AI_Cloud Essentials

CoreWeave

Breakthroughs stall when leaders are forced to build the future on foundations from another era. Modern AI demands new thinking, tooling and decision patterns, yet many executives feel trapped by outdated playbooks. AI Cloud Essentials clears that bottleneck. Hosted by Independent AI Value Strategist Ritu Jyoti, the show delivers practical guidance for leaders navigating trillion-parameter models, real-time adaptation and fast-moving AI ecosystems. Each episode offers clear frameworks to help teams innovate faster, scale smarter and reduce friction without jargon or recycled thinking.

  1. Aug 11

    Every Enterprise Decision Is a Prediction

    Enterprise AI is moving past retrieval and into prediction. In this episode of AI Cloud Essentials, host Ritu Jyoti sits down with Ben Turtel, CEO and founder, to unpack why the next generation of enterprise models needs to understand which signals actually lead to which outcomes - not just memorize company information. Ben explains how predictive analytics reframes everyday business choices: every enterprise decision is a prediction about what will happen next. From financial services use cases like forecasting earnings surprises from SEC filings to private equity and sales predictions, the conversation explores why outcome-oriented models require the right data, the right training approach, and infrastructure that can move as fast as the experiments demand. The episode also gets practical about what slows AI teams down: access to proprietary data, the need to containerize full stacks, the cost of training runs, and the importance of being able to spin GPUs up and down quickly. This conversation is for enterprise AI leaders, technical founders, and infrastructure teams who are deciding whether their AI strategy is still searching for information - or starting to reason like an expert. What you'll take away: Why every enterprise decision can be understood as a prediction How models can learn which signals and factors lead to which outcomes Why access to proprietary data is often the biggest friction point for enterprise AI How containerized small-model architectures can help teams run closer to customer data Why the enterprise needs to move from retrieval toward trained experts that know what matters Learn how predictive AI changes the enterprise question from "where is the information?" to "what is likely to happen next?"

  2. Jul 28

    AI Is a Marathon Where You Sprint the Entire Time

    The next frontier of AI may start inside a gaming clip. In this episode of AI Cloud Essentials, host Ritu Jyoti sits down with Pim, CEO and Co-Founder of General Intuition, to unpack how player-generated gaming data became the foundation for a new class of general models - and why scaling that bet requires infrastructure built for high-velocity research.Pim explains the insight behind General Intuition's work: a saved gameplay clip is not just a video; it is the end of a sequence of decisions, actions, and reasoning. That data flywheel lets the team train models that can move from information-dense gaming environments to physical robots, while a new CoreWeave pre-training cluster gives the company the performance, uptime, and support needed to keep a lean research team moving.This conversation is for AI founders, research leaders, and infrastructure teams trying to scale faster without burning out the people doing the work.What you'll take away:- Why gaming clips can function like reasoning chains for model pre-training- How a consistent controller input space helps models transfer across simulators and robots- Why CoreWeave's Kubernetes implementation and GPU uptime mattered for a lean research team- How infrastructure reliability directly affects team sleep, morale, and research velocity- Why reinforcement learning may bring the CPU stack back into the center of AI infrastructureLearn why the AI race is not a marathon or a sprint - it’s both at once, and every infrastructure decision makes the next step easier or harder.

  3. Jul 14

    Move Fast, Fail Forward—and Clone the Win

    AI cloud infrastructure is the difference between a viral moment and a missed opportunity. In this episode of AI Cloud Essentials, host Ritu Jyoti sits down with Jake Rothman, who leads Go-To-Market and Partnerships at Decart AI, to unpack how a single viral LinkedIn demo of virtual try-on turned into a commercial roadmap — and why an AI-native cloud partner like CoreWeave made it possible to say yes. Jake traces Decart's journey from Oasis One — a Minecraft-inspired, prompt-generated world model — to real-time video products demanding sub-40 millisecond latency, and shares the go-to-market playbook his team uses to turn one obsessed customer into a repeatable motion. This conversation is for AI builders, infrastructure leaders, and GTM teams deciding how fast they can afford to move. What you'll take away: Why sub-40 millisecond latency is the threshold that makes real-time AI experiences possible How burst capacity removes the internal debate when a product spikes overnight The "clone the win" playbook: find one customer who loves the product, then exhaust that track Why Decart treats GPU optimization as a commercial product, not a cost center How world models like Oasis One point toward the physical AI and robotics opportunity ahead

