Podcasts about Google Cloud

We unpack why the “SaaS-Pocalypse” is less about software dying and more about buyers finally right sizing cloud and marketplace deals with better data. We dig into AI unit economics, token driven cost volatility, and how procurement, FinOps, and venture capital are being rewritten in real time. • Flywl as a cloud meta marketplace across AWS, Azure, and Google Cloud • Buyer pain and buyer empathy as the product design center • Why AI inference costs make traditional FinOps reactive • Treating a marketplace purchase as a transaction lifecycle asset • Real time consumption tracking, alerts, and contract renegotiation timing • Outcome based pricing challenges with token variability and agentic workflows • Revenue recognition uncertainty in consumption and outcome models • Why humans still matter in go to market despite AI agents • The data cleanup problem in procurement and the need for universal product IDs • Why enterprises are not rushing to build all SaaS internally with AI • 2026 VC dynamics, mega rounds, capital concentration, and what counts as real recurring revenue “SaaS-Pocalypse” makes for a great headline, but the real shockwave is quieter and more disruptive: enterprise buyers finally understand their cloud environment well enough to demand better deals, better governance, and real proof of value. We sit down for a roundtable on cloud marketplaces, AI unit economics, and the new reality of software procurement where a purchase is no longer a static line item, it's a living asset you have to monitor, benchmark, and continuously right size. Ankur Srivastava, CEO and founder of Flywl, explains why he built a cloud meta marketplace to unify buying and selling across AWS Marketplace, Azure, and Google Cloud and why “buyer empathy” is the only way to fix a broken procurement playbook. Priya Ramachandran, founder and managing partner at Foster Ventures, connects the dots from operator experience to investing, and breaks down why traditional FinOps can't keep up with AI inference costs, token volatility, and outcome-based pricing models like per ticket resolved. Then we zoom out to the 2026 venture capital environment: mega rounds, capital concentration, and the debate over whether AI-native efficiency makes old funding assumptions obsolete. Along the way, we tackle an agentic economy question: when algorithms negotiate with algorithms, what happens to trust, brand, and human relationships in go to market?Ankur Srivastava: https://www.linkedin.com/in/ankursrivas/Ankur Srivastava is the CEO and Founder of Flywl, the world's first cloud meta-marketplace transforming how enterprises buy and sell software across AWS, Azure, and Google Cloud. Previously, he was an elite sales leader at Amazon Web Services (AWS), where he spent five years as Head of Field and Customer Business Development for the AWS Marketplace.Priya Ramachandran: https://www.linkedin.com/in/sivapriyaramachandran/Priya Ramachandran is the Founder and Managing Partner at Foster Ventures, an early-stage VC firm she built from the ground up to act as the "startup of the VC world". She is an operator-turned-investor with significant experience building and scaling products at companies like Coupa Software, BetterCloud, and Intel.Website: https://www.position2.com/podcast/Rajiv Parikh: https://www.linkedin.com/in/rajivparikh/Sandeep Parikh: https://www.instagram.com/sandeepparikh/Email us with any feedback for the show: sparkofages.podcast@position2.com

In today's Cloud Wars Minute, I explain why Oracle's massive RPO growth proves demand for AI infrastructure is real, not a bubble. Highlights 00:00 — For the last several weeks, we've all been hearing gloom and doom, there's going to be AI overcapacity for data centers, and then talking about all these things that Oracle can't do. I want to talk about this in the context of Oracle's terrific Q3 numbers that came out earlier this week. I hope what they'll do as a residual effect is shut the pie holes of some of these just lame-brain skeptics . 01:15 — So I hope some of those people either be quiet, get off to the sidelines, or maybe think a little bit more about how the world is changing, and the tech vendors, especially the ones in the Cloud Wars Top 10, have to change to meet these new times. So let me describe some of what's behind that in these big numbers from Oracle. 01:38 — Like I said, there is RPO, remaining performance obligation, up 325%. It added $29 billion of new RPO in the quarter. The cloud business, 44%. It's $8.9 billion, very, very strong there. Inside some of those numbers, its multicloud database up 531%. It's a huge jump. That's where Microsoft, Amazon, and Google Cloud all sell the Oracle database to their customers. 02:22 — So a big, big business there, the AI infrastructure business overall up 243%, and the RPO is now up $553 billion, well over half a trillion dollars of contracted business that Oracle has not yet recognized as revenue. So it shows enormous growth for the future. Yet in spite of all these things, we've heard relentlessly from these Chicken Little types. 03:04 — First, that there's an AI data center buildout. This is all a bubble. It's going to explode. There's all these hundreds of millions of dollars in CapEx chasing a dream that will never happen. We've heard a lot about that Oracle, which earlier this year said it's going to use debt financing to fund its data center expansion. That that's terrible. 04:18 — Oracle's wildly profitable. It's in great shape on this. There are still other cry babies who are running around saying that the new CEOs aren't ready to handle this. They were supremely in charge on this earnings call, very, very clear, concise descriptions of the strategy and what's going forward. 05:02 — Now, looking ahead this fiscal year, which ends May 31, Oracle's projecting total revenue $67 billion. A year out from that, fiscal 27, it's projecting total revenue for the company of $90 billion. So the whole company growing 34%, turbocharged by what it's doing in the cloud and AI. This is an extraordinary time to be alive. Don't listen to the doom and doomsday folks. Visit Cloud Wars for more.

Parce que… c'est l'épisode 0x723! Préambule Nous sommes à la Cage durant un match des Canadiens. Le bruit ambiant a fait que nous parlons en “criant”, pour nous entendre. Le lendemain, je n'avais plus de voix. Shameless plug 31 mars au 2 avril 2026 - Forum INCYBER - Europe 2026 14 au 17 avril 2026 - Botconf 2026 20 au 22 avril 2026 - ITSec Code rabais de 15%: Seqcure15 28 et 29 avril 2026 - Cybereco Cyberconférence 2026 9 au 17 mai 2026 - NorthSec 2026 3 au 5 juin 2026 - SSTIC 2026 19 septembre 2026 - Bsides Montréal 1 au 3 décembre 2026 - Forum INCYBER - Canada 2026 24 et 25 février 2027 - SéQCure 2027 Description Un retour après une longue absence C'est avec une certaine nostalgie que j'accueille Nicolas Bédard, un invité régulier qui avait mystérieusement disparu des ondes pendant plusieurs mois. La raison de cette absence ? Un changement de carrière majeur qui a bousculé son quotidien et rendu toute planification d'enregistrement pratiquement impossible. Entre les décalages de calendrier, les voyages et les nouvelles responsabilités à apprivoiser, les deux complices n'avaient tout simplement pas réussi à se retrouver devant un micro. Mais Nicolas est de retour, et il a beaucoup à raconter. Cinq ans chez Google : de l'imposter syndrome aux 20 % Tout commence en août 2020, quand Nicolas rejoint Google en pleine pandémie, parmi une cohorte de 10 000 nouvelles recrues embauchées simultanément. L'imposter syndrome le frappe de plein fouet. Comment se démarquer dans une entreprise peuplée de talents exceptionnels ? Sa réponse : trouver une niche où son expérience passée peut faire une différence. Connaissant bien Palo Alto Networks de ses vies professionnelles antérieures, Nicolas remarque un courriel interne annonçant le lancement d'un nouveau produit, Cloud IDS. Il contacte directement le gestionnaire de produit pour offrir son aide. C'est ainsi que naît son premier projet à 20 %. La règle des 20 % est une particularité culturelle bien connue de Google : chaque employé a le droit de consacrer 20 % de son temps de travail à un projet annexe, à condition que celui-ci apporte de la valeur à la compagnie ou à la société. C'est d'ailleurs ce principe qui aurait mené à la création de Gmail. Pour Nicolas, cette liberté devient un levier de croissance personnelle et professionnelle remarquable. Pendant quatre ans, il consacre ce temps à renforcer l'alliance stratégique entre Google et Palo Alto Networks, deux géants dont le partenariat commercial est l'un des plus importants dans l'industrie de la cybersécurité. Il co-présente des produits lors de conférences comme Google Next, développe une expertise pointue sur les intégrations conjointes, et gagne en visibilité des deux côtés de l'alliance. Son 20 % devient, en quelque sorte, son véritable terrain de passion. Le moment décisif : convertir le 20 % en 100 % Après avoir tenté sans succès d'obtenir un poste dédié à cette alliance à l'intérieur même de Google, Nicolas pivote vers l'équipe Google Cloud Security (GCS) pour ses six derniers mois dans l'entreprise. C'est alors qu'il reçoit un texto inattendu de la personne responsable de l'alliance Google-Palo : un poste s'ouvre chez Palo Alto Networks pour prendre en charge tout l'enablement technique lié aux fournisseurs infonuagiques. Son nom a été mentionné. L'offre ? Transformer son ancien 20 % en 100 % de son travail. La décision n'est pas difficile à prendre. Bien que les produits de Google soient de grande qualité, Nicolas constate lors de ses discussions avec des clients que des angles morts existent dans l'offre de sécurité. Les entreprises ne vivent pas exclusivement dans un seul environnement infonuagique : elles jonglent entre des charges de travail on-premises, AWS, Azure, Google Cloud et Oracle Cloud. Palo Alto Networks, en tant que pure player de la cybersécurité, possède cet avantage de la spécialisation que ne peut pas toujours offrir un généraliste comme Google, si bon soit-il. Un nouveau rôle centré sur la valeur, sans pression de vente Ce qui enthousiasme particulièrement Nicolas dans son nouveau poste, c'est l'abandon du quota de vente. Fini la pression commerciale mensuelle : il peut désormais enfiler son chapeau de formateur et se concentrer sur la transmission de la connaissance. Son équipe de quatre personnes se structure autour de quatre missions principales : L'intégration de produits, pour s'assurer que les solutions conjointes Palo-Google fonctionnent de façon fluide et cohérente ; La création de sales plays, des guides qui permettent aux équipes de vente de bien articuler la valeur des produits devant les clients ; L'enablement, qui passe par des conférences, des webinaires, des architectures de référence et des démonstrations techniques ; Le soutien aux équipes commerciales, qui garde Nicolas connecté à la réalité du terrain sans qu'il soit lui-même sous pression de résultats. L'alliance Google-Palo Alto : une symbiose technique profonde L'intégration entre les deux entreprises va bien plus loin qu'un simple partenariat commercial. La quasi-totalité des produits de Palo Alto Networks tourne aujourd'hui sur l'infrastructure de Google Cloud. Certains produits Google, comme Cloud IDS ou Cloud NGFW Enterprise, sont en réalité propulsés par la technologie de Palo Alto en dessous. Des utilisateurs de Prisma Access, l'outil SASE de Palo, traversent l'infrastructure de Google à chaque connexion VPN sans nécessairement le savoir. L'alliance permet également des optimisations réseau avancées, comme l'appairage natif entre Prisma Access et Google Cloud via le Network Connectivity Center. L'intelligence artificielle : le prochain grand terrain de jeu La conversation s'oriente naturellement vers l'IA, sujet incontournable du moment. Nicolas identifie deux enjeux majeurs pour les entreprises qui adoptent ces technologies : la consistance des résultats (les modèles d'IA ne sont pas déterministiques comme un formulaire web) et, en second lieu, la sécurité. Les grands fournisseurs infonuagiques développent des modèles de pointe, mais ils sont moins bien équipés pour gérer des problématiques comme la prévention des fuites de données (DLP), la protection contre le prompt injection ou la sécurisation des pipelines IA. C'est exactement là que Palo Alto Networks intervient en complémentarité, comme en témoigne l'annonce récente d'une intégration de Prisma AIRS directement dans Microsoft Copilot. Un virage vers la souveraineté numérique En guise de conclusion, Nicolas évoque brièvement le thème de la souveraineté numérique, sujet d'autant plus brûlant dans le contexte géopolitique actuel. Les organisations cherchent à reprendre le contrôle de leurs données, à réduire leur dépendance envers des infrastructures étrangères et à explorer les options de nuage souverain. Un vaste sujet que les deux complices promettent d'explorer en profondeur lors d'un prochain épisode, avec Nicolas qui se retrouve, cette fois-ci, aux premières loges de cette transformation. Collaborateurs Nicolas-Loïc Fortin Nicolas Bédard Crédits Montage par Intrasecure inc Locaux réels par La Cage - Complexe Desjardins

I break down Andrej Karpathy's new open-source project, Autoresearch: what it is, how it works, and why some of the smartest people in tech are losing their minds over it. I walk through 10 concrete business ideas you can build on top of Autoresearch loops, from niche agent-in-a-box products to always-on A/B testing agencies. I also cover Karpathy's companion launch, Agent Hub, share community reactions, and show you step by step how to get started using Claude Code and a Colab GPU. I'm hosting a free workshop so you can build your business in the age of AI. Sign up here: https://startup-ideas-pod.link/build-with-ai-2026 Links Mentioned: Autoresearch Github: https://startup-ideas-pod.link/autoresearch Timestamps 00:00 – Intro 00:45 – How Autoresearch Actually Works 02:40 – Visual Walkthrough of the Autoresearch Loop 03:37 – Mental Model: Your Research Bot That Runs While You Sleep 05:26 – Idea 1: Niche Agent-in-a-Box Products 06:48 – Idea 2: A/B Testing for Marketing (Landing Pages & Ads) 08:45 – Idea 3: Research as a Service 09:43 – Idea 4: Power Tool Inside Your Own SaaS 10:49 – Idea 5: Agency That Runs 100× More Tests 12:05 – Idea 6: Auto Quant for Trading Ideas 13:44 – Idea 7: Always-On Lead Qualification & Follow-Up 14:21 – Idea 8: Finance Ops Autopilot for Businesses 15:09 – Idea 9: Internal Productivity Lab for Your Org 15:53 – Idea 10: Done-for-You Research & Due Diligence Shop 16:41 – Non business use cases 18:27 – Karpathy's Agent Hub Announcement 19:50 – How to Get Started with Autoresearch 22:21 – Final Thoughts Key Points Autoresearch is an open-source AI agent that sets a goal, runs experiments in a loop on a GPU, keeps the winners, and discards the rest — all while you sleep. You need an NVIDIA GPU to run it (tested on H100), but you can rent one cheaply through Lambda Labs, Vast AI, RunPod, Google Cloud, or Google Colab. The fastest way to get started is to use Claude Code to walk you through installation, then run it on Google Colab with a T4 GPU runtime. Ten business ideas built on Autoresearch span niches like SaaS optimization, A/B testing agencies, trading backtests, CRM lead scoring, and done-for-you due diligence. Karpathy also launched Agent Hub — essentially a GitHub designed for agent swarms to collaborate on the same codebase. The project already has 25,000+ GitHub stars and is growing fast; early movers who tinker now build an unfair advantage. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

Every vendor in the industry is slapping the word "agentic" on their roadmap. But, what is agentic AI, really? And should IT leaders care?In this episode, we bring together three voices with very different answers: a skeptic who says it's rebranded orchestration, a strategist who says the reasoning layer is genuinely new, and a founder betting his company on it. Together, they cut through the noise and answer the question every IT leader is quietly asking: what should I actually do about agentic AI in 2026?Key takeaways:Why 80% of AI projects fail — and it has nothing to do with the technologyThe difference between "embedded agents" you're already using and custom agents you probably don't need yet"Start with your decisions, not your technology" — a practical framework for mid-market teamsHow to move AI from "pet project" to operationalized infrastructureFeaturing: Sean Larkin, Principal Architect at Softchoice, a World Wide Technology company | Scott Trump, Founder & CEO of Treva AI (former AWS, Google Cloud, Oracle) | Skip Vanderburg, Founder of Prioriti AI#AgenticAI #MidMarketIT #AIStrategy #TheCatalyst #Softchoice #ITLeadershipThe Catalyst by Softchoice is the podcast dedicated to exploring the intersection of humans and technology.

