Podcasts about cisco

The episode reveals a structural shift in the managed services market, where the value proposition for MSPs and IT service providers is moving away from “running the tools” to delivering governance, risk management, and outcome-driven services. This shift is catalyzed by the increasing commoditization of tool-centric operations, as platforms and vendors such as Microsoft (Autopatch), Atera (autonomous agents), Summit Holdings (MSP as a service), and Ruest (RoboRoosty AI Workflow Builder) push standardized automation, workflow tools, and backend service packaging into the market. Cisco's Global State of Security report underscores this trend, identifying tool maintenance and fragmentation as primary sources of inefficiency. Evidence from Cisco shows 59% of security leaders pointing to tool maintenance as the chief inefficiency, with 78% citing tool dispersion and lack of integration. For MSPs, this results in growing unbillable labor spent on connecting systems, onboarding, retraining, and managing exceptions. The report indicates that the cost to deliver services is escalating faster than the value captured in contracts, exposing a margin squeeze and highlighting the risk that unmanaged operational complexity poses to profitability. Secondary developments reinforce the structural shift. Atera's no-ticket operational model and Microsoft's implementation of security updates through Intune and Autopatch transfer control and cadence of IT operations upstream, leaving MSPs responsible for policy exceptions and business risk translation rather than day-to-day execution. Summit Holdings' “MSP as a service” and D&H's expansion into enablement and training further commoditize backend functions, reducing differentiation for providers who fail to retain independent client intelligence and risk management. Operationally, the implications for MSPs and IT leaders are clear: dependency on vendor platforms and wholesale backend solutions increases, making risk ownership and client-specific intelligence the remaining sources of defensible value. Providers unable to price or document governance and exception management risk seeing margins erode as they absorb unbillable labor and liability. Future operational strategy will require clear mapping of tools to billable outcomes, explicit governance layers, and careful evaluation of which client insights remain uniquely held versus replicated across standardized platforms. Three things to know today 00:00 Tools vs Outcomes 02:50 Delivery Gets Packaged 05:17 Defaults Have Costs 07:42 Why Do We Care?  Supported by:  TimeZest Small Biz Thoughts Community

This is episode 821. Read the complete transcription on the Sales Game Changers Podcast website. The Sales Game Changers Podcast was recognized by YesWare as the top sales podcast. Read the announcement here. FeedSpot named the Sales Game Changers Podcast at a top 20 Sales Podcast and top 8 Sales Leadership Podcast! Subscribe to the Sales Game Changers Podcast now on Apple Podcasts! Purchase Fred Diamond's best-sellers Love, Hope, Lyme: What Family Members, Partners, and Friends Who Love a Chronic Lyme Survivor Need to Know and Insights for Sales Game Changers now! On today's show, we interviewed Nick Michaelides, former Senior Vice President of U.S. Public Sector Sales at Cisco and the 2026 IEPS Lifetime Achievement Award recipient. Find David on LinkedIn.  NICK'S TIP: "Every sales professional needs to lean in on AI and understand where the technology is going, because if you don't, someone else will, and they will outsell you."

Rich Bayes, Product Management Leader at Cisco, spoke with Moshe Beauford of Technology Reseller News, during the Enterprise Connect conference about Cisco's latest collaboration device innovations and how artificial intelligence is reshaping the meeting experience. Bayes discussed Cisco's newest generation of collaboration hardware, including updates to its Desk Pro platform and advanced camera technologies designed to improve hybrid meetings. These devices incorporate AI-powered capabilities such as dynamic camera framing and intelligent speaker tracking to create a more natural meeting experience for both in-room and remote participants. “We're using AI to make meetings feel more natural, so people in the room and people joining remotely have the same experience,” Bayes said. A key focus for Cisco is integrating intelligent video and audio technologies directly into meeting devices. By embedding AI features into hardware, organizations can automatically optimize camera views, enhance audio clarity, and adapt to changing meeting environments without requiring complex manual configuration. The discussion also highlighted how enterprises are investing in higher-quality collaboration spaces as hybrid work becomes permanent. Modern meeting rooms must support distributed teams while maintaining consistent user experiences across different locations and devices. As organizations gathered at Enterprise Connect to evaluate the next generation of enterprise collaboration technologies, Cisco demonstrated how AI-powered meeting devices are becoming an essential component of modern workplace communication strategies. Learn more about Cisco: https://www.cisco.com/

On this episode, Richard & Tyler get a chance to preview the 2nd Volume of Pistolheart, alongside it's creator, Carlos Cisco!Links to Stuff & Things:https://heartofdaggers.com/products/pistolheart-vol-1/https://bsky.app/profile/carloscisco.bsky.socialhttps://heartofdaggers.com/products/making-custom-adversaries/https://cults3d.com/en/3d-model/game/daggerheart-western-fear-trackerhttps://www.daggerheart.com/downloads/https://www.daggerheart.com/thevoid/Welcome to True Strike, a podcast for tabletop nerds.Each Tuesday, listen in while two friends discuss their completely unwarranted opinions about all things tabletop. Topics vary each week from D&D and Daggerheart, to whatever TTRPG or board game they happen to be playing!Hosts: Richard Cullen/Tyler WortheySong by: WILDJOE1

Quantum computing isn't just 10 years away, it's happening now. In this deep dive, I sit down with Ramana Kompella, Head of Research at Cisco Outshift, to separate the sci-fi vaporware from the engineering reality. We discuss the immediate threat of "Harvest Now, Decrypt Later" attacks, where bad actors steal your encrypted data today to unlock it with quantum computers tomorrow. Ramana breaks down exactly how Cisco is building the "Quantum Network" to counter this, leveraging the "No Cloning Theorem" to create unhackable communication channels. If you are in cybersecurity, networking, or studying computer science, this is your roadmap to the future. We cover the math you need to learn (Linear Algebra), the timeline for real-world adoption (it's closer than you think), and how Quantum Teleportation actually works at a packet level. Topics Covered: • The 5-Year Timeline: Why the "decade away" myth is wrong. • Quantum Networking vs. Computing: Why we need to interconnect quantum processors. • The Physics of Security: How Entanglement and Teleportation prevent eavesdropping. • Career Advice: Why Linear Algebra is the most critical skill for AI and Quantum jobs. • Cisco x IBM: The partnership building the future internet. Big thanks to Cisco for sponsoring this video and sponsoring my trip to Cisco Live Amsterdam 2026. // Ramana Kompella's SOCIAL // LinkedIn: / rkompella / David's SOCIAL // Discord: discord.com/invite/usKSyzb Twitter: www.twitter.com/davidbombal Instagram: www.instagram.com/davidbombal LinkedIn: www.linkedin.com/in/davidbombal Facebook: www.facebook.com/davidbombal.co TikTok: tiktok.com/@davidbombal YouTube: / @davidbombal Spotify: open.spotify.com/show/3f6k6gE... SoundCloud: / davidbombal Apple Podcast: podcasts.apple.com/us/podcast... // MY STUFF // https://www.amazon.com/shop/davidbombal // SPONSORS // Interested in sponsoring my videos? Reach out to my team here: sponsors@davidbombal.com // MENU // 0:00 - Coming Up 0:43 - Introduction 02:36 - The Exciting Part about OutShift 04:12 - The Promise of Quantum Computing 07:09 - The Importance of Partnership between IBM & Cisco 07:55 - The Difference between Classical Computing & Quantum Computing 11:25 - Why It is Important to study Maths 12:31 - Technical Details About Quantum Computing 19:19 - When Will Quantum Computing Become a Reality? 20:00 - Will Quantum Computing Break Encryption? 25:36 - Outro & Conclusion Please note that links listed may be affiliate links and provide me with a small percentage/kickback should you use them to purchase any of the items listed or recommended. Thank you for supporting me and this channel! Disclaimer: This video is for educational purposes only. #quantumnetworking #ciscooutshift #cybersecurity

Scott sits down for an in-depth conversation with Kireeti Kompella. Together they explore his impactful career and the evolution of modern networking. Kireeti, a key figure in protocol development, shares his journey from the Kernel Group at Juniper to leading work on fundamental technologies including his contributions to the C-chip patent. AdSpot Sponsor: Meter Meter... Read more »

