Explore every episode of the podcast The Deep View: Conversations

Apple's first foldable iPhone makes the case that a bigger screen is better for nearly everything in the AI era. Its new Apple Watch features raise a harder question: how much of our conversations should AI remember?

In this special episode of The Deep View Conversations, we record from Apple's campus in California following its September 2026 event to unpack the iPhone Duo, the new Audio Intelligence features in Apple Watch, and what Apple's latest devices mean for AI.

We share our first hands-on impressions of the Duo, explain why foldables are becoming more useful for AI agents and multitasking, and examine the price and hardware compromises that come with Apple's new form factor. We also debate Live Rewind and Siri Recap, two new Apple Watch features coming in beta later this year. We disagree on which feature we would feel more comfortable using, opening up a broader discussion about privacy, trust, and staying present.

The conversation also covers:

• How the iPhone Duo compares with foldables from Google and Samsung

• Why Apple's software experience is the Duo's biggest advantage

• Camera, battery, durability, and Touch ID tradeoffs

• Whether foldables will eventually become the default iPhone

• Siri AI, iOS 27, and Apple's approach to other smart features without AI washing

• The social questions surrounding AI-generated conversation summaries

• The iPhone 18 Pro's camera upgrades and Apple's computational photography

• Apple silicon, the A20 Pro, and the possibilities of running AI models locally on a phone

If you're following the future of AI in phones and wearables, this conversation connects Apple's announcements to the ways people will actually use them, along with the questions that still need answers.

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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

AI is transitioning from just answering questions to doing valuable work. The next challenge is making agents more accessible and simple enough that the technical details fade into the background.

In this episode of The Deep View Conversations, we sit down with two members of OpenAI's ChatGPT Work team, Tara Seshan and Ty Geri, to dig into ChatGPT Work and what OpenAI is doing to make advanced agent capabilities useful to a lot more people. We also dig into some of the current challenges and how the team is approaching them. 

Seshan and Geri explain how scheduled tasks and proactive assistance are changing the way people start their workdays, why AI lets teams move from debating ideas to testing prototypes, and how personalized software can turn one-off needs into purpose-built tools. They also discuss the challenge of token costs and model selection, why "super app" isn't the most useful framing for ChatGPT and Codex, and what it will take for agents to become more persistent, proactive, and connected.

The conversation also covers:
• How OpenAI is trying to bridge local and cloud workflows
• Why Tara and Ty start their days with agents instead of Slack
• Building personal apps and tools without traditional software overhead
• The tradeoff between model capability, cost, and user control
• More persistent agents and proactive personal assistance
• Connecting agents to email, calendars, enterprise systems and third-party tools
• Privacy, security and administrative controls for agentic work

If you’re figuring out where agents fit into your work or what has to improve before you trust them with more of it, then this conversation offers a practical look at how OpenAI is preparing for that transition.

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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

AI makes software easier to create, but the harder and more valuable challenge is controlling what gets built, proving that it works, and managing it over time.

In this episode of The Deep View Conversations, we sit down with Florian Douetteau, CEO and co-founder of Dataiku, to explore how large organizations can turn AI agents from impressive demos into safe, maintainable systems that deliver measurable business results.

Douetteau explains why enterprise AI models are becoming commoditized, why companies may buy 90% of their agents but build the 10% that differentiates their business, and why the emerging discipline of "agent management" will be essential. He also breaks down the dilemma facing CEOs: move too slowly and competitors may gain a structural cost advantage; move too quickly without control and one major AI failure could create a crisis.

Topics covered:

• Why the cost of creating with AI is falling toward zero
• Where value will accrue as models commoditize
• How to balance openness, innovation and enterprise control
• Why subject-matter experts must retain ownership of AI agents
• Why business problems, not perfect data, should drive data strategy
• How enterprises can prioritize transformative AI use cases without stifling experimentation
• The three qualities Dataiku now values most when hiring
• How leaders can use AI without falling into cognitive laziness

If you’re trying to move enterprise AI beyond pilots, govern a growing portfolio of agents or understand where durable value will emerge as AI creation becomes cheaper, this conversation offers a practical framework for building quickly without losing control.

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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

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.

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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

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

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. 

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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

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 

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.

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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

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.

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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

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

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

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

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. 