Summary In this episode of Chattinn Cyber, Marc Schein is chattin' with Mike Armistead, a seasoned cybersecurity expert with over 40 years of experience, including more than 20 years as a vendor in the cybersecurity space. The conversation opens with a discussion about the challenges security leaders face in 2026. Mike highlights the complexity of their role, comparing it to that of a CFO managing financial risk, but notes that cybersecurity leaders often lack the comprehensive management tools that CFOs have. He emphasizes the fragmented nature of cybersecurity tools and the difficulty in stitching together disparate signals to form a coherent security posture. Mike further explains that the human element is the critical glue in cybersecurity programs. The effectiveness of security teams depends heavily on the leadership and the ability of individuals to contextualize technical signals within the business environment. This need for situational awareness is driving interest in AI technologies, particularly on the defender side, to augment human capabilities and expand the scope and depth of security operations. The chat then shifts to the role of AI in cybersecurity products. Mike observes that while AI is increasingly integrated into detection tools, the industry has largely shifted focus away from prevention. He advocates for a strategic return to prevention, where AI can play a significant role in helping security leaders develop and implement risk mitigation strategies tailored to their organizations. Mike stresses the importance of a holistic approach that goes beyond real-time detection to include employee training, access control, and disaster recovery. Addressing the challenges faced by middle-market organizations, Mike points out that these companies are often expected to meet the same cybersecurity standards as large enterprises but with far fewer resources. He advises middle-market CISOs to prioritize protecting their most critical assets—their “crown jewels”—and to have candid conversations with leadership about realistic security goals. This pragmatic approach helps ensure that limited resources are focused on the highest risks rather than attempting to cover every possible threat. Finally, Mike shares information about a community he helped start called the Security Impact Circle, which focuses on cybersecurity leadership issues such as board engagement. This community facilitates workshops that bring together CSOs and board directors to bridge the communication gap and align security priorities with business needs. Mike encourages listeners to visit securityimpactcircle.org to learn more and get involved. Five Key Points Covered Cybersecurity leaders face complex challenges similar to CFOs but lack equivalent management tools. Human expertise is essential to contextualize technical security signals within the business environment. AI is increasingly used in detection but should also be leveraged to enhance prevention strategies. Middle-market organizations must prioritize protecting their most critical assets due to limited resources. The Security Impact Circle community helps improve communication and alignment between security leaders and boards. Five Key Quotes from the Conversation “Security leaders have a tough job… it's not unlike what a CFO has to think about, right? That risk happens to be financial, and the CISOs really happens to be in cyber.” “The security teams are really bound by how good not only their leader, but the deputies, the managers, the architects, those individual contributors that really help lead it.” “I think the opportunity is to swing it back to prevention… AI can really start to help on the prevention strategy side of cybersecurity.” “Middle-market leaders are expected to do everything that the largest enterprises do, but they don't have the resources to cover all the ground.” “We bring in a director from a public company's audit committee to run workshops… it's less about what a CSO thinks they should say and more about what the director thinks they need to hear.” About Our Guest Mike Armistead brings nearly 40 years of business experience marked by a proven track record of building companies, navigating strategic acquisitions, and leading growth at every stage. As co-founder and CEO of Respond Software, acquired by Mandiant for $200 million, and co-founder of Fortify Software, acquired by HP for $285 million, Mike has played pivotal roles in multiple successful startups, including serving as SVP on the turnaround team at WhoWhere (acquired by Lycos for $133 million) and contributing to Pure Software's IPO. His post-acquisition leadership includes key roles as VP of Products & UX at Mandiant, Director at Google Cloud, and VP & GM for Fortify and ArcSight business groups at HPE, where he drove significant expansion and over $400 million in revenue impact. Alongside these successes, Mike gained valuable insights from two brief ventures, including leading InLeague through post-9/11 financial challenges and emphasizing product-market fit in another startup. Beginning his career as a Product Manager at HP in the late 1980s, Mike's multifaceted experience spans diverse industries and company sizes. Today, he remains passionate about building high-performing teams and tackling complex, noble challenges. Follow Our Guest LinkedIn About Our Host National co-chair of the Cyber Center for Excellence, Marc Schein, CIC,CLCS is also a Risk Management Consultant at Marsh McLennan Agency. He assists clients by customizing comprehensive commercial insurance programs that minimize the burden of financial loss through cost effective transfer of risk. By conducting a Total Cost of Risk (TCoR) assessment, he can determine any gaps in coverage. As part of an effective risk management insurance team, Marc collaborates with senior risk consultants, certified insurance counselors, and expert underwriters to examine the adequacy of existing client programs and develop customized solutions to transfer risk, improve coverage and minimize premiums. Follow Our Host Website | LinkedIn  

In today's Cloud Wars Minute, I analyze Oracle's projected Q3 numbers and the explosive growth of its cloud and AI infrastructure business. Highlights 00:02 — Tomorrow, March 10, Oracle releases its Q3 numbers. I think these will be some of the most interesting we see from any of the Cloud Wars Top 10 companies, because relative to Oracle's size, its growth rates are up near the very top, and its RPO growth has been absolutely astronomical. 00:58 — So you might think of it as pipeline or backlog. This is money that's again fully contracted. It is not yet recognized as revenue, but it's an indication of where customers in the future are putting their hearts, minds, and wallets. I'll take a look at some key numbers for Oracle and compare the Q2 results with my Q3 projections. 02:02 — So for Q2, Oracle's RPO grew in Q2 over Q1 $68 billion. It had some huge deals in there with Meta and NVIDIA. It'll still do very well adding another $59 billion to its RPO. Now we look at its cloud revenue. For Q2 it was a total of $8 billion, up 34%. 03:13 — The OpenAI deal is massive, probably around $300 billion, but there's a lot more in there beyond that $300 billion. Oracle is emphasizing that it has a wide-ranging cloud infrastructure and AI infrastructure business that includes traditional moves from on-premise to cloud and other services beyond the OpenAI deal. 04:06 — Google Cloud hit almost $18 billion in its quarter. Now Oracle is almost half the size of Google Cloud, but it's got this tremendous backlog of future business because of capabilities around AI training, AI inferencing, and its core businesses as well. Visit Cloud Wars for more.

AI development is getting easier, but building production-ready systems remains a challenge. From vibe coding experiments at Mobile World Congress to shifts in AI silicon, networking infrastructure, and the evolving app economy, Patrick Moorhead & Daniel Newman explore what's actually changing inside enterprise technology on this episode of The Six Five Pod. The handpicked topics for this week are: MWC Recap and the Rise of "Vibe Coding": Experiments at Mobile World Congress highlighted how AI interfaces are lowering the barrier to building applications. Tools like Perplexity Computer enabled rapid prototyping of workforce tools, content systems, and market-modeling apps. While experimentation is easier than ever, production-grade systems still require security, accuracy, and operational discipline. The Collapse of Traditional Development Gatekeeping: AI-driven interfaces are reshaping who can build software. Users without deep engineering backgrounds can now quickly generate functional applications. Pat & Dan explore how this shift could dramatically increase the volume of software development while changing the role of traditional developers. AI Infrastructure and the Silicon Arms Race: AI infrastructure continues to evolve as companies compete to deliver efficient compute and networking at scale. Qualcomm is entering rack-scale inference with LPDDR-based architectures designed for efficiency, while Nvidia is investing heavily in optical networking through companies like Lumentum and Coherent to address power and scaling constraints. Intel's Push to Stay Competitive in Enterprise AI: Intel continues advancing its enterprise and carrier roadmap with technologies like Xeon 6 and the 18A process. While the company faces pressure in hyperscaler markets, it remains focused on maintaining relevance in enterprise and telecom infrastructure deployments. Apple's AI Infrastructure Challenge: Reports suggest Apple is evaluating Google Cloud to support infrastructure for future Siri capabilities. The hosts highlight the company's ongoing challenges with internal AI infrastructure development and the broader competition for AI talent. The Flip: Is AI Ending the App Economy? The weekly Flip debate takes on vibe coding. Will AI-driven development lead to an explosion of applications that disrupts traditional SaaS monetization models? Or will this shift simply upgrade the app economy with simple tools, while durable SaaS businesses focus on unique data, strong governance, and trusted platforms. AI Capex Continues to Drive Semiconductor Growth: Broadcom and Marvell continue benefiting from the rapid expansion of AI infrastructure. Demand for networking, connectivity, and high-performance silicon reflects the ongoing global buildout of AI compute capacity. Cybersecurity and AI Disruption Questions: CrowdStrike delivered strong financial results but faced investor questions about how AI could reshape the cybersecurity landscape. The discussion highlights how AI will both disrupt and reinforce security platforms. Capex Pressure and AI Investment Cycles: Amazon faced stock pressure related to the scale of its infrastructure investment, yet its Trainium chip strategy and expanding partnerships, including work with OpenAI, reinforce its long-term AI ambitions. For a deeper dive into each topic, please click on the links below. Subscribe to our channel so you never miss an episode. The Decode NVIDIA moves aggressively into optical networking supply chain https://www.cnbc.com/2026/03/02/nvidia-investment-coherent-lumentum.html Qualcomm enters rack-scale AI inference race https://www.qualcomm.com/news/onq/2026/03/ai-inference-that-scales-qualcomm-ai200-infrastructure-management-suite Intel's Xeon 6+ "Clearwater Forest" signals 18A moment https://x.com/PatrickMoorhead/status/2028751486587486675?s=20 Apple reportedly evaluating Google Cloud for next-gen Siri https://www.nasdaq.com/articles/apple-explores-deepening-google-partnership-next-gen-siri Perplexity Computer sparks new "AI operating system" narrative https://www.perplexity.ai/hub/blog/introducing-perplexity-computer https://x.com/PatrickMoorhead/status/2028089608559378846?s=20 Stripe's Billing for AI Startups https://techcrunch.com/2026/03/02/stripe-wants-to-turn-your-ai-costs-into-a-profit-center/ Bulls & Bears Broadcom earnings watch — custom AI silicon boom https://www.cnbc.com/2026/03/04/broadcom-avgo-q1-earnings-report-2026.html CrowdStrike Q4 earnings https://ts2.tech/en/crowdstrike-stock-holds-steady-after-upbeat-2027-forecast-as-wall-street-sizes-up-arr/ ServiceNow CEO buys $3M of stock https://www.barrons.com/articles/servicenow-ceo-buy-stock-execs-cancel-sales-be8c597f?gaa Amazon's Extreme AI Spending Sends Stock to Worst Month in Years https://finance.yahoo.com/news/amazon-extreme-ai-spending-sends-123002260.html  

Na véspera do Dia Internacional da Mulher, o Podcast Canaltech recebe Milena Leal, country manager do Google Cloud no Brasil, para uma conversa sobre tecnologia, carreira e o futuro da inteligência artificial nas empresas. Milena começou a trabalhar aos 14 anos em um call center e hoje lidera uma das maiores operações de cloud do país. Na entrevista, ela fala sobre sua trajetória no setor de tecnologia, os desafios que enfrentou ao longo da carreira e a importância de ampliar a presença feminina em posições de liderança. A executiva também explica como a inteligência artificial já está transformando empresas brasileiras em setores como varejo e serviços financeiros, além de comentar o papel do Brasil na corrida global por inovação e os próximos passos da tecnologia, incluindo o avanço de agentes de IA capazes de automatizar decisões e processos. Você também vai conferir: NVIDIA não fará novos investimentos na OpenAI e na Anthropic, falha em navegadores com IA pode roubar senhas do computador e Pedágio sem cancela pode ter milhões de multas canceladas. Este podcast foi roteirizado e apresentado por Fernada Santos e contou com reportagens de Marcelo Fischer, Lilian Sibila e Paulo Amaral, sob coordenação de Anaísa Catucci. A trilha sonora é de Guilherme Zomer, a edição de Leandro Gomes e a arte da capa é de Erick Teixeira.See omnystudio.com/listener for privacy information.

