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ThursdAI - The top AI news from the past week

ThursdAI - The top AI news from the past week

By: From Weights & Biases Join AI Evangelist Alex Volkov and a panel of experts to cover everything important that happened in the world of AI from the past week
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 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.

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Episodes
  • 📅 ThursdAI - Feb 26 - Approaching singularity

    📅 ThursdAI - Feb 26 - Approaching singularity
    Feb 27 2026
    Hey, it’s Alex, let me tell you why I think this week is an inflection point.Just this week: Everyone is launching autonomous agents or features inspired by OpenClaw (Devin 2.2, Cursor, Claude Cowork, Microsoft, Perplexity and Nous announced theirs), METR and ArcAGI 2,3 benchmarks are getting saturated, 1 person companies nearing 1M ARR within months of operation by running AI agents 24/7 (we chatted with one of them on the show today, live as he broke $700K ARR barrier) and the US Department of War gives Anthropic an ultimatum to remove nearly all restrictions on Claude for war and Anthropic says NO. I’ve been covering AI for 3 years every week, and this week feels, different. So if we are nearing the singularity, let me at least keep you up to date 😅 Today on the show, we covered most of the news in the first hour + breaking news from Google, Nano Banana 2 is here, and then had 3 interviews back to back. Ben Broca with Polsia, Nader Dabit with Cognition and Philip Kiely with BaseTen. Don’t miss those conversations starting at 1 hour in. Thanks for reading ThursdAI - Highest signal weekly AI news show! This post is public so feel free to share it.Anthropic vs Department of WarEarlier this week, the US “Department of War” invited Dario Amodei, CEO of Anthropic to a meeting, where-in Anthropic was given an ultimatum. “Remove the restrictions on Claude or Anthropic will be designated as a ‘supply chain risk’ company” and the DoD will potentially go as far as using the Defence Production Act to force Anthropic to ... comply. The two restrictions that Anthropic has in place for their models are: No use for domestic surveillance of American citizens and NO fully autonomous lethal weapens decisions given to Claude. For context, Claude is the only model that’s deployed on AWS top secret GovCloud and is used through Palantir’s AI platform. As I’m writing this, Anthropic issued a statement from Dario statement saying they will not budge on this, and will not comply. I fully commend Dario and Anthropic for this very strong backbone, but I fear that this matter is far from over, and we’ll continue to see what is the government response. EDIT: Apparently the DoD is pressuring Google and OpenAI to agree to the stipulations and employees from both companies are signing this petition https://notdivided.org/ to protest against dividing the major AI labs on this topic. Anthropic and OpenAI vs upcoming DeepseekIt’s baffling just how many balls are in the air for Anthropic, as just this week also, they have publicly named 3 Chinese AI makers in “Distillation Attacks”, claiming that they have broke Terms of Service to generate over 16M conversations with Claude to improve their own models, while using proxy networks to avoid detection. This marks the first time a major AI company publicly attributed distillation attacks to specific entities by name.The most telling thing to me is not the distillation, given that Anthropic has just recently settled one of the largest copyright payouts in U.S history, paying authors about $3000/book, which was bought, trained on and destroyed by Anthropic to make Claude better. No, the most telling thing here is the fact that Anthropic chose to put DeepSeek on top of the accusation list with merely 140K conversations, where the other labs created millions. This, plus OpenAI formal memo to Congress about a similar matter, shows that the US labs are trying to prepare for Deepseek new model to drop, by saying “Every innovation they have, they stole from us”. Apparently Deepseek V4 is nearly here, it’s potentially multimodal and has been allegedly trained on Nvidia chips somewhere in Mongolia despite the export restrictions and it’s about to SLAP! Benchmark? What benchmarks? How will we know that we’re approaching the singularity? Will there be signs? Well, this week it seems that the signs are here. First, Agentica claimed that they solved all publicly available “hard for AI” tasks of the upcoming ArcAGI 3, then Confluence Labs announced that they got an unprecedented 97.9% on ArcAGI2 and finally METR published their results on the long-horizon tasks, which measure AI’s capability to solve task that take humans a certain amount of hours to do. And that graph is going parabolic, with Claude Opus 4.6 able to solve tasks of 14.6h (doubling every 49 days) with 50% success rateWhy is this important? Well, this is just the benchmarks telling the story that everyone else in the industry is seeing, that approximately since December of 2025, and definitely fueled by early Feb drop of Opus 4.6 and Codex 5.3, something major shifted. Developers no longer write code, but ship 10x more features.This became such a talking point, Swyx Latent.Space coined this with https://wtfhappened2025.com/ where he collects evidence of a shelling point, something that happened in December and I think continued throughout February. Speaking of benchmarks no longer being ...
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    1 hr and 50 mins
  • 📅 ThursdAI - Feb 19 - Gemini 3.1 Pro Drops LIVE, Sonnet 4.6 Closes Gap, OpenClaw Goes to OpenAI