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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

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

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

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

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

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

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

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 

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 

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

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

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

In this episode of The Deep View Conversations, we sit down with Alex Rinke, co-founder and co-CEO of Celonis, to unpack one of the most overlooked truths in enterprise AI.

Rinke and his co-founders started Celonis 15 years ago in Munich with just $15,000. What followed was a grind, including thousands of handwritten letters to land early customers, and a steady evolution from process simulation to what is now known as process intelligence.

Today, Celonis works with roughly half of the world’s 200 largest companies. Its platform acts like an MRI for the enterprise, creating a digital twin of how work actually happens across fragmented systems.

Rinke’s core argument is simple and provocative: there is no enterprise AI without process intelligence. Companies that deploy agents without understanding their underlying processes risk automating inefficiency at scale.

We also cover:

+ How Celonis re-engineered itself for the AI era

+ What the co-CEO model works like in practice and why it can be a competitive advantage

+ How hiring is changing inside AI-native companies

+ The tools Rinke uses to run his own workflow

If you want to understand where AI actually delivers results inside large organizations, don't sleep on this conversation.

Watch now and subscribe for more conversations at the frontier of AI.

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 

Analysts, marketers, and business owners face the same question: How do you reach audiences in an era when AI is reshaping how people search and find information they need? That’s a top-of-mind issue for Pat Brown, SVP of global marketing, growth, analytics, and platform at Adobe.

Brown joins The Deep View Conversations to share his unique perspective on the issue, with the expertise of someone who was doing marketing science before it was even called that, and who, in his current role, is responsible for global marketing execution across various forms of media and has to put these skills into practice every day.

Pat breaks down how AI is moving beyond content generation to reshape media workflows end-to-end, from audience measurement to agents that automate entire processes.

Topics covered:

+ The role of AI agents in automating marketing workflows

+ How AI in marketing can augment rather than replace creativity

+ AI-powered marketing tools that help analyze patterns and signals

+ Whether AI has “killed” SEO and what that means for marketers’ jobs

+ The rise of new terms like AEO and GEO in a “zero-click” search world

+ Why it’s still worth investing in marketing and brand strategy despite AI changes

+ Why today’s AI-driven SEO landscape feels like the early days of SEO

If you want to understand how AI is reshaping and helping individuals connect more effectively with audiences, this conversation will leave you feeling more knowledgeable about those topics.

Subscribe for weekly conversations with the leaders shaping the future of AI.

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

In this episode of Deep View Conversations, we sit down with Dave Horton, VP of Solutions Engineering at Airia, to explore one of the biggest tensions in enterprise AI today: how to move fast without losing control.

Airia is building a platform designed to plug AI into every corner of an organization while keeping data secure and systems governed. Dave breaks down why that balance is harder than it looks, and why many companies are underestimating the complexity of deploying AI agents at scale.

We also dig into the surge of interest in agentic AI in 2026, including a contrarian perspective on OpenClaw and the idea that agents will quickly replace human work. Dave argues that the real challenge is not capability, but coordination, and that success comes down to three pillars: security, governance, and orchestration.

Beyond the tech, Dave shares his journey building alongside the Airia founders, why funding is pouring into AI startups, and how the AI ecosystem is evolving across London, the UK, and Europe. He also reveals the AI tool that has most transformed the way he works.

If you want a grounded, real-world view of where enterprise AI is headed, and what it will actually take to make it work, this conversation delivers.

Watch, listen, and subscribe for more conversations at the frontier of AI.

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

What happens when AI agents outnumber humans in the enterprise? 

In this episode of The Deep View Conversations, Senior Reporter Sabrina Ortiz sits down with Jeetu Patel, President and Chief Product Officer at Cisco, to explore how the rise of AI agents is reshaping cybersecurity, software development, and enterprise strategy. 

Jeetu makes a bold prediction: today’s 150 million developers could expand to 3 billion agent builders within the next year. But that explosion comes with serious risk. As nation-states and bad actors deploy autonomous agents at scale, traditional, human-centered security models begin to break down. 

