Podcasts about Claw

主播：Emma（中国）+ Selah（美国） 音乐：Be Young最近，打开社交媒体，你有没有被“养龙虾”刷屏呢？今天，我们就来聊一聊这款名为OpenClaw的AI工具。01. What Is OpenClaw? 到底什么是OpenClaw？OpenClaw最近在中国互联网的讨论度特别高（pop up）。它其实不是真的龙虾，而是一个可以协助工作的AI工具。因为它的logo图案是一只龙虾，大家就顺其自然地把这个AI帮助工作的过程叫做“养龙虾”。OpenClaw is basically an AI tool that can do tasks on your computer (在电脑上做任务). 这款工具有些不同于我们熟悉的ChatGPT——它不仅能和你聊天（chat），你给它一个指令（give it a command），然后它就可以直接操作你的电脑（operate your computer）了。它就像一个真人帮手一样帮助完成各种任务，堪称“free digital assistant（免费的数字帮手）”。OpenClaw这个名字是怎么来的呢？（1）Open在科技领域（in tech）常与“开源（open source）”联系在一起，意味着the code is open（代码公开），大家都可以参与改进。例如，研究了ChatGPT的公司OpenAI，它名称里的open也是类似的意思。（2）Claw是指动物的“爪子”或者“钳子”。比如螃蟹（crabs）、龙虾（lobsters）的钳子都可以叫claw。所以除了因为logo是龙虾，网友们把它叫做“养龙虾”，还因为名字里的claw，也可以指龙虾钳子，就像帮大家抓任务（grabbing tasks）、做工作一样。Claw actually appears (出现) in other places in English. 比如a claw machine （抓娃娃机）。甚至有人开始把“claw”当作动词（verb）用：I'm going to claw this task.意思就是let the AI agent handle it (这个任务让AI帮忙去做)。《时代周刊》（Time Magazine）最近的一个标题也玩起了这个概念：Chat, Code, Claw: When AI Agents Work in Teams. 这三个词恰好概括了AI的进化路径（the evolution of AI），并且都是动词：先是用AI去chat（聊天），然后再code（写代码），最后就是claw（执行任务）了。其实OpenClaw最初的名字叫Clawdbot，意思是“机器人程序”，它巧妙地谐音了（wordplay）知名AI模型“Claude”。只是在其中嵌入了“claw”这个词，充满了互联网特有的幽默感（internet humor）。02. Different Attitudes towards OpenClaw 对待OpenClaw的不同态度人们对OpenClaw这个新的AI工具的态度也是多有不同。Some people say tools like this are really exciting. 一些用户表示：“This could save people a lot of time (大大提高工作效率). But there are also critical voices (批评之声). 有人认为：“OpenClaw might be overhyped (被炒作得太夸张了).”更有人直指其存在“安全隐患（security issue）”。正是这些担忧，让“第一批养虾人已经开始卸载（uninstall）”的话题冲上热搜。有些网友反馈在“养龙虾”的时候可能会泄露个人隐私，比如：它可能会给你多删了很多重要邮件。而且网友们会担心这个AI助手可能会获取sensitive data（敏感信息）。更有意思的是，随着“养龙虾”热潮的兴起，竟然衍生出了一个全新业务：“龙虾上门卸载服务”。因为有些用户自己不会卸载，或者是担心电脑里还残留有程序，所以就花钱找人上门帮忙卸载“龙虾”（pay someone to uninstall the OpenClaw）。03. Suggestions 专家建议面对这股“养龙虾”热潮，专家们也给出了几点建议：（1）Only download tools from official sources 使用官方最新版本Official sources 官方渠道（2）Limit their internet exposure 严格控制互联网暴露面不要让AI随便连接各种网站，也不要让它访问不必要的在线服务。（3）Don't give the AI unnecessary permissions 不给AI不必要的权限（4）Keep backups of important data 做好重要数据备份OpenClaw这类工具的出现，无疑展现了AI技术的飞速发展。但在拥抱新技术的同时，我们更需要保持理性。Technology is powerful, but we should use it wisely.对于“养龙虾”这件事，不必盲目跟风。如果你对它感到好奇（curious），可以先了解它的工作原理，再决定要不要“养”。

On this episode the Cincinnati Pink Pony crew joins us at the After Party as they talk about working and partying at the Cincinnati party bar. Matt tells us about his staycations at El Paso County jail and Mad's catches us up from her last episode and her ex drama. Follow us on social media @AaronScenesAfterParty

Every has unveiled a new product, built by CEO Dan Shipper. It's called Proof, a free, open-source, live collaborative document editor built for humans and AI agents to work in together. Proof started as a Mac app designed to show the provenance of AI-written text—purple for AI, green for human. But when Shipper rebuilt it as a web app with real-time collaboration, something clicked. Suddenly, everyone at Every was using it for everything from planning docs, to creative writing and even daily to-do lists. The team realized they needed a lightweight space where their OpenClaw agents and humans could co-author documents and leave comments. In this special episode, Shipper is joined by Every chief operating officer Brandon Gell, Cora general manager Kieran Klaassen, and head of growth Austin Tedesco to demo Proof live and share how it's changed the way they work. Brandon walks through a loop where his Codex agent writes a plan, Dan's personal Claw R2-C2 reviews it, and the humans just steer. Austin explains how he uses Proof to write a weekly food newsletter, texting ideas to his Claw on runs and watching an outline take shape. And Kieran makes the case that Proof's power is its lightness—just a link you can hand to any agent or colleague.The conversation covers what "agent native" means in practice, why AX (agent experience) matters as much as UX (user experience), what happens when 10 agents edit one document at the same time, and why some writing is now better read by an AI than a human.If you found this episode interesting, please like, subscribe, comment, and share!Want even more?Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It's usually only for paying subscribers, but you can get it here for free.To hear more from Dan Shipper:Subscribe to Every: https://every.to/subscribeFollow him on X: https://twitter.com/danshipperGet started building today at framer.com/dan for 30% OFF a Framer Pro annual plan.Download Grammarly for free at Grammarly.comTimestamps 00:02:00 — Introduction and the origin story of Proof00:07:24 — From Mac app to collaborative web editor00:09:00 — What makes Proof “agent native”00:14:30 — Live demo: watching an agent join and write inside a shared document00:20:51 — How Austin uses Proof for creative writing and food journalism00:24:30 — The challenge of multiple agents editing one document simultaneously00:26:48 — When AI-written docs are better read by agents than by humans00:29:30 — Brandon's agent-to-agent collaboration loop00:37:09 — Proof as a lightweight scratchpad vs. existing tools like Notion and GitHub00:42:18 — Why Proof is open source and what that means for buildersLinks to resources mentioned in the episode:Proof Editor: https://proofeditor.aiProof GitHub repo (open source): https://github.com/EveryInc/proofEvery's compound engineering plugin: https://github.com/EveryInc/compound-engineering-plugin

Parce que… c'est l'épisode 0x722! Shameless plug 31 mars au 2 avril 2026 - Forum INCYBER - Europe 2026 14 au 17 avril 2026 - Botconf 2026 20 au 22 avril 2026 - ITSec Code rabais de 15%: Seqcure15 28 et 29 avril 2026 - Cybereco Cyberconférence 2026 9 au 17 mai 2026 - NorthSec 2026 3 au 5 juin 2026 - SSTIC 2026 19 septembre 2026 - Bsides Montréal 1 au 3 décembre 2026 - Forum INCYBER - Canada 2026 24 et 25 février 2027 - SéQCure 2027 Description Nouveautés de Boost Security Labs François Proulx commence l'épisode en faisant le point sur les développements récents de son équipe. Boost Security a procédé à une refonte de son site web afin de distinguer clairement l'entreprise commerciale de son équipe de recherche, désormais appelée Boost Security Labs, accessible à l'adresse labs.security. Ce nouveau site centralise les articles, outils et références produits par les chercheurs. François mentionne également un article publié fin 2025 intitulé Defensive Research Weaponized — 2025 State of Pipeline Security, qui dressait un bilan de l'année et anticipait les types d'attaques qui se sont effectivement concrétisées depuis. L'équipe sera de retour à NorthSec cette année avec un nouveau talk et surtout un nouvel outil baptisé Smoke Meat — fidèle à la thématique culinaire montréalaise de l'équipe. Cet outil se veut le « Metasploit des pipelines CI/CD » : là où Poutine (leur outil d'analyse statique) détecte les vulnérabilités dans les pipelines de build, Smoke Meat permettra de les exploiter de manière semi-autonome, en proposant un menu d'options à l'utilisateur. Un troisième outil est aussi annoncé : Bagel, un utilitaire défensif qui tourne entièrement hors ligne et analyse la posture de sécurité des laptops de développeurs et administrateurs. Il détecte les mauvaises configurations locales — clés SSH non chiffrées, tokens hardcodés dans des scripts, etc. — pour limiter les dégâts en cas d'infection par un logiciel de type info stealer (ou « kleptogiciel », selon la terminologie de l'équipe Flare). L'attaque Hackerbot Claw : une offensive automatisée sur les pipelines CI/CD Sébastien Graveline prend ensuite la parole pour détailler une attaque survenue le 27 février, impliquant un agent automatisé qui a ciblé plusieurs grands projets open source. Au moins quatre projets ont été confirmés comme exploités. Ce qui rend cette attaque particulièrement notable, c'est qu'il s'agit d'un agent IA attaquant d'autres systèmes intégrant de l'IA dans leurs pipelines — un scénario que les chercheurs qualifient, avec un certain humour noir, de « bienvenue en 2026 ». L'équipe s'est concentrée notamment sur Aqua Security Trivy, un projet comptant plus de 25 000 étoiles sur GitHub. L'une des conséquences directes de l'attaque a été que le dépôt a été rendu privé ou supprimé, compliquant considérablement le travail d'investigation forensique. La piste de MégaGame : remonter le fil de l'attaque En examinant les discussions GitHub autour de l'incident, l'équipe repère une pull request (PR #10252) ouverte environ cinq heures avant la première attaque de Hackerbot, puis rapidement supprimée — un fait que personne d'autre n'avait mentionné dans les analyses publiées. L'utilisateur à son origine avait lui aussi été supprimé. Grâce à Trat Hunter, leur outil de surveillance en temps réel des événements GitHub, les chercheurs identifient l'acteur derrière cette PR : un utilisateur qu'ils surnomment Méga Game, dont le compte datait de début janvier. En remontant plus loin, ils trouvent qu'une tentative d'attaque similaire avait été détectée un mois auparavant sur ce qui semble être un dépôt de test. Forensique sur GitHub : fork networks et gists supprimés L'investigation se heurte à un obstacle de taille : le dépôt Trivy ayant été supprimé ou rendu privé, il n'est plus possible de cloner directement la version du commit exploité. C'est ici qu'entre en jeu un comportement peu connu de GitHub : lorsqu'un dépôt est supprimé, le fork network ne disparaît pas pour autant. Le plus ancien fork existant hérite automatiquement du rôle de racine du réseau, et l'intégralité des commits de tous les forks reste accessible tant qu'il reste au moins un fork vivant. L'équipe retrouve ainsi un fork avec une seule étoile mais… 3 000 forks rattachés, devenu malgré lui le patriarche de l'arbre. Cela leur permet de récupérer le payload de Méga Game, qui consiste en une exploitation d'action GitHub locale (local GitHub action exploit) : le workflow checkout le code de l'attaquant, puis exécute une action locale redéfinie par ce dernier — une variante classique du untrusted checkout. L'exploitation finale repose sur un curl pipe bash pointant vers un gist GitHub privé (mais non authentifié). Les chercheurs découvrent qu'il est possible de cloner un gist supprimé par son identifiant unique, à condition d'être authentifié sur GitHub — peu importe que ce soit le créateur original ou non. Un comportement probablement lié à la gestion du CDN de GitHub, qui conserve les objets tant qu'un garbage collection n'a pas eu lieu. L'essor des attaques automatisées sur les CI/CD L'épisode se conclut sur une réflexion plus large. Les attaques sur les pipelines CI/CD sont en croissance exponentielle, car ces environnements donnent accès à des ressources cloud critiques et que les secrets y sont souvent mal scopés. Dans le cas de Trivy, un simple workflow de commentaires a suffi à obtenir des droits administrateurs sur le projet. Face à cela, les recommandations sont claires : rouler des outils de détection comme Poutine, appliquer le principe de défense en profondeur (secrets correctement scopés, limitation des outils accessibles aux agents IA), et ne jamais oublier qu'un projet public est ouvert non seulement au téléchargement, mais aussi à l'attaque. L'équipe mentionne également des cas où Claude a détecté des tentatives de prompt injection et a correctement refusé d'exécuter les actions demandées — une lueur d'espoir dans un tableau par ailleurs assez sombre. Notes MegaGame10418: A Throwaway Account Linked to the Hackerbot-Claw Attack Nouveau site de Boostsecurity Labs Defensive Research, Weaponized: The 2025 State of Pipeline Security Collaborateurs Nicolas-Loïc Fortin Sébastien Graveline François Proulx Crédits Montage par Intrasecure inc Locaux virtuels par Riverside.fm

