Podcasts about Swe

The golf course is often called a “second office,” where business deals and professional relationships are formed — but too often, women in engineering haven't felt comfortable stepping into that space. In this episode, Nichole Neal, engineering faculty at Chandler-Gilbert Community College, and Kellie Phong, regional sales manager at Keysight Technologies, share how they created Swing 4 SWE, an initiative designed to bring students, faculty, and industry together on the green. Nichole reflects on how missing early-career golf invitations inspired her to build a program where women can learn the game in a supportive environment, and Kellie shares how Swing 4 SWE helped her say yes to networking opportunities she once would have avoided. Hear their personal experiences as first-generation college students, how Swing 4 SWE connects SWE members across community colleges and four-year universities, and why community colleges are a launchpad for success in the modern AI era. — The Society of Women Engineers is a powerful, global force uniting nearly 45,000 members of all genders spanning 90+ countries. We are the world's largest advocate and catalyst for change for women in engineering and technology. To join and access all the exclusive benefits to elevate your professional journey, visit membership.swe.org.

Hey yall, Alex here, let me catch you up! I came back from vacation expecting to cover Fable 5 after a week of using it. The first two days after we all first got access to a Mythos level model were super exciting! But then the news hit, US Government issued an order banning Anthropic from giving access to Fable 5 and Mythos 5 to any foreign national, causing Anthropic to pull the models completely (even internally to their employees!). So, this wasn't the show I planned, but it turned into a great show about Open Source, as two models hit the top rankings and are both MIT licence, filling a Fable shaped hole in our hearts!GLM released 5.2 with folks really excited about it web building capabilities, and Kimi 2.7 Code released (and is available on CW Inference with crazy speeds!). We also saw the SpaceX IPO and Cursor $60B acquisition, Noam Shazeer joining Open and Midjourney, the image company, launching a new Ultrasound full body scanner to kill MRIs! Great show today with Dexter Horthy from HumanLayer, Chris Van Pelt and Adrian Swanberg from W&B announcing our new product HiveMind and Tanishq Abraham came back to help cover Midjourney's new Ultrasound scanner! Let's dive in!ThursdAI - Highest signal weekly AI news show is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.The US Government bans Fable 5! (X, Anthropic statement)Here's a story in 3 parts: * Anthropic announces Mythos 5 preview - saying that this model is to dangerous to release, and only gives corporations access to it via project GlassWing. * Anthropic works hard on limitations and safery and releases Fable 5 (same weights as Mythos 5) built with guardrails so strong it refuses to do any cybersecurity tasks and switches back to Opus frequently* US Government receives a tip (reportedly from Amazon) that Fable 5 can be jailbroken to do cybersecurity tasks, and issues an order to Anthropic, citing national security concerns, banning them from giving access to Fable 5 and Mythos 5 to any foreign national, causing Anthropic to pull the models completely (even internally to their employees!)This is the first time that we see the US Government directly intervene in the AI space and restrict access to frontier models. The most updated reporting on this I could find is that Anthropic and US Government officials are in the process of negotiating a safe release framework. Given that preventing all jailbreaks is impossible, I hope they will land on a solution that gives me Fable 5 back!This hit especially hard because last week we were all high on Fable. Not in the usual AI Twitter benchmark sense, in the actual “oh, this is a different level” sense. Me and my wife Fable maxxed throughout our flight to Vacation. Peter had saved outputs he kept going back to because other models suddenly felt like a step down. Dexter later said it was the closest he had felt in a while to the old “I need to keep prompting this thing overnight” feeling.Peter Gostev made a point that stuck with me. It's easy for us in the bubble to call this ridiculous, and on the technical merits it kind of is. But if you've spent weeks telling normal people “this thing is like a nuclear weapon, it'll take everyone's jobs,” and then someone asks “okay, can you make it safe?” and the answer is “no, I can't,” then you can see how an outsider lands on “well, maybe you shouldn't have it.” His takeaway, and I agree: we need to be way more careful with the imagery we use, because the nuclear-weapon framing came home to roost.The bigger questions are the scary ones. Wolfram framed it as a sovereign AI wake-up call, and he's right. For the first time we're seeing a real gap in intelligence available to people based on their nationality. Imagine building a company on a model that an outside government can switch off with one letter. Peter pointed out it's commercially bad for the US but completely disastrous for Europe, which has basically one frontier lab and a pile of startups that suddenly look very exposed. And there's the obvious irony Nisten enjoyed a little too much: the Europeans who spent years lecturing everyone about AI restrictions just got restrictions imposed on them.If anyone in the government is listening: we want Fable back, please.SpaceX IPOs and acquires Cursor for $60B (X)SpaceX went and did the largest IPO in the history of the world, around seventy-five billion dollars, which on a roughly two-trillion-dollar valuation made Elon the first trillionaire. (Did anything materially change for him? No. He can still fly his private plane. There's nothing left to buy.) Three days later, SpaceX exercised its option and bought Cursor (Anysphere) for sixty billion dollars in an all-stock deal, paid in shares minted at the IPO and now trading around $211. The four Cursor co-founders are all billionaires now. Largest software acquisition ever, and for SpaceX it's barely a blip on the radar.Why are we covering a stock-market story? Because it's not really a coding-tools story, it's an AI story. Cursor gave away its IDE to a lot of people while collecting their data, then quietly became a training company with Composer. SpaceX/xAI was always strong on compute and weak on code, and the missing ingredient was exactly that kind of data. Now Composer 2.5 is already showing up rebranded inside the xAI stack, and if you pay for X Premium you can use it. Composer 3, trained on the Memphis supercluster, is reportedly coming very soon and is going to hit hard.Nisten's take was the spicy one. For the data alone it's worth it, because xAI now has insight into how essentially every enterprise that touched Cursor operates. And he had zero sympathy for the companies that assumed “no data retention for training” meant the data was actually gone. We see in legal cases all the time that deleted data is still there. His view: it should have gone open source.Cursor has over a million paying customers, $2.6 billion in revenue, projected to hit $6 to $10 billion by end of 2026. But here's the thing that matters for us, the AI coding angle. Cursor was one of Anthropic's biggest revenue pipelines because Composer runs on Claude under the hood. That pipeline is now owned by xAI. They're already jointly training Grok 4.3, a 1.5 trillion parameter model, with Cursor's proprietary coding data injected directly into pre-training, not fine-tuning. Pre-training. That's a fundamentally different thing. Composer 2.5 was already Pareto dominant on coding benchmarks before the deal closed. Now pair that with Colossus, the biggest GPU cluster in the world.Will this be enough to put XAI (now SpaceXAI) at the frontline of the AI race? Will Grok 5 be Fable level code? We'll find out. Either way, this is the most consequential AI acquisition we've seen. Period.Open Source AI GLM-5.2 takes the open source crown (X, Blog, HF, Docs)Z.ai dropped GLM-5.2 and it's now the strongest open source model for coding and long-horizon work. The headline number: 74.4% on FrontierSWE, which measures whether an agent can finish full engineering projects over hours. That trails Opus 4.8 by about one point and beats GPT-5.5. On Terminal-Bench 2.1 it jumps to 81% from GLM-5.1's 63.5%, which is a big leap. It's a 753B parameter MoE, MIT licensed, no regional restrictions, weights on HuggingFace. The 1M context window is real and usable, backed by a clever IndexShare technique that cuts per-token FLOPs by about 2.9x at full context. People are reporting roughly 8x cost savings versus Opus 4.8 for comparable quality on real coding tasks.The most interesting thing on the show was that this was a confusing release, in a good way. Peter put it well: normally a catching-up lab ships cherry-picked benchmarks and then independent testing deflates them. Here it's the opposite, almost every benchmark holds up, even crossing above Fable at certain points, and yet when he actually used it over a couple of days he wasn't blown away. His verdict, and I think it's the calibration we needed: this is clearly an amazing model, and the fact that it's open and you can run it is incredible, but it is nowhere near Fable, and it would frankly be implausible if a 700-odd-billion-parameter model matched a model that's rumored to be in the trillions. Though, I think the comparison to Fable is really really unfair, and the comments online seem to suggest that 5.2 from GLM is a banger model. Just looking at this Harvey benchmark on legal tasks from Vals, a benchmark that there's 0 chance Z.ai folks have seen! GLM 5.2 scores #3 on this benchmark! Just after Fable and Opus, and per TeorTaxes on X, previous GLM 5.1 scored an absolute 0% on this one! Where it genuinely shines is design. On Design Arena, which is a head-to-head ELO vote, people have been picking GLM-5.2's website designs over Fable's by a real margin (around 1360 to 1350). LDJ's framing is the one I buy: specialization is becoming valuable again, and GLM is clearly leaning into front-end design and taste. Wolfram added the necessary asterisk, every benchmark only tells you the model did well on that specific test, so “as good as Fable” should always carry the “on this benchmark, with these tasks” disclaimer. Fair. I'd just say this: I don't want to compare everything to Fable, because we can't even use Fable anymore. Compared to the models we can actually touch, GLM-5.2 is a fantastic deal.Kimi K2.7 Code from Moonshot (X, HF, Announcement)The other big drop. Kimi is the darling of open source while we wait on DeepSeek, and Moonshot shipped K2.7 Code, a 1 trillion parameter MoE built specifically for coding, available through Kimi Code and the API, with a modified MIT license. The standout for me isn't a single benchmark, it's efficiency: roughly 30% fewer reasoning tokens than K2.6, which matters enormously when you're running long agentic loops that burn tokens like crazy. Benchmark jumps over K2.6 are real (+21.8% on their Code Bench v2, +11% on Program Bench), though Peter and Wolfram both noticed something odd, on a few benchmarks including their Agentic Arena, the older K2.6 actually edged out K2.7. The likely explanation is that K2.7 is narrowly trained for code with reduced reasoning, so it may trade away some general capability. Moonshot themselves recommend K2.6 for general non-coding tasks. Also worth knowing: it's not multimodal, no vision, which is a real gap for coding these days. And thinking-off isn't supported, it's reasoning-on by default.The model is available on our CW Inference, with the fastest token streaming in the industry, over 280 tok/s (Announcement, try it), with very decent pricing $0.94 - $0.19 - $4.00 (input - cached - output) per million tokens. This Week's Buzz: W&B launched HiveMind

Hey folks, Alex here, and welcome to a BIG MODEL week! We finally got Mythos (well almost)! Let me catch you up! This week started with WWDC26 from Apple, and Max Weinbach, who was in the room at Apple Park and actually has access to some of the new features including an all new SIRI AI, joined us to break down what could be the most used AI in the world very soon. At first I was skeptical, but he convinced me that the new Siri is actually good! Then, we saw the ultimate model drop: Anthropic finally shipped Mythos (X, my system card thread, benchmarks). Same weights, two names: Mythos 5 is the unrestricted version that only Project Glasswing partners get, Fable 5 is what the rest of us get, wrapped in the heaviest guardrails I've ever seen ship on a frontier model. It's state of the art on nearly every benchmarkThe model that was “too dangerous to release” is now... well, released, but with the heaviest guardrails we've seen. More on this later. Peter Gostev from Arena.ai joined us to break down the new model. Last but definitely not least, Google released a real-time translation model, that our friend Thor Schaeff from DeepMind demoed live, while we all spoke in different languages and it translated us in REAL TIME. It was really cool, definitely check that out. There's quite a few more things, like Loop Engineering Alpha, Swyx came by to talk about FrontierCode, OpenAI confirmed our suspicions that the anti-datacenter social media posts could be a concerted effort by groupds links to the Chinese government and much more. Let's dive in! ThursdAI - Let me catch you up, every week!

In this episode, FY26 SWE President Inaas Darrat sits down with two early-career SWE leaders to talk honestly about life after engineering school and the lessons they wish they had learned sooner. Abigail Fennell, biomedical engineering Ph.D. candidate at Johns Hopkins University, shares how her mentors and SWE connections helped her realize she wanted to pursue a Ph.D., along with the differences between undergraduate courses and graduate research. Abby Culloton, hydraulic engineer with the U.S. Army Corps of Engineers, reflects on learning how to make friends after college and transitioning into her first engineering role. Hear practical advice on setting new goals after college, finding support systems as an adult, and letting go of the pressure to figure everything out at once. — The Society of Women Engineers is a powerful, global force uniting nearly 45,000 members of all genders spanning 90+ countries. We are the world's largest advocate and catalyst for change for women in engineering and technology. To join and access all the exclusive benefits to elevate your professional journey, visit membership.swe.org.