This conversation unpacks:
+ Why AI agents are becoming the new attack surface
+ What enterprises must do now to prepare for agent-driven threats
+ Jeetu’s journey from Box to Cisco, and what it taught him about leading through platform shifts
+ Practical advice for learning AI and building in an agent-first world 

But this isn't a doom-and-gloom conversation. Jeetu lays out a vision for how security can become an accelerator rather than a limiter, and why the distinction between giving agents access and giving them trusted, governed access will define which enterprises thrive in the agentic era. 

If AI agents are the next platform shift, cybersecurity may be the defining battleground. 

Watch the full conversation and subscribe for more interviews with the leaders shaping the future of AI. 

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 

What happens when a startup's mission perfectly aligns with the biggest trend in tech? That's exactly where Guild AI finds itself in 2026. 

James Everingham, CEO of Guild AI, joins The Deep View Conversations to talk about building a safety layer for AI agents. The product launched in fall 2025 and found itself at the center of the most important movement in enterprise AI just months later. 

In this conversation, James breaks down how Guild's platform deploys dozens of workflow-specific agents across different parts of a business, while giving developers the tools to iterate, spin up custom agents, and operate in a safe environment that tracks everything agents do and protects companies from unpredictable outcomes. 

Topics covered:
+ The enduring power of bottom-up innovation

+ How Guild AI's agent supervision platform works

+ Why safety infrastructure is the new competitive moat

+ Lessons from James' earlier career at Netscape and Meta

+ Open-source vs. proprietary models: how it plays out over the next few years

+ A standout leadership tip for sparking innovation on your team 

+ His best advice for getting maximum impact from today's AI tools. 

If you want to understand where AI agents are headed and what it takes to build them responsibly, this conversation is a powerful place to start. 

Subscribe for weekly conversations with the leaders shaping the future of AI. 

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 

Snowflake has been a stalwart of the SaaS economy and a leader in enterprise data for the past decade. But the company is deep in the middle of a transformation that most people haven't recognized yet.

In this episode of The Deep View Conversations, senior reporter Nat Rubio-Licht talks with Baris Gultekin, vice president of AI at Snowflake, for a candid look at how the company is navigating the AI era and what it's learning in real time.

Gultekin talks openly about how the entire team inside Snowflake is now using coding tools to build skills and automate their work. That includes non-developers who are using Project SnowWork, an AI agent for professionals across all roles.

Baris joined Snowflake in 2023 through the acquisition of blockchain startup nxyz and has spent the past three years building and running the AI teams inside the enterprise tech giant. He also brings a rare perspective from his time working on Google Assistant in the pre-LLM era, which gives him a unique lens on how much has changed.

Topics covered:

+ Why there is no AI strategy without a data strategy, and what enterprises keep getting wrong

+ How agentic AI has shifted enterprise data from question-answering to automation

+ The SaaSpocalypse and why Snowflake sees AI as a tailwind rather than a threat

+ Cortex Code (CoCo), Snowflake's coding agent that lets customers query their data in plain language instead of SQL

+ The governance and security challenges that come with multi-agent systems

+ How Baris uses coding agents in his own life

If you want to understand how a mature SaaS company reinvents itself inside an AI revolution, this one is worth your time.

Subscribe to the podcast for more conversations with the leaders, builders, and researchers shaping the future of AI.

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

Stefan Weitz thinks AI should not just make companies faster. It should make every individual inside them dramatically more capable.

In this episode of The Deep View: Conversations, the HumanX CEO explains how he’s putting that idea into practice, starting with his own team.

HumanX calls itself the most important AI conference of the year, but what makes it stand out is how intentionally it’s being built. Stefan and his team are rethinking the entire event experience for 2026, using AI to create a more personalized journey for every attendee, from curated sessions to smarter networking and discovery.

In this episode, we talk about:

+ Building a new kind of conference in the AI era
+ Using vibe coding for rapid prototyping
+ Management principles for the AI era
+ Turning every worker into a 10x employee
+ The AI tool that’s blowing Stefan’s mind

But this conversation goes beyond events. It’s really about leadership in the age of AI.

Along the way, Stefan offers a clear view of what it takes to build an organization that can actually apply AI, not just talk about it. He also shares a leadership principle that has shaped his approach.

If you’re thinking about how to scale impact across your team, or how to move from AI curiosity to real execution, this conversation delivers practical insights you can use right away.

Subscribe to the podcast for more conversations with the leaders, builders, and researchers shaping the future of AI.

