The Deep View: Conversations

#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

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#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 mobile Does Google still have the lead in AI hardware? The minimal hardware improvements to the Pixel devices The advantages of owning a foldable in the AI era How Samsung's Galaxy Z Fold 8 series compares The advantages of the Z Fold 8's "passport" form factor How 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

#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

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#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

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#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

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#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 era How AI is accelerating science, agriculture and industry The growing energy demands of AI How leaders can reinvent workflows with agents Why local AI could reduce cloud dependence and vendor lock-in Papermaster’s lessons from four decades in technology If 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

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#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

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#54 - Why sovereign AI is so urgent in the agentic era - Priya Srinivasan

Is it possible for enterprises to build AI agents they can actually trust? In this episode of The Deep View Conversations, Senior Reporter Sabrina Ortiz sat down with Priya Srinivasan of IBM to discuss Sovereign Core, IBM’s software designed to enable enterprises to deploy AI in a secure, compliant, and sovereign way. As AI moves from chatbots to agents that can take real action inside organizations, companies need more than speed. They need to know where their data lives, where their models run, who has access, and whether their AI systems comply with internal policies and external regulations. Srinivasan explains why digital sovereignty is becoming more urgent in the AI era, especially for governments, regulated industries, and enterprises trying to move AI projects from proof of concept to production. She also breaks down how Sovereign Core is designed to bring the control plane, security, access, compliance evidence, and deployment flexibility inside an organization’s own boundaries. Topics covered include: What digital sovereignty means in the age of AI Why AI agents raise new questions around governance and trust How IBM Sovereign Core helps enterprises deploy AI workloads Why compliance can slow AI projects from reaching production What "sovereignty with receipts" means How companies can balance speed, cost, compliance, and innovation Why regulated industries need stronger AI governance from day one If you’re interested in enterprise AI, agents, governance, compliance, or how major companies are trying to make AI production-ready, this conversation offers a look at what the next stage of trustworthy AI deployment will require. 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

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#53 - How to rethink AGI through multimodal systems - Caroline Ingeborn

In this episode of The Deep View Conversations, we sat down with Caroline Ingeborn, COO of Luma, an AI lab dedicated to omnimodal intelligence, to discuss where generalized physical AI could take us. Rather than focusing only on video models, Luma takes an omnimodal, or multimodal, approach, creating models that understand text, video, images and audio. This, said Ingeborn, is because humans don't think in one modality. These kinds of models have many potential use cases and could even help researchers achieve general intelligence. Luma's primary audience right now is the creative industries, such as entertainment, advertising and marketing. Ingeborn said she sees the technology as enhancing the creative experience rather than replacing creative professionals. Topics covered include: Where AI fits into creative workflows The ethical lines of AI in creativity Luma's mission towards generalized physical intelligence Physical AI's potential impact on the labor market The different approaches to building world models The dangers of centralized power in physical AGI If you're following the progress of world models, physical AI and robotics, and the use of AI in creative fields, then this episode offers a deeper look at how these technologies are being used today and the transformative impact they could have in the future. 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

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#52 - Can AI create a golden age of scientific discovery? - Yossi Matias

In this episode of The Deep View Conversations, we sit down with Yossi Matias, head of Google Research, to explore how AI is transforming the way science gets done. Rather than replacing scientists, Google is building AI systems designed to amplify human ingenuity. From searching millions of research papers to generating new hypotheses and accelerating experiments, these tools aim to help researchers move from ideas to discoveries faster than ever before. Yossi explains why he believes we're entering a new era where AI can democratize scientific research, empower the next generation of scientists, and dramatically shorten the path from breakthrough to real-world impact. Topics covered include: How Gemini for Science is changing research workflows What AI Co-Scientist, AlphaEvolve, and the Empirical Research Assistant actually do Why the scientific method is becoming even more important in the AI era How Google is partnering with universities including Stanford and Imperial College Why AI could give every researcher a "virtual lab" in their pocket What a golden age of scientific discovery might look like If you're interested in AI, scientific discovery, biotechnology, or the future of innovation, this conversation offers a look at how one of the world's leading AI research organizations sees the next decade unfolding. 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

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#51 - Why Snap chose a face computer over AI glasses - Evan Spiegel