  4. Jun 30

    How AI Is the Ultimate Horizontal Enabler

    AI agents are reshaping enterprise infrastructure, and AI-native cloud is becoming the foundation for what comes next. In this episode of AI Cloud Essentials, host Ritu Jyoti sits down with Chen Goldberg to explore how businesses are moving from models to agents—and why traditional cloud environments can’t keep up. If you want to understand how CoreWeave’s AI-native cloud drives faster experimentation, better production scale, and real business outcomes, this episode gives you the roadmap. Ritu and Chen break down how CoreWeave helps customers move beyond AI experimentation into full production, supporting everything from enterprise search to large-scale inference and agentic workflows. They discuss customer examples, revealing how bottlenecks shift from compute to data movement, why speed matters more than ever, and how organizations can “lean in” instead of falling behind. Whether you’re a CIO, CTO, platform leader, or AI innovator, this conversation will change how you think about infrastructure in the AI era. Learn why AI-native cloud is critical for moving from experimentation to production Understand how AI agents are changing the demands on infrastructure and data pipelines Discover how companies like MercadoLibre and Cohere are scaling AI workloads faster See why “speed matters” is becoming the most important strategy for enterprise AI teams Learn how leaders can avoid pilot purgatory and accelerate innovation with confidence Don’t risk building tomorrow’s AI strategy on yesterday’s infrastructure. Learn how to move faster, scale smarter, and lead the shift from models to agents before your competitors do.

  5. Jun 16

    How Marketing Is Moving to an AI-First Approach

    AI product marketing is changing fast—and the teams that win will be the ones using AI for more than just content generation. In this episode of AI Cloud Essentials, host Ritu Jyoti sits down with Susanne Seitinger, VP of Product Marketing at CoreWeave, to unpack how AI product marketing is transforming everything from messaging and naming to persona development and synthetic research. If you want to understand how to increase marketing velocity without sacrificing strategy, this conversation delivers practical insights you can use immediately. Ritu and Susanne explore how product marketing teams can move beyond surface-level AI use cases and rethink foundational practices like validation, decision-making, and customer feedback loops. They break down how synthetic research helps teams test messaging in days instead of months, why “AI slop” is a real risk for marketers, and how human discernment still separates great marketing from automated noise. Susanne also shares how her team at CoreWeave is building an AI-first product marketing function—one that balances speed, consistency, and real customer resonance. Learn how AI product marketing improves naming, messaging, and persona mapping Understand when synthetic research works—and when traditional research still matters Discover how to create faster feedback loops without losing message consistency Avoid “AI slop” by strengthening human judgment, discernment, and taste See how leading product marketing teams are building AI-first workflows that scale Don’t risk falling behind while your customers and competitors move faster than ever. Learn how to rethink product marketing from the ground up and use AI to create real business impact.