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

In this episode of The Deep View: Conversations, we talk with Olivia Moore, partner at Andreessen Horowitz (a16z), one of Silicon Valley’s flagship venture capital firms. At a16z, Olivia focuses on the rapidly evolving world of consumer AI apps. She tracks which tools are gaining traction, which ones are breaking out beyond early adopters, and which products are unlocking entirely new capabilities for everyday users.

In this conversation, we explore the key trends shaping the next wave of AI apps, including the rise of personal AI agents, the growing importance of context and memory in AI systems, and the way new tools are changing how people build, create, and work.

We cover:

+ a16z’s Top 100 Gen AI Consumer Apps report and what it reveals

+ The rise of OpenClaw and personal AI agents in 2026

+ Olivia’s current AI stack and how she uses her favorite tools

+ Why context and memory could define the next stage of AI

+ Global trends shaping the AI app ecosystem
+ The acceleration of coding agents

Few people have their finger on the pulse of the AI app ecosystem like Olivia. If you want to understand which AI tools are gaining momentum and where the next breakthroughs may come from, this conversation offers a valuable window into the space. 

There’s a great chance you’ll come away from this episode with at least one tool or idea that changes the way you work.

Subscribe to the podcast for more conversations with the leaders, builders, and researchers shaping the future of AI.

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 that keep our audience ahead of the curve and help them put AI to work every day: subscribe.thedeepview.com

In a labor market being rewired by AI, CodeSignal is betting that skills, not resumes, will decide who thrives.

For this episode of The Deep View: Conversations, I talked with Tigran Sloyan, CEO and co-founder of CodeSignal, the company building a new standard for hiring and career mobility in the age of AI.

CodeSignal’s mission starts with a simple but painful truth: resumes and interviews are a flawed way to hire talent. Countless candidates have the skills to thrive in high-paying tech roles but never get a fair shot, while others with polished credentials sometimes land jobs they’re not prepared to do. 

CodeSignal is flipping that equation with skills-based assessments that help employers discover candidates with real ability, and a free learning platform that helps candidates level up for the next opportunity.

In my conversation with Tigran, we talked about:

+ Why resumes haven’t meaningfully changed in 100 years, and why it's breaking hiring

+ How CodeSignal measures skills, and why simulation beats multiple-choice

+ What AI unlocks for assessing non-technical roles such as sales and support

+ The dark side of AI: what CodeSignal’s research shows about cheating attempts

+ Why entry-level jobs are turning into tasks, and what that means for training

+ How CodeSignal makes free learning content work economically

+ The future of re-skilling at scale, and why AI tutoring changes everything

We also dig into what’s changing fast right now: the rise of AI-assisted work, the surge in fraud in hiring assessments, and why foundational skills still matter even when AI can do the task.

Tigran shares his background from Armenia to MIT to Google, his most contrarian leadership advice, and the AI tool he'd recommend you start using every day. If you want to understand how AI is being used to fix the problems that AI is causing in the job market, this is the podcast for you.

Subscribe to The Deep View: Conversations podcast in your favorite podcast player for more unique conversations with the brightest minds solving the biggest challenges in AI. You can also subscribe on YouTube.

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 that keep our audience ahead of the curve and help them put AI to work every day: subscribe.thedeepview.com

In this episode of The Deep View Conversations, we talked with Wasim Khaled, CEO of Blackbird AI, to explore a provocative idea: What happens when reality itself becomes hackable?

Long before generative AI went mainstream, Wasim and his cofounder launched Blackbird to tackle disinformation and narrative manipulation. Their thesis was bold: that part of modern cybersecurity conflict had shifted from infrastructure to information, from networks to narratives.

It turned out to be prescient.

As AI supercharges the speed, scale, and realism of malicious content — from deepfakes to coordinated influence campaigns — Blackbird has emerged as the leader in combating narrative attacks. In fact, Gartner recently named Blackbird the company to beat in disinformation narrative intelligence in its report on the AI Vendor Race.

In our conversation, we explore:

+ What “narrative attacks” really are and why they’re so hard to detect

+ How AI has fundamentally changed the disinformation battlefield

+ Reactive vs. proactive defense strategies in cybersecurity

+ How Blackbird evolved from a lab experiment into a national security player

+ Why leaders relying on chatbots instead of AI agents are already falling behind

Wasim also shares how he optimizes his time for maximum leverage, and offers his advice for founders navigating fast-moving technology shifts.

