『Technically Speaking with Chris Wright』のカバーアート

Technically Speaking with Chris Wright

Technically Speaking with Chris Wright

著者： Red Hat
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Struggling to keep pace with the ever-changing world of technology? For experienced tech professionals, making sense of this complexity to find real strategic advantages is key. This series offers a clear path, featuring insightful, casual conversations with leading global experts, innovators, and key voices from Red Hat, all cutting through the hype. Drawing from Red Hat's deep expertise in open source and enterprise innovation, each discussion delves into new and emerging technologies-- from artificial intelligence and the future of cloud computing to cybersecurity, data management, and beyond. The focus is on understanding not just the 'what,' but the important 'why' and 'how': exploring how these advancements can shape long-term strategic developments for your organization and your career. Gain an insider’s perspective that humanizes complex topics, helping you anticipate what’s next and make informed decisions. Equip yourself with the knowledge to turn today's emerging tech into valuable, practical strategies and apply innovative thinking in your work. Tune in for forward-looking discussions that connect the dots between cutting-edge technology and real-world application, leveraging a rich understanding of the enterprise landscape. Learn to navigate the future of tech with confidence.2026 Red Hat 経済学
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    As modern IT systems grow too complex for humans to effectively manage, there's growing interest in turning to autonomous AI agents for operations. While powerful, these agents introduce new challenges around trust, reliability, and control. To explore how to solve for this, Red Hat CTO Chris Wright speaks with Bernd Greifeneder, Founder and CTO of Dynatrace [LINK: https://www.dynatrace.com], a company that has long focused on managing complexity with AI. Bernd Greifeneder shares his industry insights and expertise on: • The evolution from simple application architectures to massive, ephemeral microservices environments that are beyond human-scale to manage. • Balancing creative, generative AI with fact-based, causal AI to create a reliable and deterministic foundation for autonomous operations. • The critical need for high-quality, real-time data to create a "digital twin" of a production environment, enabling true root cause analysis instead of just correlation. • Why building trust is the biggest challenge for agentic AI and how a "human-in-the-loop" approach is essential before handing over the keys. Tune in for an in-depth discussion on the future of autonomous IT. This conversation is critical for any SRE, developer, or technology leader preparing to manage not just their systems, but the AI agents that will run them.
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  • How Red Hat cleared IT debt for scalable AI ft. Marco Bill

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    While conversations around enterprise AI tend to focus on high-level possibilities, less attention is given to the foundational plumbing required to make systems actually run. What happens when an enterprise's financial data is copied across 73 different spreadsheets or bogged down by thousands of legacy virtual machines? In this episode of Technically Speaking, host and Red Hat CTO Chris Wright sits down with Red Hat CIO Marco Bill to peek behind the curtain of enterprise IT transformation and explore why the secret to AI readiness is radical simplification. Building on 20 years of productive friction between engineering and IT, Marco shares an insider's look at what it really takes to clean up legacy technical debt. From standardizing workloads on Red Hat OpenShift to taking the bold step of decommissioning 2,400 unused dashboards, Marco explains how reducing infrastructure and data complexity creates the clean, single source of truth necessary for enterprise AI. Chris and Marco dive into the real-world trajectory of enterprise AI adoption—moving from associate productivity boosts to high-ROI business process transformation. The conversation also tackles the modern pitfalls of technology governance. They discuss how overly dense legal policies accidentally fuel "shadow AI," and why organizations must replace legalese with automated security guardrails and developer-friendly workflows. Plus, they examine why the explosive demand for AI compute and accelerators is bringing bare metal infrastructure full circle within hybrid cloud strategies. Tune in to discover why true innovation often looks like subtraction, and learn how enterprise leaders can clean up their data foundations today to build scalable, secure, and AI-native organizations for tomorrow.
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    23 分
  • Inside open source AI strategy ft. Steve Watt

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    2026/06/03
    Go behind the scenes of Red Hat's internal innovation engine to discover how we evaluate emerging open source tech and choose exactly where to place our next major technology bets. In this episode of Technically Speaking, Red Hat Chief Technology Officer Chris Wright sits down with Steve Watt, Vice President of the Office of the CTO at Red Hat, for a clear, "200-level" look at what's coming down the road. Together, they map out how Red Hat’s pathfinding group tracks open source innovations and shapes raw clay into enterprise-ready layouts. Steve shares how his teams follow proven open source innovators and build strategic university partnerships to stay ahead of an AI cycle that changes every single week. Dive into the mechanics of composable intelligence, where the conversation explores the vLLM Semantic Router. This open source project, incubated within Red Hat, allows businesses to selectively route inference requests across specialized small language models or fall back to larger cloud models based on real-time cost, data privacy, and semantic analysis. Chris and Steve also break down how confidential computing protects data, showing how secure enclaves can keep proprietary model weights safe even when running in third-party environments. Finally, discover how the hardware landscape is moving past GPU scarcity. Learn how new matrix multiplication instructions are opening up inference workloads on modern x86 CPUs, how specialized accelerators like Cerebras, Grok, and IBM Spyre are meeting strict data center power budgets, and how the OpenReg project makes it easier for silicon startups to integrate with PyTorch. Tune in to see why the real enterprise AI secret sauce is no longer just the model itself, but the open source infrastructure backing it.
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    30 分
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