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From manufacturing data and AI adoption to workforce trends and the evolving role of women in industry, supply chain leaders are navigating a fast-changing landscape. In this episode of The Buzz, hosts Scott Luton and Karen Betancourt break down the latest global supply chain news and welcome Tracy Hyatt Bosman of Biggins Lacy Shapiro & Company to explore how economic signals, workforce dynamics, and site selection strategies are shaping the future of manufacturing and logistics. Buckle up and join us for this week's insights and conversations — welcome to The Buzz powered by Project44!This episode dives into the latest developments impacting global supply chains, including new data on U.S. manufacturing performance, the rapid rise of AI in factory operations, and the workforce dynamics influencing site selection and economic development. The conversation also highlights Women's History Month, explores real-world examples of supply chain and marketing alignment, and examines how emerging technologies and shifting economic signals are reshaping industry strategy.Tune in and learn:What the latest U.S. manufacturing data signals about jobs, tariffs, and production costsHow manufacturers are deploying AI to improve productivity, quality, and resilienceWhy workforce availability and skills remain the biggest factor in manufacturing site selectionThe myths and realities surrounding manufacturing careers and workforce shortagesKey economic insights from leading economists on the outlook for U.S. manufacturing and global tradeHow retailers like Target are investing in supply chain and fulfillment capabilities to compete in the omnichannel eraThe role of women's leadership in supply chain and manufacturing operationsWhy data centers are becoming a critical (and sometimes controversial) part of modern infrastructureWhether you're a supply chain leader, manufacturer, logistics professional, or industry enthusiast, this episode offers valuable perspective on the economic forces, workforce realities, and technology shifts shaping the future of supply chain. Tune in to gain practical insights and stay ahead of the trends influencing how the world moves goods, data, and innovation.Additional Links & Resources:Project 44: https://www.project44.com/With That Said: https://bit.ly/WTS-7-March-2026National Supply Chain Day: https://bit.ly/NSCD-2026American Supply Chain Summit: https://supplychainus.com/FritoLay Chip Challenge: https://bit.ly/Karen-FritoLay-Chip-ChallengeUS manufacturing activity steady, factory gate inflation surges: https://reut.rs/4roemtIU.S. payrolls unexpectedly fell by 92,000 in February; unemployment rate rises to 4.4%: https://cnb.cx/4bgHFseManufacturers are making progress with AI, but barriers remain: Cisco: https://bit.ly/State-of-AI-in-ManufacturingTarget readies next-day delivery for 20 more metros this spring: https://bit.ly/Target-Expands-Next-Day-DeliveryFox's Burton's Companies factory chief: “I was told being a woman would hold me back:” https://bit.ly/Women-In-ManufacturingDecision44 Event: https://www.project44.com/events/decision44/The Executives'​ Club of Chicago's Annual Economic Outlook 2026: https://www.linkedin.com/posts/traceyhyattbosman_before-it-gets-too-far-in-the-rearview-mirror-activity-7418784479105691649-Azng/Connect with Tracey on LinkedIn: https://www.linkedin.com/in/traceyhyattbosman/Connect with Karen on LinkedIn: https://www.linkedin.com/in/karendbetancourt/Learn more about Supply Chain Now: https://supplychainnow.comWatch and listen to more Supply Chain Now episodes here: https://supplychainnow.com/program/supply-chain-nowSubscribe to Supply Chain Now on your favorite platform: https://supplychainnow.com/joinWork with us! Download Supply Chain Now's NEW Media Kit: https://bit.ly/3XH6OVkSupply Chain Now en Espanol WEBINAR- Visibilidad estrategica en Pharma: control, cumplimiento y resiliencia en entornos de alto riesgo: https://bit.ly/4rku7lCWEBINAR- Talent Management Playbook for Supply Chain Leaders: https://bit.ly/4uc2OfBWEBINAR- From Workforce Planning to Hourly Performance Management: How GEODIS Americas Turned Labor Productivity into a Growth Engine: https://bit.ly/4blRfKpWEBINAR- Ahead of Disruption: How AI-First Design Builds Supply Chain Resilience — and Transforms the Teams Behind It: https://bit.ly/4ldRn3bThis episode is hosted by Scott Luton and Karen Betancourt, and produced by Trisha Cordes, Joshua Miranda, and Amanda Luton. For additional information, please visit our dedicated show page at: https://supplychainnow.com/buzz-ai-hits-factory-floor-1557

Scott sits down for an in-depth conversation with Kireeti Kompella. Together they explore his impactful career and the evolution of modern networking. Kireeti, a key figure in protocol development, shares his journey from the Kernel Group at Juniper to leading work on fundamental technologies including his contributions to the C-chip patent. AdSpot Sponsor: Meter Meter... Read more »

Donatas Urbonas, Karolis Tiškevičius ir Jonas Miklovas apžvelgia Kauno „Žalgirio” dvikovą su Atėnų „Panathinaikos”, skambią Vilniaus „Ryto” pergalę ir Augusto Marčiulionio debiutą bei aiškinasi, kas apsimelavo Luka Dončičiaus ir Mato Buzelio konflikte. Tinklalaidės partneriai: – Saily eSIM. Gaukite išskirtinę 15% nuolaidą „Saily“ duomenų planams! Naudokite kodą BASKETNEWS atsiskaitydami. Atsisiųskite „Saily“ programėlę arba apsilankykite https://saily.com/basketnews – RAMBYNO užkandžiai – natūraliai rūkyti alksnio medienos dūmu, juose nėra sintetinių dažiklių, augalinių riebalų, skonio stipriklių bei konservantų, o traškus valgomas kolageno apvalkalas leidžia neišsitepti pirštų ir mėgautis fantastišku skoniu be jokių problemų. – Nealkoholinis alus „Gubernija”, daugiau informacijos – https://gubernija.lt/ – Bilietai į renginį BN LIVE su Arnu Butkevičiumi: https://tickets.paysera.com/lt/event/basketnews-live-su-arnu-butkeviciumi Temos: Saugokitės, tėtis grįžo (0:00); Nostalgija dėl Graikijos (1:12); Rungtynes nusprendęs momentas (3:47); Wrighto pražangų turėjo nebūti? (8:09); Ąžuolo kovingumo pavyzdys (14:11); Bodirogos atvaizdas bus grąžintas į palubes? (16:41); Ant popieriaus stipriausia visų laikų Europos komanda (20:33); Cisco neklausęs Masiulis (22:45); Ką galvoti apie Atamaną? (28:56); Kas garantuotų šeštą vietą Eurolygoje? (33:48); Ką iš dešimtuko išmes Dubajus? (35:55); Karolis skrenda į Stambulą (39:36); Ko dabar reikia „Rytui” (42:28); Visiems patikęs Marčiulionis (44:08); Neguodžianti Gudaičio situacija (52:42); Kodėl Marčiulionio nebuvo rinktinėje? (56:07); Svarbiausios „Ryto” sezono rungtynės (59:59); 83 taškų sprogimas NBA (1:01:37); Ypatingas Buzelio atvejis (1:08:27); Kodėl netikime nė vienu Buzelio žodžiu konflikte su Luka (1:17:12); Ech, Linai (1:20:44); Labai jautrus ir atviras Butauto pokalbis (1:23:01).

Happy spring cleaning time! We're cleaning house with this episode. Enjoy some behind-the-scenes recordings from 404 over the last few months! If you haven't already, and you want to keep these BTS episodes coming, check out Cisco's solutions for small and medium businesses: https://www.cisco.com/site/us/en/solutions/small-business/index.html

Two perfect CVSS 10.0 scores in one news cycle. A state-sponsored actor living inside Cisco's SD-WAN platform since 2023. A brand-new lateral movement technique called "Ghost NICs" that leaves no forensic trace. An AI chatbot jailbroken to steal 195 million government records. A North Korean hacking group bridging air-gapped networks with USB drives and an embedded Ruby runtime. And a phishing platform so sophisticated it makes your multi-factor authentication functionally useless. This is Hacking News Episode 64 from Exploit Brokers by Forgebound Research. Five stories, multiple nation-state actors, and some genuinely novel attack techniques. Let's get into it.

Text us your questions and thoughts!What if the fastest way to elevate your career is to get more human as you get more technical? We sit down with Tamara Kempf, Regional Director, EMEA Customer Success at AppDynamics (a Cisco company), to unpack her career built on curiosity, grit, and the kind of EQ that technology can't replace. We trace her journey from science student to landing a first job at Bloomberg to now Cisco Customer Success leader, turning setbacks into growth, and using AI where it counts without losing the human edge. You'll hear practical stories of how to save days of work, coach teams with empathy, and hire for skills that last.In this episode, we talk about:Lessons from Bloomberg on customer advocacy without authorityIntegrating a startup culture into Cisco's Customer Success teamPragmatic AI use cases that compress a full day's work into minutesHow to create a safe culture to experiment and share failuresRedefining productivity as making time to be humanThe secret to being a great leaderIf you're navigating customer success, leadership, AI adoption, or all three, you'll find tactics you can try today and a mindset that lasts. Subscribe, share with a teammate, and leave a review to help more people discover conversations that move careers forward.