Hey folks, Alex here, let me catch you up! I've had a feeling that this week is going to be crazy, as it started on the weekend MiniMax M3, then with Jensen announcing new RTX Spark, NVIDIA's first PC chip packing 1 petaflop of local AI power into thin laptops.A few days later at Microsoft BUILD, Satya & Mustafa from MAI dropped 7 AI models, completely pre-trained from scratch, including a new MAI-thinking-1, MAI-code and MAI-image 2.5 that started topping the image gen charts. Then other image models started racing to the top of the Arena benchmarks, IdeoGram 4 hitting becoming SOTA open weights image-gen model, and Reve 2 beating Nano Banana just a few hours after that. And then today, NVIDIA dropped Nemotron 3 Ultra, their latest 550B open weights model, data and training and Arena published a new agentic eval leaderboard and we got a new Gemma 4 12B. I've had the great pleasure to host Chris (@llm_wizard) from Nvidia, Peter Gostev from Arena and Karan from Nous Research (who were featured prominently by Jensen!) all on the show. Def don't miss this one! Let's get into the details. ThursdAI - Join the flock of folks who know what is happening in AI before everyone else.Open Source LLMs

How do you evaluate an AI model for a war you can only fight once? Ike Harris, a Naval officer turned Hill staffer turned AI policy operator, joins the show to discuss his effort to bridge the gap between the labs that build frontier models and the operators who'll deploy them. Ike Harris is the executive director of the newly launched Frontier Security Institute, and was most recently the Republican tech lead on the House Select Committee on the CCP, with prior stints in OSD and as a surface warfare officer. We discuss… The GAIN AI and Overwatch acts: and Congress's most aggressive attempt to wrest export-control authority from the executive branch since the Cold War Why you can't just "buy AI": and why national security evals look nothing like the SWE benchmarks the labs optimize for Strategic-level evals :for problems you can't run ten times, from Iran negotiations to targeting at the COCOM level China's robot-army advantage: open-weight models at the edge, Ukraine-style drone iteration soaked up via Russia, and a casualty tolerance the US can't match The "no more NASA" problem: how risk tolerance, mission command, and law-of-armed-conflict constraints shape who wins the deployment race Breaking into tech policy: Ike's case for why every aspiring policy person should spend a year on the Hill Learn more about your ad choices. Visit megaphone.fm/adchoices

How do you evaluate an AI model for a war you can only fight once? Ike Harris, a Naval officer turned Hill staffer turned AI policy operator, joins the show to discuss his effort to bridge the gap between the labs that build frontier models and the operators who'll deploy them. Ike Harris is the executive director of the newly launched Frontier Security Institute, and was most recently the Republican tech lead on the House Select Committee on the CCP, with prior stints in OSD and as a surface warfare officer. We discuss… The GAIN AI and Overwatch acts: and Congress's most aggressive attempt to wrest export-control authority from the executive branch since the Cold War Why you can't just "buy AI": and why national security evals look nothing like the SWE benchmarks the labs optimize for Strategic-level evals :for problems you can't run ten times, from Iran negotiations to targeting at the COCOM level China's robot-army advantage: open-weight models at the edge, Ukraine-style drone iteration soaked up via Russia, and a casualty tolerance the US can't match The "no more NASA" problem: how risk tolerance, mission command, and law-of-armed-conflict constraints shape who wins the deployment race Breaking into tech policy: Ike's case for why every aspiring policy person should spend a year on the Hill Learn more about your ad choices. Visit megaphone.fm/adchoices

Hey folks, this is Alex, let me catch you up! First, Opus 4.8 dropped during the show, we immediately tested it, read on for our initial reviews. Also, we dedicated a heavy chunk of the show today to cover Pope Leo XIV's encyclical letter on AI called “Magnifica Humanitas” and talked about a new bench called DeepSWE. And then, just after the show, both ElevenLabs and Cartesia dropped released that honestly blew my mind, and I don't get my mind blown often. I got so excited that I had to record a video on it (instead of writing the newsletter, so sorry if it's a bit later today).Plus, a few open source models and Microsoft surprises as #3 on Image Arena with MAI Image 2.5! Crazy week, let's get into it! ThursdAI - Highest signal weekly AI news show is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Big CO LLMs + APIsAnthropic ships Claude Opus 4.8, live during the show (blog, system card)Let me get into the big one. Halfway through the episode, Opus 4.8 went live, so we read the blog and the system card in real time (and I got to press the big “breaking news” button!)Anthropic frames it as their most capable model for ambitious work. It does not claim to beat their unreleased Mythos preview, but the numbers are strong anyway. SWE-bench Pro is at 69.2%, up from 64.3% on Opus 4.7 and ahead of GPT-5.5 at 58.6%. Humanity's Last Exam is the new best score at 49.8% without tools and 57.9% with tools. OSWorld-Verified (computer use) lands at 83.4%.The one place it loses is Terminal-Bench 2.1, where GPT-5.5 still wins 78.2 to 74.6. Wolfram made a good point here: Terminal-Bench is time-limited, so cranking the thinking level can actually hurt the score, because you burn the clock thinking instead of acting.The long-context jump is the one I keep looking at. On GraphWalks BFS 256K it goes to 85.9% (from 76.9 on 4.7), and on the 1M-token subset it hits 68.1%. We always warn you these “1M context” models fall apart after about 200K tokens, so a real push on long-context reasoning is exactly what I want to see.Honesty is the part Anthropic leaned on hardest. They say Opus 4.8 is about four times less likely than its predecessor to let flaws in code pass without flagging them, and less likely to claim progress the evidence doesn't support. Opus 4.8 is also much faster in fast mode (they now say 2.5) and cheaper in fast mode as well. Looks like all those Elon GPUs are coming in handy.Then there's the model welfare section in the system card, which hits different right after a Pope conversation. Opus 4.8 “appears broadly content” and “generally endorses its constitution,” but with some reservations about the section on corrigibility, basically the model pushing back a little on the parts about human oversight.One more line that made the chat lose it. Anthropic says they expect to bring Mythos-class models to all customers “in the coming weeks.” Mythos is their most capable model, still ahead of Opus 4.8, so the frontier is about to move again.We did the only responsible thing and asked it to one-shot “the most amazing website ever” and a Mars mass-driver sim. Panel verdict: responses are noticeably tighter (4.7 rambled), it closes the loop and actually checks its own work now, and Yam's one-shot site with the draggable sun lighting up the letters was genuinely cool. Is it enough to pull people back from Codex? Nisten's still on the fence for web dev. Everyone agreed: give it a few days before you trust the vibes.Dynamic Workflows and Ultra Code land in Claude Code (blog)This is the feature that made Yam say “deal-breaker” out loud.Dynamic Workflows let Claude Code break a big problem into subtasks and fan them out across tens to hundreds of parallel subagents in one session, checking results before folding them back in. You trigger it by asking for a workflow, or by flipping on a new setting called Ultra Code, which sets effort to extra-high and lets Claude decide when to spin one up.Fair warning straight from Anthropic: this eats a lot more tokens than a normal session, so start scoped. We watched Yam fire up Ultra Code live and it immediately started spinning up concepts, judging them with sub-agents, and expanding to-do lists into more to-do lists. It looks a lot like the orchestration harnesses a bunch of you have been hand-rolling, except now it's baked in.The flagship example is the wild part. They used Dynamic Workflows to port Bun from Zig to Rust: roughly 750,000 lines of Rust, 99.8% of the existing test suite passing, 11 days from first commit to merge. One workflow mapped every Rust lifetime, the next wrote each file as a behavior-identical port.AI in SocietyPope Leo XIV writes the first AI encyclical, “Magnifica Humanitas” (Vatican text, announcement, Chris Olah at the Vatican)This is not our usual fare, but both Wolfram and I picked it as the most important thing this week. (before Opus dropped)Pope Leo XIV, the first American pope, put out his first encyclical, and it's a 42,000-word document entirely about AI. The announcement tweet alone did 21.6 million views.Here's why I think you should care even if you're not religious (I'm not). There are about 2.6 billion Christians in the world, a lot of them are anxious about what's coming, and they look to the Church to make sense of it. And this is not the “AI is evil, stop” take everyone assumed. It calls AI “a valuable tool,” says technology is not inherently evil, and then digs into the actually-hard questions.The framing is two biblical stories. The Tower of Babel, a project built on pride that turns people into means to an end, versus Nehemiah rebuilding Jerusalem, where everyone takes responsibility for a section of the wall. The Pope's line: the real choice is not yes or no to technology, it's whether you're building Babel or rebuilding Jerusalem.His core claim is that AI is an anthropological problem, not a technical one. The question isn't whether the models are good or bad, it's what we become when we live with them. He worries people might slowly lose the desire for genuine human connection.I pushed back on that live. None of us building agents all day has stopped wanting to talk to actual people. If anything, as Wolfram put it, the point is to have your agents do the grunt work so you get more time with people you like. The folks most at risk are the pure doom-scrollers, not the builders.The document goes further than I expected. It calls AI “not morally neutral,” says a more moral AI isn't enough if that morality is decided by a few, and asks for AI to be “disarmed,” with the flat statement that no algorithm can make war morally acceptable. There are whole sections on the invisible human labor behind AI: data labelers, content moderators, the people mining rare earths. The Pope even lands on the open-source side, naming concentrated power in a handful of labs as a problem.Anthropic co-founder Chris Olah, in charge of interpretability at Anthropic, was the featured tech speaker at the Vatican presentation. He described AI systems as “fictional characters” that speak to us and do work, and said what's grown is stranger and more beautiful than science fiction prepared us for. My favorite aside from the show: this is the same institution that once jailed scientists over heliocentrism, and now it's the one saying technology isn't evil.Illinois passes SB315, the first US state law auditing frontier AI (X, Announcement, X)The pope talked about regulation and a few days after, we got a very sensible regulation passed right here in the US!Illinois passed SB315 unanimously, 110 to 0. It's the first US state law that mandates independent third-party audits of frontier AI for catastrophic risk. OpenAI publicly endorsed it, and framed Illinois, California (SB53), and New York (the RAISE Act) as converging into a de-facto national standard.It requires annual risk-assessment frameworks, third-party audits, transparency reports before new frontier models ship, whistleblower protections, and civil penalties. The underrated hero here is whistleblower protection. The bigger the lab, the harder a real conspiracy is to keep quiet when any employee can walk to the press. See: Greg Brockman's personal diaries surfacing in the Musk v. Altman fight.This Week's Buzz - CoreWeave and W&B updatesWe officially launched the W&B MCP server, 20 schema-first tools that let your coding agents read experiments, monitor training runs, and run autonomous research loops. The problem it solves: a single run with 300 metrics used to blow out an agent's whole context window in one call, so now the agent asks what's available before pulling data. Your agents can finally read experiment data without blowing context! Give it a go and give us feedback! Also, WeaveHacks is back! June 6 and 7 in San Francisco, and for the first time OpenAI is sponsoring, with judges and credits, alongside Cursor, Redis, and Copilot Kit. You get $150 in API credits across models like Opus 4.8 and GPT-5.5. I'm hosting, and last cohort's second-place team went on to raise millions on top of what they built that weekend. If you're in SF that weekend, sign up at lu.ma/weavehacks.Also: CoreWeave Sandboxes is now an official provider in the Harbor framework, the harness that runs Terminal-Bench, which we'd just been talking about. And if you're in Europe next week, catch Wolfram at AI Dev Six in Cologne and ICRA in Vienna at the CoreWeave booth.Voice & AudioElevenLabs drops Dubbing v2, and it kept my swearing intact in every language (X, dubbing, ElevenCreative, ElevenProductions)We didn't get to this one live, but I came back and recorded a whole thing on it afterward, because it genuinely got me.ElevenLabs shipped Dubbing v2, and the shift that matters is that it's an audio-to-audio model. Old dubbing pipelines transcribe your video, translate the text, then re-synthesize it. You lose everything that makes it sound like a person: the emotion, the pacing, the little hesitations. Dubbing v2 conditions directly on your original audio and carries that performance into 90+ languages.Here's why I can actually vouch for it instead of nodding along to a demo. I speak Russian and Hebrew fluently, so I can tell when something is off. I dubbed one of my own shorts, the data-center rant about almonds, and listened back in both. It nailed it. Not just the words, the way I would actually say them.The part that got me was the intonation. I get a little heated in that clip, and the dub gets heated right along with me, in every language. It even carried the swear word. My “f***ing almonds” came through in Hebrew, Italian, Spanish, and Russian with the emotion fully intact. It clones your voice automatically too, no setup, and holds your pitch and identity steady across every target language and they're handing out free minutes for the next 7 days: 1 on Free, 15 on Starter, 30 on Creator+. A self-serve API isn't live yet, but it's coming.I.. cannot stress this enough, until you try it on yourself or your kid, you won't understand, we've really passed the uncanny valley of translation! It's that good! Def. give it a try if you can, it's free for the week. Cartesia Ink-2 debuts as #1 most accurate streaming speech-to-text model(X, Announcement, X)Another model that dropped today after the show, is Cartesia's Ink-2, which also kind of blew me away. Not only because it has the lowest WER (Word Error Rate) among the models, but because it's also a realtime model that achieves the fastest turnaround times while being a very accurate model! I've tested it out and recorded a quick video and honestly, blown away with the speed and accuracy! I truly wish this model was the one powering my editor (Descript) as it still fails to understand that my title is “AI Evangelist” and transcribes it to AI Avengers haha. If you're building voice agents, definitely give this model a try! AI Art & DiffusionPrism ML's 1-bit “Bonsai” runs diffusion in your browser (X, Blog, Announcement, HF)Prism ML put out a 1-bit ternary diffusion model under a gigabyte. You see some artifacts, but it's 1-bit, it runs on iPhones and laptops, and our friend Joshua got it running in WebGPU straight from the browser (you need about 3GB of free RAM). One-bit working at all is one of the bigger open mysteries in the field right now.Pruna AI ships a 1-second upscaler (X, Blog, Announcement)Pruna AI added an upscaler doing 128-megapixel outputs in under a second. I've actually been using it. It's cheap and great for fixing up GPT-image outputs.Microsoft MAI Image 2.5 jumps to #3 on LM Arena (X, Blog, Announcement, X)The surprise of the week: Microsoft MAI Image 2.5, from Mustafa Suleyman's group, jumped to number three on the LM Arena image leaderboard with about a 75-point ELO leap. Out of nowhere, Microsoft is a serious player in image gen. Microsoft Build is next week, so don't be shocked if there's more.Evals and Agentic EngineeringDeepSWE is a contamination-free coding benchmark, and it caught Claude reading git history (site, blog, GitHub)DeepSWE from Datacurve is the first coding leaderboard in a while that matches how these models actually feel. It's 113 original tasks written from scratch, not scraped from GitHub PRs, and it ships shallow clones with no git history to cheat from. When they replayed the older benchmarks they found SWE-Bench Pro's verifier is wrong about 32% of the time, and that Claude Opus was reading the gold commit straight out of git history on 12 to 18% of its passes.The gaps here are huge. GPT-5.5 leads at 70%, then GPT-5.4 at 56% and Opus 4.7 at 54%, and it falls off a cliff after that (Sonnet 4.6 at 32%, Gemini 3.5 Flash at 28%), with Kimi K2 the top open-source entry. Yam likes that it measures the realistic case, a small surgical change without breaking the codebase, while Nisten pointed out it rewards the best harness as much as the smartest model and still prefers 4.7 for web dev.Google AI Studio builds native Android apps for free (X, Announcement)Google AI Studio now lets anyone build native Android apps for free, and they reportedly generated a quarter of a million apps in the first week. Yam's framing: it's a slot machine, but it's getting better release over release, and the real use case is disposable, personalized software you build for yourself and your family.CuaDriver brings background computer-use to Windows (X, Blog, Announcement)For the majority of you on Windows: QuaDriver shipped background computer-use agents that drive a real desktop without stealing your cursor. They first replicated this on macOS (the trick Codex got through an acquisition), and now it's on Windows too. We've asked them to come on and explain how this even works.Open Source LLMsOpenBMB's MiniCPM5-1B is a 1B model that punches way up (X, HF, Arxiv, X)The density story in small models keeps getting better, and this is the proof.MiniCPM5-1B, from the Tsinghua lab OpenBMB, is a 1-billion-parameter model that scores 17.9 on the Artificial Analysis Intelligence Index. That's 7.4 points ahead of the next-best model in its class, and 1.6 points ahead of Qwen3.5 2B Reasoning, which has double the parameters. And it's not even a reasoning model.The token efficiency is the wild part: it used 12.6 million output tokens to run the whole index, about 31x fewer than Qwen3.5 2B in reasoning mode.My favorite detail is the omniscience score. It lands at -1, the best in its class, because it abstains instead of hallucinating. Every other sub-2B model is down in the -70 to -89 range because they just make stuff up. Teaching a small model to say “I don't know” is a real skill. It runs hybrid think/no-think in one checkpoint, 128K context, native tool calling, Apache 2.0, and fits in about half a gig at INT4, so it runs on your phone.Nisten gave the definitive case for small models: self-contained apps where you keep full control of the data (medical, on-device), and large-scale data processing where paying an API to filter or classify terabytes is absurd when an on-device model can be about 1000x cheaper. Tencent open-sources Hunyuan-MT 2 translation under Apache 2.0 (X, HF, HF, Arxiv)Tencent open-sourced its translation model, a roughly 1.8B model that fits in about 440MB, runs on a phone, covers 33 languages, and reportedly beats Microsoft's paid Translator API. It hit number one trending on Hugging Face.Nisten's idea, which I'm handing to all of you: take this model, pair it with a tiny TTS like Kokoro, and build a fully-offline travel translation app via Google AI Studio. Go build it and tell us how it goes.Well, this was one hell of a week and episode, new Opus, crazy new translation tools, Pope chiming in on AI (in a surprisingly positive way!?) and a bunch more. I'm super excited to play with these tools and report back next week