  6. Jun 2

    How AI Is Transforming DevOps and the Developer Experience

    AI-powered engineering is reshaping how software gets built, and this episode breaks down exactly what that means for teams today. In this episode of AI Cloud Essentials, we explore AI-powered engineering through real-world use cases, revealing how autonomous agents are changing the role of developers and accelerating innovation. If you’re trying to understand where AI coding tools deliver real value—and where they still fall short—this conversation gives you a clear, practical roadmap. Hosted by Ritu Jyoti, this episode features Camille Fournier, VP of Engineering at CoreWeave, who shares how teams are moving beyond simple code completion into fully agent-driven workflows. From greenfield development to operational automation inside complex AI cloud environments, Camille explains how organizations are adopting these tools, where bottlenecks are emerging (like code review and validation), and what it takes to actually get value from AI today. You’ll walk away with a grounded understanding of how AI is transforming engineering workflows—not just in theory, but in practice. What you’ll learn: How AI agents are shifting engineering from writing code to orchestrating systems Where AI coding tools work best today (greenfield vs. legacy systems) Why code review, validation, and workflows are becoming the new bottlenecks How non-engineers are already using AI tools to build and automate work The mindset engineers need to stay relevant as AI evolves rapidly Don’t risk falling behind as AI reshapes engineering. Learn how to adapt your workflows, rethink your role, and get real value from AI—before the gap widens.

  7. May 19

    How Wall Street Can Drive The Next AI Breakthrough

    AI in financial markets is moving beyond incremental gains and into core decision-making. It’s no longer just about back-office automation, it’s beginning to reshape pricing, risk, and trading systems. In this episode, you’ll learn how to apply AI in financial markets to move beyond alpha and drive real market transformation. Hosted by Ritu Jyoti, an independent AI strategist, this episode features Dimitris Tsementzis, Founder and CEO of hLevel. Together, they explore why traditional AI approaches struggle in non-stationary markets and what it takes to build systems that can adapt, learn, and operate under constant change. From the limits of interpretability to the importance of controllability, this conversation breaks down how financial leaders can rethink models, manage risk, and apply AI to core market functions—not just incremental efficiency gains. In this episode, you’ll learn how to: Apply AI to pricing, risk, and trading systems Design AI systems for non-stationary, constantly changing markets Prioritize controllability over interpretability in high-risk environments Move beyond back-office automation to core market transformation Identify where AI can create real competitive advantage in finance Don’t risk falling behind by limiting AI to incremental improvements. Learn how to apply AI in financial markets to move beyond alpha and lead the next wave of innovation.

  8. May 5

    How Physical AI is Streamlining Engineering

    AI-powered engineering is transforming how organizations solve complex physical problems. AI-powered engineering is no longer about theory, it’s enabling faster simulation, real-world testing, and better decision-making across industries. In this episode, you’ll learn how to apply AI-powered engineering to accelerate innovation in the physical world. Hosted by Ritu Jyoti, an independent AI strategist, this episode of AI Cloud Essentials features Richard Ahlfeld, SVP for Physical and Scientific AI at CoreWeave. Together, they explore how AI is moving beyond digital systems into real-world applications like automotive, manufacturing, and robotics. From using transformers to dramatically improve simulation accuracy to learning directly from physical testing data, this conversation breaks down how leaders can move faster by combining AI with real-world iteration instead of relying on theory alone. In this episode, you’ll learn how to: Use AI to accelerate physical simulations and engineering workflows Combine simulation and real-world testing to improve outcomes Apply transformer models to complex physical systems Overcome data challenges in engineering and scientific AI Identify high-impact use cases across automotive, manufacturing, and robotics Don’t risk falling behind by relying only on traditional simulations or outdated workflows. Learn how to apply AI-powered engineering to move faster, test smarter, and build better systems.

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About

Breakthroughs stall when leaders are forced to build the future on foundations from another era. Modern AI demands new thinking, tooling and decision patterns, yet many executives feel trapped by outdated playbooks. AI Cloud Essentials clears that bottleneck. Hosted by Independent AI Value Strategist Ritu Jyoti, the show delivers practical guidance for leaders navigating trillion-parameter models, real-time adaptation and fast-moving AI ecosystems. Each episode offers clear frameworks to help teams innovate faster, scale smarter and reduce friction without jargon or recycled thinking.

Information

  • Creator
    CoreWeave
  • Years Active
    2025 - 2026
  • Episodes
    15
  • Rating
    Clean
  • Copyright
    © CoreWeave
  • Show Website
    AI_Cloud Essentials