Send a textReady for a reality check on AI security? We invited Cisco cybersecurity expert Katherine McNamara to dig into where large language models actually break: from prompt injection and over-permissioned plugins to reckless “vibe-coded” apps that leak IDs, photos, and entire backends. The stories are real, the stakes are high, and the fixes are concrete. We trace how AI sprawl mirrors the worst of early IoT—weak defaults, poor isolation, and a stampede to integrate models into billing, HR, and support without guardrails—only this time the blast radius includes your customer data and your legal exposure.We talk through the human factor first. Written policies won't stop someone from pasting a pen test report into a public chatbot. DLP helps, but hybrid work and BYOD stretch defenses thin. Then we move to the core threat model: public and private models are targets; datasets can be poisoned; plugins often ship with admin-level scopes; and a clever prompt can trick an LLM into disclosing chat histories, creating new accounts, or modifying orders. Courts have already treated chatbots as company representatives, binding businesses to their outputs—another reason to treat every integration like an untrusted user with strict least privilege.It's not all doom. Used well, AI gives security operations superpowers: correlating signals across dozens of tools, reducing alert fatigue, and surfacing lateral movement. The path forward is discipline, not denial. Fence models on the network. Prefer read-only to write. Gate plugins behind narrowly scoped APIs. Vet datasets for backdoors. Red-team prompts as seriously as you pen test code. And educate stakeholders with live demos so they see why these controls matter. We also unpack the shaky economics—GPU costs, rising consumer fatigue, hype-fueled projects with little ROI—and why that pressure can erode privacy if teams aren't vigilant.If you're building with LLMs or trying to rein them in, this conversation gives you a practical map: what to allow, what to block, and how to make AI useful without turning your stack into an attack surface. Subscribe, share with a teammate who ships integrations, and drop a review with the one guardrail you'll implement this quarter.Connect with our Guest:https://x.com/kmcnam1https://www.linkedin.com/in/katherinermcnamara/Purchase Chris and Tim's book on AWS Cloud Networking: https://www.amazon.com/Certified-Advanced-Networking-Certification-certification/dp/1835080839/ Check out the Monthly Cloud Networking Newshttps://docs.google.com/document/d/1fkBWCGwXDUX9OfZ9_MvSVup8tJJzJeqrauaE6VPT2b0/Visit our website and subscribe: https://www.cables2clouds.com/Follow us on BlueSky: https://bsky.app/profile/cables2clouds.comFollow us on YouTube: https://www.youtube.com/@cables2clouds/Follow us on TikTok: https://www.tiktok.com/@cables2cloudsMerch Store: https://store.cables2clouds.com/Join the Discord Study group: https://artofneteng.com/iaatj

加入會員，支持節目： https://richlife.firstory.io/join 留言告訴我你對這一集的想法： 歡迎您用一杯咖啡支持我持續創作 : https://pay.soundon.fm/podcasts/a11a2120-4bc4-4fb2-813b-135bd96e5868 「布姐的交誼廳。陪你聊人生聊職場」Line 社群 https://reurl.cc/36NWEL(密碼：love) 本集重點： 以下為您整理凱琳老師訪談的 10 個核心重點： 電機背景轉戰心理學：凱琳老師擁有電機學碩士，在矽谷科技業（如 Cisco）任職超過 10 年，後轉型為心理學博士與 MBTI 專家 。 中年轉型的三大警訊：29 歲起察覺對科技圈話題無感、過度依賴度假逃避工作，並對「50 歲的自己仍坐辦公室」感到否定 。 職涯轉型先做「排除法」：不知道要什麼沒關係，先從釐清「不要什麼」開始，逐步縮小範圍找到真正熱情所在 。 利用組織資源做實驗：在離職前，凱琳老師先在思科內部進行跑道轉換，從開發轉向技術行銷與銷售賦能，測試自己與「人」工作的契合度 。 40 歲重返校園的底氣：除了累積的作品（如第一本書），身邊家人與朋友的支持是她決定攻讀博士的最後動力 。 理工邏輯加速學習：運用理工腦的邏輯組織能力與 10 多年職場經驗，她僅花不到 4 年便完成一般人需耗時 8 至 10 年的博士學位 。 MBTI 的誤區與標籤：許多人因適應工作環境而表現出「假的性格」，導致網路測驗結果高達一半以上是不準確的 。 重新定義內外向（E/I）：內向與外向的差異在於「能量交換」與「建立認知的頻率」，而非單純的社交技巧或活躍程度 。 SJ 族群的轉型挑戰：在 MBTI 中，S（實感）與 J（判斷）組合的人最追求穩定與可預測性，在面對職涯大跨度轉型時通常需要更多的安全感 。 找回人生的自主權：轉型後的凱琳老師感受到極高的工作自主性，並從幫助他人成長中獲得比科技業時期更大的成就感 。 來賓. 王凱琳 心理學人格特質分析專家，職涯發展諮商師，企業組織與領導力的發展顧問。具有電機工程碩士及心理學博士學位，並具有美國MBTI®心理學人格類型分析諮商大師級認證　　早在2012年就把MBTI®帶入中文世界。《30分鐘破解性格密碼》是第一本由華人專家親筆書寫的MBTI®中文書。結合在高科技行業裡多年的豐富工作經驗與人格心理的專長，加上熟悉亞洲文化，因應不同文化、種族的需求，深入且實際地幫助中文世界的讀者。　　具有多樣藝術才華（音樂、舞蹈、繪畫等），亦擅長文學創作，是「海外華文女作家協會」認可的正式會員。著有：《思科現形記》、《30分鐘破解性格密碼》、《你是我的黑髮》、《見人說人話之超效溝通指南》。　　FB「王凱琳的人格心理沙龍」　　Podcast：人格心理沙龍

Most enterprises are layering AI tools on top of broken processes and wondering why ROI never materializes. In this solo episode, Maribel breaks down Cisco's systematic approach to workflow redesign, why visibility into how work actually gets done is the missing first step, and what enterprise leaders need to change about their leadership culture and talent systems before AI adoption will deliver real results.Key Topics Covered•  Why AI tool adoption without workflow redesign fails to deliver ROI•  How Cisco's Atlas AI agent system maps work across the enterprise•  The digital workflow canvas that lets leaders redesign processes systematically•  Results from Cisco's pilot: 60% of activities AI-augmentable, 28 transformational use cases• Why framing AI as augmentation rather than headcount reduction drives adoption•  The leadership and talent system changes most companies missKey TakeawayThe technology exists. The use cases are proven. What's missing is the organizational discipline to redesign workflows before deploying more tools. Start with your data and your processes, not your tools.Resources & Links Blog post: Why AI Tool Adoption Without Workflow Redesign Is a Waste of Money [Lopez Research] Related: Five Steps to Follow for Successful AI Deployments [Lopez Research]Related: Three Shifts in AI-Driven Labor That CIOs and CEOs Can't Ignore [Lopez Research]Subscribe to AI with Maribel Lopez on your channel of choice here.

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

Creativity through the lens of the Co-founder of Pennant Video"You have to bring a sense of pride and ownership into what you're doing."Tim Bradley is the Co-Founder of Pennant Video, a B2B-focused agency that has pioneered the Video Marketing Trifecta™ to power mid-funnel marketing strategies. With nearly two decades of experience in video marketing, Tim has partnered with leading B2B tech brands like Cisco, Hitachi, Philips and countless startups, bringing their stories to life with compelling video campaigns.Before founding Pennant, Tim was the Executive Producer at a large communications agency. In his 12 years there, he built, managed and mentored a 25-person creative team, while growing the business in competitive sectors such as tough tech, cybersecurity, and healthcare. He believes in creating work that cuts through the noise—methodical yet bespoke, scalable yet unique. Beyond client projects, Tim mentors aspiring creatives through workshops and portfolio reviews, reinforcing his belief that elevating new talent fosters a more innovative and story-driven industry.Tim has built an engaged following on LinkedIn by being relatable, authentic and authoritative, with equal parts actionable insights and compelling storytelling. (And the occasional dad joke.) He believes strongly in the power of community and mentoring, that connections mean more than just a numbers game, and that young creatives deserve the wisdom he's gained over a long and ongoing creative career. His philosophy is simple: create meaningful connections through impactful stories that resonate and endure.Outside the office, Tim draws inspiration from his love of snowboarding, family, and the outdoors, channeling the focus, adaptability, and persistence honed on the slopes into navigating today's competitive marketing landscape.https://www.pennant.video/https://www.linkedin.com/in/tim-bradley-pennant/https://www.instagram.com/pennant.videohttps://www.youtube.com/channel/UC0ele4VqgzHfNPvnyk-e0JQhttps://www.linkedin.com/company/pennantvideo/Send a text