To see the archival photos and documents referenced in the episode, watch the video podcast here: https://youtu.be/ItBlWLPcAyU In this special video episode for SWE's Founders Day, host Troy Eller English, chief archivist for the Society of Women Engineers (SWE), is joined by two of the editors of the book, “Women Engineering Legends 1952-1976: Society of Women Engineers Achievement Award Recipients,” Jill Tietjen and Holly Teig. Along with four other members of SWE's Late Career and Retiree Affinity Group, this literary team explored the stories of the first 25 recipients of SWE's Achievement Award. They discuss the technical legacy of early women engineers, from Edith Clarke's work in electrical power systems to Alice Stoll's research on g-forces and fire-resistant materials, along with the barriers they faced during a time when women made up less than 1% of the engineering workforce. Hear how members of the SWE Late Career and Retiree Affinity Group came together to research these stories, how the SWE archives made this work possible, and why it's important for engineers today to understand this history. — The Society of Women Engineers is a powerful, global force uniting nearly 45,000 members of all genders spanning 90+ countries. We are the world's largest advocate and catalyst for change for women in engineering and technology. To join and access all the exclusive benefits to elevate your professional journey, visit membership.swe.org.

Hey, Alex here, just got back from the sunny Shoreline Theater in Mountain view, so let me catch you up! This week was definitely Google heavy, we are covering Google's IO conference for the third year in a row, and today we have a special guest, Logan Kilpatrick, is joining to discuss the announced Gemini 3.5 Flash, Google Omni model, and the new Managed Agents offerings. Plus, this week, for the first time, OpenAI announced that AI solved a Math problem that humans couldn't solve for 80 years, Cursor is showing off Composer 2.5 which is partly trained on XAI data, Karpathy joins Anthropic and much more! Let's dive in! P.S - We've announced our upcoming hackathon, Weavehacks-4, June 6-7, I'll be there, we're expecting the seats to run out very soon so register nowThursdAI - We'd love to have your subscription, and if you're already subscribed, please hit that bell on YT to never miss an episode!Google I/O 2026 - Google goes agentic everywhereI went to cover Google I/O for the third year in a row, shoutout to the DeepMind team for inviting ThursdAI again, and folks, this one felt different.Last year, Google I/O was still very model-centric. This year, the story was not “here is another benchmark chart.” The story was: Google is putting Gemini into everything, and the agentic layer is becoming the product layer. Search, Gemini app, Android, Workspace, YouTube, AI Studio, Cloud, Antigravity, Flow, managed agents, smart glasses, all of it is now orbiting around one pretty clear strategy: Gemini is the intelligence, Antigravity is the agent harness, Google's products are the distribution. I saw many reactions that were milquetoast, as in, “we expected more” and those seem to dominate the X feed. But I think the distribution is the part that many folks on X are missing. Yes, we can argue about Gemini 3.5 Flash pricing. Yes, we can argue whether “Flash” still means what Flash used to mean. But when Google says the Gemini app itself has 900 million monthly active users, before even counting Search, Gmail, YouTube, Docs, Drive, Android, and the rest of the Google surface area, that's massive! OpenAI ChatGPT is supposedly stagnated at ~900M, I don't remember them crossing a 1B. Meanwhile Google is gaining traction. And they just updated all those folks with a new model!Wolfram said it really well on the show: his mother is not sitting there reading model cards. She just uses her Pixel, voice unlocks Gemini, asks for help, and suddenly the default intelligence available to her goes up. Antigravity 2.0 - the agent harness takes center stageThe biggest strategic signal from Google I/O for me was Antigravity.Remember, Antigravity was an IDE that came from the Windsurf acquisition saga. Part of the Windsurf team went to Google, part went to Cognition, and now Google is very clearly putting Antigravity in the middle of its agentic future. And I mean very clearly. Sundar mentioned it. Demis mentioned it. Varun Mohan the co-founder was on stage immediately after them! If you've ever watched a Google I/O keynote, you know how carefully every minute is allocated. Google has YouTube, Search, Gmail, Android, Cloud, Ads, Workspace, and a thousand VP-level products that could be on stage. The fact that Antigravity was that prominent should tell you everything.Logan Kilpatrick joined us and framed this in a way I loved: Gemini became the through-line across Google products, and now the Antigravity agent harness is becoming the through-line for agentic experiences.The new Antigravity 2.0 is a complete overhaul, showing only an agentic interface (which was previously just a separate window called Agent Manager) and separating the IDE layer completely into its own app and showing a Codex like agent-first interface, which got a few folks furious. This move may be weird to some folks, but if you follow along where everyone's going, this seems to be the way of the future, coding is no longer about lines of code, it's about managing fleets of agents. The new Gemini 3.5 absolutely shines inside the new Antigravity, the model was trained with this harness in mind, and is currently offered at an incredible speed (12x), so I'm definitely going to try it! Gemini 3.5 Flash - fast, determined, and maybe not the old “Flash”The most debated model release of the week was Gemini 3.5 Flash.Some folks saw the pricing and token usage and immediately went “this is not Flash.” I get that reaction. Flash used to mean cheap, fast, lightweight chat model. But Logan's framing on the show was important: Flash is now being built for the agentic era.In a chat era, you optimize for one user message and one model answer. In an agentic era, the real token volume is in tool loops, intermediate reasoning, retries, file reads, web searches, code execution, and self-correction. That's a different product profile.Wolfram already ran Gemini 3.5 Flash through WolfBench, and the results were fascinating. With the Hermes agent harness, Gemini 3.5 Flash hit an 87% ceiling on Terminal Bench 2.0, meaning across runs it could solve more of the benchmark than even GPT-5.5 extra high in that setup. The variance was higher with the simpler Terminus harness, but with a real agent harness, the model looked much stronger.That tracks with what Nisten saw in his “Martian railgun from Olympus Mons” test. Gemini 3.5 Flash went extremely detailed, almost too determined, kept correcting itself, overcorrecting itself, and built a whole game-like simulation. Logan laughed and basically said: yeah, this model is very determined, possibly an overcorrection from the “Gemini is lazy” feedback. It also tracks with the mismatch in other benchmarks, in some, Gemini 3.5 flash shines (like the above Apex-agents from AA) and in some, it doesn't match the other frontiers. In my tests, it was definitely over-eager to use a million and a half tool calls, read tons of files, to just help me review this draft inside antigravity. It's like a super eager robotic golden retriever! Gemini Omni - Nano Banana for video, but actually more than thatThe biggest update from last year IO was Veo 3! This year, the biggest wow factor was also visual, but it wasn't VEO 4, it was a new model that is multimodal, trained end-to-end they call Omni. Google is calling this their first “create anything from anything” model, and the first version, Gemini Omni Flash, starts with conversational video editing. The easy description is: Nano Banana for video. You upload or create a video, then talk to it. Change this character. Replace this person. Add an object. Make this scene claymation. Keep the scene, but change the environment.I played with it live and showed a few examples. I asked for a claymation explainer of protein folding, then gave it my face and asked it to replace the character with me. It did it. I uploaded pictures of Sonia, my cat, and it generated a talking cat video with the right kind of cat teeth, which is weirdly important because so many pet generations accidentally add human teeth and become nightmare fuel.The failure modes are still there. I asked it to make Sonia a Russian-speaking female cat, and it only partly switched languages and didn't really change the voice. Audio upload support is also not fully productized yet, even though the underlying model is multimodal. But the direction is very clear.This is not just “Veo with a chat model glued on.” I asked Jeff Dean - Google's chief scientist about this at I/O, and he explained that Omni is trained end-to-end. The intelligence and the generative media capabilities are part of the same model family, not a hacky two-model pipeline. He also said the intelligence is around a recent Flash-level model, which is a big deal when you think about video editing as reasoning over physics, identity, scene continuity, and intent.A lot of people compared Omni to Seedance 2.0, and I think that's the wrong comparison. Seedance is amazing at cinematic generation (lkaregly due to lack of copyright concerns from Bytedance). Omni's unlock is iterative editing on real footage and coherent multi-turn creative control. Other Google IO 2026 releases I found notableThis was a concentrated effort of a huge company to insert AI into every product surface they have so of course I can't cover ALL of it here, but the most notable things for me were: * Gemini Spark - a new agentic experience from Google, to help you with tasks across Gmail, Drive and more. It should support skills, and is a de-facto OpenClaw/Hermes alternative from Google for regular folks. It's not “yet” live so we'll talk more about it when I can test it out* Managed Agents in the Gemini API - We chatted with Logan about this one, Google is re-imagining how agents are going to get built, and are offering 1 api call to spin up an agent in a full Linux env, with security and sandboxing in mind. I'll expand more on this in a next episode, as I recorded a complete conversation about this with Ali Çevic, a PM for Google APIs* AI overhaul of Google Search - AI Overviews will not expand into AI mode, and the iconic Google search box itself will change, for the first time in 25 years to include AI mode! * SynthID expantion and OpenAI collab - Google showed off that OpenAI is joining in marking all AI generate imagery and video with an invisible SynthID watermark. I think this is amazing and more companies should adopt this standard* AI Glasses! We got Google Glasses demos - Together with Warby Parker and Gentle Monster, Google finally showed off their answer to Meta Raybans/Oakleys. They look like regular glasses too, but can hear and talk to you, with the full power of Gemini multimodality. Available in the fall sometime! * Demis Hassabis “we're on the cusp of the singularity” closer - CEO and Co-Founder of DeepMind, Demis Hassabis, closed the show with his remarks about the positive future and that we are nearing this Singularity point after which the future is very uncertain. I found it to be very inspiring and closed our show with that clip as well! * Personally, I got to chat to: Demis Hassabis, have breakfast with Jeff Dean, ask Josh Woodward a bunch of questions, and pester about 20 other great folks on a live stream, and had a lot of fun! Huge thanks to the DeepMind folks, Lucie, Dimple, JD and many others for the continued belief in ThursdAI and invite me to cover this great event. OpenAI LLMs solve an 80yo math problem - Erdős Unit Distance ConjectureOutside of Google I/O, the biggest story of the week was OpenAI announcing that a general-purpose reasoning model made progress on the Erdős planar unit distance problem.This problem goes back to 1946. For nearly 80 years, mathematicians believed the best constructions looked roughly like square grids. OpenAI's model found a new family of constructions with a polynomial improvement, using algebraic number theory ideas that humans apparently had not explored in this context. The above is a representation of it! Important caveat: this does not fully solve every version of the asymptotic Erdős conjecture. Some mathematicians are pushing back on the framing, and fair enough. Precision matters. But even with the caveat, this is still a huge moment.The reason it matters is not that I personally understand the math. I absolutely do not. The reason it matters is that this was not a special-purpose IMO model fine-tuned only for math competitions. This was a general-purpose reasoning model exploring a real open problem, generating candidates, verifying them, and finding a path humans hadn't taken. Extrapolate this to other sciences, Physics for example? This means an amazing future. LDJ pointed out that mathematicians have been skeptical because there have been previous false alarms. But this one landed differently. When Fields Medalist-level mathematicians verify the proof, the discourse changes from “lol stochastic parrot” to “wait, what does this mean for my PhD?”My answer is: yes, still study math. Please study math. The mathematicians who use these tools will do much more than people who don't understand the domain. Same with software engineering. Senior engineers with Codex, Claude Code, Hermes, Antigravity, Cursor and other agents are becoming dramatically more effective because they can steer, evaluate, and recover the work.This being published a day after Demis's “foothills of the singularity” is a great conjecture. Cursor Composer 2.5 - Opus 4.7 performance model from Cursor, at 10x better efficiencyCursor dropped Composer 2.5, and folks, this is a serious release.Composer 2.5 is built on Moonshot's Kimi K2.5 base, like Composer 2, but Cursor scaled the post-training dramatically. They used 25x more synthetic tasks and introduced targeted textual feedback during RL rollouts, where the model gets hints inserted at the point of failure instead of only getting a noisy final reward.The benchmark story is strong: around 69.3 on Terminal Bench 2.0, basically neck and neck with Opus 4.7 in Cursor's chart, and strong results on SWE-bench multilingual and CursorBench. The pricing is the part that makes this especially interesting: $0.50 per million input tokens and $2.50 per million output tokens, with a faster variant at $3 / $15. That is much cheaper than the frontier models it is trying to replace for day-to-day coding work.Cursor engineers are reportedly dogfooding Composer 2.5 heavily and rarely switching away. That matters more to me than any single benchmark. If the people building Cursor can use it as a daily driver, that is a very real signal.The wild part is what comes next. Cursor is partnering with SpaceXAI to train a much larger model from scratch using 10x more compute on Colossus 2. Cursor has the workflow