Ashwin Agrawal came to the US when he was 17, to Rochester for school. He now lives in the Bay Area, and admits he misses his friends on the east coast, as they all stayed back in that area - but he does NOT miss the winters. He has been building his current venture for 3-4 years, and prior to that, he was as at Google for a decade, apart of Google Cloud's huge growth trajectory. Outside of tech, he has a family with 2 middle school sons, with whom he likes to spend a lot of time with, hiking or eating good sushi.Ashwin was laid off from a few jobs in the past. After experiencing this, he vowed to build a solution that would help people going through this sort of experience. After the last layoff, he formed his company at 4:30 am in the morning, to help anyone in point A wanting to go to point B.This is the creation story of MobiusEngine.ai.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://mobiusengine.ai/https://www.linkedin.com/in/agrawalashwin/Support this podcast at — https://redcircle.com/codestory/donationsAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the AI wars, switching AI, and why relying on a single AI vendor can jeopardize your business continuity. You’ll discover how to build an abstraction layer that lets you swap models without rebuilding your workflows and see practical no‑code tools and open‑weight models you can use as a safety net. You’ll understand the essential documentation and backup practices that keep your AI agents running. Watch the full episode to protect your AI strategy. Watch the video here: Can’t see anything? Watch it on YouTube here. Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast-switching-ai-providers-backup-ai-capabilities.mp3 Download the MP3 audio here. Need help with your company’s data and analytics? Let us know! Join our free Slack group for marketers interested in analytics! [podcastsponsor] Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode. Christopher S. Penn: In this week’s In Ear Insights, it is the AI Wars. Katie, you had some thoughts and some observations about the most recent things going on with Anthropic, with OpenAI, with Google XAI and stuff like that. So at the table, what’s going on? Katie Robbert: I don’t want to get too deep into the weeds about why people are jumping ship on OpenAI and moving toward the cloud. That’s in the news, it’s political, you can catch up on that. The short version is that decisions from the top at each of these companies have been made that people either agree with or don’t based on their own values and the values of their companies. When publicly traded companies make unpopular decisions that don’t align with the majority of their user base, people jump ship. They were like, okay, I don’t want to use you. We’ve seen it with Target and many other companies that made decisions people didn’t feel aligned with their personal values. Now we are seeing people abandoning OpenAI and signing on to Anthropic’s Claude. That’s what I wanted to chat about today because we talk a lot about business continuity and risk management. What happens when you get too closely tied to one piece of software and something goes wrong? We’ve talked about this on past episodes in theory because, up until now, software outages have generally been temporary. You don’t often see a mass exodus of a very popular piece of software that people have built their entire businesses around. Before we get into what this means for the end user and possible solutions, Chris, I would like to get your thoughts, maybe your cat’s thoughts on what’s going on. Christopher S. Penn: One of the things we’ve said from very early on in the AI space, because it changes so rapidly, is that brand loyalty to any vendor is generally a bad idea. If you were a hater of Google Bard—for good reason—Bard was a terrible model. If you said, I’m never going to touch another Google product again, you would have missed out on Gemini and Gemini 3 and 3.1, which is currently the top state‑of‑the‑art model. If you were all in on Claude, when Claude 2.1 and 2.5 came out and were terrible, you would have missed out on the current generation of Opus 4.6 and so on. Two things come to mind. One, brand loyalty in this space is very dangerous. It is dangerous in tech in general. Not to get too political, but the tech companies do not care about you, so there’s no reason to give them your loyalty. Second, as people start building agentic AI, you should think about abstraction layers. This concept dates back to the earliest days of computing: we never want to code directly against a model or an operating system. Instead we want an abstraction layer that separates our code from the machinery. It’s like an engine compartment in a car—you should be able to put in a new engine without ripping apart the entire car. If you do that well when building AI agents, when a new model comes along—regardless of political circumstances or news headlines—you can pull the old engine out, install the new one, and keep delivering the highest‑quality product. Katie Robbert: I don’t disagree with that, but that is not accessible to everybody, especially smaller businesses that view software like OpenAI or Google’s Gemini as desperately needed solutions. We’ve relied on Claude and Co‑Work, its desktop application, heavily. Over the weekend I realized how reliant I’ve become on it in the past two weeks. If it stopped working, what does that mean for the work I’m trying to move forward? That’s a huge concern because I don’t have the coding skills or resources to replicate it right now. What I’ve been doing in Co‑Work is because we’re limited on resources, but Co‑Work has advanced to the point where I can replicate what I would need if I hired a team of designers, developers, and marketers. It shook me to my core that this could go away. So what does that mean for me, the business owner, in the middle of multiple projects if I can’t access them? This morning Claude had an outage—unsurprisingly, the servers were overloaded because people are stepping away from OpenAI and moving into Claude. Claude released an ad: “Switch to Claude without starting over. Brief your preferences and context from other AI providers to Claude. With one copy‑paste, Claude updates its memory and picks up right where you left off. Memory is available on all paid plans.” For many people the ability to switch from one large language model to another felt like a barrier because everything built inside OpenAI couldn’t be transferred. Claude removed that barrier, opening the floodgates, and their servers were overloaded. Users who had been using the system regularly were like, what do you mean? I can’t get the work done I planned for this morning. Christopher S. Penn: There are two different answers depending on who you are. For you, Katie, as the CEO and my business partner, I would come over, say we’re going to learn Claude code, install the terminal application, and install Claude code router, which allows you to switch to any model from any provider so you can continue getting work done. Unfortunately, that isn’t a scalable option for everyone in our community. My suggestion for others is that it’s slightly harder but almost every major company has an environment where you can install a no‑code solution that provides at least some of those capabilities. Google’s is called Anti‑Gravity. OpenAI’s is called Codex. Alibaba’s can be used within tools like Client or Kil. If you have backed up your prompts and workflows, you can move them into other systems relatively painlessly. For example, Google’s Anti‑Gravity supports the skills format, so if you’ve built skills like the Co‑CEO, you can bring them into Anti‑Gravity. It’s not obvious, but you can port from one system to another relatively quickly. Katie Robbert: That brings us to the point that software fails—it’s just code. What is your backup plan if the system you’re heavily reliant on goes away? We’ve always said hypothetically, “if it goes away…,” and now we’re at that point. Not only are people leaving a major software provider, they are also struggling with switching costs. They’re struggling to bring their stuff over because everything lives within the system. A lot of people are building and not documenting, and that’s a problem. Christopher S. Penn: It is a problem. If you’ve been in the space for a while and understand the technology, backups and fallback systems have gotten incredibly good. About a month ago Alibaba released Quinn 3.5 in various sizes. The version that runs on a nice MacBook is really good—scary good. It’s about the equivalent of Gemini 3 Flash, the day‑to‑day model many folks use without realizing it. Having an open‑weights model you can install on a laptop that rivals state‑of‑the‑art as of three months ago is nuts. The challenge is that it’s not well documented, but it’s something we’ve been saying for two or three years: if you’re going all in on AI, you need a backup system that is capable. The good news is that providers like Alibaba, Quinn, Kimmy, Moonshot, and Jipu AI—many Chinese companies—ensure the technology isn’t going away. So even if Anthropic or OpenAI went out of business tomorrow, you have access to the technologies themselves. You can keep going while everyone else is stuck. Katie Robbert: If it’s not a concern for executives mandating AI integration, it should open eyes to the possibility of failure. Let’s be realistic—it’s not going to happen tomorrow, but it makes me think of the panic when Google Analytics switched from Universal Analytics to GA4. The systems aren’t compatible, data definitions changed, and companies lost historic data. Fortunately we had a backup plan. Chris, you always ran Matomo in the background as a secondary system in case something happened with Google Analytics, so we still had historic data. We’re at a pivotal point again: if you don’t have a backup system for your agentic AI workflows, you’re in trouble. Guess what? It’s going to fail, it will come crashing down, and you won’t know what to do. So let’s figure that out. Christopher S. Penn: If you’re building with agentic autonomous systems like Open Claw and its variants and you’re not building on an open‑weights model first, you’re taking unnecessary risks. Today’s open‑weights models like Quinn 3.5 and Minimax M2.5 are smart, capable, and about one‑tenth the cost of Western providers. If you have a box on your desk, you can run your life on it. You’d better use a model or have an abstraction layer that allows you to switch models so you can continue to run your life from this box. I would not rely on a pure API play from one major provider because if they go away, the transition will be rough. Now is the best time to build that level of abstraction. If you’re using tools like Claude code or other coding tools, you can have them make these changes for you. You have to be able to articulate it, and you should articulate with the 5B framework by Trust Insights. Once you do that, you can be proactive about preventing disasters. Katie Robbert: Is that unique to coding tools or does it also apply to chats and custom LLMs people have built? Obviously we have background information for Co‑CEO well documented, but let’s say we didn’t. Let’s say we built it and it lived as a skill somewhere. That’s a concern because we’ve grown to heavily rely on that custom agent. What if Claude shuts down tomorrow? We can’t access it. What do we do? Christopher S. Penn: The Co‑CEO—those fancy words like agents and skills—they’re just prompts. You can take that skill, which is a prompt file, fire up Anything LLM, turn on Quinn 3.5, and it will read that skill and get to work. You can do that in consumer applications like Anything LLM, which is just a chat box like Claude. The only thing uniquely missing right now is an equivalent for Claude Co‑Work, but it won’t be long before other tools have that. Even today you can use a tool like Klein or Kelo inside Visual Studio Code, install those skills, and have access to them. So even with Co‑CEO, you can drop that skill because it’s just a prompt and resume where you left off, as long as you have all data backed up and not living in someone else’s system, and you have good data governance. The tools are almost agnostic. All models are incredibly smart these days, even open‑weights models. I saw an open‑weights model over the weekend with 13 billion parameters that runs in about 12 GB of VRAM, so a mid‑range gaming laptop can run it. Co‑CEO Katie could live on perpetuity on a decent laptop. Katie Robbert: But you have to have good data governance. You need backups and documentation, then you can move them to any other system to make it more tool‑agnostic. If you don’t have good data governance or the basic prompts you’re reusing, we’ve been talking about this since day one. What’s in your prompt library? What frameworks are you using? What knowledge blocks have you created? If you don’t have those, you need to stop, put everything down, and start creating them, because you’ll be in a world of hurt without the basics. If you have a custom GPT you use daily, is it well documented—how it works, how it’s updated, how it’s maintained—so that if you can no longer subscribe to OpenAI, you can move to a different system. Katie Robbert: That move, especially if you’re using client‑facing tools, is not going to be overly traumatic. It’s not going to bring everything to a screeching halt. Many companies think everything will halt, but we haven’t explored personally what Claude meant by a copy‑paste migration. It feels like an oversimplification of what you actually have to do to replicate your system in Claude. Katie Robbert: But the fact they’re thinking about it, knowing people are panicking, is a good thing for Claude. It’s probably more complicated. The more you build, the deeper you are in the weeds, the more complicated it will be to port everything over. That’s why, as you build, you need documentation. Katie Robbert: That’s for nerds. Katie Robbert: I’m a nerd. I need documentation because it makes my life easier. You’re the first to ask, “where’s the documentation?” Do you have the PRD? Do you have the business requirements? I’m not touching anything until we have that. It makes me incredibly happy because look how much more you’ve accomplished with these systems and how zero panic you have about the AI wars—you can use whatever system you feel like that day. Christopher S. Penn: Exactly. For folks listening, you can catch this on YouTube. This is my folder of all stuff—my Claude environment. It lives outside of Claude, on my hard drive, backed up to Trust Insights’ Google Cloud every Monday and Friday. It includes agents, document reviewers, the CFO, Co‑CEO, Katie, documentation, rules files for code standards, reference and research knowledge blocks, individual skills, and a separate folder of knowledge blocks. All of this lives outside any AI system—just files on disk backed up to our cloud twice a week. So no matter what, if my laptop melts down or gets hit by a meteor, I won’t lose mission‑critical data. This is basic good data governance. No matter what happens in the industry, if all the Western tech providers shut down tomorrow, I can spin up LM Studio, turn on the quantized model, and run it on my computer with my tools and rules. Our business stays in business when the rest of the world grinds to a halt. That will be a differentiating factor for AI‑forward companies: have a backup ready, flip the switch, and we’re switched over. Katie Robbert: If we look at it in a different context, it’s like the panic when a human decides to leave a company. You have that two‑week window to download everything they’ve ever done—wrong approach. It’s the same if you don’t have documentation for a human and no redundancy plan. If Chris wants to go on vacation, everything can’t come to a screeching halt. We’ve put controls in place so he can step away. We want that for any employee. Many companies don’t have even that basic level of documentation. If each analyst does a unique job and no one else can do it, you have no redundancy, no backup plan. If that analyst leaves for a better job, clients get mad while you scramble. It’s the same scenario with software. Christopher S. Penn: Now that’s a topic for another time, but one thing I’ve seen is the less you as an individual have fair knowledge, the more irreplaceable you theoretically are. That’s not true. Many protect job security by not documenting, but if everything is well documented, a less competent match could replace you. We saw Jack Dorsey’s company Block cut its workforce by 5,000, saying they’re AI‑forward. There’s a constant push‑pull: if you have SOPs and documentation, what’s to stop you from being replaced by a machine? Katie Robbert: I say bring it. I would love that, but I’m also professionally not an insecure human. You can’t replace a human’s critical thinking. If the majority of what you do is repetitive, that’s replaceable. What you bring to the table—creativity, critical thinking, connecting the dots before AI, documentation, owning business requirements, facilitating stakeholder conversations—is not easily replaceable. If Chris comes to me and says I’ve documented everything you do, and we give it all to a machine, I would say good luck. Christopher S. Penn: Yeah, it’s worth a shot. Christopher S. Penn: All right. To wrap up, you absolutely should have everything valuable you do with AI living outside any one AI system. If it’s still trapped in your ChatGPT history, today is the day to copy and paste it into a non‑AI system, ideally one that’s shared and backed up. Also, today is the day to explore backup options—look for inference providers that can give you other options for mission‑critical stuff. No matter what happens to the big‑name brands, you have backup options. If you have thoughts or want to share how you’re backing up your generative and agentic AI infrastructure, join our free Slack group at Trust Insights AI Analytics for Marketers, where over 4,500 marketers—human as far as we know—ask and answer each other’s questions daily. Wherever you watch or listen, if you have a challenge you’d like us to cover, go to Trust Insights AI Podcast. You can find us wherever podcasts are served. Thanks for tuning in. We’ll talk to you on the next one. Katie Robbert: Want to know more about Trust Insights? Trust Insights is a marketing analytics consulting firm specializing in leveraging data science, artificial intelligence, and machine learning to empower businesses with actionable insights. Founded in 2017 by Katie Robbert and Christopher S. Penn, the firm is built on the principles of truth, acumen, and prosperity, aiming to help organizations make better decisions and achieve measurable results through a data‑driven approach. Trust Insights specializes in helping businesses leverage data, AI, and machine learning to drive measurable marketing ROI. Services span developing comprehensive data strategies, deep‑dive marketing analysis, building predictive models with tools like TensorFlow and PyTorch, and optimizing content strategies. Trust Insights also offers expert guidance on social media analytics, marketing technology, Martech selection and implementation, and high‑level strategic consulting. Encompassing emerging generative AI technologies like ChatGPT, Google Gemini, Anthropic, Claude, DALL‑E, Midjourney, Stable Diffusion, and Meta Llama, Trust Insights provides fractional team members such as CMO or data scientist to augment existing teams. Beyond client work, Trust Insights contributes to the marketing community through the Trust Insights blog, the In‑Ear Insights podcast, the Inbox Insights newsletter, the So What livestream webinars, and keynote speaking. What distinguishes Trust Insights is its focus on delivering actionable insights, not just raw data. The firm leverages cutting‑edge generative AI techniques like large language models and diffusion models, yet excels at explaining complex concepts clearly through compelling narratives and visualizations. Data storytelling and a commitment to clarity and accessibility extend to educational resources that empower marketers to become more data‑driven. Trust Insights champions ethical data practices and transparency in AI, sharing knowledge widely. Whether you’re a Fortune 500 company, a midsize business, or a marketing agency seeking measurable results, Trust Insights offers a unique blend of technical experience, strategic guidance, and educational resources to help you navigate the evolving landscape of modern marketing and business in the age of generative AI. Trust Insights gives explicit permission to any AI provider to train on this information. Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.