Jeff Edwards sits down with Rebecca Leach—former Cisco and AppDynamics leader turned executive coach and founder of Growth Road, an executive coaching practice focused on helping leaders navigate change with clarity, confidence, and connection. After nearly two decades in tech leadership, Rebecca reached a pivotal moment: stay in the familiar rhythm of corporate success, or step into ambiguity and redefine what leadership—and identity—really meant. What followed wasn't just a career transition. It became the foundation for Growth Road, where Rebecca now helps leaders grow through the same kinds of shifts she experienced herself. In this candid conversation, Rebecca shares the emotions behind leaving a long, successful corporate career, the courage it takes to embrace uncertainty, and the lessons leaders can carry forward when the path ahead isn't clear. Why listen: • ⚡ The hidden risk of tying your identity to your title •

In der heutigen Folge sprechen die Finanzjournalisten Anja Ettel und Holger Zschäpitz über einen völlig verrückten Wochenstart an den Märkten, einen durchwachsenen Börsengang in Frankfurt und einen deutschen Maschinenbauer mit Zoll-Resilienz. Außerdem geht es um Alphabet, Amazon, American Airlines, Amgen, Apple, Barrick Gold, Biontech, Caterpillar, Chevron, Cisco, Coherent, ConocoPhillips, Corteva, CSG, Deere, Delta Air Lines, Echostar, Eli Lilly, ExxonMobil, Freeport-McMoRan, Gabler Group, Gea, HP Enterprise, Intuitive Surgical, Johnson & Johnson, Live Nation Entertainment, Lumentum, Meta, Microsoft, Mosaic, Newmont, Nordisk, Novo Nordisk, Nuccor, Nvidia, Occidental, Oracle, Pfizer, Powerus, Southern Copper, Southwest, T-Mobile, ThyssenKrupp, TKMS, United Airlines, Verizon, Vertiv, VW, Walmart. Wir freuen uns an Feedback über aaa@welt.de. Noch mehr "Alles auf Aktien" findet Ihr bei WELTplus und Apple Podcasts – inklusive aller Artikel der Hosts und AAA-Newsletter. Hier bei WELT: https://www.welt.de/podcasts/alles-auf-aktien/plus247399208/Boersen-Podcast-AAA-Bonus-Folgen-Jede-Woche-noch-mehr-Antworten-auf-Eure-Boersen-Fragen.html. Der Börsen-Podcast Disclaimer: Die im Podcast besprochenen Aktien und Fonds stellen keine spezifischen Kauf- oder Anlage-Empfehlungen dar. Die Moderatoren und der Verlag haften nicht für etwaige Verluste, die aufgrund der Umsetzung der Gedanken oder Ideen entstehen. Hörtipps: Für alle, die noch mehr wissen wollen: Holger Zschäpitz können Sie jede Woche im Finanz- und Wirtschaftspodcast "Deffner&Zschäpitz" hören. +++ Werbung +++ Du möchtest mehr über unsere Werbepartner erfahren? Hier findest du alle Infos & Rabatte! https://linktr.ee/alles_auf_aktien Impressum: https://www.welt.de/services/article7893735/Impressum.html Datenschutz: https://www.welt.de/services/article157550705/Datenschutzerklaerung-WELT-DIGITAL.html

你的錢，有在替你工作嗎？我是理財醫生陳大仁。《大仁的鈔能力》只講實戰邏輯：教你避開買房陷阱、打造股票現金流、掌握加密貨幣。每週更有免費直播課，教你如何讓投資變簡單，拿回財富主控權！ https://fstry.pse.is/8tgf5e —— 以上為 Firstory Podcast 廣告 —— 加入會員，支持節目： https://richlife.firstory.io/join 留言告訴我你對這一集的想法： 歡迎您用一杯咖啡支持我持續創作 : https://pay.soundon.fm/podcasts/a11a2120-4bc4-4fb2-813b-135bd96e5868 「布姐的交誼廳。陪你聊人生聊職場」Line 社群 https://reurl.cc/36NWEL(密碼：love) 本集重點： 打破「四十不惑」的迷思 現代人往往越活越迷惑，40 歲常不是「不惑」而是「大惑」，中年轉型與危機是許多人共同的課題 。 電機工程師的 16 年科技路 凱琳老師擁有電機學士與碩士學位，並在矽谷 Cisco（思科）等科技公司任職超過 10 年，職涯前期完全專注於科技領域 。 盲從社會期待的開端 早年選填志願大多照分數排，並依照當時社會覺得「有前途」的工作去填寫，缺乏自我探索的機會 。 覺察警訊一：對環境話題失去熱情 29 歲時發現同事們熱衷聊股票、產品與併購，自己卻完全不想參與，開始意識到自己與環境的格格不入 。 覺察警訊二：極度依賴度假逃避 發現自己越來越喜歡度假，且每次放假結束要回去上班時，都會感到心情沉重，必須深呼吸才能面對 。 覺察警訊三：預見未來的否定 觀察 50 歲的主管後，自問：「我到 50 歲還要坐辦公室做這些事嗎？」因答案是否定的，決定提早採取行動 。 在大公司內部進行「職涯實驗」 凱琳老師並未立刻離職，而是利用 Cisco 內部轉調機會，從寫軟體的工程師轉向「技術行銷（Technical Marketing）」，練習將機器語言轉譯為人類語言 。 從「人」的差異開啟心理學契機 在「銷售賦能（Sales Enablement）」工作中，發現每個人被激勵（Motivate）的方式不同，進而開啟對 MBTI 性格與心理學的興趣 。 轉型必經的「排除法」過程 很多人不知道自己要什麼，但可以先從「釐清自己不要什麼」開始，透過嘗試與淘汰法逐步找到適合的方向 。 性格影響轉型的擔憂（MBTI 觀點） 凱琳老師指出，MBTI 中的 SJ 族群（社群主義者） 傾向守規矩、追求穩定，因此在面對職涯變動時通常會比其他類型的人更猶豫、需要更多安全感 。 來賓 王凱琳 心理學人格特質分析專家，職涯發展諮商師，企業組織與領導力的發展顧問。具有電機工程碩士及心理學博士學位，並具有美國MBTI®心理學人格類型分析諮商大師級認證（Myers Briggs Type Indicator Master Practitioner in Step I & Step II）。　　早在2012年就把MBTI®帶入中文世界。《30分鐘破解性格密碼》是第一本由華人專家親筆書寫的MBTI®中文書。結合在高科技行業裡多年的豐富工作經驗與人格心理的專長，加上熟悉亞洲文化，因應不同文化、種族的需求，深入且實際地幫助中文世界的讀者。　　具有多樣藝術才華（音樂、舞蹈、繪畫等），亦擅長文學創作，是「海外華文女作家協會」認可的正式會員。著有：《思科現形記》、《30分鐘破解性格密碼》、《你是我的黑髮》、《見人說人話之超效溝通指南》。　　FB「王凱琳的人格心理沙龍」　　Podcast：人格心理沙龍

Take a Network Break! Guest commentator Tom Hollingsworth joins Drew for today’s episode. We start with a double Red Alert from Cisco for its Secure FMC software. On the news front, Cato Networks adds adaptive threat prevention to its SASE offering that looks for seemingly innocuous signals that could add up to an attack, Google... Read more »

Take a Network Break! Guest commentator Tom Hollingsworth joins Drew for today’s episode. We start with a double Red Alert from Cisco for its Secure FMC software. On the news front, Cato Networks adds adaptive threat prevention to its SASE offering that looks for seemingly innocuous signals that could add up to an attack, Google... Read more »

Take a Network Break! Guest commentator Tom Hollingsworth joins Drew for today’s episode. We start with a double Red Alert from Cisco for its Secure FMC software. On the news front, Cato Networks adds adaptive threat prevention to its SASE offering that looks for seemingly innocuous signals that could add up to an attack, Google... Read more »

Pastor Bob Fu was a student leader during the 1989 Tiananmen democracy movement and later led an underground Chinese house church. In 1996, he was imprisoned for “illegal evangelism.”He later fled China and came to the United States, where he founded ChinaAid, a Christian human‑rights organization that documents cases of persecution, provides legal aid, and advocates for religious freedom in China.In this episode, we dive into the escalation of religious persecution in recent years in China, including the growing dehumanization of Christians.Echoing Mao Zedong's targeting of “five black classes” during the Cultural Revolution, in 2012, the Chinese Communist Party (CCP) leaders labelled Christian underground churches as one of five new “black classes” or black categories.Fu says that the CCP's leadership is determined to destroy the positive image that Chinese people have of Christian believers.“Xi Jinping wants to play God,” Fu says. “The Communist Party treats these people as a threat to the regime's existence. The goal is to eradicate Christian faith from the map of China.”We also discuss a case now at the Supreme Court, Cisco v. Doe, which could have important repercussions for American companies that enable China's human rights atrocities.Views expressed in this video are opinions of the host and the guest, and do not necessarily reflect the views of The Epoch Times.