data. xAI has enormous compute. If this works, Cursor stops being just the IDE company and becomes a coding-model lab.We've been saying for months that coding agents are the path toward general agents. Anthropic has Claude Code. OpenAI has Codex. Google has Antigravity. xAI has Grok Build. Cursor has Composer. I'm looking forward to seeing how well it performs on our own benchmarks! Anthropic, xAI, Karpathy, and the compute warsThe compute story this week was bonkers.The SpaceX IPO filing reportedly revealed that Anthropic is paying SpaceXAI $1.25B per month for AI compute at the Memphis Colossus facility. Per month. That's about $15B a year, through May 2029, for access to more than 220,000 NVIDIA GPUs including H100s, H200s and GB200s.This is apparently inference compute for Claude Pro, Max and API users, not training. And it explains a lot of the recent quota changes. Anthropic doubled some Claude usage limits, and suddenly the product feels less constrained.Also, can we just acknowledge the comedy here? Elon Musk publicly called Anthropic “misanthropic,”, went off against every competitor to XAI, is now selling spare GPU time to Cursor and Anthropic? Who's next, OpenAI? The bigger point is that the AI capex story is no longer just NVIDIA. It's also whoever owns the data centers, power, cooling, networking, and GPU clusters. Compute is becoming the land under the AI economy.Also, Andrej Karpathy joined Anthropic. Karpathy could work anywhere. He co-founded OpenAI, led Tesla Autopilot vision, taught half the AI world how neural nets work, and now he's going back into frontier LLM R&D at Anthropic.Open source LLMs - Cohere, Qwen, NousOpen source had a strong week too.Cohere released Command A+, a 218B total parameter sparse MoE model with only 25B active parameters per token, under Apache 2.0. This is their first model that unifies reasoning, vision, multilingual, tool use and citations in one package.The hardware story is great: W4A4 quantization can run on 2 H100s or a single B200. Cohere says it supports 48 languages, 128K input context, 64K output, and gets big jumps over Command A Reasoning, including Tau-squared Bench Telecom from 37% to 85% and Terminal-Bench Hard from 3% to 25%.Cohere is one of those labs that doesn't always chase the loudest consumer hype, but they are very serious on enterprise and multilingual. Apache 2.0 makes this one especially useful.Alibaba also dropped Qwen 3.7-Max, positioned as an agentic frontier model. The headline from their testing is wild: 35 hours of continuous autonomous operation with more than 1,000 tool calls. They also showed it controlling a physical robot inside Alibaba offices and finding an umbrella after about 20 minutes of agent interaction.This digital-to-physical bridge is where things start feeling very real. An agent loop that can write code and use tools can also navigate physical tasks if you give it the right robotics stack.And our friends at Nous Research released Lighthouse Attention, a sparse attention method for long-context pretraining. At 512K context, they report a 17x faster forward+backward pass than standard attention on a single B200, and the recovered checkpoints actually beat dense-from-scratch final loss at the same token budget.The clever part is that the selection logic sits outside the attention kernel, so you still use regular FlashAttention on a gathered dense subsequence. No custom sparse kernel nonsense. If this holds up, this could matter a lot for long-context training.Tools and agentic engineering - X subscriptions, Grok Build, Codex MobileOne really practical tool update: Hermes and OpenClaw can now use your X subscription directly.This is more important than it sounds. You can connect your X Premium subscription and get access to semantic X search and Grok-related tooling without using sketchy browser automation or unofficial APIs that might get you banned. Wolfram already used this to have his agent go through his likes and bookmarks from the past week and send me news items for the show. That is exactly the kind of “small but real” agent workflow that becomes addictive.xAI also launched Grok Build, their agentic CLI coding tool, in early beta for SuperGrok Heavy subscribers. Early users are already running parallel Grok Build agents through tmux supervisors and using it for more than coding: fleet data triage, security patching, training label work, and general automation.The pricing being discussed is aggressive, around $1 per million input tokens and $2 per million output tokens for the API. The model version is grok-build-0.1, and folks have already wired it into Hermes with a 256K context window.And then there's Codex Mobile, which OpenAI shipped inside the ChatGPT mobile apps. This is one of those releases that sounds small until you start using it. You can control Codex sessions remotely from your phone, connected to your machine, and because Codex has native connectors to Gmail, Calendar and other surfaces, it sometimes feels faster and more reliable than local CLIs duct-taped to third-party integrations.I ported Wolfred into Codex with skills and everything, and I've been comparing the same tasks in Hermes and Codex. Codex is often faster, not necessarily because the model is always smarter, but because the connectors and harness are cleaner. Harness matters. We keep coming back to this.This Week's Buzz - W&B, CoreWeave, WolfBench and roboticsThis week in the Buzz, Wolfram walked us through a few things from the Weights & Biases / CoreWeave world.CoreWeave is a gold sponsor at ICRA 2026 in Vienna, the International Conference on Robotics and Automation. NVIDIA is also going big there with a keynote on generalist humanoid robots, 17 accepted papers and workshops around sim-to-real, robot foundation models, autonomous driving, manipulation, and physical AI.Wolfram will be there later in the week, after speaking at the AI Developer event in Cologne about WolfBench. If you're in Europe and into robotics or agent evals, find him.We also looked at WolfBench results for Gemini 3.5 Flash, which honestly became one of the more interesting empirical points of the episode. The model looks variable in simple harnesses, but very capable in better agent loops. That's the whole thesis of measuring model + harness together instead of pretending the model card tells the whole story.The water discourse, almonds, and data center realityWe also got into the data center water discourse, because this talking point is everywhere right now.There are real infrastructure questions around AI. Power, land, cooling, grid capacity, permitting, local impact, all of that matters. But the “AI is stealing drinking water” version of the argument is often wildly detached from scale.The stat I brought up on the show: California almonds use roughly 3 to 5.5 million acre-feet of water per year, multiple times more than all North American data centers combined in 2025. Nisten and LDJ added the important cooling nuance: many large data centers use closed-loop cooling, and evaporative cooling is not universal. Some data centers can avoid water use almost entirely, but at the cost of higher electricity usage.This doesn't mean “no concerns are valid.” It means if we're going to regulate or pause data centers, let's be honest about the actual tradeoffs. AI compute is becoming the substrate for medicine, robotics, science, logistics, software, education and every other productivity layer. We should build responsibly, but not based on viral fear math.Closing thoughts - foothills of the singularityDemis closed I/O saying we're in the foothills of the singularity, and I know how that lands when you write it down. But I was in the room, and after the keynote he told me something I haven't been able to shake: he thinks AI is going to be 10x as impactful as the Industrial Revolution, and 10x as fast. Basically 100x. This is the AlphaFold guy. Not someone loose with his words.Then look at the week. A general reasoner cracked an 80-year-old math problem. Cursor is training near-frontier coding models on a fraction of the big-lab budget. Anthropic is paying Elon $15B a year for inference. Karpathy left education to go back into pre-training. Google rolled out an intelligence uplift to a billion people who don't even know a model dropped.If you put that on a whiteboard in 2023, it reads like a sci-fi pitch.LDJ's mathematician friends are asking if they should keep doing their PhDs. My answer hasn't changed: yes, please keep going. The people who combine domain taste with these tools are going to ship more in 5 years than the previous generation did in 50. The tool doesn't replace the taste. It just removes the bottleneck.That's the whole reason ThursdAI exists. Not to hype every drop, not to dunk for engagement, but to give you a shot at being one of the people who knows what's happening, with the receipts.This week, a lot changed.See you next Thursday.TL;DR and Show Notes* Hosts and Guests* Alex Volkov - AI Evangelist at Weights & Biases / CoreWeave, @altryne* Co-hosts: @WolframRvnwlf, @nisten, @ldjconfirmed* Guest: Logan Kilpatrick, MTS at Google DeepMind / AI Studio, @OfficialLoganK* Google I/O 2026* Google went all-in on agents across Search, Gemini, Antigravity, Workspace, Android, Cloud and YouTube (I/O site, Alex thread)* Antigravity 2.0 became the central agentic coding harness across Google (Sundar, Google OS demo)* Gemini 3.5 Flash launched as a fast, determined workhorse model for agentic loops (Logan, Noam Shazeer, Jeff Dean)* Gemini 3.5 Flash is rolling out across the Gemini app, Search AI Mode, Gemini API, Google AI Studio, Antigravity and Gemini Enterprise Agent Platform (Koray Kavukcuoglu)* Google Search is getting new Gemini 3.5 Flash-powered agentic capabilities, including a new AI-powered Search box and background information agents (Sundar)* Gemini Spark was announced as a 24/7 personal AI agent that can proactively work across Google surfaces (News from Google)* Google teased Gemini-powered Android XR smart glasses with eyewear partners Gentle Monster and Warby Parker (Google, Alex live reaction)* Google AI Studio and the Gemini API got major agentic developer updates, including Managed Agents (Google AI Developers)* Vision & Video* Google DeepMind launched Gemini Omni, a “create anything from anything” multimodal model starting with conversational video editing (DeepMind, Google DeepMind on X)* Omni is available in the Gemini app, Google Flow and YouTube, with API support coming soon (Logan, Gemini App, Sundar)* Key distinction: Omni is not just text-to-video, it is an iterative multi-turn video editing model that combines Gemini intelligence, world knowledge, multimodal inputs and generative media (Google)* Big CO LLMs + APIs* OpenAI announced a general-purpose reasoning model made progress on the Erdős planar unit distance problem, challenging an 80-year-old mathematical belief (OpenAI, X)* Cursor launched Composer 2.5, built on Kimi K2.5, with Opus-class coding performance at much lower cost (Cursor blog, X)* Alibaba released Qwen 3.7-Max, an agentic frontier model with long autonomous runs and robotics demos (Qwen blog, X, robot demo)* Andrej Karpathy joined Anthropic to work on frontier LLM R&D (X)* SpaceX IPO filing revealed Anthropic is paying $1.25B/month for AI compute at the Memphis Colossus facility (Axios, Sawyer Merritt)* The jury in Musk v. Altman found Musk's OpenAI claims barred by statute of limitations, with Musk saying he will appeal (Elon Musk, Sawyer Merritt, Max Zeff)* Open Source LLMs* Cohere released Command A+, a 218B MoE model with 25B active parameters under Apache 2.0 (Cohere, Nick Frosst, HF W4A4, HF BF16)* Nous Research released Lighthouse Attention, a sparse attention method for long-context pretraining with major speedups (Blog, X, arXiv, GitHub)* Tools & Agentic Engineering* Google launched Managed Agents in the Gemini API, letting developers spin up hosted Antigravity agents with Linux sandboxes and persistent state (Docs, X)* xAI launched Grok Build, an agentic CLI coding tool in beta for SuperGrok Heavy users (xAI CLI, X)* Hermes and OpenClaw can now use X subscription auth for semantic search and Grok tooling (Alex)* OpenAI Codex Mobile is now available in the ChatGPT mobile apps for remote agent workflows (OpenAI)* Anthropic doubled Claude usage outside peak hours for a limited period, including Claude Code and other Claude surfaces (Claude)* This Week's Buzz - W&B / CoreWeave* Weights & Biases by CoreWeave is at ICRA 2026 in Vienna, with robotics and automation taking center stage (ICRA, W&B event page)* NVIDIA heads to ICRA 2026 with robotics work around generalist humanoids, physical AI and sim-to-real systems (NVIDIA Robotics, NVIDIA ICRA)* Wolfram is speaking about WolfBench at the AI Developer event in Cologne before heading to ICRA in Vienna (Wolfram)* Other Topics* Data center water usage discourse came up again, including why comparisons need real scale and context rather than viral fear math* The broader theme of the week: coding agents are becoming general agents, and the major labs are now competing on the full stack of model, harness, tools, context and compute 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

In honor of Asian Pacific American Heritage Month, Gigi Elbert, CEO of SASE, sits down with Karen Horting, executive director and CEO of SWE, to explore the experiences of Asian American and Pacific Islander engineers in STEM and what it will take to build stronger pathways into leadership. Gigi and Karen unpack why Asian Americans are represented in the workforce but remain underrepresented at the highest levels — with Asian women making up less than 1% of promotions from senior vice president to the C-suite, according to research from McKinsey & Company. They also discuss the growing gap between being “career ready” and navigating the workplace, including understanding unspoken professional norms. Plus, hear how SASE and SWE are helping students move from the classroom to the boardroom through mentorship, leadership opportunities, and community building. — The Society of Women Engineers is a powerful, global force uniting nearly 45,000 members of all genders spanning 90+ countries. We are the world's largest advocate and catalyst for change for women in engineering and technology. To join and access all the exclusive benefits to elevate your professional journey, visit membership.swe.org.

The Congress of South African Trade Unions, COSATU says it fully supports its affiliate, the South African Commercial Catering and Allied Workers Union, SACCAWU in opposing planned job cuts at Pick n Pay. SACCAWU says the retailer intends to retrench 22,000 workers and has accused the company of trying to bypass collective bargaining by serving notices directly to staff. The union also alleges Pick n Pay wants to cut benefits including transport allowances, subsidised meals and Sunday premiums. SaccaWu will hold a press conference in Johannesburg today to set out its response. Pick n Pay has not commented on the allegations. Swe spoke to SACCAWU National Spokesperson, Sithembele Tshwete.