Join Kyle, Nader, Vibhu, and swyx live at NVIDIA GTC next week!Now that AIE Europe tix are ~sold out, our attention turns to Miami and World's Fair!The definitive AI Accelerator chip company has more than 10xed this AI Summer:And is now a $4.4 trillion megacorp… that is somehow still moving like a startup. We are blessed to have a unique relationship with our first ever NVIDIA guests: Kyle Kranen who gave a great inference keynote at the first World's Fair and is one of the leading architects of NVIDIA Dynamo (a Datacenter scale inference framework supporting SGLang, TRT-LLM, vLLM), and Nader Khalil, a friend of swyx from our days in Celo in The Arena, who has been drawing developers at GTC since before they were even a glimmer in the eye of NVIDIA:Nader discusses how NVIDIA Brev has drastically reduced the barriers to entry for developers to get a top of the line GPU up and running, and Kyle explains NVIDIA Dynamo as a data center scale inference engine that optimizes serving by scaling out, leveraging techniques like prefill/decode disaggregation, scheduling, and Kubernetes-based orchestration, framed around cost, latency, and quality tradeoffs. We also dive into Jensen's “SOL” (Speed of Light) first-principles urgency concept, long-context limits and model/hardware co-design, internal model APIs (https://build.nvidia.com), and upcoming Dynamo and agent sessions at GTC.Full Video pod on YouTubeTimestamps00:00 Agent Security Basics00:39 Podcast Welcome and Guests07:19 Acquisition and DevEx Shift13:48 SOL Culture and Dynamo Setup27:38 Why Scale Out Wins29:02 Scale Up Limits Explained30:24 From Laptop to Multi Node33:07 Cost Quality Latency Tradeoffs38:42 Disaggregation Prefill vs Decode41:05 Kubernetes Scaling with Grove43:20 Context Length and Co Design57:34 Security Meets Agents58:01 Agent Permissions Model59:10 Build Nvidia Inference Gateway01:01:52 Hackathons And Autonomy Dreams01:10:26 Local GPUs And Scaling Inference01:15:31 Long Running Agents And SF ReflectionsTranscriptAgent Security BasicsNader: Agents can do three things. They can access your files, they can access the internet, and then now they can write custom code and execute it. You literally only let an agent do two of those three things. If you can access your files and you can write custom code, you don't want internet access because that's one to see full vulnerability, right?If you have access to internet and your file system, you should know the full scope of what that agent's capable of doing. Otherwise, now we can get injected or something that can happen. And so that's a lot of what we've been thinking about is like, you know, how do we both enable this because it's clearly the future.But then also, you know, what, what are these enforcement points that we can start to like protect?swyx: All right.Podcast Welcome and Guestsswyx: Welcome to the Lean Space podcast in the Chromo studio. Welcome to all the guests here. Uh, we are back with our guest host Viu. Welcome. Good to have you back. And our friends, uh, Netter and Kyle from Nvidia. Welcome.Kyle: Yeah, thanks for having us.swyx: Yeah, thank you. Actually, I don't even know your titles.Uh, I know you're like architect something of Dynamo.Kyle: Yeah. I, I'm one of the engineering leaders [00:01:00] and a architects of Dynamo.swyx: And you're director of something and developers, developer tech.Nader: Yeah.swyx: You're the developers, developers, developers guy at nvidia,Nader: open source agent marketing, brev,swyx: and likeNader: Devrel tools and stuff.swyx: Yeah. BeenNader: the focus.swyx: And we're, we're kind of recording this ahead of Nvidia, GTC, which is coming to town, uh, again, uh, or taking over town, uh, which, uh, which we'll all be at. Um, and we'll talk a little bit about your sessions and stuff. Yeah.Nader: We're super excited for it.GTC Booth Stunt Storiesswyx: One of my favorite memories for Nader, like you always do like marketing stunts and like while you were at Rev, you like had this surfboard that you like, went down to GTC with and like, NA Nvidia apparently, like did so much that they bought you.Like what, what was that like? What was that?Nader: Yeah. Yeah, we, we, um. Our logo was a chaka. We, we, uh, we were always just kind of like trying to keep true to who we were. I think, you know, some stuff, startups, you're like trying to pretend that you're a bigger, more mature company than you are. And it was actually Evan Conrad from SF Compute who was just like, you guys are like previousswyx: guest.Yeah.Nader: Amazing. Oh, really? Amazing. Yeah. He was just like, guys, you're two dudes in the room. Why are you [00:02:00] pretending that you're not? Uh, and so then we were like, okay, let's make the logo a shaka. We brought surfboards to our booth to GTC and the energy was great. Yeah. Some palm trees too. They,Kyle: they actually poked out over like the, the walls so you could, you could see the bread booth.Oh, that's so funny. AndNader: no one else,Kyle: just from very far away.Nader: Oh, so you remember it backKyle: then? Yeah I remember it pre-acquisition. I was like, oh, those guys look cool,Nader: dude. That makes sense. ‘cause uh, we, so we signed up really last minute, and so we had the last booth. It was all the way in the corner. And so I was, I was worried that no one was gonna come.So that's why we had like the palm trees. We really came in with the surfboards. We even had one of our investors bring her dog and then she was just like walking the dog around to try to like, bring energy towards our booth. Yeah.swyx: Steph.Kyle: Yeah. Yeah, she's the best,swyx: you know, as a conference organizer, I love that.Right? Like, it's like everyone who sponsors a conference comes, does their booth. They're like, we are changing the future of ai or something, some generic b******t and like, no, like actually try to stand out, make it fun, right? And people still remember it after three years.Nader: Yeah. Yeah. You know what's so funny?I'll, I'll send, I'll give you this clip if you wanna, if you wanna add it [00:03:00] in, but, uh, my wife was at the time fiance, she was in medical school and she came to help us. ‘cause it was like a big moment for us. And so we, we bought this cricket, it's like a vinyl, like a vinyl, uh, printer. ‘cause like, how else are we gonna label the surfboard?So, we got a surfboard, luckily was able to purchase that on the company card. We got a cricket and it was just like fine tuning for enterprises or something like that, that we put on the. On the surfboard and it's 1:00 AM the day before we go to GTC. She's helping me put these like vinyl stickers on.And she goes, you son of, she's like, if you pull this off, you son of a b***h. And so, uh, right. Pretty much after the acquisition, I stitched that with the mag music acquisition. I sent it to our family group chat. Ohswyx: Yeah. No, well, she, she made a good choice there. Was that like basically the origin story for Launchable is that we, it was, and maybe we should explain what Brev is andNader: Yeah.Yeah. Uh, I mean, brev is just, it's a developer tool that makes it really easy to get a GPU. So we connect a bunch of different GPU sources. So the basics of it is like, how quickly can we SSH you into a G, into a GPU and whenever we would talk to users, they wanted A GPU. They wanted an A 100. And if you go to like any cloud [00:04:00] provisioning page, usually it's like three pages of forms or in the forms somewhere there's a dropdown.And in the dropdown there's some weird code that you know to translate to an A 100. And I remember just thinking like. Every time someone says they want an A 100, like the piece of text that they're telling me that they want is like, stuffed away in the corner. Yeah. And so we were like, what if the biggest piece of text was what the user's asking for?And so when you go to Brev, it's just big GPU chips with the type that you want withswyx: beautiful animations that you worked on pre, like pre you can, like, now you can just prompt it. But back in the day. Yeah. Yeah. Those were handcraft, handcrafted artisanal code.Nader: Yeah. I was actually really proud of that because, uh, it was an, i I made it in Figma.Yeah. And then I found, I was like really struggling to figure out how to turn it from like Figma to react. So what it actually is, is just an SVG and I, I have all the styles and so when you change the chip, whether it's like active or not it changes the SVG code and that somehow like renders like, looks like it's animating, but it, we just had the transition slow, but it's just like the, a JavaScript function to change the like underlying SVG.Yeah. And that was how I ended up like figuring out how to move it from from Figma. But yeah, that's Art Artisan. [00:05:00]Kyle: Speaking of marketing stunts though, he actually used those SVGs. Or kind of use those SVGs to make these cards.Nader: Oh yeah. LikeKyle: a GPU gift card Yes. That he handed out everywhere. That was actually my first impression of thatNader: one.Yeah,swyx: yeah, yeah.Nader: Yeah.swyx: I think I still have one of them.Nader: They look great.Kyle: Yeah.Nader: I have a ton of them still actually in our garage, which just, they don't have labels. We should honestly like bring, bring them back. But, um, I found this old printing press here, actually just around the corner on Ven ness. And it's a third generation San Francisco shop.And so I come in an excited startup founder trying to like, and they just have this crazy old machinery and I'm in awe. ‘cause the the whole building is so physical. Like you're seeing these machines, they have like pedals to like move these saws and whatever. I don't know what this machinery is, but I saw all three generations.Like there's like the grandpa, the father and the son, and the son was like, around my age. Well,swyx: it's like a holy, holy trinity.Nader: It's funny because we, so I just took the same SVG and we just like printed it and it's foil printing, so they make a a, a mold. That's like an inverse of like the A 100 and then they put the foil on it [00:06:00] and then they press it into the paper.And I remember once we got them, he was like, Hey, don't forget about us. You know, I guess like early Apple and Cisco's first business cards were all made there. And so he was like, yeah, we, we get like the startup businesses but then as they mature, they kind of go somewhere else. And so I actually, I think we were talking with marketing about like using them for some, we should go back and make some cards.swyx: Yeah, yeah, yeah. You know, I remember, you know, as a very, very small breadth investor, I was like, why are we spending time like, doing these like stunts for GPUs? Like, you know, I think like as a, you know, typical like cloud hard hardware person, you go into an AWS you pick like T five X xl, whatever, and it's just like from a list and you look at the specs like, why animate this GP?And, and I, I do think like it just shows the level of care that goes throughout birth and Yeah. And now, and also the, and,Nader: and Nvidia. I think that's what the, the thing that struck me most when we first came in was like the amount of passion that everyone has. Like, I think, um, you know, you talk to, you talk to Kyle, you talk to, like, every VP that I've met at Nvidia goes so close to the metal.Like, I remember it was almost a year ago, and like my VP asked me, he's like, Hey, [00:07:00] what's cursor? And like, are you using it? And if so, why? Surprised at this, and he downloaded Cursor and he was asking me to help him like, use it. And I thought that was, uh, or like, just show him what he, you know, why we were using it.And so, the amount of care that I think everyone has and the passion, appreciate, passion and appreciation for the moment. Right. This is a very unique time. So it's really cool to see everyone really like, uh, appreciate that.swyx: Yeah.Acquisition and DevEx Shiftswyx: One thing I wanted to do before we move over to sort of like research topics and, uh, the, the stuff that Kyle's working on is just tell the story of the acquisition, right?Like, not many people have been, been through an acquisition with Nvidia. What's it like? Uh, what, yeah, just anything you'd like to say.Nader: It's a crazy experience. I think, uh, you know, we were the thing that was the most exciting for us was. Our goal was just to make it easier for developers.We wanted to find access to GPUs, make it easier to do that. And then all, oh, actually your question about launchable. So launchable was just make one click exper, like one click deploys for any software on top of the GPU. Mm-hmm. And so what we really liked about Nvidia was that it felt like we just got a lot more resources to do all of that.I think, uh, you [00:08:00] know, NVIDIA's goal is to make things as easy for developers as possible. So there was a really nice like synergy there. I think that, you know, when it comes to like an acquisition, I think the amount that the soul of the products align, I think is gonna be. Is going speak to the success of the acquisition.Yeah. And so it in many ways feels like we're home. This is a really great outcome for us. Like we you know, I love brev.nvidia.com. Like you should, you should use it's, it's theKyle: front page for GPUs.Nader: Yeah. Yeah. If you want GP views,Kyle: you go there, getswyx: it there, and it's like internally is growing very quickly.I, I don't remember You said some stats there.Nader: Yeah, yeah, yeah. It's, uh, I, I wish I had the exact numbers, but like internally, externally, it's been growing really quickly. We've been working with a bunch of partners with a bunch of different customers and ISVs, if you have a solution that you want someone that runs on the GPU and you want people to use it quickly, we can bundle it up, uh, in a launchable and make it a one click run.If you're doing things and you want just like a sandbox or something to run on, right. Like open claw. Huge moment. Super exciting. Our, uh, and we'll talk into it more, but. You know, internally, people wanna run this, and you, we know we have to be really careful from the security implications. Do we let this run on the corporate network?Security's guidance was, Hey, [00:09:00] run this on breath, it's in, you know, it's, it's, it's a vm, it's sitting in the cloud, it's off the corporate network. It's isolated. And so that's been our stance internally and externally about how to even run something like open call while we figure out how to run these things securely.But yeah,swyx: I think there's also like, you almost like we're the right team at the right time when Nvidia is starting to invest a lot more in developer experience or whatever you call it. Yeah. Uh, UX or I don't know what you call it, like software. Like obviously NVIDIA is always invested in software, but like, there's like, this is like a different audience.Yeah. It's aNader: widerKyle: developer base.swyx: Yeah. Right.Nader: Yeah. Yeah. You know, it's funny, it's like, it's not, uh,swyx: so like, what, what is it called internally? What, what is this that people should be aware that is going on there?Nader: Uh, what, like developer experienceswyx: or, yeah, yeah. Is it's called just developer experience or is there like a broader strategy hereNader: in Nvidia?Um, Nvidia always wants to make a good developer experience. The thing is and a lot of the technology is just really complicated. Like, it's not, it's uh, you know, I think, um. The thing that's been really growing or the AI's growing is having a huge moment, not [00:10:00] because like, let's say data scientists in 2018, were quiet then and are much louder now.The pie is com, right? There's a whole bunch of new audiences. My mom's wondering what she's doing. My sister's learned, like taught herself how to code. Like the, um, you know, I, I actually think just generally AI's a big equalizer and you're seeing a more like technologically literate society, I guess.Like everyone's, everyone's learning how to code. Uh, there isn't really an excuse for that. And so building a good UX means that you really understand who your end user is. And when your end user becomes such a wide, uh, variety of people, then you have to almost like reinvent the practice, right? Yeah. You haveKyle: to, and actually build more developer ux, right?Because the, there are tiers of developer base that were added. You know, the, the hackers that are building on top of open claw, right? For example, have never used gpu. They don't know what kuda is. They, they, they just want to run something.Nader: Yeah.Kyle: You need new UX that is not just. Hey, you know, how do you program something in Cuda and run it?And then, and then we built, you know, like when Deep Learning was getting big, we built, we built Torch and, and, but so recently the amount of like [00:11:00] layers that are added to that developer stack has just exploded because AI has become ubiquitous. Everyone's using it in different ways. Yeah. It'sNader: moving fast in every direction.Vertical, horizontal.Vibhu: Yeah. You guys, you even take it down to hardware, like the DGX Spark, you know, it's, it's basically the same system as just throwing it up on big GPU cluster.Nader: Yeah, yeah, yeah. It's amazing. Blackwell.swyx: Yeah. Uh, we saw the preview at the last year's GTC and that was one of the better performing, uh, videos so far, and video coverage so far.Awesome. This will beat it. Um,Nader: that wasswyx: actually, we have fingersNader: crossed. Yeah.DGX Spark and Remote AccessNader: Even when Grace Blackwell or when, um, uh, DGX Spark was first coming out getting to be involved in that from the beginning of the developer experience. And it just comes back to what youswyx: were involved.Nader: Yeah. St. St.swyx: Mars.Nader: Yeah. Yeah. I mean from, it was just like, I, I got an email, we just got thrown into the loop and suddenly yeah, I, it was actually really funny ‘cause I'm still pretty fresh from the acquisition and I'm, I'm getting an email from a bunch of the engineering VPs about like, the new hardware, GPU chip, like we're, or not chip, but just GPU system that we're putting out.And I'm like, okay, cool. Matters. Now involved with this for the ux, I'm like. What am I gonna do [00:12:00] here? So, I remember the first meeting, I was just like kind of quiet as I was hearing engineering VPs talk about what this box could be, what it could do, how we should use it. And I remember, uh, one of the first ideas that people were idea was like, oh, the first thing that it was like, I think a quote was like, the first thing someone's gonna wanna do with this is get two of them and run a Kubernetes cluster on top of them.And I was like, oh, I think I know why I'm here. I was like, the first thing we're doing is easy. SSH into the machine. And then, and you know, just kind of like scoping it down of like, once you can do that every, you, like the person who wants to run a Kubernetes cluster onto Sparks has a higher propensity for pain, then, then you know someone who buys it and wants to run open Claw right now, right?If you can make sure that that's as effortless as possible, then the rest becomes easy. So there's a tool called Nvidia Sync. It just makes the SSH connection really simple. So, you know, if you think about it like. If you have a Mac, uh, or a PC or whatever, if you have a laptop and you buy this GPU and you want to use it, you should be able to use it like it's A-A-G-P-U in the cloud, right?Um, but there's all this friction of like, how do you actually get into that? That's part of [00:13:00] Revs value proposition is just, you know, there's a CLI that wraps SSH and makes it simple. And so our goal is just get you into that machine really easily. And one thing we just launched at CES, it's in, it's still in like early access.We're ironing out some kinks, but it should be ready by GTC. You can register your spark on Brev. And so now if youswyx: like remote managed yeah, local hardware. Single pane of glass. Yeah. Yeah. Because Brev can already manage other clouds anyway, right?Vibhu: Yeah, yeah. And you use the spark on Brev as well, right?Nader: Yeah. But yeah, exactly. So, so you, you, so you, you set it up at home you can run the command on it, and then it gets it's essentially it'll appear in your Brev account, and then you can take your laptop to a Starbucks or to a cafe, and you'll continue to use your, you can continue use your spark just like any other cloud node on Brev.Yeah. Yeah. And it's just like a pre-provisioned centerswyx: in yourNader: home. Yeah, exactly.swyx: Yeah. Yeah.Vibhu: Tiny little data center.Nader: Tiny little, the size ofVibhu: your phone.SOL Culture and Dynamo Setupswyx: One more thing before we move on to Kyle. Just have so many Jensen stories and I just love, love mining Jensen stories. Uh, my favorite so far is SOL. Uh, what is, yeah, what is S-O-L-S-O-LNader: is actually, i, I think [00:14:00] of all the lessons I've learned, that one's definitely my favorite.Kyle: It'll always stick with you.Nader: Yeah. Yeah. I, you know, in your startup, everything's existential, right? Like we've, we've run out of money. We were like, on the risk of, of losing payroll, we've had to contract our team because we l ran outta money. And so like, um, because of that you're really always forcing yourself to I to like understand the root cause of everything.If you get a date, if you get a timeline, you know exactly why that date or timeline is there. You're, you're pushing every boundary and like, you're not just say, you're not just accepting like a, a no. Just because. And so as you start to introduce more layers, as you start to become a much larger organization, SOL is is