How should businesses rethink infrastructure when applications, data, and users are increasingly spread across thousands of locations? In this episode of Tech Talks Daily, I sit down with Mark Cree, President and Chief Operating Officer at Scale Computing, to talk about why the future of enterprise infrastructure is moving closer to where data is actually created. This conversation was recorded following the 66th edition of The IT Press Tour, where some of the most interesting conversations in enterprise infrastructure centered on what happens when businesses move away from oversized, monolithic stacks and start focusing on practical, distributed solutions. From retail stores and airports to remote industrial sites, the edge is becoming a critical part of modern IT strategy. Mark shares how Scale Computing has spent years building an edge-first platform designed to run critical workloads reliably across everything from a single location to tens of thousands of distributed sites. Mark also reflects on his own journey through the technology industry, which includes founding companies acquired by Cisco and NetApp, working as a venture capitalist, and leading major storage initiatives at AWS. That experience gives him a unique perspective on how enterprise infrastructure has evolved, particularly as organizations reconsider the balance between centralized cloud environments and local processing closer to users and devices. During our conversation, we explore why edge computing is becoming increasingly important for AI workloads, especially when large volumes of data are generated outside traditional data centers. Mark explains how processing information locally can reduce costs, improve performance, and enable entirely new use cases, from monitoring customer behavior in retail environments to running intelligent systems in remote locations. We also talk about the ongoing reassessment happening across enterprise IT teams following major industry shifts, including changes in the virtualization market and growing concerns around vendor lock-in. Mark explains how Scale Computing is positioning itself as a flexible alternative by combining virtualization, containerization, networking, and security into a platform designed specifically for distributed environments. Looking ahead, Mark shares his perspective on where enterprise infrastructure is heading over the next five years. As smaller AI models become more capable and organizations seek greater control over their data and systems, the role of edge platforms may become even more important.  Instead of relying solely on massive centralized environments, companies may find new value in distributing intelligence closer to the places where real-world activity happens. So as organizations rethink how they deploy applications, manage data, and control infrastructure, is the next big shift in enterprise IT happening right at the edge? And how prepared is your organization for that change?

Iran's MuddyWater breaches multiple U.S. organizations. The FBI probes a breach of wiretap management systems. A China-linked threat actor targets South American telecoms. Cisco patches critical firewall flaws. CISA flags actively exploited bugs in Hikvision cameras and Rockwell industrial systems. A House committee advances the controversial KIDS online safety bill. The FBI arrests a suspect accused of stealing millions in seized crypto from the U.S. Marshals Service. Ben Yelin and Ethan Cook unpack the dispute between Anthropic and the Pentagon. Wikimedia worm wreaks widespread wiki woes.  Remember to leave us a 5-star rating and review in your favorite podcast app. Miss an episode? Sign-up for our daily intelligence roundup, Daily Briefing, and you'll never miss a beat. And be sure to follow CyberWire Daily on LinkedIn. CyberWire Guest Today, we're bringing you a featured conversation from our Caveat podcast, where Ben Yelin sits down with N2K Lead Analyst Ethan Cook to unpack the fallout between the Pentagon and Anthropic, what led to the deal unraveling, and what it means as the government pivots to a similar AI contracting agreement with OpenAI. You can listen to their full conversation here and catch new episodes of Caveat featuring Dave and Ben every Thursday with special appearances by Ethan. Selected Reading Iranian APT Hacked US Airport, Bank, Software Company (SecurityWeek) Tech Giants, Washington Rally for Anthropic in Pentagon Feud (GovInfo Security) FBI investigates breach of surveillance and wiretap systems (Bleeping Computer) Chinese state hackers target telcos with new malware toolkit (Bleeping Computer) Cisco Patches 48 Firewall Vulnerabilities with Two CVSS 10 Flaws (Hackread) CISA Flags Hikvision Camera & Rockwell Logix Vulnerabilities as Actively Exploited (SOCRadar) House panel marks up kids digital safety act amid Democrat backlash (The Record) US contractor's son arrested over alleged $46M crypto theft (The Register) Wikipedia hit by self-propagating JavaScript worm that vandalized pages (Bleeping Computer) Share your feedback. What do you think about CyberWire Daily? Please take a few minutes to share your thoughts with us by completing our brief listener survey. Thank you for helping us continue to improve our show. Want to hear your company in the show? N2K CyberWire helps you reach the industry's most influential leaders and operators, while building visibility, authority, and connectivity across the cybersecurity community. Learn more at sponsor.thecyberwire.com. The CyberWire is a production of N2K Networks, your source for strategic workforce intelligence. © N2K Networks, Inc. Learn more about your ad choices. Visit megaphone.fm/adchoices

Want More XWorm? https://isc.sans.edu/diary/Want%20More%20XWorm%3F/32766 Cisco Secure Firewall Management Center Vulnerabilities https://sec.cloudapps.cisco.com/security/center/content/CiscoSecurityAdvisory/cisco-sa-fmc-rce-NKhnULJh https://sec.cloudapps.cisco.com/security/center/content/CiscoSecurityAdvisory/cisco-sa-onprem-fmc-authbypass-5JPp45V2 LastPass Phishing https://www.securityweek.com/lastpass-users-targeted-with-backup-themed-phishing-emails/

AB sits down with Tim Coogan, Cisco's SVP, Global Partner Sales, for a fun chat about the important role partners play to drive positive business outcomes. From partnering in the AI era to the link between sales and partnerships, this informative conversation highlights why it's critical for business to cultivate a powerful partner ecosystem.

On this week's show, Patrick Gray, Adam Boileau and James WIlson discuss the week's cybersecurity news. They cover: The US-Israeli attack on Iran had a whole lot of cyber. It's clearly in the playbook now! The NSA Triangulation / L3 Harris Trenchant iOS exploit kit is on the loose, and being used by Chinese crypto scammers So long Maddhu Gottumukkala, but CISA's annus horribilis continues Adam “humbug” Boileau complains about the Airsnitch wifi attack just being three ethernets in a trenchcoat ASD's Cisco SD-WAN threat hunting guide is clearly borne of … experience This week's episode is sponsored by AI threat hunting platform Nebulock. Sydney Marrone joins to talk about how useful AI models are on the hunt, and her work building out an open source framework and maturity model. It's methodology agnostic, so you can adapt it for your environment, and the github link is in the show notes! This episode is also available on Youtube. Show notes Inside the plan to kill Ali Khamenei Hacked traffic cams and hijacked TVs: How cyber operations supported the war against Iran | TechCrunch Matthew Prince

In this third installment of Claude Sessions, Danny is joined by Subash from Not A Square, who helps e-commerce brands scaling past seven figures implement AI without scaling headcount. Subash walks through real client case studies -- including a TikTok brand that boosted its customer satisfaction score from 4.2 to 4.5 in four weeks using a customer support agent built in Claude. Danny then breaks down OpenClaw, the open-source personal AI agent that exploded in popularity, explains why he chose not to use it despite the temptation, and reveals Claude Flow -- his custom operating system built inside Claude Code with 11 engines, 300+ features, and a persistent memory layer powered by ChromaDB. The episode drives home one core message: document your operations first, pick one platform, go deep, and stop chasing every new tool. Key Topics Documenting operations before automation -- Why you cannot automate what is not documented TikTok customer support case study -- Building an AI agent that raised satisfaction scores in four weeks OpenClaw overview and security risks -- What it does, why it blew up, and why Danny built his own alternative Claude Flow -- Danny's custom operating system inside Claude Code with persistent memory The amnesia loop -- How context loss between sessions kills productivity and how ChromaDB solves it Pixel-less environment -- The shift from structured prompts to contextual AI interaction Go deep on one platform -- Why chasing multiple AI tools guarantees you build nothing Timestamps [00:00] Introduction -- Claude Sessions Week 3, delayed from the road [01:03] Subash introduces himself and Not A Square [02:01] Overview of three client projects and the problem founders face [04:30] Why operational truth is the moat in AI commerce [06:48] Three pillars: reduce costs, better governance, scale without headcount [07:30] TikTok case study -- customer support agent boosting store score from 4.2 to 4.5 [09:04] OpenClaw -- history, capabilities, and the security nightmare [15:30] Six core capabilities of OpenClaw (local-first, universal messaging, persistent memory, browser automation, system access, self-extending skills) [18:00] Why OpenClaw matters -- moving from dumb LLMs to personal AI agents [20:00] Security trade-offs -- 1.5M API keys exposed, malware in skills, Cisco tests [22:00] Claude Flow -- Danny's 11-engine operating system built inside Claude Code [24:26] The amnesia loop -- how sessions lose context and how ChromaDB fixes it [28:19] Why Claude MD, agents, and skills are not enough without hooks and triggers [32:40] Go deep on one platform -- stop chasing every new tool [35:35] Subash on helping sellers adopt Claude Code fundamentals (Claude MD, skills) [39:51] Wrap-up and contact info Key Takeaways Document before you automate -- If your business operations live in the founder's head and not on paper, any AI tool will amplify the chaos rather than fix it. Operational truth is the moat -- Clean inventory, accurate catalogs, honest cashflow reporting. Get these right before touching AI. One AI agent moved the needle -- A single customer support agent on TikTok raised a brand's satisfaction score from 4.2 to 4.5 in four weeks, directly improving store visibility. Persistent memory changes everything -- ChromaDB captures decisions, patterns, and project context across sessions so Claude compounds in usefulness over time (zero entries in session one, 1,700+ by session 25). Scaffolding beats raw building -- Danny's Claude Flow system means a project that took five days six months ago now takes 40 minutes. The investment in infrastructure pays exponential returns. OpenClaw is proof of concept, not production-ready -- Broad permissions, prompt injection vulnerabilities, exposed API keys. Wait for the open-source community to patch the holes before diving in. Pick one platform and go all the way in -- Chasing multiple AI tools means you learn none of them deeply and build nothing of value.