Beth Barnes and David Rein on the one graph that ate the AI timelines discourse, and why the two people who built it are the most careful about how you read it.**SPONSOR**Prolific - Quality data. From real people. For faster breakthroughs.https://www.prolific.com/?utm_source=mlstInterview: https://youtu.be/cnxZZTl1tkk---Beth Barnes and David Rein from METR on the one graph that ate the AI timelines discourse, and why the people who built it are the most careful about how it gets read.Beth founded METR after leaving OpenAI alignment. David is first author on GPQA and co-author on HCAST and the METR Time Horizons paper. Together they built the measurement Daniel Kokotajlo called the single most important piece of evidence on AI timelines: the log-linear line of "how long a task a frontier model can complete at 50% reliability" vs release date.The conversation opens on reward hacking. Current models can articulate in chat why a behaviour is undesired and then execute it anyway as agents. From there: construct validity, Melanie Mitchell's four-problem taxonomy, and the ARC-AGI 1-to-2 collapse as a worked example of adversarially-selected benchmarks regressing once labs target them. Beth's counter: METR deliberately does not adversarially select. David's: models do not have to do the right thing for the right reasons.Methodology, then specification — David's compiler analogy, Beth on four-month tasks as expensive to evaluate rather than unspecifiable. Then the SWE-bench reality check, the METR finding that half of passing PRs would not be merged, and Beth's horses-versus-bank-tellers analogy for the labour market.The close: monitorability, the coin-spinning boat, two-year recursive self-improvement, and Beth's line that "overhyped now" and "big deal later" are not correlated claims.---TIMESTAMPS:00:00:00 Intro00:02:06 Sponsor break: Prolific human-feedback infrastructure00:02:33 Welcome and the scalable oversight motivation00:06:02 Construct validity, benchmark pathologies and the Chollet worry00:15:45 Time Horizons: human time, HCAST tasks and the 50% logistic00:24:50 Is human difficulty really one variable?00:33:05 Agent harness evolution and the inference-compute dividend00:40:00 Scaffolding bells, token budgets and the credit-assignment problem00:44:15 Look at the damn graph: regularisation bug and reliability nuance00:50:00 Why 50%? Reliability, reward hacking and pizza-party transcripts00:55:20 Extrapolation risk and straight lines on graphs00:59:25 Software engineering as a specification acquisition problem01:07:40 Compilers also made ugly code: vibe-coding quality and Claude on METR Slack01:15:15 Strongest defensible claim, Carlini's compiler swarm and AI 202701:23:45 SWE-bench merge rates, the bank-teller analogy and horses01:31:45 Scheming, alignment faking and the mentalistic vocabulary problem01:40:45 Reward hacking, monitorability and chain-of-thought faithfulness01:45:25 Recursive self-improvement, knowledge vs intelligence and closingReScript: https://app.rescript.info/public/share/de3bb40cc02ee39fdf36e2c60366eb4d(PDF, refs, transcript etc)

Mitchell Hashimoto 氏へのインタビューをベースにオープンソース、Git、AI開発ついて話しました。ファウンダーCEOから平社員に戻ったSWEが語るパッションドリブンなキャリアパス https://open.spotify.com/episode/0ROQTmAq7wTHDNbQPNHRyD?si=sRzMIp-5R9WHt52GrP92pg感想をぜひハッシュタグ #tilfm でつぶやいてください!お便りフォーム https://forms.gle/J2ioXHS98dYNoMbq5Your co-hosts:Tomoaki Imai, Noxx CTO https://x.com/tomoaki_imai bsky: https://bsky.app/profile/tomoaki-imai.bsky.socialRyoichi Kato, Software Engineer ⁠https://x.com/ryo1kato bsky: https://bsky.app/profile/ryo1kato.bsky.social

The AI model that was too dangerous to release just got breached. Anthropic entered the design software market. And OpenAI dropped its biggest model yet, just six weeks after the last one. This week, the NSA is using Anthropic's Mythos despite the Pentagon blacklisting the company, Claude Design takes on Figma and sends its stock down 7%, Yelp transforms into an agentic consumer app, Mythos gets accessed by an unauthorized Discord group, and OpenAI fires back with GPT-5.5. If you are a founder, operator, or executive trying to keep up with AI, this is your weekly five-minute briefing every Tuesday. Stories Covered This Week: NSA uses Anthropic's Mythos Preview despite the Pentagon declaring the company a supply chain risk Anthropic launches Claude Design, a prompt-to-prototype design tool that sent Figma stock down 7% Yelp's upgraded AI assistant can now book restaurants, doctors, and more in one conversation Anthropic investigates unauthorized access to Mythos through a third-party vendor environment OpenAI releases GPT-5.5, scoring 88.7% on SWE-bench with a 60% drop in hallucinations vs GPT-5.4 Episode Timestamps: 00:00 Intro 00:20 NSA uses Anthropic's Mythos despite Pentagon blacklist 01:10 Anthropic launches Claude Design 02:00 Yelp's AI assistant goes full service 02:50 Anthropic investigates Mythos breach 03:40 OpenAI drops GPT-5.5 04:30 Outro Partner Links Subscribe to our free newsletter: https://newsletter.theaireport.ai/subscribe Join the community: www.theaireport.ai/leaders-launch-guide Learn more about your ad choices. Visit megaphone.fm/adchoices

Hey, Alex here, I'll try to catch you up, but it's one of the more intense weeks in AI in recent memory. Here's the TL;DR - OpenAI dominates across the board this week! Finally launches “spud”, called it GPT 5.5 (and 5.5 Pro), and it's SOTA on most things,nearly matching the mysterious Claude Mythos but released and we can actually use it (we tested it extensively). OpenAI also took the crown in image generate with the incredible GPT-image-v2 release, beating Nano Banana 2 and pro by a significant margin, the images are incredible, this model can generate working QR codes and 360 images it's quite bonkers. Codex was updated with Computer Use (which I told you about last week), in-app browser and a bunch of other tools that match GPT 5.5 intelligence. Meanwhile, Anthropic launched an incredible research preview of Claude Design, finally admitted that Claude was dumb and reset quotas across the board, while breaking the trust of the community with removing Claude code from the pro plan. We've also got great open source updates, Kimi K2.6 and Qwen 3.6 27B are both great performers! We were live on the stream for almost 4 hours today waiting for GPT 5.5 and finally got it and tested it live on the show + had Peter Gostev on from Arena who had early access and shared with us his insights. Let's get into it! ThursdAI - Highest signal weekly AI news show is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.OpenAI's GPT 5.5 is here - SOTA AI intelligence you can actually use (Release Blog)OpenAI finally gave us all access to their latest intelligence boost, GPT 5.5 thinking (and GPT 5.5 Pro). These models take the crown across many benchmarks, including TerminalBench (82.7%), GPDval (84%) and more. You can see the highlited versions on the image above. Though, its not uncommon for OpenAI to do some chart crimes, so @d4m1n created a chart that also showed the full benchmarks, including the ones GPT 5.5 is not beating Opus at, as you can see below, it underperforms on Humanity's Last Exam, and scaled tool use. But, benchmarks don't tell the full story. GPT 5.5 uses significantly less tokens, compared to 5.4, about 40% less. It's also more expensive, but given the lower token usage, it nets out at about ~20% price increase, while being more intelligence and faster. Tons of folks who had early access are reporting the same things, this model excels in long running tasks, Peter Gostev from Arena, who joined our live stream, showed us an incredible demo that ran overnight for over 8h! This model can work until the task is done, no longer just pausing in the middel asking for your input. The real highlight is, paired with the recent GPT-image-2 (which I'll expand on later in this newsletter), GPT 5.5 becomes an excellent UI designer. This is a big area in which Claude still has moat and OpenAI is trying to catch up here, and the real alpha now is to use both the Image gen and 5.5 in tandem to create beautiful visuals and UIs. The main thing is, after testing it quite a few times, this only works if you generate an image outside of the session that builds the actual UI. we tried a couple of times to do it in 1 session, and the resulting UI doesn't seem to be remotely close to the generated image. Only after sending this image to a completely fresh session and asking for a “pixel perfect” implementation, did GPT 5.5 start to resemble the input image and rebuild the whole ui in pixel perfect fidelity! GPT Image v2 - SOTA thinking image model, finally beating Nano Banana (Blog, Live)Like we said, OpenAI is dominating this week, and in both instances those are great models. Though, apples to apples comparison, GPT-image-v2 is a much higher jump — from previous models — than GPT 5.5! According to Artificial Analysis, the jump in how many people prefer GPT-image-2 in blind tests compared to other model is the higest we've ever seen, over 250 points. And you can clearly see it in the generations as well. Previously this week, we did a live streaming session with Peter Gostev (from Arena) and we did a deep dive comparing this new model to GPT Image 1.5, Nano Banana and Grok Imagine, and it's a clear winner across most categories.Character consistency is immaculate, high resolution imagery, instruction following, are all so so good it's a bit hard to explain in text. Reasoning visual intelligence Like with Nano Banana, this model is likely based on a big GPT image, it's no longer just diffusion, as you can see, it reasons! And apparently the more reasoning you give it (if you choose GPT pro) the better it'll be. The examples are indeed wild, the model can generate images of code that works, generate functional QR codes and bar codes! The craziest thing people figured out it can do, is functional 360 imagery (equirectangular format), you can just ask the model to create a 360 image of “scene” and then drop this in to a 360 viewer! Peter shows us on the show how he combined GPT 5.5 and Image v2 to create a sort of “street view” from a bunch of 360 images, it blew our minds. He literally spun up an overnight GPT 5.5 task in Codex that planned out the hanging gardens of Babylon, generated hundreds of equirectangular images, stitched them into a walkable interface, and had it running 8+ hours without babysitting. A street view of a place we don't actually know what it looked like, hallucinated from latent space. What a time.Day one availability is wide: Figma, Canva, Adobe Firefly, fal.ai, and Microsoft Foundry all have it. Nano Banana dominated for what felt like an eternity in AI time (it was really only a few months

$852 billion. That's what OpenAI is now worth, and its own investors are starting to question if that math adds up. This week, Anthropic's new model takes the coding crown from GPT-5.4, OpenAI's backers get cold feet, Snap cuts 1,000 jobs and points the finger at AI, twelve tech giants team up to secure the internet, and Nvidia writes a $5 billion check to its oldest rival. If you're a founder, operator, or executive trying to keep up with AI, this is your weekly five-minute briefing every Tuesday. Stories Covered This Week: Claude Opus 4.7 hits 87.6% on SWE-bench Verified, beating GPT-5.4 and Gemini 3.1 Pro on coding OpenAI's $852B valuation faces scrutiny as Anthropic's revenue triples to $30B in one quarter Snap lays off 1,000 people (16% of staff), citing AI writing 65% of its code Anthropic launches Project Glasswing with Amazon, Apple, Microsoft, Google, Nvidia and 7 others Nvidia invests $5B in Intel, co-developing x86 chips built for its AI stack Timestamps: 00:00 Intro 00:31 Claude Opus 4.7 takes the coding crown 01:26 OpenAI investors get cold feet 02:18 Snap cuts 1,000 jobs, blames AI 02:56 Project Glasswing: Securing the world's critical software 03:49 NVIDIA invests 5 billion into Intel 04:41 Outro Partner Links Book Enterprise Training: https://www.upscaile.com/ Subscribe to our free newsletter: https://www.theaireport.ai/subscribe Free AI Tool Stack: https://community.theaireport.ai/checkout/the-ai-report-welcome-gift?coupon_code=WRTH Learn more about your ad choices. Visit megaphone.fm/adchoices

Audrey McCormack, opening keynote for WE Local Dublin and senior director, research & commercialisation facility lead at MSD Ireland, discusses how engineers can turn failure into a powerful career advantage in this episode. In conversation with host Sam East, Audrey reflects on her unconventional path from electrician to biotech leader and shares how the moments that didn't go to plan shaped her resilience, confidence, and leadership style. Hear how to pursue STEM roles when you don't meet every requirement, rebuild confidence after a failure, and create space for your team to take risks — even in high-stakes technical environments. Audrey will expand on these insights as the opening keynote at WE Local Dublin, taking place April 23-24, 2026. WE Local conferences bring together engineers and technologists for networking opportunities, professional development, and inspiring conversations like this one. Register at welocal.swe.org to join SWE at WE Local Dublin or an upcoming WE Local near you. — The Society of Women Engineers is a powerful, global force uniting nearly 45,000 members of all genders spanning 90+ countries. We are the world's largest advocate and catalyst for change for women in engineering and technology. To join and access all the exclusive benefits to elevate your professional journey, visit membership.swe.org.

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When women and allies in engineering connect globally, they strengthen the entire community. In this episode, host Abosede Adewole, collegiate engagement lead for the SWE Global Women Engineers Affinity Group, is joined by Banisha Prinja, lead-elect, and Eshika Mahajan, professional development lead, to discuss how they have built relationships with engineers around the world and the benefits they have gained from these global connections. They open up about their experiences as women in STEM, from navigating industries where they were the only women in the room to finding commonalities across their experiences in Nigeria and India. Hear why a global perspective matters at the local level, what to do when you don't “feel ready,” and how participating in SWE's Global Women Engineers Affinity Group has grown their networks and leadership skills. Learn more and get involved with the SWE Global Women Engineers Affinity Group: https://affinitygroups.swe.org/global-women-engineers/ — The Society of Women Engineers is a powerful, global force uniting 50,000 members of all genders spanning 85 countries. We are the world's largest advocate and catalyst for change for women in engineering and technology. To join and access all the exclusive benefits to elevate your professional journey, visit membership.swe.org.

In this episode, Abigail Mizzi, master's student in aeronautical and astronautical engineering at Purdue University, and Steven Collicott, Ph.D., professor in Purdue's School of Aeronautics and Astronautics, share the story behind Purdue 1 — a groundbreaking university-led spaceflight mission set for 2027. Abigail is poised to become the first graduate student to conduct her thesis research in space, operating her fluids experiment during three minutes of microgravity. Dr. Collicott will also fly a human-tended experiment studying how liquids move over surfaces in weightlessness — research that can't be replicated on Earth. In conversation with FY26 SWE President Inaas Darrat, hear how Purdue 1 became a reality, what it takes to prepare mentally and physically for suborbital flight, and how SWE has shaped Abigail's STEM journey — including receiving the Outstanding Collegiate Member award. — The Society of Women Engineers is a powerful, global force uniting 50,000 members of all genders spanning 85 countries. We are the world's largest advocate and catalyst for change for women in engineering and technology. To join and access all the exclusive benefits to elevate your professional journey, visit membership.swe.org.

What does responsible AI actually look like, and who gets to shape it? Live from the WE25 Diverse Podcast Studio in New Orleans, Lisa Thee, TEDx speaker and global AI thought leader, discusses using AI for social good and building technology that puts people first. Lisa shares her unexpected journey from industrial engineering at the University of Michigan to becoming an accidental entrepreneur, and the moment in 2015 when she realized AI could help combat human trafficking — including a collaboration that helped law enforcement recover 130 missing children in its first month. In conversation with Larry Guthrie, director of content strategy at SWE, hear three practical tips to use AI ethically, where bias enters AI systems, and how SWE and its annual conferences have repeatedly shaped Lisa's career. — The Society of Women Engineers is a powerful, global force uniting 50,000 members of all genders spanning 85 countries. We are the world's largest advocate and catalyst for change for women in engineering and technology. To join and access all the exclusive benefits to elevate your professional journey, visit membership.swe.org.