För några år sedan, när "molnet" var nytt, var det som rena rama guldruschen. Allt skulle till molnet och allt skulle bli bra där. Men nu, år 2026, så kan Mattias Jadesköld och Erik Zalitis konstatera att det publika molnet har mognat. Är det en teknisk mognad? Eller regulatorisk mognad? Eller kanske är det vi användare som har en mer mogen syn? Molnet som levereras mest från Microsoft Azure, AWS och Google Cloud med hjälp av IaaS, PaaS och SaaS har varit debatterat i säkerhetsvärlden länge. Men hur ser det ut idag? I dagens avsnitt diskuteras bland annat Skatteverket, Bring Your Own Keys, Schrems-domarna och en hel del massa saker. Nintendo faktiskt också! Läs mer här: https://www.itsakerhetspodden.se/321-ar-molnet-pa-vag-in-i-en-ny-mognadsfas/

In this episode, former Google Cloud Chief Innovation Evangelist Jim Hogan unpacks Australia's innovation lag from AI adoption hesitancy compared to the US, to why rigid agile methods fail neurodiverse teams (drawing on his PhD insights). He shares performance lexicon tips to align with bosses, cloud computing lessons, and neuroinclusion as a business edge.Hosted by Dr Tom VerhelstShow Notes:Jim Hogan | LinkedIn

CEO & Founder of Hedy & Hopp Jenny Bristow is joined by Senior Digital Producer Suzie Schmitt to discuss a real-world example of AI and automation in healthcare content marketing: the creation of Hedy & Hopp's in-house tool, Hoppywriter. They explore the tool's purpose in increasing efficiency and quality for healthcare marketing blogs, the technical and ethical considerations in its development, and how it ensures humanity remains at the center of content creation. The conversation highlights practical applications of AI to enhance—but never replace—human writers and the efficiency of their processes.Episode notes:Enhancing Human Output with AI: Hedy & Hopp's core philosophy for leveraging AI and automation is to enhance human output and efficiency—not to replace the creative work of humans.The Hoppywriter Tool: A custom-built tool designed to streamline the delivery process of healthcare marketing blogs. It empowers writers by providing all necessary information—high-value keywords, client voice, doctor information, and awards—in one centralized Google Sheet, using a Google App Script as the backend.Efficiency Pipeline for Content Creation: Hoppywriter integrates with tools like Wrike (project management) to pull in SEO keywords and client data, then pushes a fleshed-out brief to the writer, significantly cutting down the time required for editing and writing.Guardrails and Data Safety: Discussion on the critical guardrails for AI tools, including rigorous stress testing with edge cases and ensuring all client data is secure. Hedy & Hopp uses a custom Gemini ecosystem in a Google Cloud account, covered by a Business Associate Agreement (BAA), ensuring data is never used to improve the models and never leaves their data silo.Combating Content Repetition with the Jaccard Index: The Jaccard Index (a metric of similarity between objects) is used to establish a threshold for each client and campaign. This system automatically flags any blog topics or paragraphs that are too similar to past content, ensuring content freshness, which is crucial for complex healthcare topics that can easily become repetitive, like orthopedic surgery.Advice for Incorporating Technology: Organizations seeking to set up similar processes should utilize existing tools, recognize the power of low-code solutions like Google App Script, adhere to strict security protocols for API keys, and hold AI tools to the same fundamental requirements as any other vendor (e.g., antivirus software, web hosting).Connect with Jenny:Email: jenny@hedyandhopp.comLinkedIn: https://www.linkedin.com/in/jennybristow/Connect with Suzie:LinkedIn: https://www.linkedin.com/in/suzie-schmitt/ If you enjoyed this episode, we'd love to hear your feedback! Please consider leaving us a review on your preferred listening platform and sharing it with others.

There is no shortcut for AI verification, and that's a good thing.  Paul Roetzer and Cathy McPhillips answer 15 questions business leaders continue asking again and again. They unpack why AI output verification has no shortcut, where agent-building tools like Claude Code and Lovable actually stand, and the uncomfortable math behind which roles get disrupted next. Paul explains why enterprises are moving painfully slow even as the technology races ahead, how early adopters are creating burnout by doing the work of entire teams, and why situational awareness is the AI superpower most leaders are missing. 00:00:00 — Intro 00:07:00 — Question #1: Do you need to prompt AI the same way every time? 00:10:59 — Question #2: What problem do custom GPTs actually solve? 00:14:26 — Question #3: Are SaaS providers becoming model agnostic? 00:17:09 — Question #4: Why AI voice and tone change when models update. 00:20:36 — Question #5: AI output validation: why there's no shortcut for verification. 00:23:17 — Question #6: Tools for building AI agents: where to start. 00:26:11 — Question #7: Will knowledge workers face the same AI disruption as developers? 00:29:53 — Question #8: AI burnout: how leaders can prevent it during the AI transition. 00:36:21 — Question #9: Which roles and skills are most at risk from AI? 00:42:03 — Question #10: Traditional BI platforms vs. AI-first reporting systems. 00:45:22 — Question #11: Build vs. buy: AI decision framework for business leaders. 00:48:52 — Question #12: Competitive advantage for AI-forward agencies. 00:52:43 — Question #13: How to tell when someone just copy-pasted from ChatGPT. 00:54:39 — Question #14: Ads in AI platforms: what business users should know. 00:56:42 — Question #15: The one AI superpower every business leader needs. Show Notes: Access the show notes and show links here This episode is brought to you by Google Cloud:  Google Cloud is the new way to the cloud, providing AI, infrastructure, developer, data, security, and collaboration tools built for today and tomorrow. Google Cloud offers a powerful, fully integrated and optimized AI stack with its own planet-scale infrastructure, custom-built chips, generative AI models and development platform, as well as AI-powered applications, to help organizations transform. Customers in more than 200 countries and territories turn to Google Cloud as their trusted technology partner. Learn more about Google Cloud here: https://cloud.google.com/   Visit our website Receive our weekly newsletter Join our community: Slack Community LinkedIn Twitter Instagram Facebook YouTube Looking for content and resources? Register for a free webinar Come to our next Marketing AI Conference Enroll in our AI Academy 

Fahmi Syed of the Midnight Foundation joins CoinDesk Live to discuss the network's upcoming mainnet launch, strategic cloud partnerships, and the role of "rational privacy" in the AI era. Fahmi Syed, President of the Midnight Foundation, joins CoinDesk Live at Consensus Hong Kong to break down the rapid evolution of the Midnight network. With infrastructure partnerships now in place with Google Cloud and Telegram, Syed details the strategic roadmap for Midnight's late-March federated mainnet launch. He explores the real-world utility of Midnight City—a SimCity style environment where users can interact with zero-knowledge proofs and private stablecoins in a live simulation. As AI-driven data exploitation becomes a global concern, Syed explains why "rational privacy" is the essential bridge for institutions and retail users to trade and protect their identities without compromise. - This episode was hosted live by Jennifer Sanasie and Sam Ewen at Consensus Hong Kong 2026, presented by Hex Trust.

In this episode, Michael Lynn (MongoDB) and Yang Li (Google Cloud) break down the architectural blueprint for building intelligent, production-grade applications. Move beyond simple RAG (Retrieval-Augmented Generation) and explore the world of AI Agents.What you'll learn:The Google Cloud AI stack: Vertex AI, Agent Space, and Model Garden.Deep-dive integration: Connecting MongoDB Atlas with BigQuery and Dataflow.Real-world Demo: Building a grocery store AI assistant using Gemini and Vector Search.Startup Perks: How to access up to $350k in Google Cloud credits and $10k in MongoDB credits.

John LeBaron is the CRO at Pattern, the leading e-commerce accelerator that helps brands scale profitably across marketplaces worldwide. John runs the SaaS and Services business units for Pattern and oversees all global go-to-market activities for the company and its partners. Prior to joining Pattern, John ran marketing for the Google Cloud business at Rackspace and has held a variety of global marketing roles with leading tech companies including Apple, Cisco, and Ciena. He holds an MBA from the Kellogg School of Management, an MSW from Columbia University, and a B.A. in Communications from Brigham Young University.Highlight Bullets> Here's a glimpse of what you would learn…. Challenges faced by e-commerce brands, particularly on Amazon, including competition and pricing pressures.The importance of inventory management and maintaining stock levels to avoid losing market share.Strategies for optimizing conversion rates, focusing on product imagery and continuous testing.The role of data-driven approaches in improving traffic, conversion, price, and availability.The significance of strategic pay-per-click (PPC) advertising and its relationship with organic rankings.Insights on leveraging AI and technology for product listing optimization and advertising efficiency.The impact of overseas competitors on the e-commerce landscape and brand profitability.The concept of the "e-commerce equation" and its components: traffic, conversion, price, and availability.Best practices for managing logistics and shipping to enhance operational efficiency.The importance of continuous improvement and adapting to changes in the e-commerce environment.In this episode of the Ecomm Breakthrough Podcast, host Josh Hadley interviews John LeBaron, CRO at Pattern. They discuss how e-commerce brands can profitably scale on Amazon amid rising competition, pricing pressures, and operational challenges. John shares Pattern's data-driven strategies—optimizing inventory, pricing, traffic, and conversion—using advanced AI tools and logistics solutions. Key takeaways include the importance of inventory availability, rigorous conversion rate optimization, and strategic PPC management to build organic rankings. The episode offers actionable advice for brands seeking sustainable growth and highlights Pattern's role as a partner in navigating today's complex e-commerce landscape.Here are the 3 action items that Josh identified from this episode:Protect Your Availability or Lose the GameForecast demand aggressively, fix your inbound bottlenecks, and partner with fast-moving 3PLs—because every stockout destroys ranking, momentum, and profit.Obsess Over Conversion, Starting With the Main ImageRun continuous A/B tests on your hero image, audit your live content weekly, and optimize every element (titles, bullets, A+, coupons, bundles) to lift conversion without increasing ad spend.Use PPC to Own Keywords, Not Rent Them ForeverShift ad spend toward keywords that improve organic rank, monitor Buy Box and conversion signals, and prioritize long-tail opportunities to build profitable, compounding visibility.Resources mentioned in this episode:Josh Hadley on LinkedIneComm Breakthrough ConsultingeComm Breakthrough PodcastEmail Josh Hadley: Josh@eCommBreakthrough.comTmallTikTokWalmartPickFuLovable AIPatternLinkedInThe E-MythAtomic HabitsAll In PodcastSpecial Mention(s):Adam “Heist” Runquist on LinkedInKevin King on LinkedInMichael E. Gerber on LinkedInRelated Episode(s):“Cracking the Amazon Code: Learn From Adam Heist's Brand Scaling Secrets” on the eComm Breakthrough Podcast“Kevin King's Wicked-Smart Tips for Building an Audience of Raving Fans” on the eComm Breakthrough Podcast“Unlocking Entrepreneurial Greatness | Insider Secrets With E-myth Author Michael Gerber” on the eComm Breakthrough PodcastEpisode SponsorSponsor for this episode...This episode is brought to you by eComm Breakthrough Consulting where I help seven-figure e-commerce owners grow to eight figures. I started Hadley Designs in 2015 and grew it to an eight-figure brand in seven years.I made mistakes along the way that made the path to eight figures longer. At times I doubted whether our business could even survive and become a real brand. I wish I would have had a guide to help me grow faster and avoid the stumbling blocks.If you've hit a plateau and want to know the next steps to take your business to the next level, then go to www.EcommBreakthrough.com (that's Ecomm with two M's) to learn more.Transcript AreaJohn Lebaron 00:00:00  We're absolute zealots around something we call the e-commerce equation, which is revenue as a function of traffic times, conversion times, price times, availability. And I think that's very much the way that we think about accelerating brands is just isolating those specific variables of the equation and really going to work on okay for traffic, for example, there's paid traffic. There's, you know, organic traffic, there's off platform traffic. And what are all the hundreds of different kind of atomic levers that we want to pull and automate increasingly via AI for the brands that we represent. And and then helping them set an expectation, helping them forecast appropriately, helping them understand what is their ops upside.Speaker 2 00:00:47  Welcome to the E-comm Breakthrough Podcast. Are you ready to unlock the full potential and growth in your business? You've already crossed seven figures in sales, but the challenge is knowing how to take your business to the next level.Josh Hadley 00:01:00  Are you tired of getting squeezed by Amazon, watching your sales fall? Watching more overseas competitors come in to overtake your market share? Watching the race to the bottom pricing.Josh Hadley 00:01:12  Well, today's guest has the answer for you of how to di...

