The top AI news from the past week, every ThursdAI

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

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 Google and OpenAI! Google previews Gemini 3 Deep Think, top reasoning intelligence SOTA Arc AGI 2 at 84% & SOTA HLE 48.4% (X , Blog)I literally went

Hey, Alex from W&B here

Hey guys, Alex here

Hey! Alex here, with another weekly AI update! It seems like ThursdAI is taking a new direction, as this is our 3rd show this year, and a 3rd deep dive into topics (previously Ralph, Agent Skills), please let me know if the comments if you like this format. This week's deep dive is into Clawdbot, a personal AI assistant you install on your computer, but can control through your phone, has access to your files, is able to write code, help organize your life, but most importantly, it can self improve. Seeing Wolfred (my Clawdbot) learn to transcribe incoming voice messages blew my mind, and I wanted to share this one with you at length! We had Dan Peguine on the show for the deep dive + both Wolfram and Yam are avid users! This one is not to be missed. If ThursdAI is usually too technical for you, use Claude, and install Clawdbot after you read/listen to the deep dive!Also this week, we read Claude's Constitution that Anthropic released, heard a bunch of new TTS models (some are open source and very impressive) and talked about the new lightspeed coding model GLM 4.7 Flash. First the news, then deep dive, lets go

Hey ya'll, Alex here, and this week I was especially giddy to record the show! Mostly because when a thing clicks for me that hasn't clicked before, I can't wait to tell you all about it! This week, that thing is Agent Skills! The currently best way to customize your AI agents with domain expertise, in a simple, repeatable way that doesn't blow up the context window! We mentioned skills when Anthropic first released them (Oct 16) and when they became an open standard but it didn't really click until last week! So more on that below. Also this week, Anthropic released a research preview of Claude Cowork, an agentic tool for non coders, OpenAI finally let loos GPT 5.2 Codex (in the API, it was previously available only via Codex), Apple announced a deal with Gemini to power Siri, OpenAI and Anthropic both doubled down on healthcare and much more! We had an incredible show, with an expert in Agent Skills, Eleanor Berger and the usual gang on co-hosts, strongly recommend watching the show in addition to the newsletter! Also, I vibe coded skills support for all LLMs to Chorus, and promised folks a link to download it, so look for that in the footer, let's dive in! ThursdAI is where you stay up to date! Subscribe to keep us going! Big Company LLMs + APIs: Cowork, Codex, and a Browser in a WeekAnthropic launches Claude Cowork: Agentic AI for Non‑Coders (research preview)Anthropic announced Claude Cowork, which is basically Claude Code wrapped in a friendly UI for people who don't want to touch a terminal. It's a research preview available on the Max tier, and it gives Claude read/write access to a folder on your Mac so it can do real work without you caring about diffs, git, or command line.The wild bit is that Cowork was built in a week and a half, and according to the Anthropic team it was 100% written using Claude Code. This feels like a “we've crossed a threshold” moment. If you're wondering why this matters, it's because coding agents are general agents. If a model can write code to do tasks, it can do taxes, clean your desktop, or orchestrate workflows, and that means non‑developers can now access the same leverage developers have been enjoying for a year.It also isn't just for files—it comes with a Chrome connector, meaning it can navigate the web to gather info, download receipts, or do research and it uses skills (more on those later)Earlier this week I recorded this first reactions video about Cowork and I've been testing it ever since, it's a very interesting approach of coding agents that “hide the coding” to just... do things. Will this become as big as Claude Code for anthropic (which is reportedly a 1B business for them)? Let's see! There are real security concerns here, especially if you're not in the habit of backing up or using git. Cowork sandboxes a folder, but it can still delete things in that folder, so don't let it loose on your whole drive unless you like chaos.GPT‑5.2 Codex: Long‑Running Agents Are HereOpenAI shipped GPT‑5.2 Codex into the API finally! After being announced as the answer for Opus 4.5 and only being available in Codex. The big headline is SOTA on SWE-Bench and long‑running agentic capability. People describe it as methodical. It takes longer, but it's reliable on extended tasks, especially when you let it run without micromanaging.This model is now integrated into Cursor, GitHub Copilot, VS Code, Factory, and Vercel AI Gateway within hours of launch. It's also state‑of‑the‑art on SWE‑Bench Pro and Terminal‑Bench 2.0, and it has native context compaction. That last part matters because if you've ever run an agent for long sessions, the context gets bloated and the model gets dumber. Compaction is an attempt to keep it coherent by summarizing old context into fresh threads, and we debated whether it really works. I think it helps, but I also agree that the best strategy is still to run smaller, atomic tasks with clean context.Cursor vibe-coded browser with GPT-5.2 and 3M lines of codeThe most mind‑blowing thing we discussed is Cursor letting GPT‑5.2 Codex run for a full week to build a browser called FastRenderer. This is not Chromium‑based. It's a custom HTML parser, CSS cascade, layout engine, text shaping, paint pipeline, and even a JavaScript VM, written in Rust, from scratch. The codebase is open source on GitHub, and the full story is on Cursor's blog It took nearly 30,000 commits and millions of lines of code. The system ran hundreds of concurrent agents with a planner‑worker architecture, and GPT‑5.2 was the best model for staying on task in that long‑running regime. That's the real story, not just “lol a model wrote a browser.” This is a stress test for long‑horizon agentic software development, and it's a preview of how teams will ship in 2026.I said on the show, browsers are REALLY hard, it took two decades for the industry to settle and be able to render websites normally, and there's a reason everyone's using Chromium. This is VERY impressive