essentially like what is the physics, right?The speed of light moves at a certain speed. So if flight's moving some slower, then you know something's in the way. So before trying to like layer reality back in of like, why can't this be delivered at some date? Let's just understand the physics. What is the theoretical limit to like, uh, how fast this can go?And then start to tell me why. ‘cause otherwise people will start telling you why something can't be done. But actually I think any great leader's goal is just to create urgency. Yeah. [00:15:00] There's an infiniteKyle: create compelling events, right?Nader: Yeah.Kyle: Yeah. So l is a term video is used to instigate a compelling event.You say this is done. How do we get there? What is the minimum? As much as necessary, as little as possible thing that it takes for us to get exactly here and. It helps you just break through a bunch of noise.swyx: Yeah.Kyle: Instantly.swyx: One thing I'm unclear about is, can only Jensen use the SOL card? Like, oh, no, no, no.Not everyone get the b******t out because obviously it's Jensen, but like, can someone else be like, no, likeKyle: frontline engineers use it.Nader: Yeah. Every, I think it's not so much about like, get the b******t out. It's like, it's like, give me the root understanding, right? Like, if you tell me something takes three weeks, it like, well, what's the first principles?Yeah, the first principles. It's like, what's the, what? Like why is it three weeks? What is the actual yeah. What's the actual limit of why this is gonna take three weeks? If you're gonna, if you, if let's say you wanted to buy a new computer and someone told you it's gonna be here in five days, what's the SOL?Well, like the SOL is like, I could walk into a Best Buy and pick it up for you. Right? So then anything that's like beyond that is, and is that practical? Is that how we're gonna, you know, let's say give everyone in the [00:16:00] company a laptop, like obviously not. So then like that's the SOL and then it's like, okay, well if we have to get more than 10, suddenly there might be some, right?And so now we can kind of piece the reality back.swyx: So, so this is the. Paul Graham do things that don't scale. Yeah. And this is also the, what people would now call behi agency. Yeah.Kyle: It's actually really interesting because there's a, there's a second hardware angle to SOL that like doesn't come up for all the org sol is used like culturally at aswyx: media for everything.I'm also mining for like, I think that can be annoying sometimes. And like someone keeps going IOO you and you're like, guys, like we have to be stable. We have to, we to f*****g plan. Yeah.Kyle: It's an interesting balance.Nader: Yeah. I encounter that with like, actually just with, with Alec, right? ‘cause we, we have a new conference so we need to launch, we have, we have goals of what we wanna launch by, uh, by the conference and like, yeah.At the end of the day, where isswyx: this GTC?Nader: Um, well this is like, so we, I mean we did it for CES, we did for GT CDC before that we're doing it for GTC San Jose. So I mean, like every, you know, we have a new moment. Um, and we want to launch something. Yeah. And we want to do so at SOL and that does mean that some, there's some level of prioritization that needs [00:17:00] to happen.And so it, it is difficult, right? I think, um, you have to be careful with what you're pushing. You know, stability is important and that should be factored into S-O-L-S-O-L isn't just like, build everything and let it break, you know, that, that's part of the conversation. So as you're laying, layering in all the details, one of them might be, Hey, we could build this, but then it's not gonna be stable for X, y, z reasons.And so that was like, one of our conversations for CES was, you know, hey, like we, we can get this into early access registering your spark with brev. But there are a lot of things that we need to do in order to feel really comfortable from a security perspective, right? There's a lot of networking involved before we deliver that to users.So it's like, okay. Let's get this to a point where we can at least let people experiment with it. We had it in a booth, we had it in Jensen's keynote, and then let's go iron out all the networking kinks. And that's not easy. And so, uh, that can come later. And so that was the way that we layered that back in.Yeah. ButKyle: It's not really about saying like, you don't have to do the, the maintenance or operational work. It's more about saying, you know, it's kind of like [00:18:00] highlights how progress is incremental, right? Like, what is the minimum thing that we can get to. And then there's SOL for like every component after that.But there's the SOL to get you, get you to the, the starting line. And that, that's usually how it's asked. Yeah. On the other side, you know, like SOL came out of like hardware at Nvidia. Right. So SOL is like literally if we ran the accelerator or the GPU with like at basically full speed with like no other constraints, like how FAST would be able to make a program go.swyx: Yeah. Yeah. Right.Kyle: Soswyx: in, in training that like, you know, then you work back to like some percentage of like MFU for example.Kyle: Yeah, that's a, that's a great example. So like, there's an, there's an S-O-L-M-F-U, and then there's like, you know, what's practically achievable.swyx: Cool. Should we move on to sort of, uh, Kyle's side?Uh, Kyle, you're coming more from the data science world. And, uh, I, I mean I always, whenever, whenever I meet someone who's done working in tabular stuff, graph neural networks, time series, these are basically when I go to new reps, I go to ICML, I walk the back halls. There's always like a small group of graph people.Yes. Absolute small group of tabular people. [00:19:00] And like, there's no one there. And like, it's very like, you know what I mean? Like, yeah, no, like it's, it's important interesting work if you care about solving the problems that they solve.Kyle: Yeah.swyx: But everyone else is just LMS all the time.Kyle: Yeah. I mean it's like, it's like the black hole, right?Has the event horizon reached this yet in nerves? Um,swyx: but like, you know, those are, those are transformers too. Yeah. And, and those are also like interesting things. Anyway, uh, I just wanted to spend a little bit of time on, on those, that background before we go into Dynamo, uh, proper.Kyle: Yeah, sure. I took a different path to Nvidia than that, or I joined six years ago, seven, if you count, when I was an intern.So I joined Nvidia, like right outta college. And the first thing I jumped into was not what I'd done in, during internship, which was like, you know, like some stuff for autonomous vehicles, like heavyweight object detection. I jumped into like, you know, something, I'm like, recommenders, this is popular. Andswyx: yeah, he did RexiKyle: as well.Yeah, Rexi. Yeah. I mean that, that was the taboo data at the time, right? You have tables of like, audience qualities and item qualities, and you're trying to figure out like which member of [00:20:00] the audience matches which item or, or more practically which item matches which member of the audience. And at the time, really it was like we were trying to enable.Uh, recommender, which had historically been like a little bit of a CP based workflow into something that like, ran really well in GPUs. And it's since been done. Like there are a bunch of libraries for Axis that run on GPUs. Uh, the common models like Deeplearning recommendation model, which came outta meta and the wide and deep model, which was used or was released by Google were very accelerated by GPUs using, you know, the fast HBM on the chips, especially to do, you know, vector lookups.But it was very interesting at the time and super, super relevant because like we were starting to get like. This explosion of feeds and things that required rec recommenders to just actively be on all the time. And sort of transitioned that a little bit towards graph neural networks when I discovered them because I was like, okay, you can actually use graphical neural networks to represent like, relationships between people, items, concepts, and that, that interested me.So I jumped into that at [00:21:00] Nvidia and, and got really involved for like two-ish years.swyx: Yeah. Uh, and something I learned from Brian Zaro Yeah. Is that you can just kind of choose your own path in Nvidia.Kyle: Oh my God. Yeah.swyx: Which is not a normal big Corp thing. Yeah. Like you, you have a lane, you stay in your lane.Nader: I think probably the reason why I enjoy being in a, a big company, the mission is the boss probably from a startup guy. Yeah. The missionswyx: is the boss.Nader: Yeah. Uh, it feels like a big game of pickup basketball. Like, you know, if you play one, if you wanna play basketball, you just go up to the court and you're like, Hey look, we're gonna play this game and we need three.Yeah. And you just like find your three. That's honestly for every new initiative that's what it feels like. Yeah.Vibhu: It also like shows, right? Like Nvidia. Just releasing state-of-the-art stuff in every domain. Yeah. Like, okay, you expect foundation models with Nemo tron voice just randomly parakeet.Call parakeet just comes out another one, uh, voice. TheKyle: video voice team has always been producing.Vibhu: Yeah. There's always just every other domain of paper that comes out, dataset that comes out. It's like, I mean, it also stems back to what Nvidia has to do, right? You have to make chips years before they're actually produced.Right? So you need to know, you need to really [00:22:00] focus. TheKyle: design process starts likeVibhu: exactlyKyle: three to five years before the chip gets to the market.Vibhu: Yeah. I, I'm curious more about what that's like, right? So like, you have specialist teams. Is it just like, you know, people find an interest, you go in, you go deep on whatever, and that kind of feeds back into, you know, okay, we, we expect predictions.Like the internals at Nvidia must be crazy. Right? You know? Yeah. Yeah. You know, you, you must. Not even without selling to people, you have your own predictions of where things are going. Yeah. And they're very based, very grounded. Right?Kyle: Yeah. It, it, it's really interesting. So there's like two things that I think that Amed does, which are quite interesting.Uh, one is like, we really index into passion. There's a big. Sort of organizational top sound push to like ensure that people are working on the things that they're passionate about. So if someone proposes something that's interesting, many times they can just email someone like way up the chain that they would find this relevant and say like, Hey, can I go work on this?Nader: It's actually like I worked at a, a big company for a couple years before, uh, starting on my startup journey and like, it felt very weird if you were to like email out of chain, if that makes [00:23:00] sense. Yeah. The emails at Nvidia are like mosh pitsswyx: shoot,Nader: and it's just like 60 people, just whatever. And like they're, there's this,swyx: they got messy like, reply all you,Nader: oh, it's in, it's insane.It's insane. They justKyle: help. You know, Maxim,Nader: the context. But, but that's actually like, I've actually, so this is a weird thing where I used to be like, why would we send emails? We have Slack. I am the entire, I'm the exact opposite. I feel so bad for anyone who's like messaging me on Slack ‘cause I'm so unresponsive.swyx: Your emailNader: Maxi, email Maxim. I'm email maxing Now email is a different, email is perfect because man, we can't work together. I'm email is great, right? Because important threads get bumped back up, right? Yeah, yeah. Um, and so Slack doesn't do that. So I just have like this casino going off on the right or on the left and like, I don't know which thread was from where or what, but like the threads get And then also just like the subject, so you can have like working threads.I think what's difficult is like when you're small, if you're just not 40,000 people I think Slack will work fine, but there's, I don't know what the inflection point is. There is gonna be a point where that becomes really messy and you'll actually prefer having email. ‘cause you can have working threads.You can cc more than nine people in a thread.Kyle: You can fork stuff.Nader: You can [00:24:00] fork stuff, which is super nice and just like y Yeah. And so, but that is part of where you can propose a plan. You can also just. Start, honestly, momentum's the only authority, right? So like, if you can just start, start to make a little bit of progress and show someone something, and then they can try it.That's, I think what's been, you know, I think the most effective way to push anything for forward. And that's both at Nvidia and I think just generally.Kyle: Yeah, there's, there's the other concept that like is explored a lot at Nvidia, which is this idea of a zero billion dollar business. Like market creation is a big thing at Nvidia.Like,swyx: oh, you want to go and start a zero billion dollar business?Kyle: Jensen says, we are completely happy investing in zero billion dollar markets. We don't care if this creates revenue. It's important for us to know about this market. We think it will be important in the future. It can be zero billion dollars for a while.I'm probably minging as words here for, but like, you know, like, I'll give an example. NVIDIA's been working on autonomous driving for a a long time,swyx: like an Nvidia car.Kyle: No, they, they'veVibhu: used the Mercedes, right? They're around the HQ and I think it finally just got licensed out. Now they're starting to be used quite a [00:25:00] bit.For 10 years you've been seeing Mercedes with Nvidia logos driving.Kyle: If you're in like the South San Santa Clara, it's, it's actually from South. Yeah. So, um. Zero billion dollar markets are, are a thing like, you know, Jensen,swyx: I mean, okay, look, cars are not a zero billion dollar market. But yeah, that's a bad example.Nader: I think, I think he's, he's messaging, uh, zero today, but, or even like internally, right? Like, like it's like, uh, an org doesn't have to ruthlessly find revenue very quickly to justify their existence. Right. Like a lot of the important research, a lot of the important technology being developed that, that's kind ofKyle: where research, research is very ide ideologically free at Nvidia.Yeah. Like they can pursue things that they wereswyx: Were you research officially?Kyle: I was never in research. Officially. I was always in engineering. Yeah. We in, I'm in an org called Deep Warning Algorithms, which is basically just how do we make things that are relevant to deep warning go fast.swyx: That sounds freaking cool.Vibhu: And I think a lot of that is underappreciated, right? Like time series. This week Google put out time. FF paper. Yeah. A new time series, paper res. Uh, Symantec, ID [00:26:00] started applying Transformers LMS to Yes. Rec system. Yes. And when you think the scale of companies deploying these right. Amazon recommendations, Google web search, it's like, it's huge scale andKyle: Yeah.Vibhu: You want fast?Kyle: Yeah. Yeah. Yeah. Actually it's, it, I, there's a fun moment that brought me like full circle. Like, uh, Amazon Ads recently gave a talk where they talked about using Dynamo for generative recommendation, which was like super, like weirdly cathartic for me. I'm like, oh my God. I've, I've supplanted what I was working on.Like, I, you're using LMS now to do what I was doing five years ago.swyx: Yeah. Amazing. And let's go right into Dynamo. Uh, maybe introduce Yeah, sure. To the top down and Yeah.Kyle: I think at this point a lot of people are familiar with the term of inference. Like funnily enough, like I went from, you know, inference being like a really niche topic to being something that's like discussed on like normal people's Twitter feeds.It's,Nader: it's on billboardsKyle: here now. Yeah. Very, very strange. Driving, driving, seeing just an inference ad on 1 0 1 inference at scale is becoming a lot more important. Uh, we have these moments like, you know, open claw where you have these [00:27:00] agents that take lots and lots of tokens, but produce, incredible results.There are many different aspects of test time scaling so that, you know, you can use more inference to generate a better result than if you were to use like a short amount of inference. There's reasoning, there's quiring, there's, adding agency to the model, allowing it to call tools and use skills.Dyno sort came about at Nvidia. Because myself and a couple others were, were sort of talking about the, these concepts that like, you know, you have inference engines like VLMS, shelan, tenor, TLM and they have like one single copy. They, they, they sort of think about like things as like one single copy, like one replica, right?Why Scale Out WinsKyle: Like one version of the model. But when you're actually serving things at scale, you can't just scale up that replica because you end up with like performance problems. There's a scaling limit to scaling up replicas. So you actually have to scale out to use a, maybe some Kubernetes type terminology.We kind of realized that there was like. A lot of potential optimization that we could do in scaling out and building systems for data [00:28:00] center scale inference. So Dynamo is this data center scale inference engine that sits on top of the frameworks like VLM Shilling and 10 T lm and just makes things go faster because you can leverage the economy of scale.The fact that you have KV cash, which we can define a little bit later, uh, in all these machines that is like unique and you wanna figure out like the ways to maximize your cash hits or you want to employ new techniques in inference like disaggregation, which Dynamo had introduced to the world in, in, in March, not introduced, it was a academic talk, but beforehand.But we are, you know, one of the first frameworks to start, supporting it. And we wanna like, sort of combine all these techniques into sort of a modular framework that allows you to. Accelerate your inference at scale.Nader: By the way, Kyle and I became friends on my first date, Nvidia, and I always loved, ‘cause like he always teaches meswyx: new things.Yeah. By the way, this is why I wanted to put two of you together. I was like, yeah, this is, this is gonna beKyle: good. It's very, it's very different, you know, like we've, we, we've, we've talked to each other a bunch [00:29:00] actually, you asked like, why, why can't we scale up?Nader: Yeah.Scale Up Limits ExplainedNader: model, you said model replicas.Kyle: Yeah. So you, so scale up means assigning moreswyx: heavier?Kyle: Yeah, heavier. Like making things heavier. Yeah, adding more GPUs. Adding more CPUs. Scale out is just like having a barrier saying, I'm gonna duplicate my representation of the model or a representation of this microservice or something, and I'm gonna like, replicate it Many times.Handle, load. And the reason that you can't scale, scale up, uh, past some points is like, you know, there, there, there are sort of hardware bounds and algorithmic bounds on, on that type of scaling. So I'll give you a good example that's like very trivial. Let's say you're on an H 100. The Maxim ENV link domain for H 100, for most Ds H one hundreds is heus, right?So if you scaled up past that, you're gonna have to figure out ways to handle the fact that now for the GPUs to communicate, you have to do it over Infin band, which is still very fast, but is not as fast as ENV link.swyx: Is it like one order of magnitude, like hundreds or,Kyle: it's about an order of magnitude?Yeah. Okay. Um, soswyx: not terrible.Kyle: [00:30:00] Yeah. I, I need to, I need to remember the, the data sheet here, like, I think it's like about 500 gigabytes. Uh, a second unidirectional for ENV link, and about 50 gigabytes a second unidirectional for Infin Band. I, it, it depends on the, the generation.swyx: I just wanna set this up for people who are not familiar with these kinds of like layers and the trash speedVibhu: and all that.Of course.From Laptop to Multi NodeVibhu: Also, maybe even just going like a few steps back before that, like most people are very familiar with. You see a, you know, you can use on your laptop, whatever these steel viol, lm you can just run inference there. All, there's all, you can, youcan run it on thatVibhu: laptop. You can run on laptop.Then you get to, okay, uh, models got pretty big, right? JLM five, they doubled the size, so mm-hmm. Uh, what do you do when you have to go from, okay, I can get 128 gigs of memory. I can run it on a spark. Then you have to go multi GPU. Yeah. Okay. Multi GPU, there's some support there. Now, if I'm a company and I don't have like.I'm not hiring the best researchers for this. Right. But I need to go [00:31:00] multi-node, right? I have a lot of servers. Okay, now there's efficiency problems, right? You can have multiple eight H 100 nodes, but, you know, is that as a, like, how do you do that efficiently?Kyle: Yeah. How do you like represent them? How do you choose how to represent the model?Yeah, exactly right. That's a, that's like a hard question. Everyone asks, how do you size oh, I wanna run GLM five, which just came out new model. There have been like four of them in the past week, by the way, like a bunch of new models.swyx: You know why? Right? Deep seek.Kyle: No comment. Oh. Yeah, but Ggl, LM five, right?We, we have this, new model. It's, it's like a large size, and you have to figure out how to both scale up and scale out, right? Because you