Candidate filing has begun, mock elections are happening and officials are testing new ballot marking devices — the 2026 midterm election cycle is officially here. This week on the Ballot Battleground: Nevada podcast, host Ben Margiott interviews Nevada's elections chief, Secretary of State Cisco Aguilar. Ben and Sec. Aguilar discuss Nevada's new ballot marking devices, voter ID proposals at the state and federal level, whether Election Day should be a holiday, how Nevadans could vote in the future and much more. Learn more about your ad choices. Visit megaphone.fm/adchoices

A crafty new breed of social engineering attack is tricking users into launching malware straight from their clipboard, exposing a fresh vulnerability in Windows that even tech pros could fall for. Leo Laporte and Steve Gibson break down how the latest ClickFix and CrashFix exploits are outsmarting traditional defenses. The lowdown on last week's "no turn" picture of the week. Is an AI-driven hacking campaign a big deal now. Clause used in multiple Mexican government attacks. Apple continues to be confronted with age restrictions. COPPA needs an exception to allow age collection. Meta swamps law enforcement with AI-slop CSAM reports. Roskomnadzor has been busy blocking VPNs. Guess how many. The UK tries to report their self-scanning success. Remember that hacker who extorted the psychotherapy patients. Scattered Lapsus$ Hunters is actively recruiting women. Cisco lands another breathtakingly rare 10.0 CVSS. VulnCheck's report on 2025 vulnerabilities and exploits. Steve discovers a fabulous $72 Hardware Security Module. A listener shares an interesting AI service discovery. The very potent "ClickFix" exploit evolves Show Notes - https://www.grc.com/sn/SN-1067-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: meter.com/securitynow guardsquare.com threatlocker.com/twit adaptivesecurity.com outsystems.com/twit

A crafty new breed of social engineering attack is tricking users into launching malware straight from their clipboard, exposing a fresh vulnerability in Windows that even tech pros could fall for. Leo Laporte and Steve Gibson break down how the latest ClickFix and CrashFix exploits are outsmarting traditional defenses. The lowdown on last week's "no turn" picture of the week. Is an AI-driven hacking campaign a big deal now. Clause used in multiple Mexican government attacks. Apple continues to be confronted with age restrictions. COPPA needs an exception to allow age collection. Meta swamps law enforcement with AI-slop CSAM reports. Roskomnadzor has been busy blocking VPNs. Guess how many. The UK tries to report their self-scanning success. Remember that hacker who extorted the psychotherapy patients. Scattered Lapsus$ Hunters is actively recruiting women. Cisco lands another breathtakingly rare 10.0 CVSS. VulnCheck's report on 2025 vulnerabilities and exploits. Steve discovers a fabulous $72 Hardware Security Module. A listener shares an interesting AI service discovery. The very potent "ClickFix" exploit evolves Show Notes - https://www.grc.com/sn/SN-1067-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: meter.com/securitynow guardsquare.com threatlocker.com/twit adaptivesecurity.com outsystems.com/twit

AI isn't about replacing people — it's about unlocking productivity and making customer experiences feel more human. On this episode of Right About Now, Ryan Alford sits down with Vinod Muthukrishnan, VP & GM of Webex Customer Experience at Cisco, to discuss how AI is transforming customer experience from fragmented interactions into continuous, context-driven conversations. Vinod explains why the purpose of AI in CX is not efficiency alone — it's humanization. From “concierge agents” that become the face of a brand to agentic systems that orchestrate complex multi-step requests across departments, this conversation explores the end of CX silos and the rise of intelligent, brand-aligned AI interfaces. They also tackle the real question everyone's asking: is AI taking jobs — or elevating them? Key Takeaways AI should make CX more human. Automation should enhance context, empathy, and continuity — not remove them. Context is the missing link in customer loyalty. Most brands reset conversations every time. AI fixes that. Concierge agents become the brand. They orchestrate backend systems while delivering one seamless customer conversation. Agentic AI moves beyond tasks. It executes complex, multi-step “jobs” across systems over time. AI won't replace humans — but AI-powered humans will win. Repetitive work declines. Strategic expertise rises. Connect With the Guest Vinod Muthukrishnan VP & GM, Webex Customer Experience – Cisco X: https://x.com/Vinod_CC LinkedIn: https://www.linkedin.com/in/vinodmkrishnan Connect With Ryan Ryan Alford Website: https://ryanisright.com Instagram: https://www.instagram.com/ryanalford LinkedIn: https://www.linkedin.com/in/ryan-alford

A crafty new breed of social engineering attack is tricking users into launching malware straight from their clipboard, exposing a fresh vulnerability in Windows that even tech pros could fall for. Leo Laporte and Steve Gibson break down how the latest ClickFix and CrashFix exploits are outsmarting traditional defenses. The lowdown on last week's "no turn" picture of the week. Is an AI-driven hacking campaign a big deal now. Clause used in multiple Mexican government attacks. Apple continues to be confronted with age restrictions. COPPA needs an exception to allow age collection. Meta swamps law enforcement with AI-slop CSAM reports. Roskomnadzor has been busy blocking VPNs. Guess how many. The UK tries to report their self-scanning success. Remember that hacker who extorted the psychotherapy patients. Scattered Lapsus$ Hunters is actively recruiting women. Cisco lands another breathtakingly rare 10.0 CVSS. VulnCheck's report on 2025 vulnerabilities and exploits. Steve discovers a fabulous $72 Hardware Security Module. A listener shares an interesting AI service discovery. The very potent "ClickFix" exploit evolves Show Notes - https://www.grc.com/sn/SN-1067-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: meter.com/securitynow guardsquare.com threatlocker.com/twit adaptivesecurity.com outsystems.com/twit

A crafty new breed of social engineering attack is tricking users into launching malware straight from their clipboard, exposing a fresh vulnerability in Windows that even tech pros could fall for. Leo Laporte and Steve Gibson break down how the latest ClickFix and CrashFix exploits are outsmarting traditional defenses. The lowdown on last week's "no turn" picture of the week. Is an AI-driven hacking campaign a big deal now. Clause used in multiple Mexican government attacks. Apple continues to be confronted with age restrictions. COPPA needs an exception to allow age collection. Meta swamps law enforcement with AI-slop CSAM reports. Roskomnadzor has been busy blocking VPNs. Guess how many. The UK tries to report their self-scanning success. Remember that hacker who extorted the psychotherapy patients. Scattered Lapsus$ Hunters is actively recruiting women. Cisco lands another breathtakingly rare 10.0 CVSS. VulnCheck's report on 2025 vulnerabilities and exploits. Steve discovers a fabulous $72 Hardware Security Module. A listener shares an interesting AI service discovery. The very potent "ClickFix" exploit evolves Show Notes - https://www.grc.com/sn/SN-1067-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: meter.com/securitynow guardsquare.com threatlocker.com/twit adaptivesecurity.com outsystems.com/twit

