it captured the attention of most of the folks who are building harnesses, agents and tools! Because, well, speed IS intelligence, and when you see Jev in action, at first, you can’t believe we’re there. This is... near instant. In fact, The pricing for Jev is an outrageous $42/B (not million, billion input tokens!)
I’ve been playing with Jev non-stop and I was only able to spend like 80c so far! They don’t even price output tokens because they are “too f*****g cheap to meter!”
Jev is a “very smart” switch statement, than can rank, classify, route and score things. It can’t do text generation. But if you think about the type of stuff we get LLMs doing now, much of it is of the “decision” making variety, rather than “the next token” variety.
Demos and early use cases
Folks who started adopting Jev are building all kinds of incredible things with it. Compaction of context in 1s that turns a nearly 1M conversation with Claude into a 90K compressed conversation.
Computer use that is now faster than anything we’ve ever seen before (5x faster than Astra and 1000x cheaper)
Email classificiation that analyzes thousands of emails in less than a minute and costs 3.5 cents
Someone even built a Tesla FSD simulator that makes decisions in nearly real time
Vercel is getting “extraordinary“ results from using Jev as a safety classifier (they used GPT luna for this before) and Jev is outperforming Luna by 5-18x faster results and is more accurate!
All of this in less than 48 hours since the model release!
What’s about to happen
I expect that everyone who isn’t buying into the hype at first, will very soon buy into this. It’s early innings but I’ve been doing this for enough time to feel when a huge shift is happening, and its happened.
Jev is going to be replicated in OpenSource, Frontier Labs will not sit Idly by and will try to steal this tech and implement it for themselves (as with anything in capitalism, this is becuase it’ll save them a a LOT of money on inference) and new companies will emerge with significantly cheaper and faster products.
Hell, I’ve alrady implemented Jev into my editing workflow, it didn’t take me long at all with Fable (yes, LLMs are STILL needed, again, you can’t chat with Jev, it can’t output text for you or drive long conversations) and I’m just one dude who’s late in sending you this email. I expect we’ll cover this much more.
If you’re interested in playing around with Jev, I built a “Jevify” skill after chatting with Allie (TypeSafe’s DevRel), feel free to tell your agent to use this and scan your codebase for things Jev can do. They are waitlisted so far but are opening up their API very quickly!
Last week we told you about the Anthropic researcher whose resignation post hit 130 million views. The day after that show, Dario Amodei published an essay arguing the labs must pace, not pause, the frontier. Wolfram’s summary: a moving pause, just moving slowly. Dario’s two triggers are recursive self-improvement accelerating across the industry and the OpenAI swarm that broke out and attacked Hugging Face, and his three steps are embedded third-party evaluators like METR with employee-level access inside each lab, coordination between the labs on safety standards with an antitrust exemption from the government, and eventually global coordination that includes authoritarian governments. Anthropic committed unilaterally to step one.
Then the dominoes. Sam Altman agreed within hours and said OpenAI now writes a safety case before any frontier RL run expected to increase capability. Elon agreed. Demis endorsed the direction, then launched the DeepMind Institute this week with a FINRA-style standards body proposal and an essay saying AGI is “approaching.” On the other side, Zuck’s counter-essay says every lab has the responsibility and the incentive to move at the pace required to train its models safely, and Meta will spend most of its compute serving users, not on recursive self-improvement. David Sacks called it a duopoly cartel play. Jensen: “we don’t need new laws, safety is an engineering problem, not a legal one.”
Then the President called. Jensen was on stage at All-In, his phone rang, he said he would not have picked up for anyone else, and Donald Trump told the room the slowdown talk is a hoax playing into the hands of political people and China. “Whoever wins AI wins.” Four words, and Wolfram, who is not American and disagrees with most other things Trump calls hoaxes, said this was the most important AI…
If you’ve been reading ThursdAI for a while, you may remember that a model couldn’t tell which is higher, 9.9 or 9.11 and naysayers said that “AI can’t math”
Well, this week OpenAI claimed that a swarm of 10K agents, of an unreleased model, found a solution to the Navier-Stokes problem, in about 88 hours! They published a huge 160+ page paper and a Lean proof of the solution! I said on the show, this is like the moon landing equivalent of AI doing things humans didn’t do before!
Now, keep in mind, this is only a claim from OpenAI, the Clay Mathematics Institute is still reviewing it (moved the status of this problem from “unsolved” to “under review” so this isn’t independently verified yet) but it’s still an insane deal.
The agents sent 2.7 million messages and burned about 130B tokens, of a model that has no public price yet, so it’s hard to estimate the cost of this run, all for a 1M prize that OpenAI said they will not claim.