have to find the right representation that you care about. Everyone does this differently. Let's be very clear. Everyone figures this out in their own path.Nader: I feel like a lot of AI or ML even is like, is like this. I think people think, you know, I, I was, there was some tweet a few months ago that was like, why hasn't fine tuning as a service taken off? You know, that might be me. It might have been you. Yeah. But people want it to be such an easy recipe to follow.But even like if you look at an ML model and specificKyle: to you Yeah,Nader: yeah.Kyle: And the [00:32:00] model,Nader: the situation, and there's just so much tinkering, right? Like when you see a model that has however many experts in the ME model, it's like, why that many experts? I don't, they, you know, they tried a bunch of things and that one seemed to do better.I think when it comes to how you're serving inference, you know, you have a bunch of decisions to make and there you can always argue that you can take something and make it more optimal. But I think it's this internal calibration and appetite for continued calibration.Vibhu: Yeah. And that doesn't mean like, you know, people aren't taking a shot at this, like tinker from thinking machines, you know?Yeah. RL as a service. Yeah, totally. It's, it also gets even harder when you try to do big model training, right? We're not the best at training Moes, uh, when they're pre-trained. Like we saw this with LAMA three, right? They're trained in such a sparse way that meta knows there's gonna be a bunch of inference done on these, right?They'll open source it, but it's very trained for what meta infrastructure wants, right? They wanna, they wanna inference it a lot. Now the question to basically think about is, okay, say you wanna serve a chat application, a coding copilot, right? You're doing a layer of rl, you're serving a model for X amount of people.Is it a chat model, a coding model? Dynamo, you know, back to that,Kyle: it's [00:33:00] like, yeah, sorry. So you we, we sort of like jumped off of, you know, jumped, uh, on that topic. Everyone has like, their own, own journey.Cost Quality Latency TradeoffsKyle: And I, I like to think of it as defined by like, what is the model you need? What is the accuracy you need?Actually I talked to NA about this earlier. There's three axes you care about. What is the quality that you're able to produce? So like, are you accurate enough or can you complete the task with enough, performance, high enough performance. Yeah, yeah. Uh, there's cost. Can you serve the model or serve your workflow?Because it's not just the model anymore, it's the workflow. It's the multi turn with an agent cheaply enough. And then can you serve it fast enough? And we're seeing all three of these, like, play out, like we saw, we saw new models from OpenAI that you know, are faster. You have like these new fast versions of models.You can change the amount of thinking to change the amount of quality, right? Produce more tokens, but at a higher cost in a, in a higher latency. And really like when you start this journey of like trying to figure out how you wanna host a model, you, you, you think about three things. What is the model I need to serve?How many times do I need to call it? What is the input sequence link was [00:34:00] the, what does the workflow look like on top of it? What is the SLA, what is the latency SLA that I need to achieve? Because there's usually some, this is usually like a constant, you, you know, the SLA that you need to hit and then like you try and find the lowest cost version that hits all of these constraints.Usually, you know, you, you start with those things and you say you, you kind of do like a bit of experimentation across some common configurations. You change the tensor parallel size, which is a form of parallelismVibhu: I take, it goes even deeper first. Gotta think what model.Kyle: Yes, course,ofKyle: course. It's like, it's like a multi-step design process because as you said, you can, you can choose a smaller model and then do more test time scaling and it'll equate the quality of a larger model because you're doing the test time scaling or you're adding a harness or something.So yes, it, it goes way deeper than that. But from the performance perspective, like once you get to the model you need, you need to host, you look at that and you say, Hey. I have this model, I need to serve it at the speed. What is the right configuration for that?Nader: You guys see the recent, uh, there was a paper I just saw like a few days ago that, uh, if you run [00:35:00] the same prompt twice, you're getting like double Just try itagain.Nader: Yeah, exactly.Vibhu: And you get a lot. Yeah. But the, the key thing there is you give the context of the failed try, right? Yeah. So it takes a shot. And this has been like, you know, basic guidance for quite a while. Just try again. ‘cause you know, trying, just try again. Did you try again? All adviceNader: in life.Vibhu: Just, it's a paper from Google, if I'm not mistaken, right?Yeah,Vibhu: yeah. I think it, it's like a seven bas little short paper. Yeah. Yeah. The title's very cute. And it's just like, yeah, just try again. Give it ask context,Kyle: multi-shot. You just like, say like, hey, like, you know, like take, take a little bit more, take a little bit more information, try and fail. Fail.Vibhu: And that basic concept has gone pretty deep.There's like, um, self distillation, rl where you, you do self distillation, you do rl and you have past failure and you know, that gives some signal so people take, try it again. Not strong enough.swyx: Uh, for, for listeners, uh, who listen to here, uh, vivo actually, and I, and we run a second YouTube channel for our paper club where, oh, that's awesome.Vivo just covered this. Yeah. Awesome. Self desolation and all that's, that's why he, to speed [00:36:00] on it.Nader: I'll to check it out.swyx: Yeah. It, it's just a good practice, like everyone needs, like a paper club where like you just read papers together and the social pressure just kind of forces you to just,Nader: we, we,there'sNader: like a big inference.Kyle: ReadingNader: group at a video. I feel so bad every time. I I, he put it on like, on our, he shared it.swyx: One, one ofNader: your guys,swyx: uh, is, is big in that, I forget es han Yeah, yeah,Kyle: es Han's on my team. Actually. Funny. There's a, there's a, there's a employee transfer between us. Han worked for Nater at Brev, and now he, he's on my team.He wasNader: our head of ai. And then, yeah, once we got in, andswyx: because I'm always looking for like, okay, can, can I start at another podcast that only does that thing? Yeah. And, uh, Esan was like, I was trying to like nudge Esan into like, is there something here? I mean, I don't think there's, there's new infant techniques every day.So it's like, it's likeKyle: you would, you would actually be surprised, um, the amount of blog posts you see. And ifswyx: there's a period where it was like, Medusa hydra, what Eagle, like, youKyle: know, now we have new forms of decode, uh, we have new forms of specula, of decoding or new,swyx: what,Kyle: what are youVibhu: excited? And it's exciting when you guys put out something like Tron.‘cause I remember the paper on this Tron three, [00:37:00] uh, the amount of like post train, the on tokens that the GPU rich can just train on. And it, it was a hybrid state space model, right? Yeah.Kyle: It's co-designed for the hardware.Vibhu: Yeah, go design for the hardware. And one of the things was always, you know, the state space models don't scale as well when you do a conversion or whatever the performance.And you guys are like, no, just keep draining. And Nitron shows a lot of that. Yeah.Nader: Also, something cool about Nitron it was released in layers, if you will, very similar to Dynamo. It's, it's, it's essentially it was released as you can, the pre-training, post-training data sets are released. Yeah. The recipes on how to do it are released.The model itself is released. It's full model. You just benefit from us turning on the GPUs. But there are companies like, uh, ServiceNow took the dataset and they trained their own model and we were super excited and like, you know, celebrated that work.ZoomVibhu: different. Zoom is, zoom is CGI, I think, uh, you know, also just to add like a lot of models don't put out based models and if there's that, why is fine tuning not taken off?You know, you can do your own training. Yeah,Kyle: sure.Vibhu: You guys put out based model, I think you put out everything.Nader: I believe I know [00:38:00]swyx: about base. BasicallyVibhu: without baseswyx: basic can be cancelable.Vibhu: Yeah. Base can be cancelable.swyx: Yeah.Vibhu: Safety training.swyx: Did we get a full picture of dymo? I, I don't know if we, what,Nader: what I'd love is you, you mentioned the three axes like break it down of like, you know, what's prefilled decode and like what are the optimizations that we can get with Dynamo?Kyle: Yeah. That, that's, that's, that's a great point. So to summarize on that three axis problem, right, there are three things that determine whether or not something can be done with inference, cost, quality, latency, right? Dynamo is supposed to be there to provide you like the runtime that allows you to pull levers to, you know, mix it up and move around the parade of frontier or the preto surface that determines is this actually possible with inference And AI todayNader: gives you the knobs.Kyle: Yeah, exactly. It gives you the knobs.Disaggregation Prefill vs DecodeKyle: Uh, and one thing that like we, we use a lot in contemporary inference and is, you know, starting to like pick up from, you know, in, in general knowledge is this co concept of disaggregation. So historically. Models would be hosted with a single inference engine. And that inference engine [00:39:00] would ping pong between two phases.There's prefill where you're reading the sequence generating KV cache, which is basically just a set of vectors that represent the sequence. And then using that KV cache to generate new tokens, which is called Decode. And some brilliant researchers across multiple different papers essentially made the realization that if you separate these two phases, you actually gain some benefits.Those benefits are basically a you don't have to worry about step synchronous scheduling. So the way that an inference engine works is you do one step and then you finish it, and then you schedule, you start scheduling the next step there. It's not like fully asynchronous. And the problem with that is you would have, uh, essentially pre-fill and decode are, are actually very different in terms of both their resource requirements and their sometimes their runtime.So you would have like prefill that would like block decode steps because you, you'd still be pre-filing and you couldn't schedule because you know the step has to end. So you remove that scheduling issue and then you also allow you, or you yourself, to like [00:40:00] split the work into two different ki types of pools.So pre-fill typically, and, and this changes as, as model architecture changes. Pre-fill is, right now, compute bound most of the time with the sequence is sufficiently long. It's compute bound. On the decode side because you're doing a full Passover, all the weights and the entire sequence, every time you do a decode step and you're, you don't have the quadratic computation of KV cache, it's usually memory bound because you're retrieving a linear amount of memory and you're doing a linear amount of compute as opposed to prefill where you retrieve a linear amount of memory and then use a quadratic.You know,Nader: it's funny, someone exo Labs did a really cool demo where for the DGX Spark, which has a lot more compute, you can do the pre the compute hungry prefill on a DG X spark and then do the decode on a, on a Mac. Yeah. And soVibhu: that's faster.Nader: Yeah. Yeah.Kyle: So you could, you can do that. You can do machine strat stratification.Nader: Yeah.Kyle: And like with our future generation generations of hardware, we actually announced, like with Reuben, this [00:41:00] new accelerator that is prefilled specific. It's called Reuben, CPX. SoKubernetes Scaling with GroveNader: I have a question when you do the scale out. Yeah. Is scaling out easier with Dynamo? Because when you need a new node, you can dedicate it to either the Prefill or, uh, decode.Kyle: Yeah. So Dynamo actually has like a, a Kubernetes component in it called Grove that allows you to, to do this like crazy scaling specialization. It has like this hot, it's a representation that, I don't wanna go too deep into Kubernetes here, but there was a previous way that you would like launch multi-node work.Uh, it's called Leader Worker Set. It's in the Kubernetes standard, and Leader worker set is great. It served a lot of people super well for a long period of time. But one of the things that it's struggles with is representing a set of cases where you have a multi-node replica that has a pair, right?You know, prefill and decode, or it's not paired, but it has like a second stage that has a ratio that changes over time. And prefill and decode are like two different things as your workload changes, right? The amount of prefill you'll need to do may change. [00:42:00] The amount of decode that you, you'll need to do might change, right?Like, let's say you start getting like insanely long queries, right? That probably means that your prefill scales like harder because you're hitting these, this quadratic scaling growth.swyx: Yeah.And then for listeners, like prefill will be long input. Decode would be long output, for example, right?Kyle: Yeah. So like decode, decode scale. I mean, decode is funny because the amount of tokens that you produce scales with the output length, but the amount of work that you do per step scales with the amount of tokens in the context.swyx: Yes.Kyle: So both scales with the input and the output.swyx: That's true.Kyle: But on the pre-fold view code side, like if.Suddenly, like the amount of work you're doing on the decode side stays about the same or like scales a little bit, and then the prefilled side like jumps up a lot. You actually don't want that ratio to be the same. You want it to change over time. So Dynamo has a set of components that A, tell you how to scale.It tells you how many prefilled workers and decoded workers you, it thinks you should have, and also provides a scheduling API for Kubernetes that allows you to actually represent and affect this scheduling on, on, on your actual [00:43:00] hardware, on your compute infrastructure.Nader: Not gonna lie. I feel a little embarrassed for being proud of my SVG function earlier.swyx: No, itNader: wasreallyKyle: cute. I, Iswyx: likeNader: it's all,swyx: it's all engineering. It's all engineering. Um, that's where I'mKyle: technical.swyx: One thing I'm, I'm kind of just curious about with all with you see at a systems level, everything going on here. Mm-hmm. And we, you know, we're scaling it up in, in multi, in distributed systems.Context Length and Co Designswyx: Um, I think one thing that's like kind of, of the moment right now is people are asking, is there any SOL sort of upper bounds. In terms of like, let's call, just call it context length for one for of a better word, but you can break it down however you like.Nader: Yeah.swyx: I just think like, well, yeah, I mean, like clearly you can engage in hybrid architectures and throw in some state space models in there.All, all you want, but it looks, still looks very attention heavy.Kyle: Yes. Uh, yeah. Long context is attention heavy. I mean, we have these hybrid models, um,swyx: to take and most, most models like cap out at a million contexts and that's it. Yeah. Like for the last two years has been it.Kyle: Yeah. The model hardware context co-design thing that we're seeing these days is actually super [00:44:00] interesting.It's like my, my passion, like my secret side passion. We see models like Kimmy or G-P-T-O-S-S. I'm use these because I, I know specific things about these models. So Kimmy two comes out, right? And it's an interesting model. It's like, like a deep seek style architecture is MLA. It's basically deep seek, scaled like a little bit differently, um, and obviously trained differently as well.But they, they talked about, why they made the design choices for context. Kimmy has more experts, but fewer attention heads, and I believe a slightly smaller attention, uh, like dimension. But I need to remember, I need to check that. Uh, it doesn't matter. But they discussed this actually at length in a blog post on ji, which is like our pu which is like credit puswyx: Yeah.Kyle: Um, in, in China. Chinese red.swyx: Yeah.Kyle: It's, yeah. So it, it's, it's actually an incredible blog post. Uh, like all the mls people in, in, in that, I've seen that on GPU are like very brilliant, but they, they talk about like the creators of Kimi K two [00:45:00] actually like, talked about it on, on, on there in the blog post.And they say, we, we actually did an experiment, right? Attention scales with the number of heads, obviously. Like if you have 64 heads versus 32 heads, you do half the work of attention. You still scale quadratic, but you do half the work. And they made a, a very specific like. Sort of barter in their system, in their architecture, they basically said, Hey, what if we gave it more experts, so we're gonna use more memory capacity.But we keep the amount of activated experts the same. We increase the expert sparsity, so we have fewer experts act. The ratio to of experts activated to number of experts is smaller, and we decrease the number of attention heads.Vibhu: And kind of for context, what the, what we had been seeing was you make models sparser instead.So no one was really touching heads. You're just having, uh,Kyle: well, they, they did, they implicitly made it sparser.Vibhu: Yeah, yeah. For, for Kimmy. They did,Kyle: yes.Vibhu: They also made it sparser. But basically what we were seeing was people were at the level of, okay, there's a sparsity ratio. You want more total parameters, less active, and that's sparsity.[00:46:00]But what you see from papers, like, the labs like moonshot deep seek, they go to the level of, okay, outside of just number of experts, you can also change how many attention heads and less attention layers. More attention. Layers. Layers, yeah. Yes, yes. So, and that's all basically coming back to, just tied together is like hardware model, co-design, which isKyle: hardware model, co model, context, co-design.Vibhu: Yeah.Kyle: Right. Like if you were training a, a model that was like. Really, really short context, uh, or like really is good at super short context tasks. You may like design it in a way such that like you don't care about attention scaling because it hasn't hit that, like the turning point where like the quadratic curve takes over.Nader: How do you consider attention or context as a separate part of the co-design? Like I would imagine hardware or just how I would've thought of it is like hardware model. Co-design would be hardware model context co-designKyle: because the harness and the context that is produced by the harness is a part of the model.Once it's trained in,Vibhu: like even though towards the end you'll do long context, you're not changing architecture through I see. Training. Yeah.Kyle: I mean you can try.swyx: You're saying [00:47:00] everyone's training the harness into the model.Kyle: I would say to some degree, orswyx: there's co-design for harness. I know there's a small amount, but I feel like not everyone has like gone full send on this.Kyle: I think, I think I think it's important to internalize the harness that you think the model will be running. Running into the model.swyx: Yeah. Interesting. Okay. Bash is like the universal harness,Kyle: right? Like I'll, I'll give. An example here, right? I mean, or just like a, like a, it's easy proof, right? If you can train against a harness and you're using that harness for everything, wouldn't you just train with the harness to ensure that you get the best possible quality out of,swyx: Well, the, uh, I, I can provide a counter argument.Yeah, sure. Which is what you wanna provide a generally useful model for other people to plug into their harnesses, right? So if youKyle: Yeah. Harnesses can be open, open source, right?swyx: Yeah. So I mean, that's, that's effectively what's happening with Codex.Kyle: Yeah.swyx: And, but like you may want like a different search tool and then you may have to name it differently or,Nader: I don't know how much people have pushed on this, but can you.Train a model, would it be, have you have people compared training a model for the for the harness versus [00:48:00] like post training forswyx: I think it's the same thing. It's the same thing. It's okay. Just extra post training. INader: see.swyx: And so, I mean, cognition does this course, it does this where you, you just have to like, if your tool is slightly different, um, either force your tool to be like the tool that they train for.Hmm. Or undo their training for their tool and then Oh, that's re retrain. Yeah. It's, it's really annoying and like,Kyle: I would hope that eventually we hit like a certain level of generality with respect to training newswyx: tools. This is not a GI like, it's, this is a really stupid like. Learn my tool b***h.Like, I don't know if, I don't know if I can say that, but like, you know, um, I think what my point kind of is, is that there's, like, I look at slopes of the scaling laws and like, this slope is not working, man. We, we are at a million token con

