The Deep View: Conversations

The Deep View

From frontier labs and enterprise platforms to emerging startups reshaping entire industries, The Deep View: Conversations podcast interviews the brightest minds and the most influential leaders in AI.

  1. 2日前 ·  ビデオ

    #62 - How openness became AMD’s AI strategy - Andrew Dieckmann

    AI's appetite for compute keeps growing, but so does the pressure to deliver more intelligence per watt and per dollar. Can AMD's first rack-scale AI system open up an ecosystem dominated by Nvidia? In this episode of The Deep View Conversations, we sit down with Andrew Dieckmann, AMD's general manager of its data center GPU business, to unpack the company's Helios platform and the rapidly changing economics of AI infrastructure.  Dieckmann explains why frontier AI requires more than just GPUs. It demands tightly engineered racks that combine GPUs, CPUs, networking, software, cooling and serviceability. The conversation examines the tension around AI data centers: hyperscalers still cannot get enough compute, while communities worry about power, water and whether the benefits justify the buildout. Andrew argues that responsible deployment and open ecosystems are essential as these systems become intelligence factories. The conversation then turns to Helios: AMD's performance claims against Nvidia Vera Rubin, pricing and value, the first likely customers, and the Cerebras partnership for high-throughput, low-latency inference. Andrew closes with his advice for leaders navigating AI velocity: reassess priorities more often and use coding agents as force multipliers for scarce engineering talent. Topics covered: • Why AMD is moving from chips to full rack-scale systems• AI demand, data center constraints, and community impact• Open hardware, open software and customer choice• How agentic AI changed infrastructure planning• Helios performance, efficiency, pricing and customers• AMD Helios versus Nvidia Vera Rubin• How AMD and Cerebras split inference workloads This conversation offers a clear look at the technology and economics shaping the infrastructure that will power everyday AI and the breakthroughs to come. Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: tdv.transitor.fm  And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.com

    #62 - How openness became AMD’s AI strategy - Andrew Dieckmann

  2. 5日前 ·  ビデオ

    #61 - The economics pushing AI toward open models - Jeff Morgan

    AI's next power shift isn't gonna happen in a data center.  In this episode of The Deep View Conversations, we sat down with Jeff Morgan, co-founder and CEO of Ollama, to explore why open models are gaining momentum, and why enterprises and developers increasingly want more control over their AI. Morgan explains how Ollama grew from a two-week experiment into software used across 80% of the Fortune 500, how the economics of coding agents are pushing teams toward open models, and why cost, privacy and control are becoming decisive advantages. He also breaks down the hardware shift bringing data-center-class AI workloads to Apple silicon, Nvidia DGX Spark and systems powered by AMD, Intel and Qualcomm. The conversation also covers: • How the team behind Docker Desktop came to build Ollama• Why open models could soon process the majority of enterprise AI tokens• The role of harnesses, tool calling, routing and subagents• How Ollama fits into the open-source AI stack and where its business model comes in• Why new US and European open-model labs are emerging• Why companies may need to own and customize their intelligence layer If you’re interested in open models, coding agents, enterprise AI or the shift from cloud-only AI to powerful local systems, this conversation offers a clear look at where the ecosystem is heading. Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: tdv.transitor.fm  And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.com

    #61 - The economics pushing AI toward open models - Jeff Morgan

  3. 8月23日 ·  ビデオ

    #60 - Are foldables the best AI phones now? - Sabrina Ortiz

    For almost a decade, foldable phones have been a product looking for a problem to solve. They may have found their lane. In a special episode of The Deep View Conversations, we make sense of Google's and Samsung's latest hardware and the AI announcements that came with them. But mostly, we talk about the new folding phones, the Pixel 11 Pro Fold and the Z Fold 8.   While folding and flip phones have existed for years, this summer both Google and Samsung upped the ante by launching new experiences that let AI enthusiasts make the most of the added screen real estate for AI workflows.  Topics covered include: The new AI features available on the Pixel 11 phones How Gemini contributes to the AI experience on mobileDoes Google still have the lead in AI hardware?The minimal hardware improvements to the Pixel devicesThe advantages of owning a foldable in the AI era How Samsung's Galaxy Z Fold 8 series comparesThe advantages of the Z Fold 8's "passport" form factorHow Apple's foldable, rumored to launch in September, will compete  If you're trying to understand how AI is changing what you can do with a smartphone, and what your next phone purchase should be if you prioritize AI, you won't want to miss this episode.  Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: tdv.transistor.fm  And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.com

