ThursdAI - The top AI news from the past week

Hey, Alex here,
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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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!
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 files to go public
Anthropic’s S-1 - $974M operating profit, listing Monday as ANT (X, Peter’s charts, Peter’s thread)
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…


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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.
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 …


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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.
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 👏
Google is back: Gemini 4 Argon with Omar Sanseviero and Geneviève Huskens (X, Blog, Gemma speedup, Desk Racer)
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…


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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!


This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit sub.thursdai.news/subscribe