Snap CEO Evan Spiegel joins The Deep View Conversations to discuss SPECS, Snap's long-awaited augmented reality glasses and why he believes they represent a new era of computing. Senior reporter Sabrina Ortiz interviewed Evan at Augmented World Expo immediately after the SPECS unveiling and Spiegel explained why Snap spent more than a decade building toward this moment, how SPECS differ from AI smart glasses and mixed reality headsets, and why he sees AR glasses as the future beyond smartphones. Other topics covered include: Why Snap calls SPECS a "computer" instead of AI glasses How SPECS combine wearability with advanced spatial computing The role AI played in making consumer AR glasses viable Why shared experiences could become AR's killer app The challenge of competing with Apple, Meta, and other tech giants Snap's 12-year investment in augmented reality hardware and software The importance of developers in building the AR ecosystem Why Spiegel believes people are ready for an alternative to smartphones How AR glasses could make computing more human Spiegel argues that after nearly two decades of smartphone dominance, consumers are increasingly looking for a more natural way to interact with technology. Snap's bet is that augmented reality glasses can bring computing into the world around us instead of pulling us away from it. 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

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#50 - The 3 human skills that will endure in the AI era - Dmitry Shevelenko

Perplexity has become one of the most important AI companies in the world, but its ambitions now stretch far beyond AI-powered search. In this episode of The Deep View Conversations, we sit down with Dmitry Shevelenko, chief business officer at Perplexity, to discuss how the company evolved from an AI answer engine into a platform for AI agents and digital coworkers. Dmitry explains why Perplexity has focused so intensely on accuracy, how AI is changing the nature of work, and why he believes the future belongs to small, highly leveraged teams. The conversation also explores Perplexity Computer, hybrid compute, the coming shift toward AI agents, and what leaders need to do to stay relevant in a world where AI increasingly performs knowledge work. Topics covered: • Why Perplexity made accuracy its defining principle • How Perplexity grew from 20 employees to 400 • The rise of AI agents and digital coworkers • Why Perplexity abandoned advertising as a core strategy • How Perplexity Computer orchestrates multiple AI models • The future of hybrid cloud and local AI computing • Why "tokenmaxxing" may not be sustainable • How AI is reshaping entry-level jobs • Why entrepreneurship may become the new career path • The three skills that will matter most in the AI era • How leaders should think about leverage and productivity • What Perplexity sees coming next in AI If you're trying to understand where AI agents are headed, how work is changing, and why Perplexity has emerged as one of the AI industry's key players, this is a conversation you won't want to miss. Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology. 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

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#49 - Apple fixed Siri, but that's not its biggest AI story - Sabrina Ortiz

At Apple Park, Jason Hiner and Sabrina Ortiz sat down for a special episode of The Deep View Conversations at the end of WWDC 2026 to break down Apple's biggest AI announcements. After two years of delays, promises, and mounting pressure, Apple finally delivered the Siri and Apple Intelligence experience we've been waiting for. But the bigger story may be how Apple is bringing AI to everyday users without forcing them into chatbots, new apps, or complicated workflows. In this conversation, Jason and Sabrina unpack the most important announcements from WWDC, debate Apple's approach to AI, and explore where Apple's strategy differs from OpenAI, Google, Anthropic, and the rest of the industry. Topics covered include: Why Apple's new Siri is a much bigger deal than it looks How 'Personal Context' is Apple's biggest AI advantage Why Apple is betting on features over chatbots The role of privacy, trust, and Private Cloud Compute Why Spatial Reframing is Apple's most innovative AI feature How Apple Intelligence works with Apple's Foundation Models and Google Gemini The AI upgrades coming to Photos, Safari, Messages, Writing Tools, and Mac Why Jason thinks Apple needs a stronger AI agent strategy Why Sabrina believes Apple is right to avoid AI buzzwords What WWDC revealed about the future of AI on iPhone, Mac, Vision Pro, and beyond The biggest wins, misses, and unanswered questions from Apple's AI roadmap If you're trying to understand where AI is actually headed, beyond the hype cycle, this is an episode you won't want to miss. Whether you're an Apple user, an AI enthusiast, a developer, or simply curious about how AI will show up in everyday life, this conversation offers one of the clearest perspectives on Apple's next chapter. 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

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#48 - AI's real question isn't whether AGI arrives - Ahmad Al-Dahle