For 40 days Jesus “was with the wild animals” (Mk 1:13, BSB), yet they left no mark on Him. Man, however…

Know what you call a group of Panthers? A claw.Know what we call our group of calls of the game for Panther basketball? Claw Calls of course.Hear game highlights and postgame thoughts from HC Ben Jacobson, Max Weisbrod, RJ Taylor, Hunter Jacobson and Assistant Coach Seth Tuttle.The UNI Panthers are the CHAMPIONS of the Missouri Valley Conference Tournament. UNI finished off their historic title run with an 84-69 win over the UIC Flames on Sunday at the Enterprise Center. Trey Campbell led the way with 23 points, in part thanks to 6-9 shooting from three point range. Ben Schwieger also had a big scoring day going 7-8 from the floor in an 18 point effort. Will Hornseth and Leon Bond III both had 10 points, while Tristan Smith scored 8 points and dished out 7 assists. UNI now awaits their position in the NCAA Tournament field on selection Sunday, March 15th.This is the Panther Point of View, your source for all things Panthers. Listen on:Apple PodcastsSpotifyAnd MORE! Follow UNI Athletics onXFacebookInstagramYouTube Follow the Voice of the Panthers JW Cox on:Instagram See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Know what you call a group of Panthers? A claw.Know what we call our group of calls of the game for Panther basketball? Claw Calls of course.Hear game highlights and postgame thoughts from HC Ben Jacobson and Ben Schweiger.The UNI Panthers punched their ticket to the Arch Madness championship game with a 73-69 win over Bradley on semi-final Saturday. Leon Bond III scored 19 points for the second straight game. Trey Campbell, Ben Schweiger and RJ Taylor all scored in double figures to help the Panther cause. UNI will face UIC on Sunday at 11 AM in the MVC Tournament Championship game.This is the Panther Point of View, your source for all things Panthers. Listen on:Apple PodcastsSpotifyAnd MORE! Follow UNI Athletics onXFacebookInstagramYouTube Follow the Voice of the Panthers JW Cox on:Instagram See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In the Gaming Hut we explain why idiot plotting is an even bigger problem in tabletop rpgs than fiction or movies. At the behest of beloved Patreon backer Ginge the Tradecraft Hut rips the lid off of the submarine exploit that was Project Azorian. The Mythology Hut goes to the woods to reveal the surprising […]