Hey folks, Alex here from Weights & Biases, with your weekly AI update (and a first live show of this year!) For the first time, we had a co-host of the show also be a guest on the show, Ryan Carson (from Amp) went supernova viral this week with an X article (1.5M views) about Ralph Wiggum (yeah, from Simpsons) and he broke down that agentic coding technique at the end of the show. LDJ and Nisten helped cover NVIDIA's incredible announcements during CES with their Vera Rubin upcoming platform (4-5X improvements) and we all got excited about AI medicine with ChatGPT going into Health officially! Plus, a bunch of Open Source news, let's get into this: ThursdAI - Recaps of the most high signal AI weekly spaces is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Open Source: The “Small” Models Are WinningWe often talk about the massive frontier models, but this week, Open Source came largely from unexpected places and focused on efficiency, agents, and specific domains.Solar Open 100B: A Data MasterclassUpstage released Solar Open 100B, and it's a beast. It's a 102B parameter Mixture-of-Experts (MoE) model, but thanks to MoE magic, it only uses about 12B active parameters during inference. This means it punches incredibly high but runs fast.What I really appreciated here wasn't just the weights, but the transparency. They released a technical report detailing their “Data Factory” approach. They trained on nearly 20 trillion tokens, with a huge chunk being synthetic. They also used a dynamic curriculum that adjusted the difficulty and the ratio of synthetic data as training progressed. This transparency is what pushes the whole open source community forward.Technically, it hits 88.2 on MMLU and competes with top-tier models, especially in Korean language tasks. You can grab it on Hugging Face.MiroThinker 1.5: The DeepSeek Moment for Agents?We also saw MiroThinker 1.5, a 30B parameter model that is challenging the notion that you need massive scale to be smart. It uses something they call “Interactive Scaling.”Wolfram broke this down for us: this agent forms hypotheses, searches for evidence, and then iteratively revises its answers in a time-sensitive sandbox. It effectively “thinks” before answering. The result? It beats trillion-parameter models on search benchmarks like BrowseComp. It's significantly cheaper to run, too. This feels like the year where smaller models + clever harnesses (harnesses are the software wrapping the model) will outperform raw scale.Liquid AI LFM 2.5: Running on Toasters (Almost)We love Liquid AI and they are great friends of the show. They announced LFM 2.5 at CES with AMD, and these are tiny ~1B parameter models designed to run on-device. We're talking about running capable AI on your laptop, your phone, or edge devices (or the Reachy Mini bot that I showed off during the show! I gotta try and run LFM on him!)Probably the coolest part is the audio model. Usually, talking to an AI involves a pipeline: Speech-to-Text (ASR) -> LLM -> Text-to-Speech (TTS). Liquid's model is end-to-end. It hears audio and speaks audio directly. We watched a demo from Maxime Labonne where the model was doing real-time interaction, interleaving text and audio. It's incredibly fast and efficient. While it might not write a symphony for you, for on-device tasks like summarization or quick interactions, this is the future.NousCoder-14B and Zhipu AI IPOA quick shoutout to our friends at Nous Research who released NousCoder-14B, an open-source competitive programming model that achieved a 7% jump on LiveCodeBench accuracy in just four days of RL training on 48 NVIDIA B200 GPUs. The model was trained on 24,000 verifiable problems, and the lead researcher Joe Li noted it achieved in 4 days what took him 2 years as a teenager competing in programming contests. The full RL stack is open-sourced on GitHub and Nous published a great WandB results page as well! And in historic news, Zhipu AI (Z.ai)—the folks behind the GLM series—became the world's first major LLM company to IPO, raising $558 million on the Hong Kong Stock Exchange. Their GLM-4.7 currently ranks #1 among open-source and domestic models on both Artificial Analysis and LM Arena. Congrats to them!Big Companies & APIsNVIDIA CES: Vera Rubin Changes EverythingLDJ brought the heat on this one covering Jensen's CES keynote that unveiled the Vera Rubin platform, and the numbers are almost hard to believe. We're talking about a complete redesign of six chips: the Rubin GPU delivering 50 petaFLOPS of AI inference (5x Blackwell), the Vera CPU with 88 custom Olympus ARM cores, NVLink 6, ConnectX-9 SuperNIC, BlueField-4 DPU, and Spectrum-6 Ethernet.Let me put this in perspective using LDJ's breakdown: if you look at FP8 performance, the jump from Hopper to Blackwell was about 5x. The jump from Blackwell to Vera Rubin is over 3x again—but here's the kicker—while only adding about 200 watts of power draw. That's insane efficiency improvement.The real-world implications Jensen shared: training a 10 trillion parameter mixture-of-experts model now requires 75% fewer GPUs compared to Blackwell. Inference token costs drop roughly 10x—a 1MW cluster goes from 1 million to 10 million tokens per second at the same power. HBM4 memory delivers 22 TB/s bandwidth with 288GB capacity, exceeding NVIDIA's own 2024 projections by nearly 70%.As Ryan noted, when people say there's an AI bubble, this is why it's hilarious. Jensen keeps saying the need for inference is unbelievable and only going up exponentially. We all see this. I can't get enough inference—I want to spin up 10 Ralphs running concurrently! The NVL72 rack-scale system achieves 3.6 exaFLOPS inference with 20.7TB total HBM, and it's already shipping. Runway 4.5 is already running on the new platform, having ported their model from Hopper to Vera Rubin NVL72 in a single day.NVIDIA also recently acqui-hidred Groq (with a Q) in a ~$20 billion deal, bringing the inference chip expertise from the guy who created Google's TPUs in-house.Nemotron Speech ASR & The Speed of Voice (X, HF, Blog)NVIDIA also dropped Nemotron Speech ASR. This is a 600M parameter model that offers streaming transcription with 24ms latency.We showed a demo from our friend Kwindla Kramer at Daily. He was talking to an AI, and the response was virtually instant. The pipeline is: Nemotron (hearing) -> Llama/Nemotron Nano (thinking) -> Magpie TTS (speaking). The total latency is under 500ms. It feels like magic. Instant voice agents are going to be everywhere this year.XAI Raises $20B While Grok Causes Problems (Again)So here's the thing about covering anything Elon-related: it's impossible to separate signal from noise because there's an army of fans who hype everything and an army of critics who hate everything. But let me try to be objective here.XAI raised another massive Round E of $20 billion! at a $230 billion valuation, with NVIDIA and Cisco as strategic investors. The speed of their infrastructure buildout is genuinely incredible. Grok's voice mode is impressive. I use Grok for research and it's really good, notable for it's unprecedented access to X !But. This raise happened in the middle of a controversy where Grok's image model was being used to “put bikinis” on anyone in reply threads, including—and this is where I draw a hard line—minors. As Nisten pointed out on the show, it's not even hard to implement guardrails. You just put a 2B VL model in front and ask “is there a minor in this picture?” But people tested it, asked Grok not to use the feature, and it did it anyway. And yeah, putting Bikini on Claude is funny, but basic moderation is lacking! The response of “we'll prosecute illegal users” is stupid when there's no moderation built into the product. There's an enormous difference between Photoshop technically being able to do something after hours of work, and a feature that generates edited images in one second as the first comment to a celebrity, then gets amplified by the platform's algorithm to millions of people. One is a tool. The other is a product with amplification mechanics. Products need guardrails. I don't often link to CNN (in fact this is the first time) but they have a great writeup about the whole incident here which apparently includes the quitting of a few trust and safety folks and Elon's pushback on guardrails. CrazyThat said, Grok 5 is in training and XAI continues to ship impressive technology. I just wish they'd put the same engineering effort into safety as they do into capabilities!OpenAI Launches GPT HealthThis one's exciting. OpenAI CEO Fidji Simo announced ChatGPT Health, a privacy-first space for personalized health conversations that can connect to electronic health records, Apple Health, Function Health, Peloton, and MyFitnessPal.Here's why this matters: health already represents about 5% of all ChatGPT messages globally and touches 25% of weekly active users—often outside clinic hours or in underserved areas. People are already using these models for health advice constantly.Nisten, who has worked on AI doctors since the GPT-3 days and even published papers on on-device medical AI, gave us some perspective: the models have been fantastic for health stuff for two years now. The key insight is that medical data seems like a lot, but there are really only about 2,000 prescription drugs and 2,000 diseases (10,000 if you count rare ones). That's nothing for an LLM. The models excel at pattern recognition across this relatively contained dataset.The integration with Function Health is particularly interesting to me. Function does 160+ lab tests, but many doctors won't interpret them because they didn't order them. ChatGPT could help bridge that gap, telling you “hey, this biomarker looks off, you should discuss this with your doctor.” The bad news is, this is just a waitlist and you can add yourself to the waitlist here, we'll keep monitoring the situation and let you know when it opens upDoctronic: AI Prescribing Without Physician OversightSpeaking of healthcare, Doctronic launched a pilot in Utah where AI can autonomously renew prescriptions for chronic conditions without any physician in the loop. The system covers about 190 routine medications (excluding controlled substances) at just $4 per renewal. Trial data showed 99.2% concordance with physician treatment plans, and they've secured pioneering malpractice insurance that treats the AI like a clinician.Nisten made the case that it's ethically wrong to delay this kind of automation when ER wait times keep increasing and doctors are overworked. The open source models are already excellent at medical tasks. Governments should be buying GPUs rather than creating administrative roadblocks. Strong strong agree here! Google Brings Gmail into the Gemini Era (X)Breaking news from the day of our show: Google announced Gmail's biggest AI transformation since its 2004 launch, powered by Gemini 3. This brings AI Overviews that summarize email threads, natural language queries (”Who gave me a plumber quote last year?”), Help Me Write, contextual Suggested Replies matching your writing style, and the upcoming AI Inbox that filters noise to surface VIPs and urgent items.For 3 billion Gmail users, this is huge. I'm very excited to test it—though not live on the show because I don't want you reading my emails.This weeks buzz - covering Weights & Biases updatesNot covered on the show, but a great update on stuff from WandB, Chris Van Pelt (@vanpelt), one of the 3 co-founders released a great project I wanted to tell you about! For coders, this is an app that allows you to run multiple Claude Codes on free Github sandboxes, so you can code (or Ralph) and control everything away from home! GitHub gives personal users 120 free Codespaces hours/month, and Catnip automatically shuts down inactive instances so you can code for quite a while with Catnip! It's fully open source on Github and you can download the app hereInterview: Ryan Carson - What the hell is Ralph Wiggum?Okay, let's talk about the character everyone is seeing on their timeline: Ralph Wiggum. My co-host Ryan Carson went viral this week with an article about this technique, and I had to have him break it down.Ralph isn't a new model; it's a technique for running agents in a loop to perform autonomous coding. The core idea is deceptively simple: Ralph is a bash script that loops an AI coding agent. In a loop, until it a certain condition is met. But why is it blowing up? Normally when you use a coding agent like Cursor, Claude Code, or AMP, you need to be in the loop. You approve changes, look at code, fix things when the agent hits walls or runs out of context. Ralph solves this by letting the agent run autonomously while you sleep.Here's how it works: First, you write a Product Requirements Doc (PRD) by talking to your agent for a few minutes about what you want to build. Then you convert that PRD into a JSON file containing atomic user stories with clear acceptance criteria. Each user story is small enough for the agent to complete in one focused thread.The Ralph script then loops: it picks the first incomplete user story, the agent writes code to implement it, tests against the acceptance criteria, commits the changes, marks the story as complete, writes what it learned to a shared “agents.md” file, and loops to the next story. That compound learning step is crucial—without it, the agent would keep making the same mistakes.What makes this work is the pre-work. As Ryan put it, “no real work is done one-shot.” This is how software engineering has always worked—you break big problems into smaller problems into user stories and solve them incrementally. The innovation is letting AI agents work through that queue autonomously while you sleep! Ryan's excellent (and viral) X article is here! Vision & VideoLTX-2 Goes Fully Open Source (HF, Paper)Lightricks finally open-sourced LTX-2, marking a major milestone as the first fully open audio-video generation model. This isn't just “we released the weights” open—it's complete model weights (13B and 2B variants), distilled versions, controllable LoRAs, a full multimodal trainer, benchmarks, and evaluation scripts. For a video model that is aiming to be the open source SORA, supports audio and lipsyncThe model generates synchronized audio and video in a single DiT-based architecture—motion, dialogue, ambience, and music flow simultaneously. Native 4K at up to 50 FPS with audio up to 10 seconds. And there's also a distilled version (Thanks Pruna AI!) hosted on ReplicateComfyUI provided day-0 native support, and community testing shows an A6000 generating 1280x720 at 120 frames in 50 seconds. This is near Sora-level quality that you can fine-tune on your own data for custom styles and voices in about an hour.What a way to start 2026. From chips that are 5x faster to AI doctors prescribing meds in Utah, the pace is only accelerating. If anyone tells you we're in an AI bubble, just show them what we covered today. Even if the models stopped improving tomorrow, the techniques like “Ralph” prove we have years of work ahead of us just figuring out how to use the intelligence we already have.Thank you for being a ThursdAI subscriber. See you next week!As always, here's the show notes and TL;DR links: * Hosts & Guests* Alex Volkov - AI Evangelist & Weights & Biases (@altryne)* Co-Hosts - @WolframRvnwlf, @nisten, @ldjconfirmed* Special Guest - Ryan Carson (@ryancarson) breaking down the Ralph Wiggum technique.* Open Source LLMs* Solar Open 100B - Upstage's 102B MoE model. Trained on 19.7T tokens with a heavy focus on “data factory” synthetic data and high-performance Korean reasoning (X, HF, Tech Report).* MiroThinker 1.5 - A 30B parameter search agent that uses “Interactive Scaling” to beat trillion-parameter models on search benchmarks like BrowseComp (X, HF, GitHub).* Liquid AI LFM 2.5 - A family of 1B models designed for edge devices. Features a revolutionary end-to-end audio model that skips the ASR-LLM-TTS pipeline (X, HF).* NousCoder-14B - competitive coding model from Nous Research that saw a 7% LiveCodeBench accuracy jump in just 4 days of RL (X, WandB Dashboard).* Zhipu AI IPO - The makers of GLM became the first major LLM firm to go public on the HKEX, raising $558M (Announcement).* Big Co LLMs & APIs* NVIDIA Vera Rubin - Jensen Huang's CES reveal of the next-gen platform. Delivers 5x Blackwell inference performance and 75% fewer GPUs needed for MoE training (Blog).* OpenAI ChatGPT Health - A privacy-first vertical for EHR and fitness data integration (Waitlist).* Google Gmail Era - Gemini 3 integration into Gmail for 3 billion users, featuring AI Overviews and natural language inbox search (Blog).* XAI $20B Raise - Elon's XAI raises Series E at a $230B valuation, even as Grok faces heat over bikini-gate and safety guardrails (CNN Report).* Doctronic - The first US pilot in Utah for autonomous AI prescription renewals without a physician in the loop (Web).* Alexa+ Web - Amazon brings the “Smart Alexa” experience to browser-based chat (Announcement).* Autonomous Coding & Tools* Ralph Wiggum - The agentic loop technique for autonomous coding using small, atomic user stories. Ryan Carson's breakdown of why this is the death of “vibe coding” (Viral X Article).* Catnip by W&B - Chris Van Pelt's open-source iOS app to run Claude Code anywhere via GitHub Codespaces (App Store, GitHub).* Vision & Video* LTX-2 - Lightricks open-sources the first truly open audio-video generation model with synchronized output and full training code (GitHub, Replicate Demo).* Avatar Forcing - KAIST's framework for real-time interactive talking heads with ~500ms latency (Arxiv).* Qwen Edit 2512 - Optimized by PrunaAI to generate high-res realistic images in under 7 seconds (Replicate).* Voice & Audio* Nemotron Speech ASR - NVIDIA's 600M parameter streaming model with sub-100ms stable latency for massive-scale voice agents (HF). 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