    📅 ThursdAI - Feb 19 - Gemini 3.1 Pro Drops LIVE, Sonnet 4.6 Closes Gap, OpenClaw Goes to OpenAI
    Feb 20 2026
    Hey, it’s Alex, let me catch you up! Since last week, OpenAI convinced OpenClaw founder Peter Steinberger to join them, while keeping OpenClaw.. well... open. Anthropic dropped Sonnet 4.6 which nearly outperforms the previous Opus and is much cheaper, Qwen released 3.5 on Chinese New Year’s Eve, while DeepSeek was silent and Elon and XAI folks deployed Grok 4.20 without any benchmarks, and it’s 4 500B models in a trenchcoat? Also, Anthropic updated rules state that it’s breaking ToS to use their plans for anything except Claude Code & Claude SDK (and then clarified that it’s OK? we’re not sure) Then Google decided to drop their Gemini 3.1 Pro preview right at the start of our show, and it’s very nearly the best LLM folks can use right now (though it didn’t pass Nisten’s vibe checks) Also, Google released Lyria 3 for music gen (though only 30 seconds?) and our own Ryan Carson blew up on X again with over 1M views for his Code Factory article, Wolfram did a deep dive into Terminal Bench and .. we have a brand new website: https://thursdai.news 🎉Great week all in all, let’s dive in! ThursdAI - Subscribe to never feel like you’re behind. Share with your friends if you’re already subscribed!Big Companies & API updatesGoogle releases Gemini 3.1 Pro with 77.1% on ARC-AGI-2 (X, Blog, Announcement)In a release that surprised no-one, Google decided to drop their latest update to Gemini models, and it’s quite a big update too! We’ve now seen all major labs ship big model updates in the first two months of 2026. With 77.1% on ARC-AGI 2, and 80.6% on SWE-bench verified, Gemini is not complete SOTA across the board but it’s damn near close. The kicker is, it’s VERY competitive on the pricing, with 1M context, $2 / $12 (<200k tokens), and Google’s TPU speeds, this is now the model to beat! Initial vibe checks live on stage did not seem amazing, Nisten wasn’t super impressed, Ryan took one glance at the SWE-bench pro not being SOTA and decided to skip, and he’s added that, at some point, it is benefitting to pick a model and stick to it, the constant context switching is really hard for folks who want to keep shipping. But if you look at the trajectory, it’s really notable how quickly we’re moving, with this model being 82% better on abstract reasoning than the 3 pro released just a few months ago! The 1 Million Context Discrepancy, who’s better at long context? The most fascinating catch of the live broadcast came from LDJ, who has an eagle eye for evaluation tables. He immediately noticed something weird in Google’s reported benchmarks regarding long-context recall. On the MRCR v2 8-needle benchmark (which tests retrieval quality deep inside a massive context window), Google’s table showed Gemini 3.1 Pro getting a 26% recall score at 1 million tokens. Curiously, they marked Claude Opus 4.6 as “not supported” in that exact tier.LDJ quickly pulled up the actual receipts: Opus 4.6 at a 1-million context window gets a staggering 76% recall score. That is a massive discrepancy! It was addressed by a member of DeepMind on X in a response to me, saying that Anthropic used an internal model for evaluating this (with receipts he pulled from the Anthropic model card) Live Vibe-Coding Test for Gemini 3.1 ProWe couldn’t just stare at numbers, so Nisten immediately fired up AI Studio for a live vibe check. He threw our standard “build a mars driver simulation game” prompt at the new Gemini.The speed was absolutely breathtaking. The model generated the entire single-file HTML/JS codebase in about 20 seconds. However, when he booted it up, the result was a bit mixed. The first run actually failed to render entirely. A quick refresh got a version working, and it rendered a neat little orbital launch UI, but it completely lacked the deep physics trajectories and working simulation elements that models like OpenAI’s Codex 5.3 or Claude Opus 4.6 managed to output on the exact same prompt last week. As Nisten put it, “It’s not bad at all, but I’m not impressed compared to what Opus and Codex did. They had a fully working one with trajectories, and this one I’m just stuck.”It’s a great reminder that raw benchmarks aren’t everything. A lot of this comes down to the harness—the specific set of system prompts and sandboxes that the labs use to wrap their models. Anthropic launches Claude Sonnet 4.6, with 1M token context and near-Opus intelligence at Sonnet pricingThe above Gemini release comes just a few days after Anthropic has shipped an update to the middle child of their lineup, Sonnet 4.6. With much improved Computer Use skills, updated Beta mode for 1M tokens, it achieves 79.6% on SWE-bench verified eval, showing good coding performance, while maintaining that “anthropic trained model” vibes that many people seem to prefer. Apparently in blind testing inside Claude Code, folks preferred this new model outputs to the latest Opus 4.5 around ~60% of the ...
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    1 hr and 32 mins
  • 📆 Open source just pulled up to Opus 4.6 — at 1/20th the price