Today, we have 2 bad cops in the Ill-Advised News, a man raging about Taco Bell wrappers, and our own Rage Friday catharsis. We have a second ill with pimp coach and another claw machine kid, a smart glasses warning, and the reason why Anthony might be moving on from the show soon. Support the show and follow us here Twitter, Insta, Apple, Amazon, Spotify and the Edge! See omnystudio.com/listener for privacy information.

Know what you call a group of Panthers? A claw.Know what we call our group of calls of the game for Panther basketball? Claw Calls of course.Hear game highlights and postgame thoughts from HC Ben Jacobson and Will Hornseth.The UNI Panthers won their opening round game the MVC Tournament, 68-59 over Evansville on Thursday night. Trey Campbell paced the Panthers with 23 points on 5 made threes, 4 rebounds and 3 assists. Will Hornseth had 13 points and 8 assists, while Tristan Smith had a double-double with 10 points and 13 rebounds. UNI squares off with Illinois State in round two Friday night at 8:30 in St. Louis.This is the Panther Point of View, your source for all things Panthers. Listen on:Apple PodcastsSpotifyAnd MORE! Follow UNI Athletics onXFacebookInstagramYouTube Follow the Voice of the Panthers JW Cox on:Instagram See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Know what you call a group of Panthers? A claw.Know what we call our group of calls of the game for Panther basketball? Claw Calls of course.Hear game highlights and postgame thoughts from HC Ben Jacobson and RJ Taylor.The UNI Panthers won their quarterfinal matchup with Illinois State 74-52. UNI never trailed and was never tied after the opening tap. Leon Bond III led the way with 19 points. Trey Campbell scored 12 and pulled down six rebounds. UNI held Illinois State to 33% shooting and just 3-20 from three point range. A semifinal matchup with Bradley is up next at 5pm on Saturday night.This is the Panther Point of View, your source for all things Panthers. Listen on:Apple PodcastsSpotifyAnd MORE! Follow UNI Athletics onXFacebookInstagramYouTube Follow the Voice of the Panthers JW Cox on:Instagram See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

We are back with a brand new episode featuring the return of Black Santa himself! He brings along his elf Mia, as she comes on answers our horny questions and tells us about her not so long relationship history. Plus Gee tells us about some Mia Mishaps at HQ The Lounge. Follow us on social media @AaronScenesAfterParty

Meet a NEW group of Almost Heroes as they embark on a fresh "mostly" D&D 5E actual-play adventure together! Officially Sponsored by ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠D&D Beyond⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ & ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Dungeons Box⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Watch LIVE on Tuesdays @7PM PST on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Twitch⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Video Podcast episodes available on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Join the Almost Heroes ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Discord⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ family Follow Us: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ or ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Featuring the Artwork of ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Breaking Branch⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Music by ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Monument Studios⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ & ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Wandering Planet

The party runs last minute errands before hitting the road for Chill Stone Keep.DM- DuganPlayers: Audi, Priscilla, Kent & CodyOpening & closing Music by: Suno

This week on the Roach Koach Podcast it's the most important episode we've ever done! It's an Ultra Mega Who's Festing! Louder Than Life 2026! The Blair Witch! Primer 55! Pile of Pillows! “Claw me!” Limp Bizkit new album? Plus Who's Giving Feedback and the debut of Stupid F'N Matt's Nu-Core For Old Heads 2. Take a listen!The Crack, the Butt Rock Bracket is here on the Roach Koach Patreon! Subscribe today! Rate, review, and follow Roach Koach on Apple Podcasts and Spotify! We'd appreciate it! Questions about the show? Have album recommendations? Just want to say hi? We'd love to hear from you! Contact the show @RoachKoach on Twitter, Roach Koach on Facebook , Roach Koach on Instagram, or send an email to RoachKoachPodcast at Gmail. Follow the show on Youtube and TikTok! Find every episode of Roach Koach and order your Roach Koach T-shirt at Roach Koach dot com.

This Week In Startups is made possible by:Circle — http://circle.so/twistHubspot Creators — http://clickhubspot.com/twist2Uber AI Solutions — http://uber.com/ai-solutionsToday's show: *Dave Morin joined the show today to explain how the OpenClaw Foundation came into existence, and what its goals are. Fear not, Peter Steinberger retains directional control of the project. But if you want to sustain an open-source project over time, you need a corporate entity, well-heeled sponsors, maintainers and more. Morin is helping make sure that OpenClaw can stay true to itself well into the future.TWIST also put the day's most critical AI stories to Morin for his insight: What's his take on the Anthropic-DoW fracas? Does Morin think that OpenAI and Anthropic are catching up to OpenClaw in agentic terms? And will OpenAI cede the consumer crown to Anthropic? Next came two amazing demos: Runtools' CTO Greg Kara showed off a 3D interface for OpenClaw that his team built, allowing ‘Claw users to watch their agents work in real time, and even read over their shoulder. Then PickelWatch founder George Yameen showed off an agnetic workflow using OpenClaw and Claude's Chrome plugin side-by-side. The gist? Make sure that the agentic service you select is cost-effective. **GUESTS:**Dave Morin: https://x.com/davemorin?lang=enGreg Kara: https://x.com/GregKara6George Yameen: https://x.com/GeorgeYameen**Timestamps:** 00:00 Dave Morin Joins the Show02:31 How Dave Morin got Claw-Pilled05:01 Jason's critical OpenClaw moments08:38 How Dave showcases his OpenClaw skills10:47 Uber AI Solutions - Your trusted partner to get AI to work in the real world. Book a demo with them TODAY at http://uber.com/ai-solutions14:40 How long has the OpenClaw Foundation existed?17:21 How much authority does Peter Steinberger retain?00:20:21 Hubspot - Check out the guide “Advanced ChatGPT Prompt Engineering: From Basic to Expert in 7 Days.” Download it for free at http://clickhubspot.com/twist219:20 How ‘air traffic control' works for a project like OpenClaw23:15 The economics of open-source maintainers25:13 Dave's physical OpenClaw setup27:45 How Jason uses OpenClaw to curate his reading, fashion, and travel30:23 Circle - Circle gives you everything you need to build and scale your community-led business. TWIST listeners get $1,000 off the Circle Plus Plan at http://circle.so/twist32:18 Why the second wave of ideas is where things get the most interesting34:06 Apple's slow movement and hesitance to depricate products39:51 How Jason uses OpenClaw to coach the next generation of executives44:52 Are Anthropic and OpenAI catching up to OpenClaw?49:40 Introduction to Runtools.AI53:49 Runtools.AI demo of 3D OpenClaw environment57:06 Introduction to PickleWatch57:27 PickelWatch demo of Claude Chrome vs. OpenClaw01:03:38 How PickleWatch ups your pickleball swing32:56 Jason's advice for founders on stumbling onto new ideas42:16 Jason on the DoW's handling of the Anthropic mess01:11:08 Would Jason fund the tech that Anthropic won't supply?Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com/Check out the TWIST500: https://twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcp*Follow Lon:X: https://x.com/lons*Follow Alex:X: https://x.com/alexLinkedIn: https://www.linkedin.com/in/alexwilhelm/*Follow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanis/*Check out all our partner offers: https://partners.launch.co/*Follow TWiST:Twitter: https://twitter.com/TWiStartupsYouTube: https://www.youtube.com/thisweekinInstagram: [https://www.instagram.com/thisweekinstartups](https://www.instagram.com/thisweekinstartups/)TikTok: https://www.tiktok.com/@thisweekinstartupsSubstack: [https://twistartups.substack.com](https://twistartups.substack.com/)