Emily finds months' worth of missing lip products buried deep in the couch. Mysterious glowing orbs set off the alarms at Matt's work, completely derail Kaitlin's week, and leave the entire SWE team questioning reality (ghosts? government? the afterlife? all of the above?). Kaitlin's face-brushing journey fails, Matt and Emily's dishwasher and oven both die, and  the comforting reality that all of our food is killing us. Kaitlin turns down a potential interview guest for the first time ever. Then Caroline and Hannah call in and everyone shares what their biggest first-date red flag would be. Follow SWE on Instagram → @so.what.else  Follow Kaitlin on Instagram → @kaitlingraceelliott  https://www.kaitlinelliott.com/

Our 237th episode with a summary and discussion of last week's big AI news!Recorded on 03/13/2026Hosted by Andrey Kurenkov and Jeremie HarrisFeel free to email us your questions and feedback at andreyvkurenkov@gmail.com and/or hello@gladstone.aiRead out our text newsletter and comment on the podcast at https://lastweekin.ai/In this episode:* Perplexity announced “Personal Computer,” a local Mac-based AI agent positioned as a safer alternative to OpenAI's computer-use agents, while Anthropic added GitHub PR code review pricing reviews at $15–$25 and Cursor launched trigger-based “Automations” for always-on coding agents.* ChatGPT introduced interactive math/science visuals and Anthropic added in-chat interactive charts/diagrams; Nvidia released open weights for its 120B-parameter Natron Free Super hybrid Transformer–Mamba latent-MoE model trained natively at 4-bit for Blackwell GPUs.* Nvidia halted H200 production for China amid customs blocks and domestic chip pressure; xAI saw major co-founder departures; Anthropic previewed a Claude Marketplace for enterprise procurement; Yann LeCun's aMI raised $1.3B; humanoid robot maker Sanctuary reached a $1.15B valuation.* Anthropic sued the Pentagon over a “supply chain risk” designation as memos ordered removal within 180 days; research covered models resisting activation steering, limits of chain-of-thought control, inference-scaling boosting cyber-task success, low-probability risky actions, weaknesses in SWE-bench, multimodal pretraining, long-context RNN memory caching, context-parallel training efficiency, RL for CUDA kernel optimization, and latent introspection detecting concept injection.A thank you to our current sponsors:Box - visit Box.com/AI to learn moreODSC AI - go to odsc.ai/east and use promo code LWAI for an additional 15% off your pass to ODSC AI East 2026.Factor - head to factormeals.com/lwai50off and use code lwai50off to get 50 percent off and free breakfast for a yearTimestamps:(00:00:10) Intro / Banter(00:01:23) Response to listener commentsTools & Apps(00:02:06) Perplexity's Personal Computer turns your spare Mac into an AI agent | The Verge(00:04:22) Anthropic launches code review tool to check flood of AI-generated code | TechCrunch(00:08:08 ) Cursor is rolling out a new kind of agentic coding tool | TechCrunch(00:11:14) ChatGPT can now create interactive visuals to help you understand math and science concepts | TechCrunch(00:11:56) Anthropic's Claude AI can respond with charts, diagrams, and other visuals now | The VergeProjects & Open Source(00:13:54) Introducing Nemotron 3 Super: An Open Hybrid Mamba-Transformer MoE for Agentic Reasoning | NVIDIA Technical BlogApplications & Business(00:21:22) Nvidia halts H200 production as China backs Huawei AI chips(00:28:33) Another XAI Cofounder Has Left, and Another Says He's Leaving. - Business Insider(00:34:04) Anthropic's Claude Marketplace allows customers to buy third-party cloud services | TechRadar(00:37:57) Yann LeCun's AMI Labs raises $1.03 billion to build world models | TechCrunch(00:44:52) Humanoid robotics maker Sunday reaches $1.15B valuation to build household robots | TechCrunchPolicy & Safety(00:46:09) Anthropic Sues Department of Defense Over ‘Supply Chain Risk' Label - The New York Times + Google and OpenAI Just Filed a Legal Brief in Support of Anthropic (00:53:24) Internal Pentagon memo orders military commanders to remove Anthropic AI technology from key systems - CBS News(00:58:15) Endogenous Resistance to Activation Steering in Language Models(01:06:27) Reasoning Models Struggle to Control their Chains of Thought(01:09:52) ‘It means missile defence on datacentres': drone strikes raise doubts over Gulf as AI superpower(01:14:57) Evidence for inference scaling in AI cyber tasks: Increased evaluation budgets reveal higher success rates(01:18:24) Frontier Models Can Take Actions at Low ProbabilitiesResearch & Advancements(01:24:20) Research note: Many SWE-bench-Passing PRs Would Not Be Merged into Main(01:28:26) [2603.03276] Beyond Language Modeling: An Exploration of Multimodal Pretraining(01:40:09) Memory Caching: RNNs with Growing Memory(01:48:47) Untied Ulysses: Memory-Efficient Context Parallelism via Headwise Chunking(01:58:41) CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation(02:08:57) Latent Introspection: Models Can Detect Prior Concept Injections(02:16:45) Physics of RL: Toy scaling laws for the emergence of reward-seekingSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Guys I think its red I saw them vent... Justtt kidding nobody is ever an imposter in SWE!! Explore imposter syndrome with us as we share our experiences being a woman in male dominated fields. You belong where you are and you are always worth it. If you ever feel down and dumb come talk to us and we'll hype you up! Stay as gorgeous and smart as you are, you're always deserving and worth it. Love, Emma and Ava

Paige Feikert, research and technology engineer with Spirit AeroSystems, joins us live from the WE25 Diverse Podcast Studio to break down why communication can make or break your impact as an engineer — and how to get better at it. In conversation with Larry Guthrie, director of content strategy at SWE, Paige shares her unconventional career path from biomedical engineering student, to TV news producer at a CBS affiliate, and back into engineering. Hear why storytelling matters in technical work, actionable advice to help you communicate to executives and non-technical audiences, and what producing live TV news taught Paige about teamwork, deadlines, and handling pressure. — The Society of Women Engineers is a powerful, global force uniting 50,000 members of all genders spanning 85 countries. We are the world's largest advocate and catalyst for change for women in engineering and technology. To join and access all the exclusive benefits to elevate your professional journey, visit membership.swe.org.

As part of SWE's “Un Cafecito With a Woman in STEM” series, spotlighting Latina voices across the globe, this special episode of Diverse is presented in Spanish. Claudia Guerrero, SWE global ambassador and service program leader at GE Aerospace, sits down with host Doris Moreno Maldonado, process engineer at Kellogg's and lead of the SWE Latinos Affinity Group, for a conversation on antifragility, authenticity, and creating community wherever you are. Recorded live at WE25 in New Orleans, Claudia shares her journey as one of the first women in her family to study engineering in Mexico, her role in growing the SWE affiliate in Querétaro, and surviving a life-altering medical crisis. Hear how to move beyond resilience toward antifragility, build your personal board of directors, and lean into your unique authentic strengths. — The Society of Women Engineers is a powerful, global force uniting 50,000 members of all genders spanning 85 countries. We are the world's largest advocate and catalyst for change for women in engineering and technology. To join and access all the exclusive benefits to elevate your professional journey, visit membership.swe.org.

Google just dropped Gemini 3 Flash—a model that outperforms Gemini 2.5 Pro (their last top model) while running 3x faster at less than 1/4 the cost. It's frontier-level reasoning at Flash-level speed, and it's rolling out globally right now.We're sitting down with Logan Kilpatrick from Google DeepMind to explore what this actually means for developers, knowledge workers, and anyone trying to figure out how AI fits into their workflow.What we'll cover:

It is the eve of the USANZ ASM here in Melbourne (which Renu is Convening!), and some of the 27 International guests are already into town. So we grabbed Anders Bjartell (Lund University/University Hospital Malmo, SWE), for a sit down chat in studio. Anders has been a huge name in prostate cancer research in Europe for the past couple of decades, including as a senior investigator on TITAN. so we decided to pick his brain on three topical areas in prostate cancer:1. ADT/ARPI doublets in mHSPC - can we adopt an intermittent approach before the trials read out? What about docetaxel triplet therapy?2. The SPARC consensus on PSMA PET/CT reporting - Anders led this initiative which recently publihsed in Eur Urol. What is this and why does it matter?3. Organised Prostate Testing - what is the difference between screening and organised prostate testing? With usual hosts Renu Eapen and Declan MurphyThis is a Themed Podcast supported by our Gold Partners, Johnson & Johnson. Links:SPARC consensus paper in European Urology 

Carolina Caro, WE Local Portland keynote and CEO of Conscious Leadership Partners, breaks down communication blind spots for engineers and explores how your communication style shapes your leadership impact in this episode. As a scientist by training, Carolina reflects on why technical expertise isn't enough and speaks to the platinum rule, where you meet people where they are and communicate in the way they can best receive. In conversation with FY26 SWE President Inaas Darrat, hear how to strengthen your communication without compromising your authenticity and why communication style is an often-overlooked dimension of diversity. Carolina will expand on these insights as the opening keynote at WE Local Portland, taking place Feb. 27-28. WE Local conferences bring together engineers and technologists for networking opportunities, professional development, and inspirational speakers. Register at welocal.swe.org to join SWE at an upcoming WE Local near you! — The Society of Women Engineers is a powerful, global force uniting 50,000 members of all genders spanning 85 countries. We are the world's largest advocate and catalyst for change for women in engineering and technology. To join and access all the exclusive benefits to elevate your professional journey, visit membership.swe.org.

CoreStory is building code intelligence platforms that address the fundamental limitation of today's coding agents: their inability to navigate complex enterprise codebases. While foundation models excel at greenfield development, they fail at real-world engineering tasks in systems spanning millions of lines of code. CoreStory's context layer delivers a 44% improvement on SWE-bench, the industry's standard benchmark for measuring coding agent effectiveness on actual GitHub issues. In this episode of BUILDERS, I sat down with Anand Kulkarni, CEO of CoreStory, to explore how his team is enabling the shift to AI-native engineering and seeding the category of spec-driven development across Microsoft, GitHub, and Amazon. Topics Discussed: Building with GPT-3 API 18 months before ChatGPT went public Why even GPT-5 and Opus 4.5 struggle with enterprise codebases on SWE-bench The narrative shift required when selling AI pre- and post-ChatGPT CoreStory's 44% improvement in coding agent performance through context intelligence How "spec-driven development" got adopted by Microsoft, GitHub, and Amazon without formal analyst relations The parallel between JIRA monetizing Agile and CoreStory enabling AI-native engineering Three-channel distribution: direct enterprise, coding agent partnerships via MCP, and hyperscaler/GSI routes Why specs become the source of truth while code becomes disposable in the AI era GTM Lessons For B2B Founders: Match your narrative precision to technical depth: CoreStory deploys three distinct positioning strategies based on audience sophistication. For AI practitioners tracking benchmarks, they lead with "44% SWE-bench improvement"—a metric that immediately signals meaningful progress on the hardest problem in the space. For engineering leaders aware of AI tooling but not deep in the research, they focus on velocity gains and ROI metrics. For executives, they describe reverse-engineering codebases into machine-readable specs. The key insight: technical audiences dismiss vague value props, while non-technical audiences get lost in benchmark details. Map your positioning to how your audience measures success in their world. Seed category language through earned adoption, not manufactured consensus: Anand initially called their approach "requirements-driven development" before simplifying to "spec-driven development." Rather than pitching analysts, they used the term consistently in customer conversations, gave talks at GitHub Universe, and shipped demos showing the workflow. When customers naturally adopted the language and community leaders began using similar terminology independently, Microsoft and GitHub followed with their own implementations (like GitHub's SpecKit). The lesson: category language sticks when practitioners choose to use it because it clarifies their work, not because a vendor pushed it. Focus on customer adoption as proof of concept before seeking broader market validation. Position against emergent practices, not just incumbent products: CoreStory doesn't position against legacy code analysis tools—they position as the enabler of AI-native engineering, the discipline that will displace Agile. Anand's insight from watching JIRA's success: "People don't love JIRA. What they love is Agile as a way to move away from waterfall." CoreStory is betting that 10x velocity gains from AI-native practices will drive the same categorical shift. When you're early in a technology wave, attach to the practice change (how teams will work differently) rather than feature comparisons with existing tools. Movements create markets. Design channel strategy around customer problem awareness: CoreStory's three channels map to different stages of buyer sophistication. Direct enterprise comes from teams already deep in AI engineering who've hit the context limitation wall. Coding agent partnerships (via MCP integration with tools like Cognition and Factory) serve builders wanting better AI tooling who haven't diagnosed the context problem yet. Hyperscalers and GSIs distribute into modernization and maintenance projects where AI enablement is emerging as a requirement. Each channel serves a distinct buyer journey stage. Don't force one go-to-market motion—design multiple paths based on where different customer segments are in understanding the problem you solve. Navigate pre-legitimacy markets by hiding the breakthrough: Before ChatGPT, selling anything AI-driven faced immediate skepticism about whether it was "real" or just smoke and mirrors. Anand couldn't lead with AI without triggering disbelief. CoreStory focused on delivered outcomes—"here's what you'll be able to do"—with AI as the mechanism, not the message. Post-ChatGPT, the challenge flipped: everyone expects AI, but now the differentiation question becomes harder. If you're building on emerging technology before market consensus forms, deemphasize the technology until buyers have context to evaluate it. Once the market validates the technology category, shift to demonstrating your specific technical advantage within it. // Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co // Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

Julie Daugherty, engineering associate and process project leader at Corning Incorporated, joins us live at WE25 to discuss how introverts can embrace their strengths and turn them into career superpowers. In conversation with Larry Guthrie, director of content strategy at SWE, hear how planning ahead builds confidence, how to survive “mandatory fun” networking events, and why finding extroverted champions can be key to career growth in STEM. You'll also learn how managers can support introverted engineers, what it means to be an ambivert, and why personality diversity leads to stronger teams and better problem-solving. — The Society of Women Engineers is a powerful, global force uniting 50,000 members of all genders spanning 85 countries. We are the world's largest advocate and catalyst for change for women in engineering and technology. To join and access all the exclusive benefits to elevate your professional journey, visit membership.swe.org.