Hey all, Happy new year! This is Alex, writing to you for the very fresh start of this year, it's 2026 already, can you believe it? There was no live stream today, I figured the cohosts deserve a break and honestly it was a very slow week. Even the chinese labs who don't really celebrate X-mas and new years didn't come out with a banger AFAIK. ThursdAI - AI moves fast, we're here to make sure you never miss a thing! Subscribe :) Tho I thought it was an incredible opportunity to finally post the Will Brow interview I recorded in November during the AI Engineer conference. Will is a researcher at Prime Intellect (big fans on WandB btw!) and is very known on X as a hot takes ML person, often going viral for tons of memes! Will is the creator and maintainer of the Verifiers library (Github) and his talk at AI Engineer was all about RL Environments (what they are, you can hear in the interview, I asked him!) TL;DR last week of 2025 in AIBesides this, my job here is to keep you up to date, and honestly this was very easy this week, as… almost nothing has happened, but here we go: Meta buys ManusThe year ended with 2 huge acquisitions / aquihires. First we got the news from Alex Wang that Meta has bought Manus.ai which is an agentic AI startup we covered back in March for an undisclosed amount (folks claim $2-3B) The most interesting thing here is that Manus is a Chinese company, and this deal requires very specific severance from Chinese operations.Jensen goes on a new years spending spree, Nvidia buys Groq (not GROK) for $20BGroq which we covered often here, and are great friends, is going to NVIDIA, in a… very interesting acqui-hire, which is a “non binding license” + most of Groq top employees apparently are going to NVIDIA. Jonathan Ross the CEO of Groq, was the co-creator of the TPU chips at Google before founding Groq, so this seems like a very strategic aquihire for NVIDIA! Congrats to our friends from Groq on this amazing news for the new year! Tencent open-sources HY-MT1.5 translation models with 1.8B edge-deployable and 7B cloud variants supporting 33 languages (X, HF, HF, GitHub)It seems that everyone's is trying to de-throne whisper and this latest attempt from Tencent is a interesting one. a 1.8B and 7B translation models with very interesting stats. Alibaba's Qwen-Image-2512 drops on New Year's Eve as strongest open-source text-to-image model, topping AI Arena with photorealistic humans and sharper textures (X, HF, Arxiv)Our friends in Tongyi decided to give is a new years present in the form of an updated Qwen-image, with much improved realismThat's it folks, this was a quick one, hopefully you all had an amazing new year celebration, and are gearing up to an eventful and crazy 2026. I wish you all happiness, excitement and energy to keep up with everything in the new year, and will make sure that we're here to keep you up to date as always! P.S - I got a little news of my own this yesterday, not related to AI. She said yes

Ho Ho Ho, Alex here! (a real human writing these words, this needs to be said in 2025) Merry Christmas (to those who celebrate) and welcome to the very special yearly ThursdAI recap! This was an intense year in the world of AI, and after 51 weekly episodes (this is episode 52!) we have the ultimate record of all the major and most important AI releases of this year! So instead of bringing you a weekly update (it's been a slow week so far, most AI labs are taking a well deserved break, the Cchinese AI labs haven't yet surprised anyone), I'm dropping a comprehensive yearly AI review! Quarter by quarter, month by month, both in written form and as a pod/video! Why do this? Who even needs this? Isn't most of it obsolete? I have asked myself this exact question while prepping for the show (it was quite a lot of prep, even with Opus's help). I eventually landed on, hey, if nothing else, this will serve as a record of the insane week of AI progress we all witnessed. Can you imagine that the term Vibe Coding is less than 1 year old? That Claude Code was released at the start of THIS year? We get hedonicly adapt to new AI goodies so quick, and I figured this will serve as a point in time check, we can get back to and feel the acceleration! With that, let's dive in - P.S. the content below is mostly authored by my co-author for this, Opus 4.5 high, which at the end of 2025 I find the best creative writer with the best long context coherence that can imitate my voice and tone (hey, I'm also on a break!

Hey folks

Hey everyone, December started strong and does NOT want to slow down!? OpenAI showed us their response to the Code Red and it's GPT 5.2, which doesn't feel like a .1 upgrade! We got it literally as breaking news at the end of the show, and oh boy! The new kind of LLMs is here. GPT, then Gemini, then Opus and now GPT again... Who else feels like we're on a trippy AI rolercoaster? Just me?

Hey yall, Alex here

Hey, Alex here, I recorded these conversations just in front of the AI Engineer auditorium, back to back, after these great folks gave their talks, and at the epitome of the most epic AI week we've seen since I started recording ThursdAI.This is less our traditional live recording, and more a real podcast-y conversation with great folks, inspired by Latent.Space. I hope you enjoy this format as much as I've enjoyed recording and editing it. AntiGravity with KevinKevin Hou and team just launched Antigravity, Google's brand new Agentic IDE based on VSCode, and Kevin (second timer on ThursdAI) was awesome enough to hop on and talk about some of the product decisions they made, what makes Antigravity special and highlighted Artifacts as a completely new primitive. Gemini 3 in AI StudioIf you aren't using Google's AI Studio (ai.dev) then you're missing out! We talk about AI Studio all the time on the show, and I'm a daily user! I generate most of my images with Nano Banana Pro in there, most of my Gemini conversations are happening there as well! Ammaar and Kat were so fun to talk to, as they covered the newly shipped “build mode” which allows you to vibe code full apps and experiences inside AI Studio, and we also covered Gemini 3's features, multimodality understanding, UI capabilities. These folks gave a LOT of Gemini 3 demo's so they know everything there is to know about this model's capabilities! Tried new things with this one, multi camera angels, conversation with great folks, if you found this content valuable, please subscribe :) Topics Covered:* Inside Google's new “AntiGravity” IDE* How the “Agent Manager” changes coding workflows* Gemini 3's new multimodal capabilities* The power of “Artifacts” and dynamic memory* Deep dive into AI Studio updates & Vibe Coding* Generating 4K assets with Nano Banana ProTimestamps for your viewing convenience. 00:00 - Introduction and Overview01:13 - Conversation with Kevin Hou: Anti-Gravity IDE01:58 - Gemini 3 and Nano Banana Pro Launch Insights03:06 - Innovations in Anti-Gravity IDE06:56 - Artifacts and Dynamic Memory09:48 - Agent Manager and Multimodal Capabilities11:32 - Chrome Integration and Future Prospects20:11 - Conversation with Ammar and Kat: AI Studio Team21:21 - Introduction to AI Studio21:51 - What is AI Studio?22:52 - Ease of Use and User Feedback24:06 - Live Demos and Launch Week26:00 - Design Innovations in AI Studio30:54 - Generative UIs and Vibe Coding33:53 - Nano Banana Pro and Image Generation39:45 - Voice Interaction and Future Roadmap44:41 - Conclusion and Final ThoughtsLooking forward to seeing you on Thursday

Hey ya'll, Happy Thanskgiving to everyone who celebrates and thank you for being a subscriber, I truly appreciate each and every one of you!Just wrapped up the third (1, 2) Thanksgiving special Episode of ThursdAI, can you believe November is almost over? We had another banger week in AI, with a full feast of AI released, Anthropic dropped the long awaited Opus 4.5, which quickly became the top coding LLM, DeepSeek resurfaced with a math model, BFL and Tongyi both tried to take on Nano Banana, and Microsoft dropped a 7B computer use model in Open Source + Intellect 3 from Prime Intellect! With so much news to cover, we also had an interview with Ido Sal & Liad Yosef (their second time on the show!) about MCP-Apps, the new standard they are spearheading together with Anthropic, OpenAI & more! Exciting episode, let's get into it! (P.S - I started generating infographics, so the show became much more visual, LMK if you like them) ThursdAI - I put a lot of work on a weekly basis to bring you the live show, podcast and a sourced newsletter! Please subscribe if you find this content valuable!Anthropic's Opus 4.5: The “Premier Intelligence” Returns (Blog)Folks, Anthropic absolutely cooked. After Sonnet and Haiku had their time in the sun, the big brother is finally back. Opus 4.5 launched this week, and it is reclaiming the throne for coding and complex agentic tasks.First off, the specs are monstrous. It hits 80.9% on SWE-bench Verified, topping GPT-5.1 (77.9%) and Gemini 3 Pro (76.2%). But the real kicker? The price! It is now $5 per million input tokens and $25 per million output—literally one-third the cost of the previous Opus.Yam, our resident coding wizard, put it best during the show: “Opus knows a lot of tiny details about the stack that you didn't even know you wanted... It feels like it can go forever.” Unlike Sonnet, which sometimes spirals or loses context on extremely long tasks, Opus 4.5 maintains coherence deep into the conversation.Anthropic also introduced a new “Effort” parameter, allowing you to control how hard the model thinks (similar to o1 reasoning tokens). Set it to high, and you get massive performance gains; set it to medium, and you get Sonnet-level performance at a fraction of the token cost. Plus, they've added Tool Search (cutting enormous token overhead for agents with many tools) and Programmatic Tool Calling, which effectively lets Opus write and execute code loops to manage data.If you are doing heavy software engineering or complex automations, Opus 4.5 is the new daily driver.