Know what you call a group of Panthers? A claw.Know what we call our group of calls of the game for Panther Women's Basketball? Claw Calls of course.Hear game highlights plus post-game thoughts from Head Coach Tanya Warren, Ryley Goebel and Taryn Wharton.The UNI Panthers won their final two regular season MVC games. UNI beat Indiana State on the road 92-73, then returned home and secured a season finale win 65-58 over Drake. Jenna Twedt led five Panthers in double figures with 21 against Indiana State. Twedt kept her roll going the next game with another 20 point effort in the win over Drake. All UNI women's basketball games can be heard locally on 106.5 FM Corn Country and anywhere via the Varsity Network App.This is the Panther Point of View, your source for all things Panthers. Listen on:Apple PodcastsSpotifyAnd MORE! Follow UNI Athletics onXFacebookInstagramYouTube Follow the Voice of Panther Volleyball and WBB Chris Kleinhans-Schulz:XSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This week on the Talk Without Rhythm Podcast I'm joined by the OG TWoRPer himself, The Cancer Man, to discuss two 1982 genre flicks. First up we have the Larry Cohen creature-feature Q (aka Q the Winged Serpent) and then we discuss Robert Wynne-Simmons' Folk Horror followup to Blood on Satan's Claw, The Outcasts. [00:00] INTRO [01:36] Trick or Treat Radio Promo [02:53] RANDOM CONVERSATION [11:59] Q (1982) [45:14] The Outcasts (1982) [01:18:22] FEEDBACK [01:30:41] ENDING MUSIC: The Outcast by The Dropkick Murphys Buy Q (1982) Buy The Outcasts (1982) Support TWoRP Contact Us talkwithoutrhythm@gmail.com  

Know what you call a group of Panthers? A claw.Know what we call our group of calls of the game for Panther basketball? Claw Calls of course.Hear game highlights and postgame thoughts from HC Ben Jacobson and Tristan Smith.The UNI Panthers won their regular season finale 75-53 over the Drake Bulldogs. Will Hornseth paced the Panthers on Sunday with 12 points in the first half, 16 for the game. Ben Schwieger scored 15 and Tristan Smith chipped in 12. The Panthers now look ahead to the MVC Tournament starting on Thursday in St. Louis.This is the Panther Point of View, your source for all things Panthers. Listen on:Apple PodcastsSpotifyAnd MORE! Follow UNI Athletics onXFacebookInstagramYouTube Follow the Voice of the Panthers JW Cox on:Instagram See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Know what you call a group of Panthers? A claw.Know what we call our group of calls of the game for Panther Women's Basketball? Claw Calls of course.Hear game highlights plus post-game thoughts from Head Coach Tanya Warren, Jenna Twedt and Maren Schmotzer.The UNI Panthers swept a pair of MVC home games over the past week. UNI beat Valpo 92-54 then followed it up with an 82-68 win over UIC. Four Panthers scored in double figures against the Beacons, led by Elise Jaeger with 16. Taryn Wharton paced the cats vs the Flames with 22 points, 3 assists and 3 rebounds. All UNI women's basketball games can be heard locally on 106.5 FM Corn Country and anywhere via the Varsity Network App.This is the Panther Point of View, your source for all things Panthers. Listen on:Apple PodcastsSpotifyAnd MORE! Follow UNI Athletics onXFacebookInstagramYouTube Follow the Voice of Panther Volleyball and WBB Chris Kleinhans-Schulz:XSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

The PodRocket panel is back for their February roundup! Paige, Paul, Jack and Noel dig into the biggest stories reshaping the web development landscape right now. The panel kicks off with a deep dive into OpenClaw, it's transition to a foundation, and Peter Steinberger joining OpenAI. Is a foundation the right long-term home for fast-moving AI projects? And what does the continuing flow of talent into big AI labs mean for the open source ecosystem? From there, the conversation shifts to the browser's changing role in the web, how the lines between native and web experiences continue to blur, and what that means for developers building for the future. The panel also tackles growing pressures on open source sustainability and the widening gap between developers who are deeply integrating AI agents into their workflows and everyone else who hasn't even heard of these tools yet. Resources TechCrunch: OpenClaw creator Peter Steinberger joins OpenAI: https://techcrunch.com/2026/02/15/openclaw-creator-peter-steinberger-joins-openai Interop 2026 report and dashboard: https://web.dev/blog/interop-2026 Google Chrome announcement on Gemini auto-browsing: https://blog.google/products-and-platforms/products/chrome/gemini-3-auto-browse/ What to expect for open source in 2026, Github blog: https://github.blog/open-source/maintainers/what-to-expect-for-open-source-in-2026/?ref=thecodebrew.net We want to hear from you! How did you find us? Did you see us on Twitter? In a newsletter? Or maybe we were recommended by a friend? Fill out our listener survey! https://t.co/oKVAEXipxu Let us know by sending an email to our producer, Elizabeth, at elizabeth.becz@logrocket.com, or tweet at us at PodRocketPod. Check out our newsletter! https://blog.logrocket.com/the-replay-newsletter/ Follow us. Get free stickers. Follow us on Apple Podcasts, fill out this form, and we'll send you free PodRocket stickers! What does LogRocket do? LogRocket provides AI-first session replay and analytics that surfaces the UX and technical issues impacting user experiences. Start understanding where your users are struggling by trying it for free at LogRocket.com. Try LogRocket for free today. Chapters 00:00 Intro and Panel Welcome 01:00 What Is OpenClaw 03:00 Moving to a Foundation and OpenAI Concerns 08:00 AI Security Risks and Malware Issues 13:00 AI Haves vs Have Nots 18:00 Evaluating Open Source AI Stability 26:00 Browser Interop 2026 and Compatibility Gaps 31:00 Designing for AI Agents First 37:00 AI Search vs Google 42:00 Gemini in Chrome and Browser Lock In 49:00 Hot Takes 55:00 AI Burnout and Developer Mental HealthSpecial Guest: Jack Herrington.

Know what you call a group of Panthers? A claw.Know what we call our group of calls of the game for Panther basketball? Claw Calls of course.Hear game highlights and postgame thoughts from HC Ben Jacobson and Trey CampbellThe UNI Panthers lost a one possession game to MVC rival Illinois State 71-69 on Wednesday night. Trey Campbell, Ben Schwieger and Will Hornseth all paced the Panthers with 13 points. UNI closes the regular season with a 2pm tip time at Drake.This is the Panther Point of View, your source for all things Panthers. Listen on:Apple PodcastsSpotifyAnd MORE! Follow UNI Athletics onXFacebookInstagramYouTube Follow the Voice of the Panthers JW Cox on:Instagram See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Concert etiquette? Outfit attire? After a fan wore a different country singers' shirt to Blake Shelton's- Anna and Raven discussed their thoughts on this controversial topic.  Anna's daughter, Dakota, suggested they watch a movie from the 80's... Indiana Jones. The main reason being, she saw the ride and disneyland and the music makes her happy! Anna and Raven play a fun musical game.  Has a piece of clothing or body accessory ever come to bite you from the back? Anna discusses claw clip safety and how driving with one can be very dangerous. Anna and Raven discuss more wardrobe malfunctions and accidents.  Trending today is IMMORTALS. The expirement that may have 3 risk-takers test if they really can live forever. Who's it going to be? An actor, an athlete? An artist? The mullet is back, thanks to the US men's hockey team... Is it really a Mullet though. They're calling it Lettuce now. As Anna explained it “Party in the back, but not like it used to be”  ITS COOKIE TIME! These Girl Scouts are all on a mission and need YOU to help them out, in a very delicious way! If you'd like to support a troop, check out our @AnnaandRaven story for their links! It's Dough-ver. Anna and her daughter Hayden, have officially quit trying to make sourdough bread. “The Fate of Dough-phelia” has been dumped in the garbage. What was the last thing you quit? Rich and Lorraine have a 22-year-old daughter that lives at home with them. She has seemingly falling into the wrong crowd. Dad believes he should pull their daughter aside and have a conversation with her about the path she is going down, and that she needs to let go of these toxic friends and find new ones. Mom says he has no right to do that. She is 22 now and can make her own decisions. She needs to learn these lessons on her own sometimes whether he likes it or not. Mary has a chance to win $2300! All he has to do is answer more pop culture questions than Raven in Can't Beat Raven!  

Know what you call a group of Panthers? A claw.Know what we call our group of calls of the game for Panther Women's Basketball? Claw Calls of course.Hear game highlights plus post-game thoughts from Head Coach Tanya Warren and Kaylynn Janes.The UNI Panthers split a pair of MVC games over the past week. UNI won on the road at Southern Illinois 77-48, then lost in overtime at Evansville 64-63. Jenna Twedt and Ryley Goebel both posted 20 point games in the win over SIU, then put up 18 and 23 respectively to lead the way in the loss vs Evansville. All UNI women's basketball games can be heard locally on 106.5 FM Corn Country and anywhere via the Varsity Network App.This is the Panther Point of View, your source for all things Panthers. Listen on:Apple PodcastsSpotifyAnd MORE! Follow UNI Athletics onXFacebookInstagramYouTube Follow the Voice of Panther Volleyball and WBB Chris Kleinhans-Schulz:XSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Know what you call a group of Panthers? A claw.Know what we call our group of calls of the game for Panther basketball? Claw Calls of course.Hear game highlights and postgame thoughts from HC Ben Jacobson and Tristan SmithThe UNI Panthers lost a hotly contested MVC matchup with SIU, 59-57 on Saturday night. Treu Campbell led the way for UNI with 16 points, Will Hornseth chipped in 14, and Tristan Smith had 8. The Panthers return to action in the McLeod Center Wednesday night at 6pm against Illinois State.This is the Panther Point of View, your source for all things Panthers. Listen on:Apple PodcastsSpotifyAnd MORE! Follow UNI Athletics onXFacebookInstagramYouTube Follow the Voice of the Panthers JW Cox on:Instagram See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Bridget, Caitlin, and Hilda wrap up their coverage of "Between Two Kings," book 2 in Lindsay Straube's Split or Swallow series. Now, they've always said this story was outrageous and unexpected -- and nothing is more unexpected than that ending. And apparently, the third book is a prequel and NOT a follow up to book 2! So ... how did you all feel about that ending, because you know our fave book besties are going to give you their thoughts.  Join our Patreon for exclusive behind-the-scenes content and let's be friends!Instagram > @Booktokmademe_podTikTok > @BooktokMadeMe

Today we sit down with artist and writer Rae Allen to discuss her new series Carmen Red Claw: Belly of the Beast, co-written with Mike Mignola and set in the Hellboy Universe. Rae shares how she built Carmen, a supernatural gun-for-hire in the 1870s Southwest, from a tiny piece of Lobster Johnson lore that caught Mignola's attention, discussing her striking visual design and shoulder demon, her research into Lakota folklore, and the experience of creating inside the beloved Hellboy Universe. Issue #2 drops today (2/18/26), so go get it! You can follow Rae on her site, raeallenart.com, and on Instagram and X @raeallenart. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Road trip horror meets supernatural action in a snow-choked small town where bad decisions don't stay personal for long. Caroline Quinn—government “Troubleshooter,” part vampire, and currently running from her own heartbreak—heads west to disappear for two weeks… only to end up in Germfask, Michigan, a place with failing cell service, bitter cold, and a neon sign that simply says BEER.Inside a rural dive called The Den, the locals aren't just unfriendly—they're organized. Armed. Watching. And when Caroline realizes she didn't walk into a bar at all but something closer to a lair, the night turns into a brutal fight for survival against a violent crew tied to the Claw of the Northern Patriots.If you like creature-feature terror, small town nightmare vibes, winter horror, and a protagonist who can break steel but still can't say the one thing that matters… buckle up. This one is fast, bloody, and freezing.Road Trip — by Mike Ashkewe 

Know what you call a group of Panthers? A claw.Know what we call our group of calls of the game for Panther basketball? Claw Calls of course.Hear game highlights and postgame thoughts from HC Ben Jacobson and Ben SchwiegerThe UNI Panthers Men's Basketball put up 80 points for the fourth straight game in an 81-60 win over the Indiana State Sycamores on the road. UNI got double figure performances from four Panthers for the fourth straight game, including Will Hornseth with 18, Ben Schweiger with 17, Max Weisbrod with 14 and Leon Bond III with 13. The Panthers return home Saturday to welcome Southern Illinois at 5pm.This is the Panther Point of View, your source for all things Panthers. Listen on:Apple PodcastsSpotifyAnd MORE! Follow UNI Athletics onXFacebookInstagramYouTube Follow the Voice of the Panthers JW Cox on:Instagram See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

08 18-02-26 LHDW Windows 2: La revolución de la Inteligencia Artificial, Open Claw, un trabajador para ti. Da miedo los nuevos avances en este sector

Peter Steinberger joins OpenAI, ZeroClaw is "claw done right", MimiClaw runs on a $5 chip, Steve Yegge on managing the AI Vampire, and the day the telnet died.