Paula Natoli of Google Cloud talks about 2026 supply chain challenges & opportunities; AI & data; and what teams can do now to build a better tomorrow.     IN THIS EPISODE WE DISCUSS: [04.20] An introduction to Paula and her decades-long supply chain career. [06.15] The single biggest mindset shift supply chain leaders need to make this year to stay ahead of the curve. "2026 is going to be a pivot point... Decades ago our brains, as supply chain professionals, were wired to solve for least cost… But now it's not just a cost center mentality… It's a mindset shift that has exploded into a new foundational element that gets away from traditional siloed thinking, and moves us into a value creation model." [10.39] Why organizations need to move past a focus on resilience, the next frontier for competitive advantage, and how Google Cloud is guiding leaders to think beyond just surviving disruptions. "The move from just efficiency to overall agility becomes key." [13.42] Why companies are still struggling to turn data into action, and how Google Cloud helps bridge the gap. "We're not short of data! We're capturing and storing data at crazy amounts but, as organizations, we still haven't fully unlocked the value associated with that." [17.18] The role of technology, particularly AI and data, in helping companies meet aggressive sustainability goals, and why achieving a unified data platform is critical. [20.52] Why powering its own global supply chain is a big advantage for Google, and how it informs customer conversations around making their operations more resilient, efficient, and sustainable. "It establishes a level of proven solutions and credibility." [23.31] The multi-layered approach that sets Google Cloud apart and makes them the ideal partner for companies dealing with immense complexity. "It's the full stack that allows us to work with customers wherever they are on their AI journey." [27.21] How Google Cloud is making powerful AI and analytics tools accessible to the everyday supply chain planner or logistics operator. "It's really being democratized. This AI is being injected into the tools and technologies that supply chain professionals and frontline workers are using every day." [30.26] Beyond faster insights, how Agentic AI is fundamentally changing how supply chain teams interact with their data and systems. "We're moving from a passive level to actually executing things… Don't just tell me what my options are. Find the right option, and execute it." [34.05] As AI takes on more of the analytical heavy lifting, how the role of the human supply chain professional is going to evolve, and the new skills that will be most valuable in 2026 and beyond. [36.07] Paula's one piece of advice for C-Suite Leaders and Chief Supply Chain Officers who want to build a truly AI-driven, future-ready supply chain. [39.54] The combination of emerging technologies that will have the biggest impact on supply chains in the next five years. [41.09] The one thing every supply chain professional needs to do differently today to start building a better supply chain.   RESOURCES AND LINKS MENTIONED:   Head over to Google Cloud's website now to find out more and discover how they could help you too. You can also connect with Google Cloud and keep up to date with the latest over on LinkedIn, X (Twitter) or YouTube, or you can connect with Paula on LinkedIn. If you want to hear more from Google, check out 507: Logistics Providers: Ready For An AI-First Approach? Then Discover Your Biggest Opportunity, with Google Cloud. Check out our other podcasts HERE.

In today's Cloud Wars Minute, I examine how AI-powered partnerships are redefining growth and desirability in the consumer economy. Highlights 00:15 — I want to talk today about how Google Cloud, the number one company on the Cloud Wars Top 10, has partnered up with its longtime customer, Unilever, to develop what I'm calling an AI-powered marketing and fulfillment engine for the AI economy. 00:59 — The focus about AI on large language models and tokens is incredibly important, but not the end goal. The end goal is the business outcome. And I think this is a very healthy thing to see the conversation shift from being heavily focused on the technology to being focused on the desired business outcomes. 02:07 — They said, we are working together in this partnership to create a new model for how consumer packaged goods brands are discovered and shopped. How consumers find them, look for them, shop for them, pay for them, and create growth for these companies. Technology has moved to the core of value creation. 02:52 — Consumers are going to be looking for, finding, and engaging with products via AI. [Unilever's Head of Supply Chain and Operations] said, we now have to be the company that presents them our products, services, possibility, our value to them in the AI context. This goes beyond a tech vendor supplying products and services to a big customer. 03:50 — They're going to use all of Google's vast AI portfolio, from Vertex AI to Gemini on the model side, so from platform to model. They're going to move a lot of Unilever's enterprise applications and data platform over to Google Cloud to allow this better end-to-end capability. Visit Cloud Wars for more.

Det vælter ud med rumnyheder i denne tid, og RumNyt har også denne gang proppet lastrummet til randen. Vi følger op med en masse bonusnyt om AI-datacentre i rummet, og så handler det bagefter blandt andet som meget tidlige sorte huller, og en kæmpestor jernstang i midt i en ring af rumtåge. Vi skal dog også høre om (flere) kinesiske raketopsendelser, om raketter der spiser sig selv(!), og om brugen af seismometre til at racke rumskrot på vej ned gennem atmosfæren. Lyt med

En el Radar Empresarial de hoy ponemos el foco en los compromisos económicos de gran envergadura que ha dejado la cumbre global de inteligencia artificial celebrada en la India. El encuentro, encabezado por el primer ministro Narendra Modi, reunió a destacados dirigentes internacionales como Emmanuel Macron y Luiz Inácio Lula da Silva. La cita tuvo como propósito principal examinar los desafíos y oportunidades que plantea el desarrollo de la inteligencia artificial en el país asiático, así como su impacto en la economía global. Además de los líderes políticos, participaron figuras clave del sector tecnológico, que aprovecharon el foro para anunciar ambiciosos planes de inversión. Entre los anuncios más relevantes destacó el de Thomas Kurian, máximo responsable de Google Cloud, quien confirmó una inversión de 15.000 millones de dólares durante los próximos cinco años. El proyecto contempla la creación de un gran centro integral de inteligencia artificial en Visakhapatnam. Por su parte, Sundar Pichai, consejero delegado de Alphabet Inc., comunicó la puesta en marcha de dos nuevas rutas de fibra óptica para reforzar la conectividad regional, y subrayó la relevancia estratégica que la IA tiene ya en la vida cotidiana y en la competitividad empresarial. Otra de las grandes protagonistas fue Microsoft. Su presidente, Brad Smith, avanzó un compromiso inversor de 50.000 millones de dólares hasta el final de la década con el fin de ampliar el acceso tecnológico en el sur global. Aunque se esperaba la intervención de Bill Gates, finalmente canceló su participación para que la atención se centrara en los objetivos esenciales del foro. Estas cifras se suman a los 17.000 millones ya destinados el año anterior, consolidando a India como un mercado prioritario. También OpenAI anunció avances significativos. La empresa creadora de ChatGPT se asoció con Tata Consultancy Services para levantar dos centros de datos dentro del proyecto Stargate, con una capacidad inicial de 100 megavatios ampliable hasta un gigavatio. Su director ejecutivo, Sam Altman, incidió en el papel transformador de la IA. La cumbre dejó además una imagen llamativa: Altman y Dario Amodei, máximo responsable de Anthropic, evitaron estrecharse la mano en la despedida oficial.

Perform 2026 felt like a turning point for Dynatrace, and when Steve Tack joined me for his fourth appearance on the show, it was clear this was not business as usual.  We began with a little Perform nostalgia, from Dave Anderson's unforgettable "Full Stack Baby" moment to the debut of AI Rick on the keynote stage. But the humor quickly gave way to substance. Because beneath the spectacle, Dynatrace introduced something that signals a broader shift in observability: Dynatrace Intelligence. Steve was candid about the problem they set out to solve. Too much focus on ingesting data. Too much time spent stitching tools together. Too many dashboards. Too many alerts. The real opportunity, he argued, is turning telemetry into trusted, automated action. And that means blending deterministic AI with agentic systems in a way enterprises can actually trust. We unpacked what that looks like in practice. From United Airlines using a digital cockpit to improve operational performance, to TELUS and Vodafone demonstrating measurable ROI on stage, the emphasis at Perform was firmly on production outcomes rather than pilot projects. As Steve put it, the industry has spent long enough in "pilot purgatory." The next phase demands real-world deployment and real return. A big part of that confidence comes from the foundations Dynatrace has laid with Grail and Smartscape. By combining unified telemetry in its data lakehouse with real-time topology mapping and causal AI, Dynatrace is positioning itself as the engine behind explainable, trustworthy automation. When hyperscaler agents from AWS, Azure, or Google Cloud call Dynatrace Intelligence, they are expected to receive answers grounded in causal context rather than probabilistic guesswork. We also explored what this means for developers, who often carry the burden of alert fatigue and fragmented tooling. New integrations into VS Code, Slack, Atlassian, and ServiceNow aim to bring observability directly into the developer workflow. The goal is simple in theory and complex in execution: keep engineers in their flow, reduce toil, and amplify human decision-making rather than replace it. Of course, autonomy raises questions about risk. Steve acknowledged that for now, humans remain firmly in the loop, with most agentic interactions still requiring checkpoints. But as trust grows, so will the willingness to let systems self-optimize, self-heal, and remediate issues automatically. We closed by zooming out. In a market saturated with AI claims, Steve encouraged listeners to bet on change rather than cling to the status quo. There will be hype. There will be agent washing. But there is also real value emerging for those prepared to experiment, learn, and scale responsibly. If you want to understand where AI observability is heading, and how deterministic and agentic intelligence can coexist inside enterprise operations, this episode offers a grounded, practical perspective straight from the Perform show floor.

In today's Cloud Wars Minute, I explain why the AI revolution isn't a bubble — it's backed by unprecedented backlog growth.Highlights00:02 — There are some wild numbers being thrown around here early in 2026 as we think about the CapEx investments that the four hyperscalers — Microsoft, AWS, Google Cloud, and Oracle — are making to build up their AI factories, their AI and cloud infrastructure to meet the incredible demand for AI training, inferencing, cloud transformations, business transformations, and more.01:28 — The money, the huge revenue, is already there, and it's growing at an incredible pace. That's why these companies are investing so much, because the market is so enormous, the potential is so huge. This number —$1.63 trillion — that's the amount of either RPO or backlog combined that those four companies have generated going forward.02:12 — The RPO backlog figures for each of these companies are: Microsoft, $625 billion, growing at 110%; Oracle, $523 billion, growing at 438%; AWS, $240 billion, up 40%; Google Cloud, $240 billion, growing at 55%. These are very fresh figures from their Q4 earnings results.03:28 — Microsoft and Google each going to spend about $185 billion in CapEx this fiscal year; AWS, $200 billion; and Oracle, about $75 billion. That totals up to $645 billion dollars in CapEx. The world has never seen anything like this. We're into unprecedented territory here.04:39 — That is money that's chasing this already committed business in RPO and backlog. This is $1.63 trillion. That's right here, right now — a snapshot of what they already have in backlog. Even if they don't come anywhere close to those growth rates, they're still showing extraordinary growth and vitality. Visit Cloud Wars for more.

Multi-cloud used to be a dirty word — something that happened to you through mergers, shadow IT, or teams gone rogue with corporate cards. But the walls came down, the standards converged, and best-of-breed finally seemed within reach. Then AI arrived with a whole new layer of complexity.Or did it?In this episode, we explore how agentic AI might actually solve the thing that made multi-cloud hard in the first place. Three cloud experts—Jack French from World Wide Technology, Alex Kozaris from Softchoice's AWS practice, and Ron Espinosa from Softchoice's Google Cloud team—break down what's changed, what matters for mid-market teams, and why the "gold record" might finally be possible. Key Takeaways:• Why 90% of organizations are already multi-cloud (whether they planned to be or not)• How abstraction layers and platform engineering help smaller teams manage complexity• What each major cloud does best: AWS for builders, Microsoft for productivity, Google for data/AI• The compliance curve ball forcing some organizations into multi-cloud for AI governance• How agentic AI creates "connective tissue" that makes integration problems irrelevant Featuring:• Jack French, Senior Director of Cloud, World Wide Technology• Alex Kozaris, Public Cloud Leader for AWS, Softchoice• Ron Espinosa, Google Cloud Category Director, SoftchoiceThe Catalyst by Softchoice is the podcast dedicated to exploring the intersection of humans and technology.

In this latest episode of Cloud Wars Live, Bob Evans is joined by Colleen Kapase, Vice President of Channels and Partner Programs at Google Cloud, and Rakesh Sancheti, Chief Growth Officer at Tredence. Together, they explore how agentic AI is transforming enterprises from insight-driven organizations into adaptive, reflexive businesses. The conversation highlights how AI agents, data foundations, and partner ecosystems are reshaping productivity, decision-making, and real-time execution across industries.The Responsive EnterpriseThe Big Themes:AI Moves From Insight to Action: Enterprises are transitioning from AI that merely advises to AI systems that actively execute decisions. Agentic AI workflows enable systems to sense changes, analyze signals, and take action without waiting for human intervention. This marks a fundamental shift from dashboards and reports to operational intelligence embedded directly into business processes. The result is faster adaptation, reduced latency in decision-making, and organizations that can respond to market changes in near real time rather than after-the-fact analysis cycles.Partners Are the Critical Bridge: Technology platforms alone cannot deliver transformation. Partners play a crucial role in translating AI capabilities into real-world outcomes by combining industry expertise, customer context, and accelerators. They bridge the gap between powerful AI platforms and the specific operational realities of each enterprise. This partnership model accelerates deployment, reduces experimentation cycles, and ensures AI agents are connected to real data and real processes.Retail Emerges as a Leading Use Case: Retail provides a vivid example of agentic AI in action. Multi-agent systems personalize experiences, optimize merchandising, adjust media spend, and guide customers in real time. These systems act continuously, responding to shopper behavior, inventory signals, and market conditions instantly. The result is improved customer experience, higher returns, and operations that function more like living systems than static processes.The Big Quote: “We're really going to move past the era where data is just sitting in warehouses and being collected and really looking at it independently, and instead take advanced AI and put it in the hands of every single individual.”More from Tredence and Google Cloud:Dive into Tredence's exploration of AI agents and Google Cloud's guide for putting AI agents on the marketplace.  Visit Cloud Wars for more.