Hey everyone, Alex here

Hey, this is Alex! We're finally so back! Tons of open source releases, OpenAI updates GPT and a few breakthroughs in audio as well, makes this a very dense week! Today on the show, we covered the newly released GPT 5.1 update, a few open source releases like Terminal Bench and Project AELLA (renamed OASSAS), and Baidu's Ernie 4.5 VL that shows impressive visual understanding! Also, chatted with Paul from 11Labs and Dima Duev from the wandb SDK team, who brought us a delicious demo of LEET, our new TUI for wandb! Tons of news coverage, let's dive in

Hey, Alex here! Quick note, while preparing for this week, I posted on X that I don't remember such a quiet week in AI since I started doing ThursdAI regularly, but then 45 min before the show started, Kimi dropped a SOTA oss reasoning model, turning a quiet week into an absolute banger. Besides Kimi, we covered the updated MCP thinking from Anthropic, and had Kenton Varda from cloudflare as a guest to talk about Code Mode, chatted about Windsurf and Cursor latest updates and covered OpenAI's insane deals. Also, because it was a quiet week, I figured I'd use the opportunity to create an AI powered automation, and used N8N for that, and shared it on the stream, so if you're interested in automating with AI with relatively low code, this episode is for you. Let's dive inThursdAI - Recaps of the most high signal AI weekly spaces is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Kimi K2 Thinking is Here and It's a 1 Trillion Parameter Beast! (X, HF, Tech Blog)Let's start with the news that got everyone's energy levels skyrocketing right as we went live. Moonshot AI dropped Kimi K2 Thinking, an open-source, 1 trillion-parameter Mixture-of-Experts (MoE) model, and it's an absolute monster.This isn't just a numbers game; Kimi K2 Thinking is designed from the ground up to be a powerful agent. With just around 32 billion active parameters during inference, a massive 256,000 token context window, and an insane tool-calling capacity. They're claiming it can handle 200-300 sequential tool calls without any human intervention. The benchmarks are just as wild. On the Humanities Last Exam (HLE), they're reporting a score of 44.9%, beating out both GPT-5 and Claude 4.5 Thinking. While it doesn't quite top the charts on SWE-bench verified, it's holding its own against the biggest closed-source models out there. Seeing an open-source model compete at this level is incredibly exciting.During the show, we saw some truly mind-blowing demos, from a beautiful interactive visualization of gradient descent to a simulation of a virus attacking cells, all generated by the model. The model's reasoning traces, which are exposed through the API, also seem qualitatively different from other models, showing a deep and thoughtful process. My co-hosts and I were blown away. The weights and a very detailed technical report are available on Hugging Face, so you can dive in and see for yourself. Shout out to the entire Moonshot AI team for this incredible release!Other open source updates from this week* HuggingFace released an open source “Smol Training Playbook” on training LLMs, it's a 200+ interactive beast with visualizations, deep dives into pretraining, dataset, postraining and more! (HF)* Ai2 launches OlmoEarth — foundation models + open, end-to-end platform for fast, high-resolution Earth intelligence (X, Blog)* LongCat-Flash-Omni — open-source omni-modal system with millisecond E2E spoken interaction, 128K context and a 560B ScMoE backbone (X, HF, Announcement)Big Tech's Big Moves: Apple, Amazon, and OpenAIThe big companies were making waves this week, starting with a blockbuster deal that might finally make Siri smart. Apple is reportedly will be paying Google around $1 billion per year to license a custom 1.2 trillion-parameter version of Gemini to power a revamped Siri.This is a massive move. The Gemini model will run on Apple's Private Cloud Compute, keeping user data walled off from Google, and will handle Siri's complex summarizer and planner functions. After years of waiting for Apple to make a significant move in GenAI, it seems they're outsourcing the heavy lifting for now while they work to catch up with their own in-house models. As a user, I don't really care who builds the model, as long as Siri stops being dumb!In more dramatic news, Perplexity revealed that Amazon sent them a legal threat to block their Comet AI assistant from shopping on Amazon.com. This infuriated me. My browser is my browser, and I should be able to use whatever tools I want to interact with the web. Perplexity took a strong stand with their blog post, “Bullying is Not Innovation,” arguing that user agents are distinct from scrapers and act on behalf of the user with their own credentials. An AI assistant is just that—an assistant. It shouldn't matter if I ask my wife or my AI to buy something for me on Amazon. This feels like a move by Amazon to protect its ad revenue at the expense of user choice and innovation, and I have to give major props to Perplexity for being so transparent and fighting back.Finally, OpenAI continues its quest for infinite compute, announcing a multi-year strategic partnership with AWS. This comes on top of massive deals with NVIDIA, Microsoft, Oracle, and others, bringing their total commitment to compute into the trillions of dollars. It's getting to a point where OpenAI seems “too big to fail,” as any hiccup could have serious repercussions for the entire tech economy, which is now heavily propped up by AI investment. Sam has clarified that they don't think OpenAI wants to be too big to fail in a recent post on X, and that the recent miscommunications around the US government backstopping OpenAI's infrastructure bailouts were taken out of context.

Hey, it's Alex! Happy Halloween friends! I'm excited to bring you this weeks (spooky) AI updates! We started the show today with MiniMax M2, the currently top Open Source LLM, with an interview with their head of eng, Skyler Miao, continued to dive into OpenAIs completed restructuring into a non-profit and a PBC, including a deep dive into a live stream Sam Altman had, with a ton of spicy details, and finally chatted with Arjun Desai from Cartesia, following a release of Sonic 3, a sub 49ms voice model! So, 2 interviews + tons of news, let's dive in! (as always, show notes in the end)Hey, if you like this content, it would mean a lot if you subscribe as a paid subscriber.Open Source AIMiniMax M2: open-source agentic model at 8% of Claude's price, 2× speed (X, Hugging Face )We kicked off our open-source segment with a banger of an announcement and a special guest. The new king of open-source LLMs is here, and it's called MiniMax M2. We were lucky enough to have Skyler Miao, Head of Engineering at Minimax, join us live to break it all down.M2 is an agentic model built for code and complex workflows, and its performance is just staggering. It's already ranked in the top 5 globally on the Artificial Analysis benchmark, right behind giants like OpenAI and Anthropic. But here's the crazy part: it delivers nearly twice the speed of Claude 3.5 Sonnet at just 8% of the price. This is basically Sonnet-level performance, at home, in open source.Skylar explained that their team saw an “impossible triangle” in the market between performance, cost, and speed—you could only ever get two. Their goal with M2 was to build a model that could solve this, and they absolutely nailed it. It's a 200B parameter Mixture-of-Experts (MoE) model, but with only 10B active parameters per inference, making it incredibly efficient.One key insight Skylar shared was about getting the best performance. M2 supports multiple APIs, but to really unlock its reasoning power, you need to use an API that passes the model's “thinking” tokens back to it on the next turn, like the Anthropic API. Many open-source tools don't support this yet, so it's something to watch out for.Huge congrats to the MiniMax team on this Open Weights (MIT licensed) release, you can find the model on HF! MiniMax had quite a week, with 3 additional releases, MiniMax speech 2.6, an update to their video model Hailuo 2.3 and just after the show, they released a music 2.0 model as well! Congrats on the shipping folks! OpenAI drops gpt-oss-safeguard - first open-weight safety reasoning models for classification ( X, HF )OpenAI is back on the open weights bandwagon, with a finetune release of their previously open weighted gpt-oss models, with gpt-oss-safeguard. These models were trained exclusively to help companies build safeguarding policies to make sure their apps remains safe! With gpt-oss-safeguards 20B and 120B, OpenAI is achieving near parity with their internal safety models, and as Nisten said on the show, if anyone knows about censorship and safety, it's OpenAI! The highlight of this release is, unlike traditional pre-trained classifiers, these models allow for updates to policy via natural language!These models will be great for businesses that want to safeguard their products in production, and I will advocate to bring these models to W&B Inference soon! A Humanoid Robot in Your Home by 2026? 1X NEO announcement ( X, Order page, Keynote )Things got really spooky when we started talking about robotics. The company 1X, which has been on our radar for a while, officially launched pre-orders for NEO, the world's first consumer humanoid robot designed for your home. And yes, you can order one right now for $20,000, with deliveries expected in early 2026.The internet went crazy over this announcement, with folks posting receipts of getting one, other folks stoking the uncanny valley fears that Sci-fi has built into many people over the years, of the Robot uprising and talking about the privacy concerns of having a human tele-operate this Robot in your house to do chores. It can handle chores like cleaning and laundry, and for more complex tasks that it hasn't learned yet, it uses a teleoperation system where a human “1X Expert” can pilot the robot remotely to perform the task. This is how it collects the data to learn to do these tasks autonomously in your specific home environment.The whole release is very interesting, from the “soft and quiet” approach 1X is taking, making their robot a 66lbs short king, draped in a knit sweater, to the $20K price point (effectively at loss given how much just the hands cost), the teleoperated by humans addition, to make sure the Robot learns about your unique house layout. The conversation on the show was fascinating. We talked about all the potential use cases, from having it water your plants and look after your pets while you're on vacation to providing remote assistance for elderly relatives. Of course, there are real privacy concerns with having a telepresence device in your home, but 1X says these sessions are scheduled by you and have strict no-go zones.Here's my prediction: by next Halloween, we'll see videos of these NEO robots dressed up in costumes, helping out at parties. The future is officially here. Will you be getting one? If not this one, when will you think you'll get one? OpenAI's Grand Plan: From Recapitalization to ASIThis was by far the biggest update about the world of AI for me this week! Sam Altman was joined by Jakub Pachocki, chief scientist and Wojciech Zaremba, a co-founder, on a live stream to share an update about their corporate structure, plans for the future, and ASI goals (Artificial Superintelligence) First, the company now has a new structure: a non-profit OpenAI Foundation governs the for-profit OpenAI Group. The foundation starts with about 26% equity and has a mission to use AI for public good, including an initial $25 billion commitment to curing diseases and building an “AI Resilience” ecosystem.But the real bombshells were about their research timeline. Chief Scientist Jakub Pachocki stated that they believe deep learning systems are less than a decade away from superintelligence (ASI). He said that at this point, AGI isn't even the right goal anymore. To get there, they're planning to have an “AI research intern” by September 2026 and a fully autonomous AI researcher comparable to their human experts by March 2028. This is insane if you think about it. As Yam mentioned, OpenAI is already shipping at an insane speed, releasing Models and Products, Sora, Atlas, Pulse, ChatGPT app store, and this is with humans, assisted by AI. And here, they are talking about complete and fully autonomous researchers, that will be infinitely more scalable than humans, in the next 2 years. The outcomes of this are hard to imagine and are honestly mindblowing. To power all this innovation, Sam revealed they have over $1.4 trillion in obligations for compute (over 30 GW). And said even that's not enough. Their aspiration is to build a “compute factory” capable of standing up one gigawatt of new compute per week, and he hinted they may need to “rethink their robotics strategy” to build the data centers fast enough. Does this mean OpenAI humanoid robots building factories?