    #60 - Are foldables the best AI phones now? - Sabrina Ortiz

  4. 8月16日 ·  ビデオ

    #59 - Let's talk about AI bubbles - Nat Rubio-Licht

    AI bubble talk is rearing its head again, but the context is very different from the conversations in late 2025.  In this episode of The Deep View Conversations, we unpack the common arguments about an AI bubble and explain why reality naturally falls somewhere in between the doomsayers and AI absolutists.  We look at AI's "Tinker Bell problem": the boom depends partly on people continuing to believe in AI's potential, even as public skepticism grows. Beneath that belief cushion, enterprise contracts drive most of AI labs' revenue, while strong hyperscaler earnings and compute shortages suggest durable demand is building.  We debunk a viral claim that a $200 Claude subscription costs Anthropic $8,000 to serve. We also look at enterprises' push for more control, efficiency and measurable ROI, including one company's claim that some engineers' token use costs 1.5 times their compensation.  Other topics include:• Training, inference, API pricing and token economics• Real value, snake oil and the hype cycle• Why AI demand outruns compute supply• Why the AI bubble may look more like bubble wrap• Market rotation into energy and materials  If you're trying to separate durable AI demand from hype and understand where a real correction could begin, then this conversation offers a framework for thinking about what may pop, what may deflate and what may keep growing. Keep in mind that this is industry analysis and not investor advice.  Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: tdv.transitor.fm  And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.com

    #59 - Let's talk about AI bubbles - Nat Rubio-Licht

  5. 8月13日 ·  ビデオ

    #58 - Android's big leap is from apps to agents - Sameer Samat

    The smartphone has been built around apps and taps for nearly two decades. Google thinks AI will fundamentally change that. In this episode of The Deep View Conversations, we talked with Sameer Samat, president of Android ecosystem at Google, about what the company means when it says it's transforming Android from an operating system into an intelligence system.  Samat explains why the next generation of computing could shift us from micromanaging our devices to simply telling them what we want to accomplish. We dig into how AI agents could navigate apps and complete multistep tasks and why those agents need to follow us across phones, computers, cars, watches and glasses. And what happens to the app-centric model that has defined smartphones for the past 15 years? We also get into some of the practical ways this is already taking shape. Samat discusses Google’s app automations and Rambler, the new Google Keyboard experience that can turn your voice brain-dumps into polished text. He also explains how Google is thinking about permissions, sandboxing and human oversight as AI agents gain the ability to take action on our behalf. The conversation goes well beyond the phone. We talk about why smart glasses and cars could be especially powerful interfaces for AI agents, what Google learned from the original Google Glass, and why the best AI features may be the ones consumers barely think of as AI. Other topics covered include:• How AI is already changing work inside Google• Why product managers can now build functional prototypes themselves• Samat's favorite overlooked AI tool• His "calendar cleanse" strategy for getting time back If you’re trying to understand where mobile computing goes next, what AI agents will actually look like on phones, and how Google plans to weave intelligence across devices, this conversation offers insights into what the company is building and why. Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: tdv.transitor.fm  And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.com