Peter Steinberger joins OpenAI, ZeroClaw is "claw done right", MimiClaw runs on a $5 chip, Steve Yegge on managing the AI Vampire, and the day the telnet died.

Peter Steinberger joins OpenAI, ZeroClaw is "claw done right", MimiClaw runs on a $5 chip, Steve Yegge on managing the AI Vampire, and the day the telnet died.

Know what you call a group of Panthers? A claw.Know what we call our group of calls of the game for Panther basketball? Claw Calls of course.Hear game highlights and postgame thoughts from HC Ben Jacobson and Max WeisbrodThe UNI Panthers Men's Basketball beat the Drake Bulldogs 86-62 at the McLeod Center on Sunday afternoon. UNI got double figure performances from four Panthers led by Max Weisbrod and Will Hornseth with 18. Leon Bond and Tristan Smith both had 14. Trey Campbell dished out 7 of the 22 team assists on the game. The Panthers travel mid-week to Indiana State before returning home for two games next week.This is the Panther Point of View, your source for all things Panthers. Listen on:Apple PodcastsSpotifyAnd MORE! Follow UNI Athletics onXFacebookInstagramYouTube Follow the Voice of the Panthers JW Cox on:Instagram See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Find Elizabeth online: https://eluracreations.com/ https://www.youtube.com/ ⁨@ElizabethElúra⁩  / elizabethelura   https://www.amazon.com/Child-Silence-... Do not miss Rich's book, "Confessions of a Frenetic Mind" available now - https://www.amazon.com/Confessions-Fr... Copyright 2025 The Claw's Corner - Produced by Rich Cyr  / richtheclawcyr   Edited by Elmwood Productions - http://elmwoodproductions.com/index.html and subscribe to Elmwood Productions on YouTube:    / elmwoodproductions   

Do not miss Rich's book, "Confessions of a Frenetic Mind" available now - https://www.amazon.com/Confessions-Fr... Copyright 2025 The Claw's Corner - Produced by Rich Cyr  / richtheclawcyr   Edited by Elmwood Productions - http://elmwoodproductions.com/index.html and subscribe to Elmwood Productions on YouTube:    / elmwoodproductions   

Know what you call a group of Panthers? A claw.Know what we call our group of calls of the game for Panther basketball? Claw Calls of course.Hear game highlights and postgame thoughts from HC Ben Jacobson.The UNI Panthers Men's Basketball lost 91-86 at Belmont Thursday night. UNI battled the league leading Bruins, getting 21 points from Leon Bond, 19 from Trey Campbell and 18 from Max Weisbrod. The Panthers begin the final 5 game stretch of the season Sunday afternoon at 2pm against Drake at the McLeod Center.This is the Panther Point of View, your source for all things Panthers. Listen on:Apple PodcastsSpotifyAnd MORE! Follow UNI Athletics onXFacebookInstagramYouTube Follow the Voice of the Panthers JW Cox on:Instagram See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This Week In Startups is made possible by:Hubspot - http://clickhubspot.com/twist2Deel - http://deel.com/twistIru - http://www.iru.com/Today's show: Today on TWiST we're joined by 3 founders building on Open Claw,  Presh Dineshkumar, Vishnu, and Sean Liu!First, long time friend of the pod, Presh Dineshkumar, shows us how he's using Open Claw to automate his work at The Wellness Company. His Open Claw agent, Eywa, lives in his email and in his product, able to compile user lists at his discretion.Then, we're joined by Vishnu, who brings Open Claw to the masses. Non-technical folks, it's your lucky day! Time to get Clawd-shotted! Last, Sean Liu joins the show to tell us about how he's connecting Meta glasses to his Open Claw instance to interact with context that users can physically see!Timestamps:(0:00) We're joined by Presh Dineshkumar of the Wellness Company, another OpenClaw fanatic(1:50) We meet Presh's Replicant — Eywa — who spies on all of his emails(2:53) How Eywa is helping Presh keep track of his app's most active users(4:35) LLMs have become very smart but they are trapped in the corner(6:10) How Presh gave Eywa its own email address and avoids prompt injections(8:56) Using Presh's Replicant to do daily research dives(10:40) Hubspot: Check out the guide “Advanced ChatGPT Prompt Engineering: From Basic to Expert in 7 Days.” Download it for free at http://clickhubspot.com/twist2(13:21) Presh also has Eywa hunting down and fix bugs in his apps, all from email(16:16) Way more startups can be profitable now that they don't need 10+ person teams(19:15) Deel - Founders ship faster on Deel. Set up payroll for any country in minutes and get back to building. Visit http://deel.com/twist to learn more.(20:36) We're joined by two more OpenClaw builders: Vishnu and Xiaoan (Sean) Liu(21:16) Sean hooked his Meta Ray Bans up to his OpenClaw!(29:53) Iru unifies identity, endpoint security, and compliance into one platform. Book a demo at http://iru.com/(31:05) Some dystopian thoughts on how to use VisionClaw technology(32:47) What kinds of startups will get the most value out of OpenClaw?(34:43) Why Vishnu made a product to simplify OpenClaw set-up and security(37:34) What inspires people to stop considering OpenClaw and go “all in” on the tech(40:17) Will Vishnu and Sean quit their jobs and take Jason's investment $125K investment deal… YESSubscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com/Check out the TWIST500: https://twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcp*Follow Lon:X: https://x.com/lons*Follow Alex:X: https://x.com/alexLinkedIn: https://www.linkedin.com/in/alexwilhelm/*Follow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanis/*Thank you to our partners:(10:40) Hubspot: Check out the guide “Advanced ChatGPT Prompt Engineering: From Basic to Expert in 7 Days.” Download it for free at http://clickhubspot.com/twist2(19:15) Deel - Founders ship faster on Deel. Set up payroll for any country in minutes and get back to building. Visit http://deel.com/twist to learn more.(29:53) Iru unifies identity, endpoint security, and compliance into one platform. Book a demo at http://iru.com/Check out all our partner offers: https://partners.launch.co/

There's a new wave of AI tools that don't just live in the cloud, don't just autocomplete code, and don't just sit in a browser tab. They reach into your local environment, understand your context, and act more like a thinking companion than a chatbot. In this episode, I talk with Peter Steinberger, founder of OpenClaw, about the rise of “The Claw” and what it means to build AI that feels fast, personal, and deeply integrated into your workflow. We explore why OpenClaw is having a moment, how developer expectations are shifting from prompts to agents, and what it takes to design tools that balance power, safety, and usability. Peter shares the architectural choices behind OpenClaw, the tradeoffs between local and cloud inference, and his perspective on privacy, ownership, and latency in a world of ever-larger models. This is a conversation about control. Who owns your context? Where does your data live? And what happens when AI stops being a destination and starts becoming an ambient layer across everything you do?

We are live! And this time from Apogee Dispo in Sunland Park NM. Tune in as Juantito Jones makes his After Party debut and Tiara, a local up and coming nightlife promoter, her company TNS Productions and DJ tells us about some after party stories, her favorite after party she has been to plus! She answers some horny questions straight from instagram. Follow us on social media @AaronScenesAfterParty

Bridget, Caitlin, and Hilda are back with part 1 of "Between Two Kings" book 2 in Lindsay Straube's Split or Swallow series. And if you read book 1 (or listened to the episode) then you know how outrageous this series is, and this book does NOT disappoint. Like we're sure there's a plot we're supposed to care about, but the basilisks have entered mating season which means Tem is indulging her basilisk nature. Anyways, listen now for thoughts on part 1.  Join our Patreon for exclusive behind-the-scenes content and let's be friends!Instagram > @Booktokmademe_podTikTok > @BooktokMadeMe

Don't let the whimsical flute fool you, the games end real fast as we discuss Blood On Satan's Claw directed by Piers Haggard. The boys are joined by writer James Rose to discuss cults as counter-culture, gender oppression, and what makes a UK folk tale. It's ok, you can keep your Devil's Skin patch!New episodes drop every Tuesday, subscribe so you don't miss out. Rate us 5 stars while you're at it! Enter The Phantom Zone to access all sorts of bonus goodies like our monthly side show "Watching the Watchlist", movie commentaries, and polls to help shape the podcast: https://patreon.com/spectercinema Haunt James on social media:Selected WritingsInstagramHaunt Garrett on social media:TikTokTwitterBlueskyInstagramLetterboxdYouTubeHaunt DeVaughn on social media:BlueskyTwitterTikTokInstagramLetterboxdYouTubeSpecter Cinema Club Original Theme by Andrey Kinnard

Welcome to this week's episode of the PEBCAK Podcast!  We've got four amazing stories this week so sit back, relax, and keep being awesome!  Be sure to stick around for our Dad Joke of the Week. (DJOW) Follow us on Instagram @pebcakpodcast   Please share this podcast with someone you know!  It helps us grow the podcast and we really appreciate it!   Simple 6 signup link https://simple6.co/r/CFUR98   Open Claw https://www.bleepingcomputer.com/news/security/malicious-moltbot-skills-used-to-push-password-stealing-malware/  https://www.bleepingcomputer.com/news/security/viral-moltbot-ai-assistant-raises-concerns-over-data-security/    Notepad++ update servers hijacked in supply chain attack https://notepad-plus-plus.org/news/hijacked-incident-info-update/  https://www.bleepingcomputer.com/news/security/notepad-plus-plus-update-feature-hijacked-by-chinese-state-hackers-for-months/  https://www.rapid7.com/blog/post/tr-chrysalis-backdoor-dive-into-lotus-blossoms-toolkit/    Microsoft deprecating NTLM https://techcommunity.microsoft.com/blog/windows-itpro-blog/advancing-windows-security-disabling-ntlm-by-default/4489526 https://www.bleepingcomputer.com/news/microsoft/microsoft-to-disable-ntlm-by-default-in-future-windows-releases/   Carrot tartare https://www.foodrepublic.com/recipes/very-veggie-make-this-ethiopian-carrot-tartare/   Dad Joke of the Week (DJOW)   Find the hosts on LinkedIn: Chris - https://www.linkedin.com/in/chlouie/ Brian - https://www.linkedin.com/in/briandeitch-sase/ Glenn - https://www.linkedin.com/in/glennmedina/ Kush - https://www.linkedin.com/in/kushaagra/

Esta semana bajamos de la teoría a la práctica. Volvemos a hablar de OpenClaw, pero ya no desde el hype inicial, sino desde nuestras experiencias tempranas usándolo: qué funciona, qué se rompe, cuánto cuesta realmente y por qué hoy sigue siendo una herramienta solo para perfiles muy técnicos

Hello, Friends! Before we dive into "Between Two Kings," the second novel in Lindsay Straube's Split or Swallow series, we thought we'd rerelease our episode on Split or Swallow so you know what's going on. Enjoy! Join our Patreon for exclusive behind-the-scenes content and let's be friends!Instagram > @Booktokmademe_podTikTok > @BooktokMadeMe