Hey everyone, Alex here! Welcome... to the browser war II - the AI edition! This week we chatted in depth about ChatGPT's new Atlas agentic browser, and the additional agentic powers Microsoft added to Edge with Copilot Mode (tho it didn't work for me) Also this week was a kind of crazy OCR week, with more than 4 OCR models releasing, and the crown one is DeepSeek OCR, that turned the whole industry on it's head (more later) Quite a few video updates as well, with real time lipsync from Decart, and a new update from LTX with 4k native video generation, it's been a busy AI week for sure! Additionally, I've had the pleasure to talk about AI Browsing agents with Paul from BrowserBase and real time video with Kwindla Kramer from Pipecat/Daily, so make sure to tune in for those interviews, buckle up, let's dive in! Thanks for reading ThursdAI - Recaps of the most high signal AI weekly spaces! This post is public so feel free to share it.Open Source: OCR is Not What You Think It Is (X, HF, Paper)The most important and frankly mind-bending release this week came from DeepSeek. They dropped DeepSeek-OCR, and let me tell you, this is NOT just another OCR model. The cohost were buzzing about this, and once I dug in, I understood why. This isn't just about reading text from an image; it's a revolutionary approach to context compression.We think that DeepSeek needed this as an internal tool, so we're really grateful to them for open sourcing this, as they did something crazy here. They are essentially turning text into a visual representation, compressing it, and then using a tiny vision decoder to read it back with incredible accuracy. We're talking about a compression ratio of up to 10x with 97% decoding accuracy. Even at 20x compression they are achieving 60% decoding accuracy! My head exploded live on the show when I read that. This is like the middle-out compression algorithm joke from Silicon Valley, but it's real. As Yam pointed out, this suggests our current methods of text tokenization are far from optimal.With only 3B and ~570M active parameters, they are taking a direct stab at long context inefficiency, imagine taking 1M tokens, encoding them into 100K visual tokens, and then feeding those into a model. Since the model is tiny, it's very cheap to run, for example, alphaXiv claimed they have OCRd' all of the papers on ArXiv with this model for $1000, a task that would have cost $7500 using MistalOCR - as per their paper, with DeepSeek OCR, on a single H100 GPU, its possible to scan up to 200K pages!

Hey folks, Alex here. Can you believe it's already the middle of October? This week's show was a special one, not just because of the mind-blowing news, but because we set a new ThursdAI record with four incredible interviews back-to-back!We had Jessica Gallegos from Google DeepMind walking us through the cinematic new features in VEO 3.1. Then we dove deep into the world of Reinforcement Learning with my new colleague Kyle Corbitt from OpenPipe. We got the scoop on Amp's wild new ad-supported free tier from CEO Quinn Slack. And just as we were wrapping up, Swyx ( from Latent.Space , now with Cognition!) jumped on to break the news about their blazingly fast SWE-grep models. But the biggest story? An AI model from Google and Yale made a novel scientific discovery about cancer cells that was then validated in a lab. This is it, folks. This is the “let's f*****g go” moment we've been waiting for. So buckle up, because this week was an absolute monster. Let's dive in!ThursdAI - Recaps of the most high signal AI weekly spaces is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Open Source: An AI Model Just Made a Real-World Cancer DiscoveryWe always start with open source, but this week felt different. This week, open source AI stepped out of the benchmarks and into the biology lab.Our friends at Qwen kicked things off with new 3B and 8B parameter versions of their Qwen3-VL vision model. It's always great to see powerful models shrink down to sizes that can run on-device. What's wild is that these small models are outperforming last generation's giants, like the 72B Qwen2.5-VL, on a whole suite of benchmarks. The 8B model scores a 33.9 on OS World, which is incredible for an on-device agent that can actually see and click things on your screen. For comparison, that's getting close to what we saw from Sonnet 3.7 just a few months ago. The pace is just relentless.But then, Google dropped a bombshell. A 27-billion parameter Gemma-based model they developed with Yale, called C2S-Scale, generated a completely novel hypothesis about how cancer cells behave. This wasn't a summary of existing research; it was a new idea, something no human scientist had documented before. And here's the kicker: researchers then took that hypothesis into a wet lab, tested it on living cells, and proved it was true.This is a monumental deal. For years, AI skeptics like Gary Marcus have said that LLMs are just stochastic parrots, that they can't create genuinely new knowledge. This feels like the first, powerful counter-argument. Friend of the pod, Dr. Derya Unutmaz, has been on the show before saying AI is going to solve cancer, and this is the first real sign that he might be right. The researchers noted this was an “emergent capability of scale,” proving once again that as these models get bigger and are trained on more complex data—in this case, turning single-cell RNA sequences into “sentences” for the model to learn from—they unlock completely new abilities. This is AI as a true scientific collaborator. Absolutely incredible.Big Companies & APIsThe big companies weren't sleeping this week, either. The agentic AI race is heating up, and we're seeing huge updates across the board.Claude Haiku 4.5: Fast, Cheap Model Rivals Sonnet 4 Accuracy (X, Official blog, X)First up, Anthropic released Claude Haiku 4.5, and it is a beast. It's a fast, cheap model that's punching way above its weight. On the SWE-bench verified benchmark for coding, it hit 73.3%, putting it right up there with giants like GPT-5 Codex, but at a fraction of the cost and twice the speed of previous Claude models. Nisten has already been putting it through its paces and loves it for agentic workflows because it just follows instructions without getting opinionated. It seems like Anthropic has specifically tuned this one to be a workhorse for agents, and it absolutely delivers. The thing to note also is the very impressive jump in OSWorld (50.7%), which is a computer use benchmark, and at this price and speed ($1/$5 MTok input/output) is going to make computer agents much more streamlined and speedy! ChatGPT will loose restrictions; age-gating enables “adult mode” with new personality features coming (X) Sam Altman set X on fire with a thread announcing that ChatGPT will start loosening its restrictions. They're planning to roll out an “adult mode” in December for age-verified users, potentially allowing for things like erotica. More importantly, they're bringing back more customizable personalities, trying to recapture some of the magic of GPT-4.0 that so many people missed. It feels like they're finally ready to treat adults like adults, letting us opt-in to R-rated conversations while keeping strong guardrails for minors. This is a welcome change, and we've been advocating for this for a while, and it's a notable change from the XAI approach I covered last week. Opt in for adults with verification while taking precautions vs engagement bait in the form of a flirty animated waifu with engagement mechanics. Microsoft is making every windows 11 an AI PC with copilot voice input and agentic powers (Blog,X)And in breaking news from this morning, Microsoft announced that every Windows 11 machine is becoming an AI PC. They're building a new Copilot agent directly into the OS that can take over and complete tasks for you. The really clever part? It runs in a secure, sandboxed desktop environment that you can watch and interact with. This solves a huge problem with agents that take over your mouse and keyboard, locking you out of your own computer. Now, you can give the agent a task and let it run in the background while you keep working. This is going to put agentic AI in front of hundreds of millions of users, and it's a massive step towards making AI a true collaborator at the OS level.NVIDIA DGX - the tiny personal supercomputer at $4K (X, LMSYS Blog)NVIDIA finally delivered their promised AI Supercomputer, and while the excitement was in the air with Jensen hand delivering the DGX Spark to OpenAI and Elon (recreating that historical picture when Jensen hand delivered a signed DGX workstation while Elon was still affiliated with OpenAI). The workstation was sold out almost immediately. Folks from LMSys did a great deep dive into specs, all the while, folks on our feeds are saying that if you want to get the maximum possible open source LLMs inference speed, this machine is probably overpriced, compared to what you can get with an M3 Ultra Macbook with 128GB of RAM or the RTX 5090 GPU which can get you similar if not better speeds at significantly lower price points. Anthropic's “Claude Skills”: Your AI Agent Finally Gets a Playbook (Blog)Just when we thought the week couldn't get any more packed, Anthropic dropped “Claude Skills,” a huge upgrade that lets you give your agent custom instructions and workflows. Think of them as expertise folders you can create for specific tasks. For example, you can teach Claude your personal coding style, how to format reports for your company, or even give it a script to follow for complex data analysis.The best part is that Claude automatically detects which “Skill” is needed for a given task, so you don't have to manually load them. This is a massive step towards making agents more reliable and personalized, moving beyond just a single custom instruction and into a library of repeatable, expert processes. It's available now for all paid users, and it's a feature I've been waiting for. Our friend Simon Willison things skills may be a bigger deal than MCPs!