If you care about cybersecurity, AI, information warfare, or the future of leadership in the age of intelligent agents, this is a conversation you'll want to hear.

Subscribe to The Deep View: Conversations podcast in your favorite podcast player for more unique conversations with the brightest minds solving the biggest challenges in AI. You can also subscribe on YouTube.

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 that keep our audience ahead of the curve and help them put AI to work every day: subscribe.thedeepview.com

What does it actually take for enterprises to adopt AI at scale? 

In this episode of Deep View Conversations, we sit down with Shibani Ahuja, Senior Vice President of Enterprise IT Strategy at Salesforce. Over the past year, Shibani has met with 587 C-suite leaders to understand how Salesforce can evolve into an agentic AI platform for the world’s largest organizations. 

We unpack what she’s learned from those conversations, including the real blockers to AI adoption, how leading enterprises are progressing, and why shared context and trust matter more than raw model capabilities. 

Shibani also breaks down Salesforce’s Agentic Maturity Model, a framework designed to help organizations assess their current AI readiness and chart a path forward. 

We also explore:

+ How AI is reshaping the banking and financial services industry, where Shibani spent a good part of her career
+ The story of how Shibani joined Salesforce after challenging Marc Benioff and his leadership team as a customer
+ Why clear, jargon-free communication is one of the most underrated skills in AI, and how to do it well in high-stakes settings 

Shibani is one of the most cogent communicators in tech today, and this conversation is packed with practical insights for anyone leading, building, or communicating about AI inside an organization or in public settings. 

Subscribe to The Deep View: Conversations podcast in your favorite podcast player for more unique conversations with the brightest minds solving the biggest challenges in AI. You can also subscribe on YouTube. 

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 that keep our audience ahead of the curve and help them put AI to work every day: subscribe.thedeepview.com

AI agents in business aren't something that will happen in the future. They’re already here, and they're scaling a lot more rapidly than we expected.

In this episode of The Deep View: Conversations, Editor-in-Chief Jason Hiner talks to Matt Yanchyshyn, who leads AWS Marketplace at Amazon Web Services. Yanchyshyn's team helps organizations discover, buy, and deploy software on AWS, and one of the biggest shifts they’ve seen over the past six months is the explosion of AI agents in real-world use cases.

When AWS unveiled its agent marketplace in mid-2025, the internal goal was initially to launch with 50 agents. By early 2026, that number had surged past 2,600 agents, making it the fastest-growing category in the history of the world’s largest cloud platform.

So what’s driving that surge? Yanchyshyn breaks it down.

In this conversation, we cover:
+ Which types of AI agents are seeing the fastest enterprise adoption
+ The industries and use cases leading the charge
+ How companies are handling data security and sovereignty concerns
+ The role of multi-model orchestration in agent effectiveness
+ How AWS is using agents internally to drive lots of different wins

If you're trying to understand where AI agents are actually being deployed — not the hype, but the reality — then this conversation will reset your expectations. It will help you see where agentic AI is already delivering business value, and where it’s heading next.

Subscribe to The Deep View: Conversations in your favorite podcast player for more unique conversations with the brightest minds solving the biggest challenges in AI. You can also subscribe here on YouTube.

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 that keep our audience ahead of the curve and help them put AI to work every day: subscribe.thedeepview.com

Thank you to our sponsor, Deel, an AI-native platform for HR, IT, and payroll. Hire, manage, pay, and equip anyone, anywhere. https://www.deel.com/deepview

AI could change the way we remember, and the way we pay attention. 

In this episode of The Deep View: Conversations, Editor-in-Chief Jason Hiner sits down with Bobak Tavangar, CEO of Brilliant Labs, one of the most intriguing startups in AI hardware today. 

While trillion-dollar giants like Meta and Google race to define the future of AI glasses, Brilliant Labs is taking a radically different path: building in public, going open-source with both software and hardware, and centering their next product, the Halo glasses, around something deeply human. 

The focus? A conversational AI agent for your long-term memories and conversations. 