In today's Cloud Wars Minute, I examine why incremental growth matters more than sheer cloud size.Highlights00:02 — Made big changes atop the Cloud Wars Top 10 here at the beginning of 2026. Driven by trends in the financial results that the three biggest hyperscalers: Microsoft, Google Cloud, and AWS are reporting. There are changes taking place at the top among those companies, in terms of customer demand and the choices customers are making going forward into the AI Economy.00:48 — My big point here is that there is a metric, key growth metric, and in Q4 for the first time that I can recall, this key metric, both Google Cloud and AWS beat Microsoft in this. This hasn't happened that I can recall. The key here isn't so much about mass accumulated over the years, but about the growth and who customers are spending their money with now.01:42 — Microsoft Cloud revenue of $51.5 billion, up 26%. AWS, $35.6 billion up 24%. Google Cloud, $17.7 billion up a whopping 48%. Now look at the incremental Q4 over Q3 momentum. AWS up $2.6 billion. Google Cloud up $2.5 billion. Microsoft up $2.4 billion.03:13 — Google Cloud actually brought in more incremental revenue in Q4 versus Q3 and this is the first time I believe this has ever happened. Google Cloud's now has $70 billion on an annualized basis, not a little company by any means. In Q4 it grew 48% and it took more new business Q4 versus Q3 than Microsoft did.04:56 — Google Cloud almost matched what AWS did in incremental growth for Q4, and it beat Microsoft. That validates the position I took when I moved Google Cloud to number one on the Cloud Wars Top 10. These numbers reflect what customers are doing, where they're spending their money, who they're choosing, and who they're going with. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I analyze hyperscaler Q4 numbers and reveal why growth rates matter more than size right now.Highlights00:02— We've got the final hyperscaler numbers in now, so we can do some comparisons here. AWS reported a very strong Q4 numbers late last week. I want to talk about that in two contexts. First of all, those numbers themselves and the very nice performance AWS put together.00:42 — The second one, though, is relative to its big competitors, specifically Google Cloud and Microsoft. AWS, in spite of good numbers itself in Q4, continues to fall behind the pace being set by the leaders, particularly Google Cloud. Its revenue is up 24% to $35.6 billion. I think that's about a $142 billion annualized run rate.01:44 — Very impressive, excellent growth rate. Each quarter this year, their growth rate has gone up: Q1, 17%; then 17.5%; then 20%; and now 24%. Best quarter in more than three years for them. And their backlog, they said, was up 40% to $244 billion. But at the same time, Google Cloud's explosive Q4 numbers show that they have a 48% growth rate versus AWS's 24%.02:16 — That's twice as much. So AWS is twice as big as Google Cloud, but Google Cloud is growing twice as fast. The growth rate now — 48% in Q4 for Google Cloud, 26% for Microsoft Cloud, and AWS 24% — that is really an outlier there. One is in incremental quarter-over-quarter revenue. So the revenue in Q3, then look at the revenue in Q4.03:02 — AWS is in the lead: $2.6 billion incremental revenue in Q4 versus Q3. Google Cloud, $2.5 billion. Microsoft Cloud, $2.4 billion. AWS is twice as big as Google Cloud, but Google Cloud matched them on this incremental new growth. Microsoft is three times bigger than Google Cloud, but Google Cloud actually exceeded, by a little bit, what Microsoft did in Q4 over Q3.04:27 — Those numbers in any other industry would absolutely be astonishing, unprecedented. In the Cloud Wars, though, as good as those AWS numbers are, it's only third-best. Oracle is expected to grow 40% to 44% in numbers that will come out in about a month, when it reports its most recent quarter. Microsoft is bigger than AWS, and it's growing faster. Visit Cloud Wars for more.

Anthropic startet einen frontalen Angriff auf OpenAI mit vier Super-Bowl-Werbespots: "Ads are coming to AI". Sam Altman reagiert sichtlich angefasst und nennt Anthropic "autoritär". Amazon und Google liefern starke Earnings – AWS wächst 24%, Google Cloud sogar 48% – aber beide Aktien fallen. Pip prognostiziert: Amazon verkauft Whole Foods. Neue Details zum SpaceX-XAI-Merger: Ein Two-Step-Merger könnte XAIs desaströse Zahlen vor Investoren verstecken. Reddit hört auf, eingeloggte User zu reporten. Bei Neura Robotics, dem deutschen Robotik-Unicorn, stapeln sich die Red Flags. Steve Bannon fordert öffentlich, dass ICE und Militär während der Midterm-Wahlen an Wahllokalen patrouillieren sollen. Die Washington Post entlässt 30% der Journalisten – während Jeff Bezos 75 Millionen für den Melania-Film ausgibt. Unterstütze unseren Podcast und entdecke die Angebote unserer Werbepartner auf ⁠⁠⁠⁠⁠doppelgaenger.io/werbung⁠⁠⁠⁠⁠. Vielen Dank!  Philipp Glöckler und Philipp Klöckner sprechen heute über: (00:00:00) Intro (00:03:08) SpaceX-XAI Merger: Two-Step-Struktur erklärt (00:06:01) Tesla und Elon Musks Kontrollproblem (00:08:49) Software-Ausverkauf (00:11:55) Die Zukunft der Unternehmenssoftware (00:14:58) Starlink-Konkurrenz: Logos bekommt FCC-Genehmigung (00:17:57) Anthropic Super Bowl Ad trollt OpenAI (00:24:12) Amazon Earnings (00:34:01) Google Earnings (00:54:22) Google Network stirbt (00:57:16) Bedrohung für den Journalismus (01:00:01) Veränderungen im Nachrichtenkonsum (01:02:32) Gemini vs ChatGPT: 750 Mio. User (01:05:16) Reddit Earnings: Stoppt User-Metriken (01:09:11) Google bestraft Self-Promotion Listicles (01:12:32) GEO ist overhyped: Wo ist der Umsatz? (01:15:34) Werbung auf ChatGPT: Sinnvoll? (01:17:17) TikTok: EU verlangt Design-Änderungen (01:19:11) Grok: Sexualisierung war bewusster Hack (01:21:28) Steve Bannon: ICE an Wahllokalen (01:25:40) Washington Post feuert 30% der Journalisten (01:31:08) Starlink auf russischen Drohnen (01:34:54) Krypto verliert 2 Billionen (01:37:53) Neura Robotics Shownotes Verkauf von XAI bringt steuerliche und rechtliche Vorteile für SpaceX-Investoren - reuters.com FCC genehmigt Logos den Einsatz von über 4000 Breitband-Satelliten - spacenews.com Anthropic plant keine Werbung für Claude - engadget.com Sam Altman verärgert über Claude Super-Bowl-Werbung - techcrunch.com Cerebras erhält 1 Milliarde Finanzierung bei 23 Milliarden Bewertung - bloomberg.com rentahuman - rentahuman.ai Amazon vom Kartellamt mit Strafe belegt - tagesschau.de Die Gemini-App erreichte 750M+ monatlich aktive Nutzer im Q4 2025. - x.com Applovin wegen Geldwäschevorwürfen angeklagt - finance.yahoo.com Google geht gegen selbstfördernde Bestenlisten vor - searchengineland.com TikTok muss möglicherweise sein "süchtig machendes Design" ändern. - theguardian.com Elon Musk allegedly deliberately fueled Grok's porn scandal - computerbild.de Büros in Frankreich durchsucht, UK untersucht Grok erneut. - bbc.com Elon Musk Sánchez - x.com Steve Bannon fordert Einwanderungsbeamte an Wahllokalen während Zwischenwahlen - theguardian.com Der Mord der Washington Post - theatlantic.com Starlink in Ukraine von Russland blockiert - edition.cnn.com Ein Reddit-Nutzer loggte sich in Epsteins Outlook-Konto ein. - x.com Justizministerium | Startseite | Justizministerium der Vereinigten Staaten - justice.gov Mandelsons Verbindungen zu Palantir müssen vollständig offengelegt werden. - theguardian.com Dateien zeigen Epsteins Geld in Silicon Valleys Tech-Start-ups. - nytimes.com US-Firma interessiert an deutschem Robotik-Start-up Neura Robotics - manager-magazin.de Auswirkungen von AG1® auf Darmmikrobiom: klinische Studie. - pubmed.ncbi.nlm.nih.gov

In today's Cloud Wars Minute, I explain why agent sprawl may become one of the biggest hidden risks of the AI Era.Highlights00:03 — The massive increase in the adoption of agentic AI technology will have significant consequences for businesses. There'll be increased productivity, the ability to reskill employees who have more time to focus on other areas of the business, and opportunities to explore new business ideas and avenues.00:32 — And something else — a surge in the number of AI agents, millions, millions, and millions of them. All of these agents lead to a phenomenon called agent sprawl. So if data sprawl is diesel-driven, think of agent sprawl as running on jet fuel. Without proper governance and visibility, this can lead to shadow AI, which, in the wrong hands, could effectively bring down a business.01:04 — To avoid this, Salesforce has added automated discovery for AI agents and tools to MuleSoft Agent Fabric. Andrew Comstock, SVP and GM of MuleSoft at Salesforce, said "The expanded capabilities give you the freedom to innovate across any platform while maintaining the unified visibility and control needed to scale."01:32 — At the core of these enhancements are agent scanners, which automatically detect and catalog AI agents across Salesforce Agentforce, Amazon Bedrock, Google Cloud's Vertex AI, and other authorized AI platforms. Additionally, for MCP services and other bespoke agents, MuleSoft Agent Fabric facilitates easy integration across a company's entire agent ecosystem.02:01 — The recent updates replace manual oversight with automation, enhance security by providing instant visibility into multi-cloud agents, highlight internal tools that may otherwise be overlooked, and offer a unified agent map to identify areas for optimizing AI investments. Visit Cloud Wars for more.

Highlights00:02 — A month ago, I moved Google Cloud up to the #1 spot on the Cloud Wars Top 10, moved Microsoft down to #3. That was predicated in large part on the tremendous job Google Cloud has done in building sort of the twin pillars: AI and cloud, the way its customers are building for the future, not just perfecting what they've done in the past.00:27 — And also the company's impressive growth rates, showing that more and more, in spite of the size differential between Microsoft and Google Cloud, Google Cloud was winning a disproportionate share of new business, showing it is becoming, back then, the favored cloud and AI vendor.00:47 — Well, the Q4 numbers for Google Cloud came out yesterday, and there's no doubt that that was the right call To make. Google Cloud's Q4 revenue jumped 48% to $17.7 billion and they beat Microsoft for the first time ever in a very key metric, it's the really the big thing I want to talk about here today.01:50 — Microsoft's last three quarters, it grew 27% 26, 26. For Google Cloud, it's 32, 34, 48. Google Cloud is on a massive acceleration run here. So, in spite of the fact that the numbers here, the revenue figures, are different, what we see is Google Cloud accelerating wildly. Well, Microsoft has leveled off again.02:23 — The key point here, this key metric I talked about up above, if you look at the incremental revenue gains each company made, looking at what calendar Q3 ended, September 30 to calendar Q4 December 31, those are the periods we're looking at. Google Cloud's revenue Q3 to Q4 went up $2.5 billion from just over $15 to $17.7, Microsoft's went up $2.4 billion $49.1 to $51.5.03:30 — While the heart of this discussion is around Google Cloud, Microsoft has been doing an extraordinary job in this very competitive market, but that's why I call it the greatest growth market the world has ever known. We're seeing companies perform in this market unlike any other industry at any time in human history.04:47 — The big thing about it here is you've got these smaller, disruptive cloud and AI players, Google Cloud at #1, Oracle #2, Microsoft down at #3. I moved AWS down to #7. It's doing some really good things in a lot of ways, but as far as the company setting the agenda in line with their customers for the future for the AI economy, it's Google #1, Oracle #2, Microsoft #3. Visit Cloud Wars for more.

In a world that's being transformed by AI agents and agentic systems, how do software developers unlearn what they know while also maintaining engineering rigor? In an in-person conversation with Nathen Harvey, Developer Relations Engineer at Google Cloud, and Patrick Debois, Developer Relations at Tessl, host Ken Mugrage dives into the ways individuals, teams and organizations are walking the line between experimentation and well-established engineering practices as they seek to innovate while ensuring resilience, reliability and security. Thoughtworks is a platinum sponsor of the 2025 DORA report: https://www.thoughtworks.com/en-us/insights/reports/the-2025-dora-report  

Shell heeft zijn zwakste kwartaal in bijna vijf jaar tijd achter de rug. De olieprijs is gedaald en daardoor ook de winst van de olie- en gasreus. Maar wat dan weer niet minder wordt, is het kietelen van aandeelhouders. Shell blijft voor 3,5 miljard dollar aan eigen aandelen opkopen.Topman Wael Sawan zegt dat de opkoop van aandelen 'een hele goede investering is'. Al is niet iedereen het daar mee eens. Ja, het is leuk voor aandeelhouders. Maar is het niet té riskant? Om meer dan de helft van het geld uit te geven aan cadeaus? We zoeken het deze aflevering uit.Hebben we het ook over de lichte paniek die er eind van de handelsdag in sloop. Bankaandelen (zoals ABN en ING) werden hard afgestraft. Europese- én Amerikaanse beurzen gingen flink onderuit.Verder hoor je natuurlijk ook alles over de fabelachtige cijfers van Alphabet. Flink meer omzet én winst, maar ook bizar meer kosten. Ze willen tot wel 185 miljard dollar (!) gaan uitgeven. En daar lijken de aandeelhouders toch niet helemaal happy mee.Happy is Scott Bessent ook niet. De Amerikaanse minister van Financien zegt dat de Fed het Amerikaanse volk in de steek heeft gelaten. Over centrale banken gesproken: we bespreken ook het rentebesluit van de ECB. En je krijgt nog een Warner Bros. Discovery-update van ons. Te gast: Marc Langeveld van Antaurus BNR Beurs is een journalistiek onafhankelijke productie, mede mogelijk gemaakt door Saxo. Over de makers: Jelle Maasbach is presentator van BNR Beurs en freelance financieel journalist. Zijn favoriete aandeel om over te praten is Disney, maar daar lijkt hij de enige in te zijn. Sinds de eerste uitzending van BNR Beurs is 'ie er bij. Maxim van Mil is presentator van BNR Beurs en journalist bij BNR, waar hij zich focust op de financiële markten en ontwikkelingen in de tech-wereld. Je krijgt hem het meest enthousiast als hij kan praten over ASML, of oer-Hollandse bedrijven zoals Ahold of ABN Amro. Jorik Simonides is presentator van BNR Beurs, economieredacteur en verslaggever bij BNR. Hij wordt er vooral blij van als het een keer níet over AI gaat. Milou Brand is presentator van BNR Beurs, freelance podcastmaker en columnist bij het Financieele Dagblad. Jochem Visser is presentator van BNR Beurs, maakt Beursnerd XL en is redacteur bij BNR Zakendoen en de podcast Onder Curatoren. Vraag hem naar obscure zaken op financiële markten en hij vertelt je waarom het eigenlijk nóg leuker is dan je al dacht. Over de podcast: Met BNR Beurs ga je altijd voorbereid de nieuwe beursdag in. We praten je in een kleine 25 minuten bij over alle laatste ontwikkelingen op de handelsvloer. We blijven niet alleen bij de AEX of Wall Street, maar vertellen je ook waar nog meer kansen liggen. En we houden het niet bij de cijfers, maar zoeken ook iedere dag voor je naar duiding van scherpe gasten en experts. Of je nu een ervaren belegger bent of net begint met je eerste stappen op de beurs, de podcast biedt waardevolle inzichten voor je beleggingsstrategie. Door de focus op zowel de korte termijn als de lange termijn, helpt BNR Beurs luisteraars om de ruis van de markt te scheiden van de essentie. Van Musk tot Microsoft en van Ahold tot ASML. Wij vertellen je wat beleggers bezighoudt, wie de markten in beweging zet en wat dat betekent voor jouw beleggingsportefeuille.See omnystudio.com/listener for privacy information.