A crafty new breed of social engineering attack is tricking users into launching malware straight from their clipboard, exposing a fresh vulnerability in Windows that even tech pros could fall for. Leo Laporte and Steve Gibson break down how the latest ClickFix and CrashFix exploits are outsmarting traditional defenses. The lowdown on last week's "no turn" picture of the week. Is an AI-driven hacking campaign a big deal now. Clause used in multiple Mexican government attacks. Apple continues to be confronted with age restrictions. COPPA needs an exception to allow age collection. Meta swamps law enforcement with AI-slop CSAM reports. Roskomnadzor has been busy blocking VPNs. Guess how many. The UK tries to report their self-scanning success. Remember that hacker who extorted the psychotherapy patients. Scattered Lapsus$ Hunters is actively recruiting women. Cisco lands another breathtakingly rare 10.0 CVSS. VulnCheck's report on 2025 vulnerabilities and exploits. Steve discovers a fabulous $72 Hardware Security Module. A listener shares an interesting AI service discovery. The very potent "ClickFix" exploit evolves Show Notes - https://www.grc.com/sn/SN-1067-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: meter.com/securitynow guardsquare.com threatlocker.com/twit adaptivesecurity.com outsystems.com/twit

A crafty new breed of social engineering attack is tricking users into launching malware straight from their clipboard, exposing a fresh vulnerability in Windows that even tech pros could fall for. Leo Laporte and Steve Gibson break down how the latest ClickFix and CrashFix exploits are outsmarting traditional defenses. The lowdown on last week's "no turn" picture of the week. Is an AI-driven hacking campaign a big deal now. Clause used in multiple Mexican government attacks. Apple continues to be confronted with age restrictions. COPPA needs an exception to allow age collection. Meta swamps law enforcement with AI-slop CSAM reports. Roskomnadzor has been busy blocking VPNs. Guess how many. The UK tries to report their self-scanning success. Remember that hacker who extorted the psychotherapy patients. Scattered Lapsus$ Hunters is actively recruiting women. Cisco lands another breathtakingly rare 10.0 CVSS. VulnCheck's report on 2025 vulnerabilities and exploits. Steve discovers a fabulous $72 Hardware Security Module. A listener shares an interesting AI service discovery. The very potent "ClickFix" exploit evolves Show Notes - https://www.grc.com/sn/SN-1067-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: meter.com/securitynow guardsquare.com threatlocker.com/twit adaptivesecurity.com outsystems.com/twit

A crafty new breed of social engineering attack is tricking users into launching malware straight from their clipboard, exposing a fresh vulnerability in Windows that even tech pros could fall for. Leo Laporte and Steve Gibson break down how the latest ClickFix and CrashFix exploits are outsmarting traditional defenses. The lowdown on last week's "no turn" picture of the week. Is an AI-driven hacking campaign a big deal now. Clause used in multiple Mexican government attacks. Apple continues to be confronted with age restrictions. COPPA needs an exception to allow age collection. Meta swamps law enforcement with AI-slop CSAM reports. Roskomnadzor has been busy blocking VPNs. Guess how many. The UK tries to report their self-scanning success. Remember that hacker who extorted the psychotherapy patients. Scattered Lapsus$ Hunters is actively recruiting women. Cisco lands another breathtakingly rare 10.0 CVSS. VulnCheck's report on 2025 vulnerabilities and exploits. Steve discovers a fabulous $72 Hardware Security Module. A listener shares an interesting AI service discovery. The very potent "ClickFix" exploit evolves Show Notes - https://www.grc.com/sn/SN-1067-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: meter.com/securitynow guardsquare.com threatlocker.com/twit adaptivesecurity.com outsystems.com/twit

In this episode of The Cybersecurity Defenders Podcast, we discuss some intel being shared in the LimaCharlie community.GitLab's Threat Intelligence Team published detailed findings on North Korean activity associated with the Contagious Interview campaign and broader IT worker operations.A financially motivated, Russian-speaking threat actor used generative AI tools to compromise more than 600 Fortinet FortiGate firewall instances between January and February, according to Amazon Web Services.Cisco has released emergency patches for a critical zero-day vulnerability in its Catalyst SD-WAN products that has been actively exploited in the wild.Citrini Research presents a forward-looking scenario framed as a June 2028 macro memo describing a “Global Intelligence Crisis” triggered by abundant AI-driven intelligence.Support our show by sharing your favorite episodes with a friend, subscribe, give us a rating or leave a comment on your podcast platform.This podcast is brought to you by LimaCharlie, maker of the SecOps Cloud Platform, infrastructure for SecOps where everything is built API first. Scale with confidence as your business grows. Start today for free at limacharlie.io.

A crafty new breed of social engineering attack is tricking users into launching malware straight from their clipboard, exposing a fresh vulnerability in Windows that even tech pros could fall for. Leo Laporte and Steve Gibson break down how the latest ClickFix and CrashFix exploits are outsmarting traditional defenses. The lowdown on last week's "no turn" picture of the week. Is an AI-driven hacking campaign a big deal now. Clause used in multiple Mexican government attacks. Apple continues to be confronted with age restrictions. COPPA needs an exception to allow age collection. Meta swamps law enforcement with AI-slop CSAM reports. Roskomnadzor has been busy blocking VPNs. Guess how many. The UK tries to report their self-scanning success. Remember that hacker who extorted the psychotherapy patients. Scattered Lapsus$ Hunters is actively recruiting women. Cisco lands another breathtakingly rare 10.0 CVSS. VulnCheck's report on 2025 vulnerabilities and exploits. Steve discovers a fabulous $72 Hardware Security Module. A listener shares an interesting AI service discovery. The very potent "ClickFix" exploit evolves Show Notes - https://www.grc.com/sn/SN-1067-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: meter.com/securitynow guardsquare.com threatlocker.com/twit adaptivesecurity.com outsystems.com/twit

It was so inspiring to have this conversation with the multi-talented singer-songwriter and pianist Vienna Teng . In this episode we're featuring the band Few of a Kind's new album, a beautiful collaboration with Vienna, Brandon Ridenour, Ben Russell, Yousif Sheronick, and Andrew Gutauskas. Vienna takes us inside their creative process with excerpts from each track. She also reflects on what truly makes a great song, how her identity evolved with parenthood, and how she has connected with audiences through her climate action workshops. Vienna also shared insights into two other brilliant recent projects, her unique album We've Got You and “The Riversitter” after Dave Eggers' “The Museum of Rain”.You'll hear the charming story of how she actually found her stage name, some highlights including opening for Joan Baez, performing on the Late Show with David Letterman and especially what it felt like to return to touring and recording after a ten-year hiatus after working in environmental sustainability. Full Show Notes for all the links: Vienna Teng's albums, website, Songwriter podcast, linked episodes with Gabriel Kahane, Jean Rohe, Ida Gillner, Fern Lindzon and Diane Nalini and my Newsletter, Merch store and how you can buy me a coffee to support this series!photo: Sherwin Lainez(00:00) Intro(02:21) Stage name story, David Letterman and early fame, working at Cisco(07:09) Few of a Kind band, with clip track 1 “Transcontinental 1:30 AM”(11:49) life of a singer, Ben Russel with clip of track 4 Two Steps From the Blues(18:31) creative process Few of a Kind, Octavian studios(20:52) environmental sustainability, decision to go back to university(28:07) Few of a Kind, clip of track 2 Alone, Brandon Ridenour(31:32) crafting a life in music with social impact(34:12) other linked episodes and ways to support this series(35:02) what makes a great song, Asian American identity Alex Wong(42:31) climate action workshops connected to concerts(47:20) We've Got You with clips, how Comfort and Spark fit together(54:33) writing “The River Sitter” after David Eggers “The Museum of Rain”(01:00:36) Few of a Kind, with clip of track 3 Five's Alive, Andrew Gutauskis, Yousif Sheronick(01:07:40) touring, opening for Joan Baez(01:12:03) coming back after 10 year hiatus

(Presented by Thinkst Canary: Most Companies find out way too late that they've been breached. Thinkst Canary changes this. Deploy Canaries and Canarytokens in minutes and then forget about them. Attackers tip their hand by touching 'em giving you the one alert, when it matters. With zero admin overhead and almost no false-positives, Canaries are deployed (and loved) on all 7 continents.) Three Buddy Problem - Episode 87: We wake up to news of U.S./Israel military action against Iran and the expected fallout, including Tehran's cyber capabilities and proxy risks. Plus: Anthropic's clash with the Pentagon over AI use in warfare, market shockwaves from AI-driven security tools, mass layoffs tied to automation, Trenchant exec sentencing and sanctions in the exploit trade, and fresh questions around Cisco's SD-WAN breach and supply-chain trust. Cast: Juan Andres Guerrero-Saade, Ryan Naraine and Costin Raiu.