This isn’t just about smarter wearables. It’s about a bigger idea: 

+ Can AI help us be more present, not less? 
+ Could technology support memory, reflection, and intention instead of distraction? 
+ What does privacy look like when AI can recall your life? 

Jason and Bobak also explore: 

+ What he learned during his time at Apple 
+ Why AI hardware is one of the hardest frontiers in tech 
+ The challenging process of finding a co-founder 
+ Bobak’s philosophy on communicating on social media with purpose, not hype 

Bobak is one of the most thoughtful founders in the AI space, consistently elevating the conversation beyond features and into questions of values, agency, and human experience. 

If you care about where AI, wearables, memory, and attention intersect, this is a conversation you don’t want to miss. 

Subscribe to the podcast for more unique conversations with the brightest minds solving the biggest challenges in AI. 

And don't miss 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 that keep our audience ahead of the curve and help them put AI to work every day: https://subscribe.thedeepview.com/ 

How do you make AI inference affordable enough to deliver real ROI in the enterprise? 

In this episode of The Deep View Conversations, we talk with Rob May, founder and CEO of Neurometric AI, to break down one of the most urgent challenges in AI today: the soaring cost of inference, and how to bring it down without sacrificing performance. 

Today's AI is increasingly powerful, but it’s also expensive. For enterprises to see real returns, inference costs have to drop dramatically. Neurometric believes the answer lies in "thinking algorithms" paired with small, specialized models and workload-specific optimization. This approach can significantly reduce costs while often improving accuracy and efficiency. Rob walks through how this works in practice and why it matters as AI moves from experimentation to scaled deployment. 

We also talk about:
+ Why the current AI boom pulled Rob back into operating a startup after multiple exits and a move into investing 
+ How founders should think about AI infrastructure, efficiency, and long-term economics 
+ What startup leaders can do to get journalists to pay attention — and a pivotal early-career conversation that led to coverage which changed the trajectory of one of Rob’s companies 

If you’re building, deploying, or investing in AI and wrestling with the economics of inference, this conversation offers a clear, practical perspective on what comes next. 

Thank you to our sponsor, Deel, an AI-native platform for HR, IT, and payroll. Hire, manage, pay, and equip anyone, anywhere. https://www.deel.com/deepview 

Subscribe to the podcast for more unique conversations with the brightest minds solving the biggest challenges in AI. 

And don't miss 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 that keep our audience ahead of the curve and help them put AI to work every day: https://subscribe.thedeepview.com/ 

In this episode of The Deep View Conversations, we sit down with Merrill Lutsky, cofounder and CEO of Graphite — a company using artificial intelligence to transform how engineers write, review, and ship code.

What started as an internal tool to streamline software deployment has grown into something larger: a vision for how AI can augment, not replace, the craft of engineering — and reshape how teams collaborate at scale.

Merrill walks us through Graphite’s early pivots, the development of its AI reviewer Diamond, and how the company is rethinking the bottleneck that stands between building and shipping code.

We also go beyond the product to explore deeper questions:
Will coding become fully automated?
How do we balance speed and safety in an era of AI-written software?
And what does craftsmanship mean when machines start to create?

In this episode of The Deep View Conversations, we sit down with Patrick Leung, CTO of Faro Health — a startup using artificial intelligence to streamline and reimagine clinical trials. What began as a push to speed up drug development turned into something bigger: a mission to reduce suffering, elevate consciousness, and reshape how we think about AI’s role in health and society.

Patrick walks us through the challenges of clinical trial design, the limits of large language models, and how thoughtful AI implementation could unlock faster, safer, and more inclusive access to medicine.

We also go beyond tech to explore deep questions: Is AI truly intelligent? How do we balance speed and safety? And are we building tools — or something closer to gods?

In this episode of The Deep View Conversations, we sit down with Russ d'Sa, founder and CEO of LiveKit — the open-source infrastructure powering voice mode for OpenAI, Character.AI, and a fast-emerging voice-first internet.

Russ walks us through how a pandemic side project evolved into the nervous system for the next generation of AI-powered voice applications. But this episode goes far beyond infrastructure. We dive into big, human questions: What does it mean to interact naturally with AI? Are we moving back toward voice as the dominant interface? How will AI reshape work, leisure, and even our sense of identity?