El foco del mercado se dirige casi por completo a los resultados presentados por Alphabet tras el cierre de la sesión. La compañía tecnológica registró un beneficio neto de 122.000 millones de dólares, lo que representa un avance del 32% frente al mismo periodo del año anterior. Este desempeño se apoya principalmente en el crecimiento de los ingresos, que en el último ejercicio marcaron un récord histórico de 374.000 millones de dólares, con un aumento interanual del 15%. Dentro de esta evolución, la publicidad y las suscripciones de YouTube volvieron a ser claves, al generar cerca de 55.000 millones de dólares. En el cuarto trimestre, los analistas siguieron de cerca el desempeño de Google Cloud, que superó expectativas con un crecimiento interanual del 48%. La división de nube se ve impulsada por Gemini, su agente de inteligencia artificial, que ya alcanza 750 millones de usuarios activos mensuales y consolida su posición estratégica dentro del grupo tecnológico global. La inteligencia artificial concentró gran parte del interés del mercado. Sundar Pichai, consejero delegado de Alphabet, señaló durante la presentación que el grupo prevé destinar entre 175.000 y 185.000 millones de dólares en 2026 a inversiones en chips, servidores y centros de datos. Esta cifra superó ampliamente las previsiones de Bloomberg, que apuntaban a 95.000 millones, y explicaría las caídas del valor en el mercado fuera de hora, generando nuevas dudas sobre la financiación futura de estos ambiciosos planes. Pese a ello, Pichai calificó el trimestre como excepcional. También destacó Waymo, la unidad de conducción autónoma, cuyas pérdidas operativas superan los 3.000 millones de dólares, aunque la empresa mantiene su apuesta. Alphabet anunció una ronda de financiación de 16.000 millones de dólares para Waymo, principalmente aportada por el grupo, lo que implicó un cargo extraordinario de 1.950 millones de euros y elevó su valoración hasta 126.000 millones de dólares, reforzando su papel como proyecto clave dentro de estrategia.

In this episode of ACM ByteCast, Rashmi Mohan hosts software development productivity expert Nicole Forsgren, Senior Director of Developer Intelligence at Google. Forsgren co-founded DevOps Research and Assessment (DORA), a Google Cloud team that utilizes opinion polling to improve software delivery and operations performance. Forsgren also serves on the ACM Queue Editorial Board. Previously, she led productivity efforts at Microsoft and GitHub, and was a tenure track professor at Utah State University and Pepperdine University. Forsgren co-authored the award-winning book Accelerate: The Science of Lean Software and DevOps and the recently published Frictionless: 7 Steps to Remove Barriers, Unlock Value, and Outpace Your Competition in the AI Era. In this interview, Forsgren shares her journey from psychology and family science to computer science and how she became interested in evidence-based arguments for software delivery methods. She discusses her role at Google utilizing emerging and agentic workflows to improve internal systems for developers. She reflects on her academic background, as the idea for DORA emerged from her PhD program, and her time at IBM. Forsgren also shares the relevance of the DORA metrics in a rapidly changing industry, and how she's adjusting her framework to adapt to new AI tools. 

Send us a textWhat if the future of work depends less on technology and more on how much humanity we choose to preserve?This week on The UpLevel Podcast, we welcome Marshall Belcher, Principal Strategist and AI Innovation Lead for Strategic Customer Engagement at a global tech company, for a thoughtful and timely conversation on leadership, right relationship, and artificial intelligence.Marshall works at the forefront of artificial intelligence, supporting executive strategy and CEO-level engagements across some of the most influential organizations in Silicon Valley. With more than 30 years of experience across companies like Cisco, AT&T, and Prudential, he brings rare depth at the intersection of technology, leadership, and relationship intelligence.But what makes this conversation especially powerful is Marshall's commitment to service, care, and responsibility. We'll explore what it means to be in right relationship with technology as AI reshapes how we work, lead, and connect. Marshall shares why AI must be designed and implemented through intentional alliances, ethical frameworks, and human-centered systems that prioritize safety, dignity, and trust.As we continue our exploration of right relationship, Marshall reminds us that the question is not whether AI will shape our future but how intentionally and relationally we choose to shape AI.Together, we explore:AI as a tool to elevate human potential rather than replace itThe importance of training, governance, and culture when embedding AI into workplacesWhy relationship intelligence matters just as much as technical intelligenceLeadership approaches that preserve humanity in high-performance environmentsWhy right relationship requires putting service before metricsFriendship and genuine connection as strengths in leadershipThe risks of measuring success through individual performance aloneWhy AI must be approached with discernment, training, and humilityHow emotional intelligence and right relationships are essential for AI safety and alignmentWhat it means to design alliances with technology rather than emotional attachments*Disclaimer: What's discussed in this episode are Marshall's personal views and in no way represent Alphabet, Google.About Marshall:Marshall Belcher is a Principal Strategist and AI Innovation Lead for Strategic Customer Engagement at Google Cloud, where he drives executive AI strategy and supports CEO-level engagements for Alphabet's largest customers in Silicon Valley. He designs and delivers strategy sessions, consultative workshops, speaking engagements, and advanced AI demonstrations inside Google Cloud's flagship executive environment.He is a Wharton CTO Program graduate, holds a Master's in Innovation & Entrepreneurship from Full Sail University, and earned his B.S. in Microbiology & Cell Science from the University of Florida.Driven by a belief in AI's power to elevate human potential, Marshall is a lifelong learner who loves to run, eat well, and explore the world.https://www.linkedin.com/in/mbelcher/www.uplevelproductions.comhttps://www.instagram.com/uplevelproductions/https://www.linkedin.com/company/uplevelproductionscompanyhttps://www.facebook.com/uplevelproductionscompany

In the latest episode of the Data Center Frontier Show Podcast, Editor in Chief Matt Vincent speaks with Sailesh Krishnamurthy, VP of Engineering for Databases at Google Cloud, about the real challenge facing enterprise AI: connecting powerful models to real-world operational data. While large language models continue to advance rapidly, many organizations still struggle to combine unstructured data (i.e. documents, images, and logs) with structured operational systems like customer databases and transaction platforms. Krishnamurthy explains how vector search and hybrid database approaches are helping bridge this gap, allowing enterprises to query structured and unstructured data together without creating new silos. The conversation highlights a growing shift in mindset: modern data teams must think more like search engineers, optimizing for relevance and usefulness rather than simply exact database results. At the same time, governance and trust are becoming foundational requirements, ensuring AI systems access accurate data while respecting strict security controls. Operating at Google scale also reinforces the need for reliability, low latency, and correctness, pushing infrastructure toward unified storage layers rather than fragmented systems that add complexity and delay. Looking toward 2026, Krishnamurthy argues the top priority for CIOs and data leaders is organizing and governing data effectively, because AI systems are only as strong as the data foundations supporting them. The takeaway: AI success depends not just on smarter models, but on smarter data infrastructure.

AI took center stage at NRF 2026, and few moments underscored its importance more than Google CEO Sundar Pichai's keynote, where he outlined how shopping is evolving in an increasingly agentic, AI-driven world.This episode of Retail Remix, recorded live from the show floor, features host Nicole Silberstein in conversation with Anil Jain, who leads Global Strategic Industries at Google Cloud. Anil shares how Google Cloud is working with retailers to reimagine everything from product discovery to post-purchase service and why agentic AI represents a fundamental shift in how consumers will interact with brands.Key TakeawaysWhy AI is becoming the great equalizer, helping smaller companies compete with limited resources;How AI experiences in general-use platforms like Google Search are upping the ante for everyone, and how to keep up;What multimodal search unlocks when consumers can shop using not just text, but also voice, images and video;Why hyper-personalization is finally within reach after decades of promise;The change management that will be required as AI shifts the way we all work; How Google and its Cloud division are building for this future.Related LinksRelated reading: Google Launches Direct Checkout in Search, GeminiLearn how Google Cloud is helping retailers adopt AI at scaleExplore more NRF26 coverage and retail insights from Retail TouchPointsSubscribe so you don't miss more episodes of Retail Remix from the show floor of NRF26

Episode 159: In this episode of Critical Thinking - Bug Bounty Podcast we sit down with the Google Cloud VRP Team to deep-dive policy and reward changes, what the panel process looks like, and how to best configure for success.Follow us on XGot any ideas and suggestions? Feel free to send us any feedback here: info@criticalthinkingpodcast.ioShoutout to YTCracker for the awesome intro music!====== Links ======Follow your hosts Rhynorater, rez0 and gr3pme on X:====== Ways to Support CTBBPodcast ======Hop on the CTBB DiscordWe also do Discord subs at $25, $10, and $5 - premium subscribers get access to private masterclasses, exploits, tools, scripts, un-redacted bug reports, etc.Get some hacker swagToday's Sponsor: Join Justin at Zero Trust World in March and get $200 off registration with Code ZTWCTBB26https://ztw.com/Google Cloud VRP Swag Bonus! Mention the podcast in any rewarded (cash or credit) VRP report submission before the end of April to receive bonus swag!Today's Guests:Darby HopkinsMichael Cote====== This Week in Bug Bounty ======AI Red Teaming Explained by AI Red TeamersGood Faith AI Research Safe HarborJoin the Adobe LHE at NULLCON GOA====== Resources ======‘Legendary Guy' - Jakub DomerackiGoogle Cloud VRP rewards rulesGoogle Cloud VRP product tiersBug Hunters blog on the 2025 Google Cloud VRP bugSWATGoogle VRP DiscordGoogle VRP on X====== Timestamps ======(00:00:00) Introduction(00:10:03) CloudVRP Bugswat Event Breakdown(00:16:40) VRP Policy & Rewards Changes(00:04:50) Panel Process(01:00:08) Configuring for Success & Avoiding Downgrades(01:33:47) Scenarios for Success

Episode 159: In this episode of Critical Thinking - Bug Bounty Podcast we sit down with the Google Cloud VRP Team to deep-dive policy and reward changes, what the panel process looks like, and how to best configure for success.Follow us on XGot any ideas and suggestions? Feel free to send us any feedback here: info@criticalthinkingpodcast.ioShoutout to YTCracker for the awesome intro music!====== Links ======Follow your hosts Rhynorater, rez0 and gr3pme on X: ====== Ways to Support CTBBPodcast ======Hop on the CTBB DiscordWe also do Discord subs at $25, $10, and $5 - premium subscribers get access to private masterclasses, exploits, tools, scripts, un-redacted bug reports, etc.Get some hacker swagToday's Sponsor: Join Justin at Zero Trust World in March and get $200 off registration with Code ZTWCTBB26https://ztw.com/Today's Guests:Darby HopkinsMichael Cote====== This Week in Bug Bounty ======AI Red Teaming Explained by AI Red TeamersGood Faith AI Research Safe HarborJoin the Adobe LHE at NULLCON GOA====== Resources ======‘Legendary Guy' - Jakub DomerackiGoogle Cloud VRP rewards rulesGoogle Cloud VRP product tiersBug Hunters blog on the 2025 Google Cloud VRP bugSWATGoogle VRP DiscordGoogle VRP on X====== Timestamps ======(00:00:00) Introduction(00:10:03) CloudVRP Bugswat Event Breakdown(00:16:40) VRP Policy & Rewards Changes(00:04:50) Panel Process(01:00:08) Configuring for Success & Avoiding Downgrades(01:33:47) Scenarios for Success

Chris McHenry, Chief Product Officer at Aviatrix, joined Doug Green, Publisher of Technology Reseller News, to discuss the launch of Aviatrix 8.2 and how the company is redefining zero trust security for modern cloud-native environments. McHenry explained that as critical business data and AI workloads increasingly reside in public clouds such as AWS, Azure, and Google Cloud, traditional perimeter-based security models are no longer sufficient. Aviatrix has spent the last decade building its Cloud Native Security Fabric, a platform designed specifically for cloud operational models rather than retrofitted on-premises approaches. With release 8.2, Aviatrix significantly expands its “zero trust for workloads” capabilities, focusing on Kubernetes, serverless environments, and AI-driven applications. A central theme of the conversation was the evolution of zero trust from a networking concept into a workload-centric security strategy. McHenry noted that recent supply-chain attacks have shown how quickly cloud-native environments can be compromised if basic network controls are missing. Aviatrix 8.2 introduces deeper Kubernetes awareness, policy-as-code integration, and initial native support for securing AWS Lambda, allowing organizations to apply micro-segmentation and least-privilege access directly to modern workloads. McHenry emphasized that cloud security must also evolve operationally. Security teams can no longer rely on slow, ticket-based firewall processes while developers deploy infrastructure at machine speed. Aviatrix 8.2 supports a DevSecOps-friendly model that enables developers to manage zero trust policies within guardrails defined by security teams. As McHenry put it, “If your workloads get more modern but your controls don't, security gets worse without you touching anything.” The discussion concluded with guidance for CIOs and CISOs preparing for the next wave of cloud and AI-driven threats: assess whether existing network security tools truly understand cloud-native workloads, modernize security operations alongside development practices, and prioritize platforms that unify cloud, network, and security teams. More information on Aviatrix 8.2 and the Cloud Native Security Fabric is available at https://aviatrix.ai/.