Ahmad Al-Dahle has been at the center of some of the biggest technology and societal shifts of the past two decades. He helped develop the early iPhone at Apple, spearheaded the open-source Llama models at Meta to help decentralize AI power and influence, and now serves as CTO of Airbnb, where he's using AI to help people spend more time in the real world. In this episode of The Deep View Conversations, we sat down with Ahmad to discuss Airbnb's vision for AI, why he believes AGI is coming, how AI agents are revolutionizing executive workflows, and why technology should ultimately help people spend less time with technology and more time having human experiences. Topics covered include: + Why Ahmad left Apple after over 15 years + How Airbnb is using AI to reimagine travel and drive more meaningful connections + The future of open-source AI and the impact of Llama + Why Ahmad believes AGI is inevitable and what comes next + How AI agents are transforming leadership and productivity + Lessons from working with Steve Jobs, Mark Zuckerberg, and Brian Chesky If you're a leader, AI builder, entrepreneur, investor, or anyone trying to understand where AI is headed beyond the hype, you don't want to miss this episode. Ahmad's insights on AGI, open models, AI agents, and the future of human connection make this one of the most thoughtful discussions we've had on the show. Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology. 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

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#47 - How Google wants to turn prompts into companies - Logan Kilpatrick

Behind the current AI boom is a developer community that both uses and builds powerful tools. Google recently released a wave of new developer-focused AI tools at Google I/O, but one person has gone further: fostering an entire online community. Google's Logan Kilpatrick joined Sabrina Ortiz on The Deep View Conversations podcast straight from Google I/O, not only to share more insights on the new products but also to draw on his rich quilt of experiences to address the broader AI space, the future of software engineering, the developer community and more. While Logan's official role is as a member of technical staff at Google DeepMind, he has become a well-respected voice in the developer community, accumulating over 320K followers on X and constantly engaging with users. Prior to joining Google, Logan worked for NASA, OpenAI, Apple, and other AI startups, making him a builder at his core. Topics covered in this episode: + 'Vibe coding' compared to agentic engineering + The capabilities of Google's new Gemini 3.5 Flash + The internal "flywheel" at Google, where teams use AI to accelerate the development of products + The differences between AI Studio and Project Antigravity + The need for developers to regularly "reset their level of ambition” If you want to understand the distinction between rapid prototyping and managing million-line production codebases with AI, this conversation will leave you much more knowledgeable about the principles of agentic engineering. Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology. 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

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#46 - Why ChatGPT won't stay a chatbot forever - Ian Silber

In this episode of The Deep View Conversations, senior reporter Nat Rubio-Licht sits down with Ian Silber, Head of Product Design at OpenAI, to explore how ChatGPT is evolving for the future. Silber explains why designing for AI requires a different mindset than designing traditional apps. Instead of treating the model as something behind the interface, he says designers now have to think of the model itself as part of the material they work with. That shift changes everything from product decisions and user experience to ethics, safety, and human judgment. The conversation also covers Silber’s experience at Instagram, how that shaped his approach to building fast-growing consumer products, and how OpenAI’s design team is thinking about the next phase of ChatGPT, including more proactive and agentic experiences. Silber also shares how he personally uses AI in his work, from brainstorming design principles to prototyping ideas with Codex. Topics covered: + How OpenAI approaches product design for ChatGPT + Why AI changes the traditional design process + What designers can learn from fast-growing consumer products like Instagram + How ethics, safety, and responsibility show up in AI design + Why human judgment will become more important as AI tools improve + How Codex and image generation are changing prototyping workflows + What young designers should know as they enter the AI era + Why curiosity and adaptability matter in a fast-changing industry If you’re a designer, product leader, builder, technologist, or anyone trying to understand how AI is changing creative work, product development, and human decision-making, you don’t want to miss this episode. Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology. 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

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#45 - Google's new AI glasses: The inside story - Juston Payne