From the democratization of high-tech tools to the societal shifts driven by intelligent systems, this is a wide-ranging and deeply thoughtful conversation on what comes next in the age of synthetic intelligence.

Boost your CRM with Salesforce – tdv.co/sf

In this episode of The Deep View Conversations, we explore the world of machine translation and artificial intelligence with Olga Beregovaya — Smartling’s VP of Machine Translation and Artificial Intelligence. Olga takes us through the evolution of machine translation, from rule-based systems to statistical models to today’s neural networks and large language models.

She sheds light on how translation has shifted from being a purely linguistic endeavor to one that now sits at the intersection of data science, AI, and human creativity. We dive into hallucinations, under-resourced languages, the rise of synthetic data, and what it truly means to maintain quality in a multilingual world. If you've ever wondered what makes AI translation tick — and where it's going — this is the episode for you.

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Artificial intelligence is a complicated topic, bound by a number of complex threads — technical science, ethics, safety, regulation, neuroscience, psychology, philosophy, investment and — above all — humanity. On The Deep View: Conversations we break it all down, cutting through the hype to make clear what's important and why you should care.

In this episode of The Deep View Conversations, we dive into the chaotic world of social media, misinformation, and the growing need for scientific credibility with Brinleigh Murphy Reuter — founder of the Harvard-incubated nonprofit, Science to People. Brinleigh unpacks why it’s become so hard to find accurate health and science information online, and how her organization is using generative AI to fix the broken flow of facts between researchers, influencers, and everyday users.

We explore everything from the overwhelming noise of algorithm-driven content and the dangers of viral misinformation, to how AI can empower creators with reliable, vetted science. If you’re curious about how tech, trust, and truth collide in the age of TikTok and ChatGPT, this is an episode you won’t want to miss.

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Artificial intelligence is a complicated topic, bound by a number of complex threads — technical science, ethics, safety, regulation, neuroscience, psychology, philosophy, investment and — above all — humanity. On The Deep View: Conversations we break it all down, cutting through the hype to make clear what's important and why you should care.

In this episode of The Deep View Conversations, we dive into the complex intersection of artificial intelligence and healthcare with Pelu Tran, co-founder and CEO of Ferrum Health. Pelu shares his deeply personal motivation behind founding Ferrum, why AI adoption in healthcare is slow, and how Ferrum aims to solve the “last mile” problem of bringing AI into clinical practice.

We explore everything from trust in algorithms, systemic challenges, and outdated infrastructure to the ethical implications of AI in medicine and the risk of over-efficiency. If you’re curious about the real-world application of AI in hospitals and how to bridge the gap between innovation and implementation, this is a must-listen.

Outline: 

00:00 – Intro: AI and healthcare — promise vs. reality
01:00 – Meet Pelu Tran, CEO of Ferrum Health
03:10 – A personal tragedy leads to a mission: Ferrum’s origin
07:00 – The real reason AI adoption is slow in hospitals
10:00 – Infrastructure, security & why hospitals still use fax machines
13:30 – What Ferrum Health actually does
16:10 – Why FDA clearance isn’t enough for AI trust
19:00 – Ferrum’s approach: Validating models with AI itself
22:30 – AI performance drift & automated monitoring
25:00 – Diagnostic tools, LLMs, and AI's current limitations
28:40 – The illusion of language fluency and AI “hallucinations”
31:00 – Burnout, administrative burden & where AI helps
34:30 – Will AI speed things up or make hospitals worse?
38:00 – Hospital incentives & risks of productivity pressure
41:10 – AI replacing admin, not doctors (yet)
44:10 – Communicating AI performance to clinicians
47:30 – Measuring outcomes, not just accuracy
50:00 – Trust, governance, and safe deployment
53:15 – Why flexibility is key for AI in healthcare
56:00 – The future: Safe disruption vs. blind disruption
59:00 – Will AI replace doctors? Why not anytime soon
1:01:00 – Final thoughts: AI’s promise and pitfalls 

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Artificial intelligence is a complicated topic, bound by a number of complex threads — technical science, ethics, safety, regulation, neuroscience, psychology, philosophy, investment and — above all — humanity. On The Deep View: Conversations we break it all down, cutting through the hype to make clear what's important and why you should care.