Hey everyone, Alex here

Hey everyone, Alex here (yes the real me if you're reading this) The weeks are getting crazier, but what OpenAI pulled this week, with a whole new social media app attached to their latest AI breakthroughs is definitely breathtaking! Sora2 released and instantly became a viral sensation, shooting to the top 3 free iOS spot on AppStore, with millions of videos watched, and remixed. On weeks like these, even huge releases like Claude 4.5 are taking the backseat, but we still covered them! For listeners of the pod, the second half of the show was very visual heavy, so it may be worth it watching the YT video attached in a comment if you want to fully experience the Sora revolution with us! (and if you want a SORA invite but don't have one yet, more on that below) ThursdAI - if you find this valuable, please support us by subscribing! Sora 2 - the AI video model that signifies a new era of social mediaLook, you've probably already heard about the SORA-2 release, but in case you haven't, OpenAI released a whole new model, but attached it to a new, AI powered social media experiment in the form of a very addictive TikTok style feed. Besides being hyper-realistic, and producing sounds and true to source voice-overs, Sora2 asks you to create your own “Cameo” by taking a quick video, and then allows you to be featured in your own (and your friends) videos. This makes a significant break from the previously “slop” based meta Vibes, becuase, well, everyone loves seeing themselves as the stars of the show! Cameos are a stroke of genius, and what's more, one can allow everyone to use their Cameo, which is what Sam Altman did at launch, making everyone Cameo him, and turning him, almost instantly into one of the most meme-able (and approachable) people on the planet! Sam sharing away his likeness like this for the sake of the app achieved a few things, it added trust in the safety features, made it instantly viral and showed folks they shouldn't be afraid of adding their own likeness. Vibes based feed and remixingSora 2 is also unique in that, it's the first social media with UGC (user generated content) where content can ONLY be generated, and all SORA content is created within the app. It's not possible to upload pictures that have people to create the posts, and you can only create posts with other folks if you have access to their Cameos, or by Remixing existing creations. Remixing is also a way to let users “participate” in the creation process, by adding their own twist and vibes! Speaking of Vibes, while the SORA app has an algorithmic For You page, they have a completely novel and new way to interact with the algorithm, by using their Pick a Mood feature, where you can describe which type of content you want to see, or not see, with natural language! I believe that this feature will come to all social media platforms later, as it's such a game changer. Want only content in a specific language? or content that doesn't have Sam Altman in it? Just ask! Content that makes you feel goodThe most interesting thing is about the type of content is, there's no sexualisation (because all content is moderated by OpenAI strong filters), and no gore etc. OpenAI has clearly been thinking about teenagers and have added parent controls, things like being able to turn of the For You page completely etc to the mix. Additionally, SORA seems to be a very funny model, and I mean this literally. You can ask the video generation for a joke and you'll often get a funny one. The scene setup, the dialogue, the things it does even unprompted are genuinely entertaining. AI + Product = Profit? OpenAI shows that they are one of the worlds best product labs in the world, not just a foundational AI lab. Most AI advancements are tied to products, and in this case, the whole experience is so polished, it's hard to accept that it's a brand new app from a company that didn't do social before. There's very little buggy behavior, videos are loaded up quick, there's even DMs! I'm thoroughly impressed and am immersing myself in the SORA sphere. Please give me a follow there and feel free to use my Cameo by tagging @altryne in there. I love seeing how folks have used my Cameo, it makes me laugh