This is a special episode of The Deep View Conversations podcast, recorded at Google I/O on Tuesday, May 19, 2026. AI smart glasses have quietly built momentum over the past several years, promising to put artificial intelligence directly in your line of sight. Now, Google has shown us the final product of its first AI glasses, which appear to have a clear competitive edge. Juston Payne, Google's director of product management for XR, joins The Deep View Conversations straight from Google I/O, where the company pulled the curtain back and gave the world a first look at two of the pairs that will lead the collection when they launch in the fall: a pair from Gentle Monster and one from Warby Parker. Juston discusses how the AI smartglasses came to be, including the collaboration between Samsung, Google, Warby Parker, and Gentle Monster. In addition to discussing details of the new launch, including design, product choices, functionality, the roadmap, and more, Juston also sheds light on the broader AI glasses market and why people should give them a shot. Topics covered: + The thought put into the aesthetics and comfort of smart glasses + What products will be available for users to purchase at launch + How the glasses act as an equivalent of a touchscreen on a phone for interacting with Gemini + The computation offloading strategy that leverages the user’s smartphone + The choice to first launch with an audio-only product rather than in-lens displays + How Google is approaching privacy concerns with the cameras on the glasses + Real-world use cases for AI smart glasses If you want to understand how AI glasses are reshaping the way people connect, this conversation will leave you much more knowledgeable about Google's strategy. Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology. 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

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#44 - How the compute crisis is defining the future of AI - Robert Brooks IV

In this episode of The Deep View Conversations, we sit down with Robert Brooks IV, chief commercial officer at Lambda, to talk about the massive AI infrastructure buildout now underway. Lambda’s mission is to build supercomputers for superintelligence. But Brooks argues that the story is bigger than GPUs, data centers, and rising demand. It is about why compute is becoming one of the most strategically important resources in the AI economy, and why Lambda believes compute is not a commodity. The conversation goes deep on Lambda’s vision for democratizing AI, why the company invests in research, and how its experience building physical infrastructure shapes what it can offer AI labs, hyperscalers, enterprises, and researchers. Topics covered include: + Why Lambda thinks “one GPU per person” is achievable + The hidden complexity behind modern AI data centers + Why compute demand keeps surprising the industry + His $40,000 robot experiment and what it taught him about the future of work + How AI is changing the way leaders spend their time If you want to better understand the physical and economic foundations powering the AI boom, this conversation is worth your time. Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology. 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

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#43 - Android's new AI trades flashiness for smarts - Mindy Brooks

Android’s latest AI update is less about flashy demos and more about solving everyday problems. In this special episode of Deep View Conversations, senior reporter Sabrina Ortiz sits down with Mindy Brooks, VP of Product Management for Google Android, for an exclusive interview on Gemini Intelligence for Android. Brooks explains why Google is focusing its Android AI strategy on saving users small amounts of time across daily tasks. The conversation explores how Android is evolving from an operating system into a more personalized, context-aware "intelligence system" powered by Gemini. Topics covered include: + Rambler for Gboard, Google’s new AI-powered voice dictation system to rival Wispr Flow + The expansion of Task Automation across more apps + How Create My Widget uses AI to generate custom widgets on demand + How Intelligent Autofill is powered by Gemini's Personal Intelligence + The Android AI feature Brooks personally uses the most If you want to understand where mobile AI is headed next, and why Google believes utility matters more than spectacle, this conversation breaks it down. Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology. 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

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#42 - Why the future of AI is hybrid and not cloud - Dr. Olena Zhu

What happens when AI moves from cloud-only to running everywhere, including on your laptop, your phone, and other devices around you? In this episode of Deep View Conversations, senior reporter Sabrina Ortiz sits down with Olena Zhu, who leads AI for the client computing group at Intel, to explore one of the biggest shifts underway in AI: the move toward accessible, affordable, and privacy-first AI systems. Zhu explains why the economics and infrastructure demands of cloud-only AI may not scale indefinitely, and why on-device AI could become a critical part of the industry's future. She also reflects on the evolution from traditional AI systems to LLMs and now to agentic AI, and why this wave feels fundamentally different from the hype cycles that came before it. The conversation also dives into how AI is changing the way people work, learn, and experiment, including the surprising mindset Zhu believes helps people get the most value from AI tools today. Topics covered include: + Why cloud-only AI has limits + The future of on-device and edge AI + AI affordability, energy use, and data sovereignty + How agentic AI changed Zhu’s workflow + Why experimentation matters more than expertise + Intel’s vision for privacy-first AI systems + The hidden infrastructure challenge behind AI growth + Why AI adoption may depend on trust and accessibility If you're concerned about the affordability, accessibility, and privacy of AI, you don't want to miss this episode. Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology. 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

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