    📆 Open source just pulled up to Opus 4.6 — at 1/20th the price
    Feb 13 2026
    Hey dear subscriber, Alex here from W&B, let me catch you up! This week started with Anthropic releasing /fast mode for Opus 4.6, continued with ByteDance reality-shattering video model called SeeDance 2.0, and then the open weights folks pulled up! Z.ai releasing GLM-5, a 744B top ranking coder beast, and then today MiniMax dropping a heavily RL’d MiniMax M2.5, showing 80.2% on SWE-bench, nearly beating Opus 4.6! I’ve interviewed Lou from Z.AI and Olive from MiniMax on the show today back to back btw, very interesting conversations, starting after TL;DR!So while the OpenSource models were catching up to frontier, OpenAI and Google both dropped breaking news (again, during the show), with Gemini 3 Deep Think shattering the ArcAGI 2 (84.6%) and Humanity’s Last Exam (48% w/o tools)... Just an absolute beast of a model update, and OpenAI launched their Cerebras collaboration, with GPT 5.3 Codex Spark, supposedly running at over 1000 tokens per second (but not as smart) Also, crazy week for us at W&B as we scrambled to host GLM-5 at day of release, and are working on dropping Kimi K2.5 and MiniMax both on our inference service! As always, all show notes in the end, let’s DIVE IN! ThursdAI - AI is speeding up, don’t get left behind! Sub and I’ll keep you up to date with a weekly catch upOpen Source LLMsZ.ai launches GLM-5 - #1 open-weights coder with 744B parameters (X, HF, W&B inference)The breakaway open-source model of the week is undeniably GLM-5 from Z.ai (formerly known to many of us as Zhipu AI). We were honored to have Lou, the Head of DevRel at Z.ai, join us live on the show at 1:00 AM Shanghai time to break down this monster of a release.GLM-5 is massive, not something you run at home (hey, that’s what W&B inference is for!) but it’s absolutely a model that’s worth thinking about if your company has on prem requirements and can’t share code with OpenAI or Anthropic. They jumped from 355B in GLM4.5 and expanded their pre-training data to a whopping 28.5T tokens to get these results. But Lou explained that it’s not only about data, they adopted DeepSeeks sparse attention (DSA) to help preserve deep reasoning over long contexts (this one has 200K)Lou summed up the generational leap from version 4.5 to 5 perfectly in four words: “Bigger, faster, better, and cheaper.” I dunno about faster, this may be one of those models that you hand off more difficult tasks to, but definitely cheaper, with $1 input/$3.20 output per 1M tokens on W&B! While the evaluations are ongoing, the one interesting tid-bit from Artificial Analysis was, this model scores the lowest on their hallucination rate bench! Think about this for a second, this model is neck-in-neck with Opus 4.5, and if Anthropic didn’t release Opus 4.6 just last week, this would be an open weights model that rivals Opus! One of the best models the western foundational labs with all their investments has out there. Absolutely insane times. MiniMax drops M2.5 - 80.2% on SWE-bench verified with just 10B active parameters (X, Blog)Just as we wrapped up our conversation with Lou, MiniMax dropped their release (though not weights yet, we’re waiting ⏰) and then Olive Song, a senior RL researcher on the team, joined the pod, and she was an absolute wealth of knowledge! Olive shared that they achieved an unbelievable 80.2% on SWE-Bench Verified. Digest this for a second: a 10B active parameter open-source model is directly trading blows with Claude Opus 4.6 (80.8%) on the one of the hardest real-world software engineering benchmark we currently have. While being alex checks notes ... 20X cheaper and much faster to run? Apparently their fast version gets up to 100 tokens/s. Olive shared the “not so secret” sauce behind this punch-above-its-weight performance. The massive leap in intelligence comes entirely from their highly decoupled Reinforcement Learning framework called “Forge.” They heavily optimized not just for correct answers, but for the end-to-end time of task performing. In the era of bloated reasoning models that spit out ten thousand “thinking” tokens before writing a line of code, MiniMax trained their model across thousands of diverse environments to use fewer tools, think more efficiently, and execute plans faster. As Olive noted, less time waiting and fewer tools called means less money spent by the user. (as confirmed by @swyx at the Windsurf leaderboard, developers often prefer fast but good enough models) I really enjoyed the interview with Olive, really recommend you listen to the whole conversation starting at 00:26:15. Kudos MiniMax on the release (and I’ll keep you updated when we add this model to our inference service) Big Labs and breaking newsThere’s a reason the show is called ThursdAI, and today this reason is more clear than ever, AI biggest updates happen on a Thursday, often live during the show. This happened 2 times last week and 3 times today, first with MiniMax and then with both ...
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    1 hr and 28 mins
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