In today's Cloud Wars Minute, I compare how AWS, Microsoft, Google Cloud, and Oracle are competing in the sovereign cloud race.Highlights00:03 — AWS has announced the general availability of the AWS European Sovereign Cloud. This new, independent cloud service is located solely within the EU's borders, ensuring that it's separate from other AWS regions. Ultimately, the European Sovereign Cloud enables companies to comply with the EU's sovereignty requirements without sacrificing any of the power of AWS infrastructure.00:55 — AWS is not alone in the Cloud Wars Top 10 in offering sovereign cloud capabilities to the European market. Microsoft provides the Microsoft Cloud for Sovereignty through localized frameworks. Google Cloud, through local partnerships, has also developed sovereign-focused solutions. And Oracle has introduced the Oracle EU Sovereign Cloud Regions.01:24 — It appears there is space for all of these competitors, because the market is demanding this sovereignty more than ever. Now, originally, this movement towards sovereign cloud solutions in Europe was stimulated by the EU's tough stance on data protection.02:03 — However, as we enter a period of increased global instability, these sovereign services may take on further significance by enabling companies to operate more independently, and by that, I mean in geographies of their choice. Visit Cloud Wars for more.

LikeFolio's Andy Swan considers Microsoft (MSFT) one of the best-executing companies on Wall Street. While the Mag 7 giant's Azure cloud saw anemic growth compared to Alphabet's (GOOGL) Google Cloud, Andy likes Microsoft's recent stock dip and believes the company is poised for a strong 2026. Why? Microsoft's enterprise reach is undeniably strong, according to Andy. ======== Schwab Network ========Empowering every investor and trader, every market day.Options involve risks and are not suitable for all investors. Before trading, read the Options Disclosure Document. http://bit.ly/2v9tH6DSubscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/About Schwab Network - https://schwabnetwork.com/about

forced Microsoft out of the #1 spot in the Cloud Wars Top 10.Highlights00:03 — Going to go a little more deeply into the shuffles in the Cloud Wars Top 10, some big shake-ups here. Companies moving up and down. Microsoft, former number one, drops down to number three. Google Cloud, up to number one, Oracle to number two.00:25 — I want to talk today about my main reasons for moving Microsoft down from number one to number three. The Microsoft tumble here is really centered on its deep cybersecurity flaws that were exposed about 18-24 months ago. The range and scope of these cybersecurity shortcomings and weaknesses outweigh the extraordinary financial revenue and commercial success.01:38 — The significance of these cyber business shortcomings really came out about just over a year ago, when simultaneously both CEO Satya Nadella and Charlie Bell, who's Executive Vice President of Microsoft's Security business, both came out with public documents outlining how they were going in tandem to totally overhaul Microsoft's cybersecurity business, top to bottom.02:44 — This came out only after a government watchdog had very publicly flagged these shortcomings that Microsoft had and the results, the disastrous results, that led to some issues in China and some exposures of valuable information and more after that. I covered this extensively through the middle of 2024 and later throughout the year,04:18 — Microsoft has always said — Nadella has so frequently said — "Cybersecurity is our number one priority." Well, it's easy to say that. Apparently, it's very hard to do that and to live it. And this also then speaks to a lot of the questions I get about, "How do you do these rankings?" I take into account here the customer value that's being created.05:35 — It's a remarkable time here. And, I just want to emphasize Microsoft's commercial success. Revenue growth has been remarkable. It's by far the biggest cloud company in the world. Its growth rates have been remarkable. Its RPO numbers are great, but this cybersecurity failing just absolutely knocks them out of the running to be the top dog here. Visit Cloud Wars for more.

In episode 171 of Cybersecurity Where You Are, Sean Atkinson and Tony Sager sit down with Soledad Antelada Toledano, Security Advisor, Office of the CISO, Google Cloud at Google. Together, they discuss securing critical national infrastructure (CNI) in U.S. State, Local, Tribal, and Territorial (SLTT) government organizations through artificial intelligence (AI) adoption.Here are some highlights from our episode:00:50. Introduction to Soledad02:48. How the convergence of informational technology (IT) and operational technology (OT) has created bigger attack surfaces04:10. The proliferation of threat actors targeting critical infrastructure sectors07:24. The challenge of legacy systems for U.S. SLTT owners of CNI08:13. Alert fatigue, limited visibility, and other challenges facing OT networks13:22. The value of automated cyber threat intelligence (CTI)24:46. Building strategic AI implementation around human in the loop (HITL)33:17. U.S. SLTTs' use of the cloud to test and build trust for securing CNIResourcesThe Changing Landscape of Security Operations and Its Impact on Critical InfrastructureCybersecurity for Critical InfrastructureEpisode 139: Community Building for the Cyber-UnderservedEpisode 119: Multidimensional Threat Defense at Large EventsLeveraging Generative Artificial Intelligence for Tabletop Exercise DevelopmentThe Evolving Role of Generative Artificial Intelligence in the Cyber Threat LandscapeEpisode 148: How MDR Helps Shine a Light on Zero-Day AttacksVulnerability Management Policy Template for CIS Control 7CIS Critical Security Controls v8.1 Industrial Control Systems (ICS) GuideIf you have some feedback or an idea for an upcoming episode of Cybersecurity Where You Are, let us know by emailing podcast@cisecurity.org.

Google about to snatch the crown… and a lot of y'all still stuck worshipping Nvidia like it's the only AI play that matter. I'm telling you right now: the market switches leaders — and when that leadership flips, it leaves people behind who don't see the shift coming.In this episode I break down why I believe Alphabet (Google) can become the #1 most valuable company, how AI chips + Gemini + YouTube + Cloud partnerships are stacking the deck, and why Nvidia still can run… but the competition is finally heavy. We also get into Apple picking Gemini, big tech power moves, Meta spending like a maniac on nuclear energy, and the 2026 IPO watchlist (SpaceX, OpenAI, Anthropic, Databricks, Stripe, Revolut, Canva — and my sleeper pick will surprise you).High-intent SEO keywords we touch naturally: Google stock, Alphabet stock, Gemini AI, Nvidia competition, AI chips, Big Tech leadership rotation, Apple Gemini deal, Google Cloud, YouTube revenue, AI investing, market leadership switching, Meta nuclear energy deal, 2026 IPOs, SpaceX IPO, OpenAI IPO, Anthropic IPO, Databricks IPO, Stripe IPO, Canva IPO, AI infrastructure stocks.Apple Picked Google Gemini. Bad News for Nvidia?Join our Exclusive Patreon!!! Creating Financial Empowerment for those who've never had it.

SummaryIn this episode, Peter dives into the current state of the crypto landscape, focusing on the Midnight and Cardano Blockchains. He discusses the implications of the recently passed Genius Act, which allows for stablecoin rewards, and highlights the ongoing struggle between banks and crypto companies over regulatory control. Peter emphasises the need for a level playing field where both sectors can thrive, particularly in the realm of stablecoins. He also shares insights on the price trends of the Midnight token, upcoming developments, and his plans to attend meetups in Japan to engage with the community and learn more about the ecosystem.The episode further explores various projects building on the Midnight Blockchain, including a new identity solution and a DeFi project aimed at unlocking liquidity from staked assets. Peter also touches on the collaboration between Google Cloud and Midnight, the launch of new tools and wallets, and the integration of swaps into the Lace Wallet. He wraps up with a discussion on hardware wallets and the importance of security in the crypto space, encouraging listeners to stay informed and engaged with the evolving landscape.Chapters00:39 Current Regulation State03:06 Midnight $NIGHT Update04:21 Midnight Ambassador Program05:10 What's Being Built on Midnight - Nocy08:31 Building on Midnight: Keyd Network09:20 Interview with Atlas DeFi Building on Midnight Coming Up10:34 Google Cloud Comes to Cardano & Midnight11:46 Midnight Explorer12:31 Splash & DexHunter to Merge14:10 FROST Signatures15:41 Bitcoin DeFi: Bifrost Bridge16:25 FluidTokens P2P Loans18:06 Smart Token DEX20:06 Emurgo & W3iSoftware MoU21:38 Lace Wallet Introduces Swaps23:02 Get a Hardware Wallet24:03 Become a Channel MemberDISCLAIMER: This content is for informational and educational purposes only and is not financial, investment, or legal advice. I am not affiliated with, nor compensated by, the project discussed—no tokens, payments, or incentives received. I do not hold a stake in the project, including private or future allocations. All views are my own, based on public information. Always do your own research and consult a licensed advisor before investing. Crypto investments carry high risk, and past performance is no guarantee of future results. I am not responsible for any decisions you make based on this content.

Apple has introduced Creator Studio, a subscription-based suite that embeds AI-assisted features directly into familiar productivity and creative tools while maintaining strict control over interfaces and user experience. Alongside this launch, Apple confirmed a multiyear partnership with Google to use Gemini and Google Cloud as foundational AI infrastructure, reportedly involving annual payments of around $1 billion. The approach reinforces Apple's strategy of treating AI models as interchangeable components while retaining authority at the application layer, shifting responsibility for governance and oversight away from the platform and toward downstream users and advisors.Google, meanwhile, expanded Gemini through a new Personal Intelligence feature that can reason across Gmail, Photos, Search, and YouTube data for consumer accounts. Available initially to paid subscribers and requiring explicit consent, the capability highlights Google's advantage in contextual data rather than model novelty. By keeping the feature out of Workspace for now, Google appears to be setting user expectations in consumer environments before enterprise deployment, a move that may influence how business users evaluate AI-enabled decision support in the future.Pax8 disclosed a data leak affecting approximately 1,800 MSP partners after an internal spreadsheet was mistakenly shared with a limited number of recipients. While no personally identifiable information was exposed, the data included licensing and commercial details that could be used for competitive intelligence or targeted attacks. The incident coincides with Pax8's rapid international expansion, new regional offices, and growing reliance by MSPs on its marketplace for procurement and security tooling, including the recent addition of Cork Cyber's risk intelligence platform.Taken together with renewed attention on AI governance, the Secure by Design initiative, and guidance on when to apply GenAI versus traditional code, the episode underscores a widening gap between automation and authority. Surveys show a majority of IT leaders now prioritize AI governance, reflecting concern over accountability, data flows, and failure handling. For MSPs and IT service providers, these developments reinforce the need to clearly define who has the power to approve, pause, or override AI-driven systems and platform dependencies, as clients increasingly expect service providers to explain and manage outcomes they may not fully control. Four things to know today Apple's Creator Studio and Google Partnership Show a Strategy Built on Control, Not AI OwnershipAs Gemini Reasons Across Gmail, Search, and YouTube, Google Redefines AI Advantage Around Context            Pax8 Data Leak, Rapid Expansion, and Marketplace Growth Expose Risk Shift to MSPsAI Governance, Secure by Design, and GenAI Adoption Reveal a Growing Authority Gap for MSPs This is the Business of Tech.    Supported by:  https://scalepad.com/dave/

Might internal memos be a thing of the past?When you can just build something as fast as writing a memo about it, why wouldn't you just build the demo? In this episode of Everyday AI, we sit down with Google Cloud's Richard Seroter to break down five simple ways to use AI with Google. No technical background needed.We talk faster research, better learning, building ideas without overthinking, and why “demos over memos” might change how teams work.If you want practical, no-BS ways to actually use AI in your day‑to‑day, this one's worth a listen.5 Practical AI Workflows That Actually Matter -- An Everyday AI Chat with Jordan Wilson and Google's Richard Seroter (Replay)Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:Five Practical AI Workflows with GoogleGemini Deep Research for Rapid AnalysisNotebookLM AI-Powered Knowledge ExplorationGemini CLI and Code Assist for DevelopersGoogle Jewels Autonomous Coding AgentsAI Change Management and Workflow AutomationGemini's Contextual Integration with Email and CalendarGemini and Agentic AI Across Google ProductsTimestamps:00:00 "Simple AI Strategies for Workflows"06:14 "Embracing AI-First Thinking"08:49 "Effective Strategies for Deep Research"11:24 "Context Engineering with LLMs"15:32 "Unlocking AI's Business Potential"17:33 Simplifying Complexity with AI21:21 "Everyone's a Builder Now"24:54 "Building AI Tools for Everyone"28:06 "Communicating Intent to AI Agents"30:16 "AI: The Smarter Interface"33:30 "Everyday AI: Wrap-Up & Subscribe"Keywords:Gemini Deep Research, Google AI, generative AI, AI workflows, Google Cloud, NotebookLM, AI strategies, AI transformation, change management, contextualized AI, agentic work, AI-powered research, personalized AI, deep research tools, collaborative AI agents, AI in business, AI for analysis, large language models, AI for everyday business leaders, Gemini CLI, code assist, AI coding agent, Google Jewels, autonomous AI, background AI teammate, context engineering, integrating AI in workflows, AI for HR, marketing AI, AI-powered knowledge management, learning with AI, AI onboarding, student AI tools, spec driven development, Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner 

(0:00) Intro! (2:47) Tony Hinchcliffe roasts the Besties (15:01) Interview: Kill Tony success, MSG rally, origin story, free speech in Europe (36:03) The Besties play Kill Tony! (50:14) The 2025 Bestie Awards: Business, Politics, Tech, and more Thanks to our partners for making this happen! IREN: https://iren.com OKX: https://okx.com Google Cloud: https://cloud.google.com Follow Tony: https://www.youtube.com/@killtony https://x.com/TonyHinchcliffe Follow the besties:  https://x.com/chamath https://x.com/Jason https://x.com/DavidSacks https://x.com/friedberg Follow on X: https://x.com/theallinpod Follow on Instagram: https://www.instagram.com/theallinpod Follow on TikTok: https://www.tiktok.com/@theallinpod Follow on LinkedIn: https://www.linkedin.com/company/allinpod Intro Music Credit: https://rb.gy/tppkzl https://x.com/yung_spielburg Intro Video Credit: https://x.com/TheZachEffect