This is a free preview of a paid episode. To hear more, visit sub.thursdai.newsHola AI aficionados, it's yet another ThursdAI, and yet another week FULL of AI news, spanning Open Source LLMs, Multimodal video and audio creation and more! Shiptember as they call it does seem to deliver, and it was hard even for me to follow up on all the news, not to mention we had like 3-4 breaking news during the show today! This week was yet another Qwen-mas, with Alibaba absolutely dominating across open source, but also NVIDIA promising to invest up to $100 Billion into OpenAI. So let's dive right in! As a reminder, all the show notes are posted at the end of the article for your convenience. ThursdAI - Because weeks are getting denser, but we're still here, weekly, sending you the top AI content! Don't miss outTable of Contents* Open Source AI* Qwen3-VL Announcement (Qwen3-VL-235B-A22B-Thinking):* Qwen3-Omni-30B-A3B: end-to-end SOTA omni-modal AI unifying text, image, audio, and video* DeepSeek V3.1 Terminus: a surgical bugfix that matters for agents* Evals & Benchmarks: agents, deception, and code at scale* Big Companies, Bigger Bets!* OpenAI: ChatGPT Pulse: Proactive AI news cards for your day* XAI Grok 4 fast - 2M context, 40% fewer thinking tokens, shockingly cheap* Alibaba Qwen-Max and plans for scaling* This Week's Buzz: W&B Fully Connected is coming to London and Tokyo & Another hackathon in SF* Vision & Video: Wan 2.2 Animate, Kling 2.5, and Wan 4.5 preview* Moondream-3 Preview - Interview with co-founders Via & Jay* Wan open sourced Wan 2.2 Animate (aka “Wan Animate”): motion transfer and lip sync* Kling 2.5 Turbo: cinematic motion, cheaper and with audio* Wan 4.5 preview: native multimodality, 1080p 10s, and lip-synced speech* Voice & Audio* ThursdAI - Sep 25, 2025 - TL;DR & Show notesOpen Source AIThis was a Qwen-and-friends week. I joked on stream that I should just count how many times “Alibaba” appears in our show notes. It's a lot.Qwen3-VL Announcement (Qwen3-VL-235B-A22B-Thinking): (X, HF, Blog, Demo)Qwen 3 launched earlier as a text-only family; the vision-enabled variant just arrived, and it's not timid. The “thinking” version is effectively a reasoner with eyes, built on a 235B-parameter backbone with around 22B active (their mixture-of-experts trick). What jumped out is the breadth of evaluation coverage: MMU, video understanding (Video-MME, LVBench), 2D/3D grounding, doc VQA, chart/table reasoning—pages of it. They're showing wins against models like Gemini 2.5 Pro and GPT‑5 on some of those reports, and doc VQA is flirting with “nearly solved” territory in their numbers.Two caveats. First, whenever scores get that high on imperfect benchmarks, you should expect healthy skepticism; known label issues can inflate numbers. Second, the model is big. Incredible for server-side grounding and long-form reasoning with vision (they're talking about scaling context to 1M tokens for two-hour video and long PDFs), but not something you throw on a phone.Still, if your workload smells like “reasoning + grounding + long context,” Qwen 3 VL looks like one of the strongest open-weight choices right now.Qwen3-Omni-30B-A3B: end-to-end SOTA omni-modal AI unifying text, image, audio, and video (HF, GitHub, Qwen Chat, Demo, API)Omni is their end-to-end multimodal chat model that unites text, image, and audio—and crucially, it streams audio responses in real time while thinking separately in the background. Architecturally, it's a 30B MoE with around 3B active parameters at inference, which is the secret to why it feels snappy on consumer GPUs.In practice, that means you can talk to Omni, have it see what you see, and get sub-250 ms replies in nine speaker languages while it quietly plans. It claims to understand 119 languages. When I pushed it in multilingual conversational settings it still code-switched unexpectedly (Chinese suddenly appeared mid-flow), and it occasionally suffered the classic “stuck in thought” behavior we've been seeing in agentic voice modes across labs. But the responsiveness is real, and the footprint is exciting for local speech streaming scenarios. I wouldn't replace a top-tier text reasoner with this for hard problems, yet being able to keep speech native is a real UX upgrade.Qwen Image Edit, Qwen TTS Flash, and Qwen‑GuardQwen's image stack got a handy upgrade with multi-image reference editing for more consistent edits across shots—useful for brand assets and style-tight workflows. TTS Flash (API-only for now) is their fast speech synth line, and Q‑Guard is a new safety/moderation model from the same team. It's notable because Qwen hasn't really played in the moderation-model space before; historically Meta's Llama Guard led that conversation.DeepSeek V3.1 Terminus: a surgical bugfix that matters for agents (X, HF)DeepSeek whale resurfaced to push a small 0.1 update to V3.1 that reads like a “quality and stability” release—but those matter if you're building on top. It fixes a code-switching bug (the “sudden Chinese” syndrome you'll also see in some Qwen variants), improves tool-use and browser execution, and—importantly—makes agentic flows less likely to overthink and stall. On the numbers, Humanities Last Exam jumped from 15 to 21.7, while LiveCodeBench dipped slightly. That's the story here: they traded a few raw points on coding for more stable, less dithery behavior in end-to-end tasks. If you've invested in their tool harness, this may be a net win.Liquid Nanos: small models that extract like they're big (X, HF)Liquid Foundation Models released “Liquid Nanos,” a set of open models from roughly 350M to 2.6B parameters, including “extract” variants that pull structure (JSON/XML/YAML) from messy documents. The pitch is cost-efficiency with surprisingly competitive performance on information extraction tasks versus models 10× their size. If you're doing at-scale doc ingestion on CPUs or small GPUs, these look worth a try.Tiny IBM OCR model that blew up the charts (HF)We also saw a tiny IBM model (about 250M parameters) for image-to-text document parsing trending on Hugging Face. Run in 8-bit, it squeezes into roughly 250 MB, which means Raspberry Pi and “toaster” deployments suddenly get decent OCR/transcription against scanned docs. It's the kind of tiny-but-useful release that tends to quietly power entire products.Meta's 32B Code World Model (CWM) released for agentic code reasoning (X, HF)Nisten got really excited about this one, and once he explained it, I understood why. Meta released a 32B code world model that doesn't just generate code - it understands code the way a compiler does. It's thinking about state, types, and the actual execution context of your entire codebase.This isn't just another coding model - it's a fundamentally different approach that could change how all future coding models are built. Instead of treating code as fancy text completion, it's actually modeling the program from the ground up. If this works out, expect everyone to copy this approach.Quick note, this one was released with a research license only! Evals & Benchmarks: agents, deception, and code at scaleA big theme this week was “move beyond single-turn Q&A and test how these things behave in the wild.” with a bunch of new evals released. I wanted to cover them all in a separate segment. OpenAI's GDP Eval: “economically valuable tasks” as a bar (X, Blog)OpenAI introduced GDP Eval to measure model performance against real-world, economically valuable work. The design is closer to how I think about “AGI as useful work”: 44 occupations across nine sectors, with tasks judged against what an industry professional would produce.Two details stood out. First, OpenAI's own models didn't top the chart in their published screenshot—Anthropic's Claude Opus 4.1 led with roughly a 47.6% win rate against human professionals, while GPT‑5-high clocked in around 38%. Releasing a benchmark where you're not on top earns respect. Second, the tasks are legit. One example was a manufacturing engineer flow where the output required an overall design with an exploded view of components—the kind of deliverable a human would actually make.What I like here isn't the precise percent; it's the direction. If we anchor progress to tasks an economy cares about, we move past “trivia with citations” and toward “did this thing actually help do the work?”GAIA 2 (Meta Super Intelligence Labs + Hugging Face): agents that execute (X, HF)MSL and HF refreshed GAIA, the agent benchmark, with a thousand new human-authored scenarios that test execution, search, ambiguity handling, temporal reasoning, and adaptability—plus a smartphone-like execution environment. GPT‑5-high led across execution and search; Kimi's K2 was tops among open-weight entries. I like that GAIA 2 bakes in time and budget constraints and forces agents to chain steps, not just spew plans. We need more of these.Scale AI's “SWE-Bench Pro” for coding in the large (HF)Scale dropped a stronger coding benchmark focused on multi-file edits, 100+ line changes, and large dependency graphs. On the public set, GPT‑5 (not Codex) and Claude Opus 4.1 took the top two slots; on a commercial set, Opus edged ahead. The broader takeaway: the action has clearly moved to test-time compute, persistent memory, and program-synthesis outer loops to get through larger codebases with fewer invalid edits. This aligns with what we're seeing across ARC‑AGI and SWE‑bench Verified.The “Among Us” deception test (X)One more that's fun but not frivolous: a group benchmarked models on the social deception game Among Us. OpenAI's latest systems reportedly did the best job both lying convincingly and detecting others' lies. This line of work matters because social inference and adversarial reasoning show up in real agent deployments—security, procurement, negotiations, even internal assistant safety.Big Companies, Bigger Bets!Nvidia's $100B pledge to OpenAI for 10GW of computeLet's say that number again: one hundred billion dollars. Nvidia announced plans to invest up to $100B into OpenAI's infrastructure build-out, targeting roughly 10 gigawatts of compute and power. Jensen called it the biggest infrastructure project in history. Pair that with OpenAI's Stargate-related announcements—five new datacenters with Oracle and SoftBank and a flagship site in Abilene, Texas—and you get to wild territory fast.Internal notes circulating say OpenAI started the year around 230MW and could exit 2025 north of 2GW operational, while aiming at 20GW in the near term and a staggering 250GW by 2033. Even if those numbers shift, the directional picture is clear: the GPU supply and power curves are going vertical.Two reactions. First, yes, the “infinite money loop” memes wrote themselves—OpenAI spends on Nvidia GPUs, Nvidia invests in OpenAI, the market adds another $100B to Nvidia's cap for good measure. But second, the underlying demand is real. If we need 1–8 GPUs per “full-time agent” and there are 3+ billion working adults, we are orders of magnitude away from compute saturation. The power story is the real constraint—and that's now being tackled in parallel.OpenAI: ChatGPT Pulse: Proactive AI news cards for your day (X, OpenAI Blog)In a #BreakingNews segment, we got an update from OpenAI, that currently works only for Pro users but will come to everyone soon. Proactive AI, that learns from your chats, email and calendar and will show you a new “feed” of interesting things every morning based on your likes and feedback! Pulse marks OpenAI's first step toward an AI assistant that brings the right info before you ask, tuning itself with every thumbs-up, topic request, or app connection. I've tuned mine for today, we'll see what tomorrow brings! P.S - Huxe is a free app from the creators of NotebookLM (Ryza was on our podcast!) that does a similar thing, so if you don't have pro, check out Huxe, they just launched! XAI Grok 4 fast - 2M context, 40% fewer thinking tokens, shockingly cheap (X, Blog)xAI launched Grok‑4 Fast, and the name fits. Think “top-left” on the speed-to-cost chart: up to 2 million tokens of context, a reported 40% reduction in reasoning token usage, and a price tag that's roughly 1% of some frontier models on common workloads. On LiveCodeBench, Grok‑4 Fast even beat Grok‑4 itself. It's not the most capable brain on earth, but as a high-throughput assistant that can fan out web searches and stitch answers in something close to real time, it's compelling.Alibaba Qwen-Max and plans for scaling (X, Blog, API)Back in the Alibaba camp, they also released their flagship API model, Qwen 3 Max, and showed off their future roadmap. Qwen-max is over 1T parameters, MoE that gets 69.6 on Swe-bench verified and outperforms GPT-5 on LMArena! And their plan is simple: scale. They're planning to go from 1 million to 100 million token context windows and scale their models into the terabytes of parameters. It culminated in a hilarious moment on the show where we all put on sunglasses to salute a slide from their presentation that literally said, “Scaling is all you need.” AGI is coming, and it looks like Alibaba is one of the labs determined to scale their way there. Their release schedule lately (as documented by Swyx from Latent.space) is insane. This Week's Buzz: W&B Fully Connected is coming to London and Tokyo & Another hackathon in SFWeights & Biases (now part of the CoreWeave family) is bringing Fully Connected to London on Nov 4–5, with another event in Tokyo on Oct 31. If you're in Europe or Japan and want two days of dense talks and hands-on conversations with teams actually shipping agents, evals, and production ML, come hang out. Readers got a code on stream; if you need help getting a seat, ping me directly.Links: fullyconnected.comWe are also opening up registrations to our second WeaveHacks hackathon in SF, October 11-12, yours trully will be there, come hack with us on Self Improving agents! Register HEREVision & Video: Wan 2.2 Animate, Kling 2.5, and Wan 4.5 previewThis is the most exciting space in AI week-to-week for me right now. The progress is visible. Literally.Moondream-3 Preview - Interview with co-founders Via & JayWhile I've already reported on Moondream-3 in the last weeks newsletter, this week we got the pleasure of hosting Vik Korrapati and Jay Allen the co-founders of MoonDream to tell us all about it. Tune in for that conversation on the pod starting at 00:33:00Wan open sourced Wan 2.2 Animate (aka “Wan Animate”): motion transfer and lip sync Tongyi's Wan team shipped an open-source release that the community quickly dubbed “Wanimate.” It's a character-swap/motion transfer system: provide a single image for a character and a reference video (your own motion), and it maps your movement onto the character with surprisingly strong hair/cloth dynamics and lip sync. If you've used runway's Act One, you'll recognize the vibe—except this is open, and the fidelity is rising fast.The practical uses are broader than “make me a deepfake.” Think onboarding presenters with perfect backgrounds, branded avatars that reliably say what you need, or precise action blocking without guessing at how an AI will move your subject. You act it; it follows.Kling 2.5 Turbo: cinematic motion, cheaper and with audioKling quietly rolled out a 2.5 Turbo tier that's 30% cheaper and finally brings audio into the loop for more complete clips. Prompts adhere better, physics look more coherent (acrobatics stop breaking bones across frames), and the cinematic look has moved from “YouTube short” to “film-school final.” They seeded access to creators and re-shared the strongest results; the consistency is the headline. (Source X: @StevieMac03)I've chatted with my kiddos today over facetime, and they were building minecraft creepers. I took a screenshot, sent to Nano Banana to make their creepers into actual minecraft ones, and then with Kling, Animated the explosions for them. They LOVED it! Animations were clear, while VEO refused for me to even upload their images, Kling didn't care hahaWan 4.5 preview: native multimodality, 1080p 10s, and lip-synced speechWan also teased a 4.5 preview that unifies understanding and generation across text, image, video, and audio. The eye-catching bit: generate a 1080p, 10-second clip with synced speech from just a script. Or supply your own audio and have it lip-sync the shot. I ran my usual “interview a polar bear dressed like me” test and got one of the better results I've seen from any model. We're not at “dialogue scene” quality, but “talking character shot” is getting… good. The generation of audio (not only text + lipsync) is one of the best ones besides VEO, it's really great to see how strongly this improves, sad that this wasn't open sourced! And apparently it supports “draw text to animate” (Source: X) Voice & AudioSuno V5: we've entered the “I can't tell anymore” eraSuno calls V5 a redefinition of audio quality. I'll be honest, I'm at the edge of my subjective hearing on this. I've caught myself listening to Suno streams instead of Spotify and forgetting anything is synthetic. The vocals feel more human, the mixes cleaner, and the remastering path (including upgrading V4 tracks) is useful. The last 10% to “you fooled a producer” is going to be long, but the distance between V4 and V5 already makes me feel like I should re-cut our ThursdAI opener.MiMI Audio: a small omni-chat demo that hints at the floorWe tried a MiMI Audio demo live—a 7B-ish model with speech in/out. It was responsive but stumbled on singing and natural prosody. I'm leaving it in here because it's a good reminder that the open floor for “real-time voice” is rising quickly even for small models. And the moment you pipe a stronger text brain behind a capable, native speech front-end, the UX leap is immediate.Ok, another DENSE week that finishes up Shiptember, tons of open source, Qwen (Tongyi) shines, and video is getting so so good. This is all converging folks, and honestly, I'm just happy to be along for the ride! This week was also Rosh Hashanah, which is the Jewish new year, and I've shared on the pod that I've found my X post from 3 years ago, using the state of the art AI models of the time. WHAT A DIFFERENCE 3 years make, just take a look, I had to scale down the 4K one from this year just to fit into the pic! Shana Tova to everyone who's reading this, and we'll see you next week