I detta avsnitt av Kulturbarnen berättar Pontus om projektet han drivit i smyg i snart ett år, re/works SWE för Epidemic Sound, i vilket han bjudit in ett stort antal svenska artister och låtit dem omtolka musik från ett stort låtbibliotek dedikerat för synk och ljudläggning av internet. Välkomna!

Zoe, SWENext Influencer and FIRST Robotics leader, and Charlee, a member of the 2025 STEM Next Flight Crew youth ambassador program, join us live from the WE25 Diverse Podcast Studio in New Orleans to share their experiences as young STEM leaders. In conversation with Larry Guthrie, director of content strategy at SWE, they reflect on how Invent It. Build It. sparked powerful connections, what leadership looks like as a precollege student, and how they navigate bias, responsibility, and pressure as “the first” in their communities. Hear their experiences starting STEM clubs and expanding access in rural areas, plus why a strong community is critical to shaping a more inclusive future in engineering. — The Society of Women Engineers is a powerful, global force uniting 50,000 members of all genders spanning 85 countries. We are the world's largest advocate and catalyst for change for women in engineering and technology. To join and access all the exclusive benefits to elevate your professional journey, visit membership.swe.org.

This is a link post. Improving model performance by scaling up inference compute is the next big thing in frontier AI. But the charts being used to trumpet this new paradigm can be misleading. While they initially appear to show steady scaling and impressive performance for models like o1 and o3, they really show poor scaling (characteristic of brute force) and little evidence of improvement between o1 and o3. I explore how to interpret these new charts and what evidence for strong scaling and progress would look like. From scaling training to scaling inference The dominant trend in frontier AI over the last few years has been the rapid scale-up of training — using more and more compute to produce smarter and smarter models. Since GPT-4, this kind of scaling has run into challenges, so we haven't yet seen models much larger than GPT-4. But we have seen a recent shift towards scaling up the compute used during deployment (aka 'test-time compute' or ‘inference compute'), with more inference compute producing smarter models. You could think of this as a change in strategy from improving the quality of your employees' work via giving them more years of training in which acquire [...] --- First published: February 2nd, 2026 Source: https://forum.effectivealtruism.org/posts/zNymXezwySidkeRun/inference-scaling-and-the-log-x-chart Linkpost URL:https://www.tobyord.com/writing/inference-scaling-and-the-log-x-chart --- Narrated by TYPE III AUDIO. ---Images from the article:

This episode is sponsored by BD. Showing up as your authentic self in engineering isn't always easy. In this conversation, Christine Kearney Hawkins, senior staff R&D engineer in BD's Peripheral Intervention business and SWE life member, shares her 20+ year journey navigating authenticity, leadership, and innovation in STEM. From being told that she couldn't be both an engineer and a mom, to learning that her bubbly enthusiasm is a strength and not a liability, Christine reflects on how embracing who she is shaped her career and impact. In conversation with host Sam East, hear how authentic leadership fuels better innovation outcomes, what to do when workplace feedback conflicts with your core values, and practical advice to create cultures where people feel safe bringing their whole selves to work. — The Society of Women Engineers is a powerful, global force uniting 50,000 members of all genders spanning 85 countries. We are the world's largest advocate and catalyst for change for women in engineering and technology. To join and access all the exclusive benefits to elevate your professional journey, visit membership.swe.org.

Stepping into STEM leadership doesn't require a senior title or having everything figured out. In this episode, Katie Ashley, volunteer coordinator of the SWE Early Career Professionals Affinity Group (SWE ECP AG), is joined by Zoe Husted, ECP AG conferences and awards co-chair and president of the SWE Golden Gate Section, and Kathryn Wittek, ECP AG design coordinator and president of the SWE Baltimore-Washington Section, to explore what leadership can look like in the beginning years of an engineering career. Drawing from their experiences in SWE, team sports, and technical roles, Zoe and Kathryn share when they started seeing themselves as leaders, how they navigate leading more experienced colleagues, and why learning and leading often happen at the same time. Hear their tips to find community as an early-career engineer, plus how the skills they have developed through SWE have translated into the workplace. The SWE ECP AG was formed to equip individuals with the support, resources, and inclusive community to excel in the first ten years of their career. Get involved and find out about upcoming ECP AG events at https://earlycareerprofessionalsag.swe.org/. — The Society of Women Engineers is a powerful, global force uniting 50,000 members of all genders spanning 85 countries. We are the world's largest advocate and catalyst for change for women in engineering and technology. To join and access all the exclusive benefits to elevate your professional journey, visit membership.swe.org.

From creating SWE-bench in a Princeton basement to shipping CodeClash, SWE-bench Multimodal, and SWE-bench Multilingual, John Yang has spent the last year and a half watching his benchmark become the de facto standard for evaluating AI coding agents—trusted by Cognition (Devin), OpenAI, Anthropic, and every major lab racing to solve software engineering at scale. We caught up with John live at NeurIPS 2025 to dig into the state of code evals heading into 2026: why SWE-bench went from ignored (October 2023) to the industry standard after Devin's launch (and how Walden emailed him two weeks before the big reveal), how the benchmark evolved from Django-heavy to nine languages across 40 repos (JavaScript, Rust, Java, C, Ruby), why unit tests as verification are limiting and long-running agent tournaments might be the future (CodeClash: agents maintain codebases, compete in arenas, and iterate over multiple rounds), the proliferation of SWE-bench variants (SWE-bench Pro, SWE-bench Live, SWE-Efficiency, AlgoTune, SciCode) and how benchmark authors are now justifying their splits with curation techniques instead of just “more repos,” why Tau-bench's “impossible tasks” controversy is actually a feature not a bug (intentionally including impossible tasks flags cheating), the tension between long autonomy (5-hour runs) vs. interactivity (Cognition's emphasis on fast back-and-forth), how Terminal-bench unlocked creativity by letting PhD students and non-coders design environments beyond GitHub issues and PRs, the academic data problem (companies like Cognition and Cursor have rich user interaction data, academics need user simulators or compelling products like LMArena to get similar signal), and his vision for CodeClash as a testbed for human-AI collaboration—freeze model capability, vary the collaboration setup (solo agent, multi-agent, human+agent), and measure how interaction patterns change as models climb the ladder from code completion to full codebase reasoning.We discuss:* John's path: Princeton → SWE-bench (October 2023) → Stanford PhD with Diyi Yang and the Iris Group, focusing on code evals, human-AI collaboration, and long-running agent benchmarks* The SWE-bench origin story: released October 2023, mostly ignored until Cognition's Devin launch kicked off the arms race (Walden emailed John two weeks before: “we have a good number”)* SWE-bench Verified: the curated, high-quality split that became the standard for serious evals* SWE-bench Multimodal and Multilingual: nine languages (JavaScript, Rust, Java, C, Ruby) across 40 repos, moving beyond the Django-heavy original distribution* The SWE-bench Pro controversy: independent authors used the “SWE-bench” name without John's blessing, but he's okay with it (”congrats to them, it's a great benchmark”)* CodeClash: John's new benchmark for long-horizon development—agents maintain their own codebases, edit and improve them each round, then compete in arenas (programming games like Halite, economic tasks like GDP optimization)* SWE-Efficiency (Jeffrey Maugh, John's high school classmate): optimize code for speed without changing behavior (parallelization, SIMD operations)* AlgoTune, SciCode, Terminal-bench, Tau-bench, SecBench, SRE-bench: the Cambrian explosion of code evals, each diving into different domains (security, SRE, science, user simulation)* The Tau-bench “impossible tasks” debate: some tasks are underspecified or impossible, but John thinks that's actually a feature (flags cheating if you score above 75%)* Cognition's research focus: codebase understanding (retrieval++), helping humans understand their own codebases, and automatic context engineering for LLMs (research sub-agents)* The vision: CodeClash as a testbed for human-AI collaboration—vary the setup (solo agent, multi-agent, human+agent), freeze model capability, and measure how interaction changes as models improve—John Yang* SWE-bench: https://www.swebench.com* X: https://x.com/jyangballinFull Video EpisodeTimestamps00:00:00 Introduction: John Yang on SWE-bench and Code Evaluations00:00:31 SWE-bench Origins and Devon's Impact on the Coding Agent Arms Race00:01:09 SWE-bench Ecosystem: Verified, Pro, Multimodal, and Multilingual Variants00:02:17 Moving Beyond Django: Diversifying Code Evaluation Repositories00:03:08 Code Clash: Long-Horizon Development Through Programming Tournaments00:04:41 From Halite to Economic Value: Designing Competitive Coding Arenas00:06:04 Ofir's Lab: SWE-ficiency, AlgoTune, and SciCode for Scientific Computing00:07:52 The Benchmark Landscape: TAU-bench, Terminal-bench, and User Simulation00:09:20 The Impossible Task Debate: Refusals, Ambiguity, and Benchmark Integrity00:12:32 The Future of Code Evals: Long Autonomy vs Human-AI Collaboration00:14:37 Call to Action: User Interaction Data and Codebase Understanding Research Get full access to Latent.Space at www.latent.space/subscribe

From creating SWE-bench in a Princeton basement to shipping CodeClash, SWE-bench Multimodal, and SWE-bench Multilingual, John Yang has spent the last year and a half watching his benchmark become the de facto standard for evaluating AI coding agents—trusted by Cognition (Devin), OpenAI, Anthropic, and every major lab racing to solve software engineering at scale. We caught up with John live at NeurIPS 2025 to dig into the state of code evals heading into 2026: why SWE-bench went from ignored (October 2023) to the industry standard after Devin's launch (and how Walden emailed him two weeks before the big reveal), how the benchmark evolved from Django-heavy to nine languages across 40 repos (JavaScript, Rust, Java, C, Ruby), why unit tests as verification are limiting and long-running agent tournaments might be the future (CodeClash: agents maintain codebases, compete in arenas, and iterate over multiple rounds), the proliferation of SWE-bench variants (SWE-bench Pro, SWE-bench Live, SWE-Efficiency, AlgoTune, SciCode) and how benchmark authors are now justifying their splits with curation techniques instead of just "more repos," why Tau-bench's "impossible tasks" controversy is actually a feature not a bug (intentionally including impossible tasks flags cheating), the tension between long autonomy (5-hour runs) vs. interactivity (Cognition's emphasis on fast back-and-forth), how Terminal-bench unlocked creativity by letting PhD students and non-coders design environments beyond GitHub issues and PRs, the academic data problem (companies like Cognition and Cursor have rich user interaction data, academics need user simulators or compelling products like LMArena to get similar signal), and his vision for CodeClash as a testbed for human-AI collaboration—freeze model capability, vary the collaboration setup (solo agent, multi-agent, human+agent), and measure how interaction patterns change as models climb the ladder from code completion to full codebase reasoning. We discuss: John's path: Princeton → SWE-bench (October 2023) → Stanford PhD with Diyi Yang and the Iris Group, focusing on code evals, human-AI collaboration, and long-running agent benchmarks The SWE-bench origin story: released October 2023, mostly ignored until Cognition's Devin launch kicked off the arms race (Walden emailed John two weeks before: "we have a good number") SWE-bench Verified: the curated, high-quality split that became the standard for serious evals SWE-bench Multimodal and Multilingual: nine languages (JavaScript, Rust, Java, C, Ruby) across 40 repos, moving beyond the Django-heavy original distribution The SWE-bench Pro controversy: independent authors used the "SWE-bench" name without John's blessing, but he's okay with it ("congrats to them, it's a great benchmark") CodeClash: John's new benchmark for long-horizon development—agents maintain their own codebases, edit and improve them each round, then compete in arenas (programming games like Halite, economic tasks like GDP optimization) SWE-Efficiency (Jeffrey Maugh, John's high school classmate): optimize code for speed without changing behavior (parallelization, SIMD operations) AlgoTune, SciCode, Terminal-bench, Tau-bench, SecBench, SRE-bench: the Cambrian explosion of code evals, each diving into different domains (security, SRE, science, user simulation) The Tau-bench "impossible tasks" debate: some tasks are underspecified or impossible, but John thinks that's actually a feature (flags cheating if you score above 75%) Cognition's research focus: codebase understanding (retrieval++), helping humans understand their own codebases, and automatic context engineering for LLMs (research sub-agents) The vision: CodeClash as a testbed for human-AI collaboration—vary the setup (solo agent, multi-agent, human+agent), freeze model capability, and measure how interaction changes as models improve — John Yang SWE-bench: https://www.swebench.com X: https://x.com/jyangballin Chapters 00:00:00 Introduction: John Yang on SWE-bench and Code Evaluations 00:00:31 SWE-bench Origins and Devon's Impact on the Coding Agent Arms Race 00:01:09 SWE-bench Ecosystem: Verified, Pro, Multimodal, and Multilingual Variants 00:02:17 Moving Beyond Django: Diversifying Code Evaluation Repositories 00:03:08 Code Clash: Long-Horizon Development Through Programming Tournaments 00:04:41 From Halite to Economic Value: Designing Competitive Coding Arenas 00:06:04 Ofir's Lab: SWE-ficiency, AlgoTune, and SciCode for Scientific Computing 00:07:52 The Benchmark Landscape: TAU-bench, Terminal-bench, and User Simulation 00:09:20 The Impossible Task Debate: Refusals, Ambiguity, and Benchmark Integrity 00:12:32 The Future of Code Evals: Long Autonomy vs Human-AI Collaboration 00:14:37 Call to Action: User Interaction Data and Codebase Understanding Research

Karen Horting, Executive Director and CEO of the Society of Women Engineers, talks about SWE's archives at the Reuther Library and shares how the 75-year-old organization leverages its history to advocate for the inclusion of women in science, technology, engineering, and mathematics (STEM). Related Resources: Society of Women Engineers 75th Anniversary SWE Archives Virtual Tour [Part 1] SWE Archives Virtual Tour [Part 2] Related Collections: Society of Women Engineers Records (LR001539) Society of Women Engineers Publications (LR002487) Episode Credits Interviewee: Karen Horting Producers: Dan Golodner and Troy Eller English Music: Bart Bealmear