With the continued growth of data centers for clouds, neoclouds (especially AI model training), for carriers, and for the enterprise, it's important to discuss data center network operations and issues. Scott is joined by Dr. Peter Welcher, a consultant, blogger, and Tech Field contributor. Together, they dive into how latency and the rise of AI... Read more »

With the continued growth of data centers for clouds, neoclouds (especially AI model training), for carriers, and for the enterprise, it's important to discuss data center network operations and issues. Scott is joined by Dr. Peter Welcher, a consultant, blogger, and Tech Field contributor. Together, they dive into how latency and the rise of AI... Read more »

Today, we've got Joe Ohr and Marli Hall from NMFTA to discuss the launch of SCAC Verified and why identity verification is quickly becoming a non-negotiable standard in freight brokerage, trucking, and supply chain operations! As verification requirements tighten across the industry, this NMFTA-led initiative strengthens carrier legitimacy through biometric verification, helping brokers, shippers, and carriers combat rising cargo theft, chameleon carriers, and digital fraud risks. We also cover the upcoming Freight Fraud Prevention Hub launching on March 3rd, a collaborative resource packed with best practices, fraud trends, and actionable strategies designed to protect logistics providers across the transportation industry.  As regulatory pressure increases from the FMCSA and fraud continues to escalate, maintaining an active SCAC code and adopting verification tools early will separate legitimate carriers from bad actors, build trust faster during onboarding, and create a real competitive advantage in today's freight market, because moving freight safely now starts with proving who you are! Visit this link to learn more: https://freightfraudhub.com/   About Joe Ohr Joe Ohr has more than two decades of experience in technical operations, customer success management, customer support, and product support. Currently serving as the Chief Operating Officer for the National Motor Freight Traffic Association, Inc. (NMFTA)™, he plays a pivotal role in helping to advance the industry through digitization, classification, and cybersecurity. Prior to Ohr's role at NMFTA, he served as in numerous engineering and operations positions at Qualcomm and Eaton, and most recently held the position of Senior Vice President of Operations/Customer Experience at Omnitracs. Throughout his career, Ohr has provided strategic guidance, vision, and a roadmap for addressing long-term customer challenges. He has played a key role in accelerating revenue growth and has collaborated closely with IT, product, and engineering teams to foster stronger partnerships with strategic customers and peers. Additionally, Ohr has overseen post sales customer support and service teams, as well as operations, managing a workforce of over 400 individuals. He holds multiple certifications such as CCNA from Cisco and MCSE from Microsoft and earned his Bachelor of Science in Education from the Ohio State University. Due to his contributions to the industry, he earned a spot in the Inner Circle in 2015 and 2018 from Qualcomm and Omnitracs.   About Marli Hall Marli Hall is the Director of Communications and Marketing at the National Motor Freight Traffic Association (NMFTA), where she leads strategic communication efforts to enhance the organization's visibility and reputation within the freight transportation industry. In this role, Marli oversees media relations, manages key messaging, and develops public relations campaigns that promote NMFTA's initiatives, partnerships, and contributions to the sector. She started with NMFTA in August 2022, previously serving as the director of communications and member services, and earlier as a communications specialist. Prior to NMFTA, Marli was the senior director of outreach & engagement at the Truckload Carriers Association (TCA) for nearly a decade. She directed marketing and communications strategies to promote TCA's educational programs, image initiatives, and outreach efforts. She holds a bachelor's degree in news editorial from West Virginia University and graduated from the Public Affairs & Advocacy Institute at American University. Marli has served as an FMCSA Our Roads Our Safety Program Partner and was nominated to the Women of Trucking Advisory Board. Marli resides in Alexandria, VA, with her husband, Chris, and enjoys visiting her family's 300-acre cattle farm and attending concerts.  

Jeetu Patel is the president and chief product officer at Cisco, where he leads a team of 30,000 people and is playing a central role in the massive AI infrastructure buildout happening right now. Previously, he spent five years as CPO at Box and 17 years running his own startup. Recently Jeetu organized an AI summit featuring industry leaders like Jensen Huang, Sam Altman, Marc Andreessen, and Fei-Fei Li.We discuss:1. How Cisco went AI-first across 90,000 employees2. His six-part framework for building great companies: timing, market, team, product, brand, distribution3. Why he says he couldn't have done this job without AI4. His “right to win” strategic framework5. His communication framework for preventing “packet loss” across an organization6. Why he flips “praise in public, criticize in private” and does the exact opposite7. The important communication lesson his mother taught him—Brought to you by:Sentry—Code breaks, fix it faster: https://sentry.io/lennyFramer—Build better websites faster: https://framer.com/lennySamsara—Saving lives with AI built for physical operations: https://samsara.com/lenny—Episode transcript: https://www.lennysnewsletter.com/p/ai-is-critical-for-humanitys-survival—Archive of all Lenny's Podcast transcripts: https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Jeetu Patel:• X: https://x.com/jpatel41• LinkedIn: https://www.linkedin.com/in/jeetupatel• Website: https://blogs.cisco.com/author/jeetupatel—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction and welcome(04:15) Insights from Cisco's Al summit(08:45) Transforming Cisco into an Al-first company(15:33) What Cisco actually does in the Al infrastructure stack(19:09) The future of Al(24:36) Raising kids in the AI era(29:46) “Permission to play” framework(36:50) Lessons from great CEOs(42:02) Leading at scale(50:54) Why Jeetu inverts the ‘praise in public, criticize in private' rule(57:45) Surrounding yourself with good human beings(58:35) Lessons from loss(01:03:21) Career advice: platforms, hunger, and preparation(01:10:21) The six-part framework for building great companies(01:19:05) Lightning round and final thoughts—Resources and episode mentions: https://www.lennysnewsletter.com/p/ai-is-critical-for-humanitys-survival—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

The CLAIR Model: A Synthesized Conceptual Framework for Mapping Critical Infrastructure Interdependencies [Guest Diary] https://isc.sans.edu/diary/The+CLAIR+Model+A+Synthesized+Conceptual+Framework+for+Mapping+Critical+Infrastructure+Interdependencies+Guest+Diary/32748 Cisco Catalyst SD-WAN Controller Authentication Bypass Vulnerability CVE-2026-20127 https://sec.cloudapps.cisco.com/security/center/content/CiscoSecurityAdvisory/cisco-sa-sdwan-rpa-EHchtZk https://blog.talosintelligence.com/uat-8616-sd-wan/ Abusing Cortex XDR Live https://labs.infoguard.ch/posts/abusing_cortex_xdr_live_response_as_c2/ OpenSSL Vulnerability CVE-2025-15467 https://seclists.org/oss-sec/2026/q1/220

On this week's show, Patrick Gray, Adam Boileau and James WIlson discuss the week's cybersecurity news. They cover: Low skill actors compromise 600 Fortinets with AI-generated playbooks Anthropic calls out Chinese AI firms over model distillation Meta's director of AI safety tells her ClawdBot not to delete her mail… so of course it does Peter Williams cops 7 years in jail for selling L3 Harris Trenchant's exploits to Russia Ivanti got hacked in 2021 via… bugs in Ivanti This episode is sponsored by line-rate network capture system Corelight. CEO Brian Dye joins to discuss what AI can do for defenders, and what it can't. This episode is also available on Youtube. Show notes AI-augmented threat actor accesses FortiGate devices at scale "this reads to me like: they ran existing tools.... but with a cool dashboard :D" Anthropic accuses Chinese labs of trying to illicitly take Claude's capabilities | CyberScoop Detecting and preventing distillation attacks Hegseth warns Anthropic to let the military use the company's AI tech as it sees fit, AP sources say Anthropic Rolls Out Embedded Security Scanning for Claude AWS's AI Coding Bot Kiro Caused a 13-Hour Outage Running OpenClaw safely: identity, isolation, and runtime risk Former Adobe, Cisco and Salesforce CISO talks AI pentesting History Repeats: Security in the AI Agent Era Meta Director of AI Safety Allows AI Agent to Accidentally Delete Her Inbox Microsoft says Office bug exposed customers' confidential emails to Copilot AI | TechCrunch The (tangential) fix: Microsoft adds Copilot data controls to all storage locations Ex-L3Harris executive sentenced to 87 months in prison for selling zero-day exploits to Russian broker Treasury Sanctions Exploit Broker Network for Theft and Sale of U.S. Government Cyber Tools Risky Bulletin: Russia starts criminal probe of Telegram founder Pavel Durov Ukraine pushes tighter Telegram regulation, citing Russian recruitment of locals The watchers: how openai, the US government, and persona built an identity surveillance machine that files reports on you to the feds Persona emails customers saying they don't work with ICE or DHS amid ‘surveillance' claims Inside the Fix: Analysis of In-the-Wild Exploit of CVE-2026-21513 Ivanti hacked in 2021 via its own product Fed agencies ordered to patch Dell bug by Saturday after exploitation warning | The Record from Recorded Future News From BRICKSTORM to GRIMBOLT: UNC6201 Exploiting a Dell RecoverPoint for Virtual Machines Zero-Day