Hey folks, What an absolute packed week this week, which started with yet another crazy model release from OpenAI, but they didn't stop there, they also announced GPT-5 winning the ICPC coding competitions with 12/12 questions answered which is apparently really really hard! Meanwhile, Zuck took the Meta Connect 25' stage and announced a new set of Meta glasses with a display! On the open source front, we yet again got multiple tiny models doing DeepResearch and Image understanding better than much larger foundational models.Also, today I interviewed Jeremy Berman, who topped the ArcAGI with a 79.6% score and some crazy Grok 4 prompts, a new image editing experience called Reve, a new world model and a BUNCH more! So let's dive in! As always, all the releases, links and resources at the end of the article. ThursdAI - Recaps of the most high signal AI weekly spaces is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Codex comes full circle with GPT-5-Codex agentic finetune (X, OpenAI Blog)My personal highlight of the week was definitely the release of GPT-5-Codex. I feel like we've come full circle here. I remember when OpenAI first launched a separate, fine-tuned model for coding called Codex, way back in the GPT-3 days. Now, they've done it again, taking their flagship GPT-5 model and creating a specialized version for agentic coding, and the results are just staggering.This isn't just a minor improvement. During their internal testing, OpenAI saw GPT-5-Codex work independently for more than seven hours at a time on large, complex tasks—iterating on its code, fixing test failures, and ultimately delivering a successful implementation. Seven hours! That's an agent that can take on a significant chunk of work while you're sleeping. It's also incredibly efficient, using 93% fewer tokens than the base GPT-5 on simpler tasks, while thinking for longer on the really difficult problems.The model is now integrated everywhere - the Codex CLI (just npm install -g codex), VS Code extension, web playground, and yes, even your iPhone. At OpenAI, Codex now reviews the vast majority of their PRs, catching hundreds of issues daily before humans even look at them. Talk about eating your own dog food!Other OpenAI updates from this weekWhile Codex was the highlight, OpenAI (and Google) also participated and obliterated one of the world's hardest algorithmic competitions called ICPC. OpenAI used GPT-5 and an unreleased reasoning model to solve 12/12 questions in under 5 hours. OpenAI and NBER also released an incredible report on how over 700M people use GPT on a weekly basis, with a lot of insights, that are summed up in this incredible graph:Meta Connect 25 - The new Meta Glasses with Display & a neural control interfaceJust when we thought the week couldn't get any crazier, Zuck took the stage for their annual Meta Connect conference and dropped a bombshell. They announced a new generation of their Ray-Ban smart glasses that include a built-in, high-resolution display you can't see from the outside. This isn't just an incremental update; this feels like the arrival of a new category of device. We've had the computer, then the mobile phone, and now we have smart glasses with a display.The way you interact with them is just as futuristic. They come with a "neural band" worn on the wrist that reads myoelectric signals from your muscles, allowing you to control the interface silently just by moving your fingers. Zuck's live demo, where he walked from his trailer onto the stage while taking messages and playing music, was one hell of a way to introduce a product.This is how Meta plans to bring its superintelligence into the physical world. You'll wear these glasses, talk to the AI, and see the output directly in your field of view. They showed off live translation with subtitles appearing under the person you're talking to and an agentic AI that can perform research tasks and notify you when it's done. It's an absolutely mind-blowing vision for the future, and at $799, shipping in a week, it's going to be accessible to a lot of people. I've already signed up for a demo.Jeremy Berman: Beating frontier labs to SOTA score on ARC-AGIWe had the privilege of chatting with Jeremy Berman, who just achieved SOTA on the notoriously difficult ARC-AGI benchmark using checks notes... Grok 4!

Hey Everyone, Alex here, thanks for being a subscriber! Let's get you caught up on this weeks most important AI news! The main thing you need to know this week is likely the incredible Image model that ByteDance released, that overshoots the (incredible image model from last 2 weeks) nano

Wohoo, hey ya'll, Alex here,I'm back from the desert (pic at the end) and what a great feeling it is to be back in the studio to talk about everything that happened in AI! It's been a pretty full week (or two) in AI, with Coding agent space heating up, Grok entering the ring and taking over free tokens, Codex 10xing usage and Anthropic... well, we'll get to Anthropic. Today on the show we had Roger and Bhavesh from Nous Research cover the awesome Hermes 4 release and the new PokerBots benchmark, then we had a returning favorite, Kwindla Hultman Kramer, to talk about the GA of RealTime voice from OpenAI. Plus we got some massive funding news, some drama with model quality on Claude Code, and some very exciting news right here from CoreWeave aquiring OpenPipe!

Hey everyone, Alex here

Hey everyone, Alex here

Hey folks

This is a free preview of a paid episode. To hear more, visit sub.thursdai.newsWoohoo, we're almost done with July (my favorite month) and the Open Source AI decided to go out with some fireworks

What a WEEK! Qwen-mass in July. Folks, AI doesn't seem to be wanting to slow down, especially Open Source! This week we see yet another jump on SWE-bench verified (3rd week in a row?) this time from our friends at Alibaba Qwen. Was a pleasure of mine to host Junyang Lin from the team at Alibaba to come and chat with us about their incredible release with, with not 1 but three new models! Then, we had a great chat with Joseph Nelson from Roboflow, who not only dropped additional SOTA models, but was also in Washington at the annocement of the new AI Action plan from the WhiteHouse. Great conversations this week, as always, TL;DR in the end, tune in! Open Source AI - QwenMass in JulyThis week, the open-source world belonged to our friends at Alibaba Qwen. They didn't just release one model; they went on an absolute tear, dropping bomb after bomb on the community and resetting the state-of-the-art multiple times.A "Small" Update with Massive Impact: Qwen3-235B-A22B-Instruct-2507Alibaba called this a minor refresh of their 235B parameter mixture-of-experts.Sure—if you consider +13 points on GPQA, 256K context window minor. The 2507 drops hybrid thinking. Instead, Qwen now ships separate instruct and chain-of-thought models, avoiding token bloat when you just want a quick answer. Benchmarks? 81 % MMLU-Redux, 70 % LiveCodeBench, new SOTA on BFCL function-calling. All with 22 B active params.Our friend of the pod, and head of development at Alibaba Qwen, Junyang Lin, join the pod, and talked to us about their decision to uncouple this model from the hybrid reasoner Qwen3."After talking with the community and thinking it through," he said, "we decided to stop using hybrid thinking mode. Instead, we'll train instruct and thinking models separately so we can get the best quality possible."The community felt the hybrid model sometimes had conflicts and didn't always perform at its best. So, Qwen delivered a pure non-reasoning instruct model, and the results are staggering. Even without explicit reasoning, it's crushing benchmarks. Wolfram tested it on his MMLU-Pro benchmark and it got the top score of all open-weights models he's ever tested. Nisten saw the same thing on medical benchmarks, where it scored the highest on MedMCQA. This thing is a beast, getting a massive 77.5 on GPQA (up from 62.9) and 51.8 on LiveCodeBench (up from 32). This is a huge leap forward, and it proves that a powerful, well-trained instruct model can still push the boundaries of reasoning. The New (open) King of Code: Qwen3-Coder-480B (X, Try It, HF)Just as we were catching our breath, they dropped the main event: Qwen3-Coder. This is a 480-billion-parameter coding-specific behemoth (35B active) trained on a staggering 7.5 trillion tokens, with a 70% code ratio, that gets a new SOTA on SWE-bench verified with 69.6% (just a week after Kimi got SOTA with 65% and 2 weeks after Devstral's SOTA of 53%

Hey everyone, Alex here

Hey everyone, Alex hereDon't you just love "new top LLM" drop weeks? I sure do! This week, we had a watch party for Grok-4, with over 20K tuning in to watch together, as the folks at XAI unveiled their newest and best model around. Two models in fact, Grok-4 and Grok-4 Heavy. We also had a very big open source week, we had the pleasure to chat with the creators of 3 open source models on the show, first with Elie from HuggingFace who just released SmoLM3, then with our friend Maxime Labonne who together with Liquid released a beautiful series of tiny on device models. Finally we had a chat with folks from Reka AI, and as they were on stage, someone in their org published a new open source Reka Flash model

Hey everyone, Alex here