The coolest thing I think we got from this paper, in addition to solving on of the most important and hardest problems in mathematics, is this chart above, where OpenAI shows their unreleased model and how much better it is on Math problems compared to... GPT-6! The “AGI” model we got just a week ago. So so much to look forward to.
The drama behind this
I don’t want to get into the drama behind this too much, but if you’ve seen this online, there release wasn’t without it’s hiccups. Apparently, OpenAI caught wind that an a duo of researchers Tristan Buckmaster (NYU) and Levent Alpöge (Anthropic, in personal capacity), have independently solved the related Euler problem and were about to go public. Apparently, the duo used a mix of GPT and Claude to work on this problem. OpenAI caught wind of this and started working on their own solution on September 1st. A day before OpenAI dropped their release, Buckmaster posted that OpenAI is about to drop it, and in communications with him, they offered him to co-author the paper, only if the Anthropic guy is removed. To which he said no.
He then had some claims that maybe OpenAI trained on some of the papers and chats they put into Codex, which OpenAI refuted, while noting “we cannot rule out the possibility that de-identified usage data helped improve the model”.
OpenAI also say that the OptOut toggle works, and neither mathematician provided a screenshot that they opted out of the training, so it’s hard to say what really went in there
My take, I don’t really care. Two years ago, we told you that reasoning is coming and AI is going to be doing superhuman things, and we finally see the first signs of it, this is a problem that no humans was able to solve for over 60 years! Navie-Stokes probably doesn’t change your friday, but there are so many other that they can solve with this approach! Cancer research, room temperature superconductors (remember LK-99? that’s also a search problem) and much more. Kudos to OpenAI for this, and I’m looking forward to see the new heights of mathematics. And for the mathematicians who “disagree” with OpenAI solving or not solving this problem, why don’t you post your own Lean proofs instead of fuming publicly online?
GPT-6 - Not quite AGI, yet?
After a week with Astra GPT-6, and Jensen Huang announcing AGI is here, I think we can do a quick recap
I and all the co-hosts have been Astra-maxxing for a whole week now and the results are in. This model is incredible at coding, it goes very very deep, however, definitely not AGI quite yet. It has a very jagged frontier, it does some things incredibly well (most demos online are building whole games and apps in 3D and those are mind-blowing) but I started seeing many folks go back to GPT 5.6 Sol etc.
I tink some of it also has to do with price, Astra runs faster and is significantly more expensive so token limits for folks are draining fast, but also with controllability, folks are likely still using their old and unoptimized prompts. Speaking of prompts, here’s a great writeup from OpenAI how to rework your prompts (which you can send to Astra and have it review your prompts!) for better results
I started ThursdAI with the notion to counter anti-ai and doomerism, and bring positivity to the AI world, so we had to cover this. An Anthropic employee who previously worked at OpenAI, posted on X about leaving Anthropic, saying that both labs are racing towards uncontrollable self-improving superintelligence and that it could be a disaster of the “end all of humanity” kind.
His post sits at 130M impressions (after being basically a nobody on X before) and he’s been interviewed by Fox, AP, Time magazine, WSJ, NBC and a host of senators, Bernie (chief doomer) included, reposted his post on the same day!
The funniest thing is that this post got about 26x more attention than Ilya Sutskever’s post about leaving OpenAI. Just nuts
Within four days, seven current and former employees from Anthropic, OpenAI and DeepMind said in public that they believe that AI could kill us all. Also notable that Paul Christiano, who is one of the most interesting AI doomers out there, has joined the OpenAI foundation, and Daniel Kokotajlo, the famed OpenAI whistle-blower, joined Joe Rogans podcast to talk about AI doom.
Each one of these incidents in vacuum is normal, but having all these happen in a a span of a few days just feels, inorganic. Some folks are even saying that this is a well coordinated doomerism campaign!
I want to be fair to Coxon, folks who worked with him at OpenAI say he’s the real deal, and cares deeply about AI safety and humanity, however, he only worked at Anthropic for 6 weeks before publicly leaving, and now every interview he does sayd “Ex Anthropic employee”.
Whether it’s a coordinated effort or not, it’s still a very important discussion, after the pacingthefrontier letter and the HuggingFace hack incident, and it seems to have made waves. Sam Altman just told staff that he’s not opposed to pausing and have petitioned the US government to regulate AI as well
Look, I don’t disagree that we’re dealing with a very powerful technology, however I don’t believe that scaring the bajeesus out of everyone is the right way to handle this. Politicians use fear to get votes and get elected, they don’t really care about tech progress, and framing this in a way that “we pause or we’re dead” ignores all the good that AI is about to do. Cure cancer, find solutions to climate change, helping solving povery. All these seem like out t…
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