    #58 - Android's big leap is from apps to agents - Sameer Samat

  6. 8月9日 ·  ビデオ

    #57 - Why AI's next era may not belong to LLMs - Zuzanna Stamirowska

    What comes after large language models? In this episode of The Deep View Conversations, we talked with Zuzanna Stamirowska, CEO of Pathway, to explore why her team believes today’s dominant AI architecture has fundamental limits, and what it could take to move beyond them. Pathway is developing Dragon Hatchling, a new architecture designed to give AI native memory, continual learning, and a different approach to reasoning. Stamirowska explains why today’s LLMs can appear to remember without actually internalizing what they learn, why reasoning through language creates its own constraints and costs, and how Pathway is trying to build models that can think in a more abstract way.  The conversation looks at how those architectural changes could affect hallucinations, interpretability, safety, and the enormous compute demands of modern AI. Stamirowska shares how her background in complex systems and game theory shaped Pathway’s approach, why the company made an early bet on challenging the transformer, and how the AI coding revolution has already radically changed the way her own team works. Topics covered:• Why transformers struggle with memory and continual learning• How Pathway’s Dragon Hatchling architecture works• How a different architecture could reduce compute costs• How interpretability could make advanced AI more predictable• Why Pathway’s engineers have largely stopped writing code themselves• How Stamirowska uses Codex, Claude Code, and other AI tools• Why leaders should be ruthless about identifying the critical path If you’re interested in what could come after today’s LLMs, and whether the next big leap in AI will require more than simply scaling transformers, this conversation offers a fascinating look at one of the teams betting on a fundamentally different path. Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: tdv.transitor.fm  And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.com

    #57 - Why AI's next era may not belong to LLMs - Zuzanna Stamirowska

  7. 8月3日 ·  ビデオ

    #56 - Why AI’s next power shift starts on your desk - Mark Papermaster

    What happens when powerful AI no longer has to live in the cloud? In this episode of The Deep View Conversations, we talked with Mark Papermaster, CTO of AMD, about why the next major shift in AI could happen on the device sitting on your desk. Papermaster explains how computers could soon run sophisticated models and teams of private AI agents locally, offering greater speed, security and control without recurring token costs. He also makes the case that AI will be even more transformative than the smartphone because it will be embedded across nearly every device, industry and aspect of daily life. The conversation also covers: Why open ecosystems matter in the AI eraHow AI is accelerating science, agriculture and industryThe growing energy demands of AIHow leaders can reinvent workflows with agentsWhy local AI could reduce cloud dependence and vendor lock-inPapermaster’s lessons from four decades in technologyIf you’re interested in less lock-in, open ecosystems, and how enterprises can run AI more efficiently and privately, this conversation offers a look at what a more distributed and secure AI future could look like. Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: tdv.transitor.fm  And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.com

    #56 - Why AI’s next power shift starts on your desk - Mark Papermaster

  8. 7月27日 ·  ビデオ

    #55 - Why modeling 'I don’t know' is AI's most urgent problem - Ruchir Puri

    AI systems almost always have an answer, even when they should say, “I don’t know.” In this episode of The Deep View Conversations, senior reporter Sabrina Ortiz speaks with Ruchir Puri, chief scientist at IBM Research, about why uncertainty modeling may be AI’s most urgent technical challenge. Puri explains why today’s models struggle to recognize the limits of their own knowledge, how that failure contributes to hallucinations, and what researchers must solve before AI can become more reliable. He also explores the need for self-improving models, the enormous energy gap between artificial and human intelligence, and why the future of AI depends on doing more with less compute. The conversation also covers: • Why Puri predicted in 2020 that AI would transform software development• How big data, GPUs, and transformer architectures created the current AI boom• Why intelligence involves more than IQ• The roles of emotional and relationship intelligence• Why language models cannot capture the full complexity of the physical world• How AI could help redesign software, quantum computing, and chip development• Why Puri prefers "artificial useful intelligence" over AGI Rather than chasing abstract definitions of general intelligence, Puri argues that the industry should focus on building AI that is useful, efficient, adaptable, and honest about what it does not know. Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: tdv.transitor.fm  And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.com

    #55 - Why modeling 'I don’t know' is AI's most urgent problem - Ruchir Puri
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番組について

From frontier labs and enterprise platforms to emerging startups reshaping entire industries, The Deep View: Conversations podcast interviews the brightest minds and the most influential leaders in AI.

情報

  • クリエイター
    The Deep View
  • 配信期間
    24年 - 26年
  • エピソード
    62
  • 制限指定
    不適切な内容を含まない
  • Copyright
    © 2026 The Deep View
  • 番組のWebサイト
    The Deep View: Conversations

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