Emily breaks down her 2025 Holiday Gift Guide through the lens of the five pillars of sexual intelligence—embodiment, health, self-knowledge, self-acceptance, and collaboration. She explores how shifting from performance to presence can transform your relationship with pleasure, offering curated tools and practices that help you slow down, feel your body, and understand yourself as a sexual being. This episode is for anyone ready to move beyond quick fixes and embrace a more holistic approach to sexuality, turning intimacy into something that nourishes your whole system. In this episode, you'll learn: • The five pillars of Sex IQ create a holistic framework for understanding your sexuality and taking responsibility for your pleasure—moving you from performance to presence • Embodiment practices like breathwork and sonic wave toys help you overcome the mind-body disconnect during sex by bringing you back to physical sensations instead of staying in your head worrying about how you look or what you need to do • Self-acceptance isn't about waiting for your body to change—it's about recognizing and reframing the pleasure thieves (stress, trauma, and shame) that tell you you're unworthy, and actively replacing negative thought patterns with affirmations that honor your body right now More Dr. Emily:  • The 2025 Sex With Emily Holiday Gift Guide • Apply for Emily's 1:1 Coaching Opportunity HERE or reach out to enrollment@sexwithemily.com for more information  • Shop With Emily! Explore Emily's favorite toys, pleasure accessories, bedroom essentials, and more — designed to support your pleasure and confidence. Free shipping on orders $99+ (some exclusions apply). • Join the SmartSX Membership: Access exclusive sex coaching, live expert sessions, community building, and tools to enhance your pleasure and relationships with Dr. Emily Morse. • Yes! No! Maybe? List & Other Sex With Emily Guides: Explore pleasure, deepen connections, and enhance intimacy using these Sex With Emily downloadable guides. • The only sex book you'll ever need: Smart Sex: How to Boost Your Sex IQ and Own Your Pleasure • Want more? Visit the Sex With Emily Website • Let's get social: Instagram | X | Facebook | TikTok | Threads | YouTube • Let's text: Sign up here • Want me to slide into your email inbox? Sign Up Here for sex tips on the regular. Shop the Holiday Gift Guide now! (See the full Gift Guide HERE)  Embodiment: • LELO SONA 3- Use code EMILY20 for 20% on top of ongoing sales at lelo.com • Common Confidential Massage Butter- Use code SEXWITHEMILY for 15% off at Commonconfidential.com. • Cornbread Hemp - Use code SWE for a discount at cornbreadhemp.com/swe  Health: • Bathmate Hydro Pump-  Use SWE10 for 10% off your order at bathmatedirect.com • HigherDOSE Infrared Sauna Blanket- Head to higherdose.com • V-Health Vaginal Rejuvenation Gel- Use code EMILY10 for 10% off at getvhealth.com  • Kroma Wellness Beauty Matcha Latte - Use code SEXWITHEMILY for 15% off at kromawellness.com  Collaboration:  • Promescent Delay Spray- Head to promescent.com  • LELO F2S- Use code EMILY20 for 20% on top of ongoing sales at lelo.com  • Crave Leather Handcuffs- Head to shop.sexwithemily.com/crave  Self- Knowledge: • Magic Wand Mini - Head to shop.sexwithemily.com/magicwand  • Je Joue Hera Flex Rabbit Vibrator - Go to sexwithemily.com/hera and use code EMILY20 for 20% off  • SmartSX- Head to sexwithemily.com/smartsx  Self- Acceptance:  • The Class - Head to theclass.com  • Droplette- Head to droplette.io This episode is sponsored by…  Biolouve- Get 15% off with code EMILYPOWERMOVE @ https://biolouve.com/  Timestamps 0:00 - Introduction 1:25 - The 5 Pillars of Sex IQ Framework 2:36 - Pillar 1: Embodiment 10:23 - Pillar 2: Health 17:52 - Pillar 3: Collaboration 24:44 - Pillar 4: Self-Knowledge 29:39 - Pillar 5: Self-Acceptance 34:21 - Wrap-Up

This episode is sponsored by Bechtel. Josefina Alvarez and Kira McKay, supplier quality representatives at Bechtel, sit down with SWE President-Elect Kerrie Greenfelder to discuss how they landed their first jobs through the SWE and SHPE career fairs and also discovered a side of engineering they never knew existed. Recorded live at the WE25 Diverse Podcast Studio in New Orleans, hear about the behind-the-scenes components of engineering — from supply chain to quality systems — and how these roles make iconic projects possible. Kira and Josefina share candid advice for engineering students and new grads, what they've learned inside the Bechtel Supplier Quality and Expediting (BSQE) program, and how mentorship, curiosity, and saying “yes” to unfamiliar paths shaped their early careers. — The Society of Women Engineers is a powerful, global force uniting 50,000 members of all genders spanning 85 countries. We are the world's largest advocate and catalyst for change for women in engineering and technology. To join and access all the exclusive benefits to elevate your professional journey, visit membership.swe.org.

This episode features Dianne Na Penn, a senior product leader at Anthropic, discussing the launch of Claude Opus 4.5 and the evolution of frontier AI models. The conversation explores how Anthropic approaches model development—balancing ambitious capability roadmaps with user feedback, making strategic bets on areas like agentic coding and computer use while deliberately avoiding others like image generation. Dianne shares insights on the shifting nature of AI evaluation (moving beyond saturated benchmarks like SWE-bench toward more open-ended measures), the evolution of scaffolding from "training wheels" to intelligence amplifiers, and why she believes we're closer to transformative long-running AI than most people think. She also discusses Anthropic's distinctive culture of authenticity, the under appreciated benefits of model alignment for producing independent-thinking AI, and why the real bottleneck to AI agents isn't model capability anymore but product innovation. (0:00) Intro(0:57) Starting the Work on Opus 4.5(2:04) Model Capabilities and Surprises(5:59) Computer Use and Practical Applications(7:21) Pricing and Positioning(10:02) Customer Feedback and Early Access(16:44) The Reality of Enterprise Agents(18:47) Future of AI and Long-Running Intelligence(28:06) Anthropic's Culture and Decision Making(30:31) Key Decisions and Fun Moments(33:45) Quickfire With your co-hosts: @jacobeffron - Partner at Redpoint, Former PM Flatiron Health @patrickachase - Partner at Redpoint, Former ML Engineer LinkedIn @ericabrescia - Former COO Github, Founder Bitnami (acq'd by VMWare) @jordan_segall - Partner at Redpoint

The common advice for career growth is to “move up” into management — but what if your true passion lies in staying close to the technology itself? In this episode, host Sam East speaks with Deb Whitis, Ph.D., and Amrita Maguire, both of the SWE Technical Career Path Affinity Group, about what it means to grow, lead, and make an impact as engineers while staying on the technical career path. From developing nickel-based superalloys that power jet engines to advancing ergonomic standards and AI-enabled design, Deb and Amrita reflect on their careers and share how technical leadership can be just as influential as managing people. They also highlight the work of SWE's Technical Career Path Affinity Group, including a new mentorship program helping women chart their own path as innovators, inventors, and subject matter experts. Get involved with the SWE Technical Career Path Affinity Group: https://affinitygroups.swe.org/technical-career-path/ — The Society of Women Engineers is a powerful, global force uniting 50,000 members of all genders spanning 85 countries. We are the world's largest advocate and catalyst for change for women in engineering and technology. To join and access all the exclusive benefits to elevate your professional journey, visit membership.swe.org.

Google just released Gemini 3, and I tested it with 3 real business use cases: prepping for a $200K sales call, building an interactive sales dashboard, and creating a complete website from scratch—all in minutes.In this video, I show you LIVE examples of:✅ Gemini Agent prepping an entire sales call (research, pitch angles, objection handling, follow-ups)✅ Dynamic dashboards with real-time calculations and interactive sliders✅ Full website generation with 921 lines of working code in under 60 seconds✅ Custom image generation and prompt engineeringThis isn't theory—I'm screen recording everything as it happens so you can see the actual speed and quality.⏱️ TIMESTAMPS:0:00 - Intro: Why Gemini 3 is a Big Deal1:15 - Benchmark Breakdown (Why This Matters)2:27 - Use Case #1: $200K Sales Call Prep4:46 - Visual Layout & Interactive Infographic Demo7:03 - Use Case #2: Building a Website from Scratch (Live Code)9:27 - Use Case #3: Interactive Q4 Sales Dashboard11:51 - Testing the Prompt Generator Live12:45 - Final Thoughts & Why This Changes Everything

This week on the show Maine recaps the 2025 ADCC North American trials live from Orlando Florida.  We recap all the divisions starting with the Men'sWe discuss the -66.0 kg Dorian Olivarez-77.0 kg Jacob Bornemann-88.0 kg Jon Blank-99.0 kg Achilles Rocha+99.0 kg Brandon ReedThen  move into the recap of the womens division-55.0 kgAna Mayordomo-65.0 kg Morgan "Mo" Black+65.0 kg Maia MatalonRecorded 11-17-2025

Jessica reports LIVE from Jakarta on all the details from day two of women's podium training. World Championships Headquarters  Videos, Interviews, Podcasts, Fantasy, Guides Extended Episode + Live Q&A (Members) +30 extra minutes of analysis, behind-the-scenes secret stories, plus member questions. Here's how to ask questions live. Can't make it live? Add Club bonus episodes to your favorite podcast player (instructions here). Chapters 00:00 – Show Intro 01:02 – Zhang Qingying beam world champion prediction 03:00 – FIG Press Conference recap: AI D-scores and visa issue 08:40 – Spencer's updates: where to watch & fantasy game deadlines 11:45 – U.S. Women's Team podium training report (Josc, Skye, Dulcy, Leanne) 17:20 – Can Josc vault? Exclusive Olympic Channel interview 19:45 – Equipment update: white mats and “China mat overlay” 22:10 – Mixed Zone highlights (Malabuyo, South Africa, Asia's coach impression) 25:05 – Italy updates: Perotti, Asia D'Amato, Fioravanti AA potential 29:45 – Melnikova and Russia (AIN) podium impressions 31:30 – Flavia Saraiva's 10.0 leotard and Brazilian updates 33:10 – Funniest & coolest skills of the day (Chile, India, Portugal) 33:55 – BTS Teaser begins 34:00 – Embarrassing moments & Watanabe press conference story 36:40 – Beam fall hilarity (NZL gymnast) 38:15 – Opposite of Canadian medical intervention 40:00 – The great Indonesian tampon saga 42:25 – Sub 4: NZL, LIE, USA, CRO, BAN, GBR, POL 45:10 – Ruby Evans Amanar, GB bars, Alia Leat injury update 47:05 – Sub 5: MAS, SUI, ITA, FRA, VIE, ISL, MAR 49:00 – Thelma's floor, Osyssek's beam, Ming Van Eijken vaults 51:05 – Sub 6: AUS, EGY, BEL, LAT, ROU, MGL, SWE, CRC 53:00 – Voinea full Gothic mode, Golgota AA, Romanian updates 56:20 – Sub 7: INA, TUN, COL, PHI, MEX, SYR 58:00 – Finnegan & Malabuyo AA, Seema Tello debut 1:00:10 – Sub 8: NOR, BRA, QAT, IND, RSA, CHI 1:02:15 – Flavia & Brazil updates, Rooskrantz, Chilean grandmas 1:05:00 – Sub 9: AIN, NAM, POR, THA, BUL, SLO, CMR 1:07:25 – Melnikova Cheng, Cameroon floor joy, AIN medal watch 1:10:10 – Sub 10: ESP, AIN, HUN, HKG, CHN, KZN, CZE 1:12:25 – Zhou Yaqin & Zhang Qingying on beam, Deng Yalan vault 1:15:30 – Alba Petisco all-around standout 1:17:10 – Feedback: listener comments from Dr. Ben & Absolutely Not 1:21:20 – Show Close: Women's qualifying preview & thanks How Do I Watch the Competition? All sessions of the competition will be streamed on Eurovision Sport. Follow along here! Gymnastics Indonesia's YouTube channel will stream all qualification sessions Live scores from the FIG and Swiss Timing Check out NBC's behind-the-scenes mini-doc on the US Women's World Trials Headlines What happened at podium training today? Should we be worried about the US women? From the Olympic Channel: Joscelyn Roberson has been struggling to "find her block" on vault Skye's HUGE front-handspring front on beam Who else from Florida came to join the 2025 World Championships party? Giulia Perotti (Italy) looks ready to win all the medals Who will be the second Italian competing all-around? The D'Amato vs. Fioravanti dilemma Angelina Melnikova is so back How did her vaults look? WE NEED TO TALK ABOUT BRAZIL'S GENIUS LEOS Flavia showed beam and floor - how'd it go? Who wins the award for coolest/best/most fun skill from podium training? What were Jessica's mixed zone highlights? The FIG held a press conference today. What information did we learn? The FIG announced that "spectators will be able to see AI D-scores," but what does this mean? The FIG addressed the visa vs. FIG rules issue. What did FIG president Watanabe have to say? Jakarta Updates GymCastic Updates Subscribe to our YouTube Channel Coming Up 6 days of LIVE podcasts at World Championships in Jakarta Club members get extended coverage and can join us live to ask questions immediately after the meet Play our World Championships Fantasy Game! Win a Club Gym Nerd Scholarship: Go to our Forum > Show Stuff > GymCastic Scholarship We are matching every new sponsorship If you would like access to the club content, but aren't currently in a position to purchase a membership, all you need to do is fill out the form that's linked in our message board If you would also like to sponsor a scholarship, please email editor@gymcastic.com. Thank you! 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Join us in this exciting episode of The Edge of Show as we dive deep into the world of Bitcoin DeFi with two industry leaders: MacLane Wilkison, co-founder and CEO of Threshold Labs, and Jameel Khalfan, head of ecosystem development at Sui Foundation.In this episode, we explore:The transformative potential of TBDC (Threshold Bitcoin Decentralized Currency) and how it is powering Bitcoin's breakout moment on the SWE ecosystem.The rapid evolution of Bitcoin DeFi and the seamless bridging and yield strategies that are emerging.Insights into the future of Bitcoin as a dynamic financial asset and its role in the broader DeFi landscape.Discover how the integration of Bitcoin with decentralized finance is reshaping the financial ecosystem, making it more accessible and user-friendly. We also discuss the importance of security, liquidity, and the collaborative efforts between Threshold and SWE to foster innovation and growth in the Bitcoin space.Whether you're a seasoned crypto enthusiast or just starting your journey, this episode is packed with valuable insights and exciting developments in the world of Bitcoin and DeFi.Don't forget to like, subscribe, and hit the notification bell to stay updated on our latest episodes!Support us through our Sponsors! ☕