In this gripping episode, we dive into the life-saving mission behind ZeroEyes, a pioneering company using artificial intelligence to detect visible weapons before shots are fired. The Deep View Team sits down with co-founder and Chief Revenue Officer Sam Alaimo, a former Navy SEAL, to explore how a tragic school shooting and military discipline inspired a groundbreaking solution to one of America’s most pressing issues: gun violence.

I sat down with Dr. Aaron Andalman, the Chief Science Officer and co-founder of Cognitiv. Andalman holds a PhD in neuroscience, and so today, we’re breaking down the gaps, connections and inspirations between AI and neuroscience; all the things we’ve learned and the many things we still don’t know. 

Episode links: 

• The giant squid: https://medium.com/the-quantastic-journal/from-squids-to-ai-how-neuroscience-and-physics-sparked-a-technological-revolution-06d8c291717c
• Neuroscience and AI: https://neuroscience.stanford.edu/news/neuroscience-and-ai-what-artificial-intelligence-teaches-us-about-brain-and-vice-versa
• The specter of AGI: https://www.thedeepview.co/p/how-big-tech-is-using-the-ai-race-and-the-specter-of-agi-to-cement-its-power-agi-openai-google
• Scale it up: https://www.thedeepview.co/p/progress-predictions-2025-robots-avs-and-technical-advancements
• Animal intelligence: https://www.discovermagazine.com/planet-earth/how-intelligence-is-measured-in-the-animal-kingdom

Outline

0:00 – Intro

1:45 – The roots of AI 
7:12 – The different types of intelligence

12:05 – Neural networks VS artificial neural networks

19:19 – Efficiency in intelligence

23:51 – Why pursue AGI at all? 
28:44 – Reinforcement learning in machines VS animals

35:25 – Advancements in one, advancements in the other

43:46 – Being curious in the age of AI 

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Artificial intelligence is a complicated topic, bound by a number of complex threads — technical science, ethics, safety, regulation, neuroscience, psychology, philosophy, investment and — above all — humanity. On The Deep View: Conversations, Ian Krietzberg, host and Editor-in-Chief at The Deep View, breaks it all down, cutting through the hype to make clear what's important and why you should care.

I sat down with Brad Zamft, the co-founder and CEO of Heritable Agriculture, to take a deep dive into all the science (both biology and computer science) behind the effort to program plants, why it’s needed and what impacts it might have. 

Episode links: 

• Heritable Agriculture: https://heritable.ag/
• Heritable goes after indoor strawberries: https://heritable.ag/heritable-strawberries 
• The sustainability threat of farming: https://vlsci.com/blog/top-issues-in-agriculture-2024/ ; https://www.epa.gov/climateimpacts/climate-change-impacts-agriculture-and-food-supply
• The risks of monoculture and monocropping: https://foodrevolution.org/blog/monocropping-monoculture/
• The promise of regenerative agriculture: https://theclimatecenter.org/our-work/research/report-the-promise-of-regenerative-agriculture/
• Farming resiliency in the face of climate change: https://sustainability.mit.edu/article/making-agriculture-more-resilient-climate-change

Outline

0:00 – Intro

2:18 – Brad’s journey to Heritable Agriculture

9:29 – Why we need programmable plants

14:23 – Challenges of biology

19:38 – Validating the models

22:14 – How does this all physically work? 

31:05 – The challenge of adjusting 2 billion years of evolutionary success

34:48 – The risks of AI cracking plant DNA

39:50 – Regenerative Agriculture and tuning for resiliency in the face of climate change

47:53 – How farmers view the approach

51:59 – Tree adjustments

56:28 – The future outlook

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Artificial intelligence is a complicated topic, bound by a number of complex threads — technical science, ethics, safety, regulation, neuroscience, psychology, philosophy, investment and — above all — humanity. On The Deep View: Conversations, Ian Krietzberg, host and Editor-in-Chief at The Deep View, breaks it all down, cutting through the hype to make clear what's important and why you should care.

I sat down with Dr. Nada Sanders, a distinguished professor of supply chain management at Northeastern University, to better understand the impact that tariffs and a trade war could have on the business and field of AI. 

Episode Links: 

• The semiconductor pipeline: https://datacenterpost.com/ais-hardware-hunger-the-global-semiconductor-supply-chain-under-pressure/
• The latest on the tariffs and trade war: https://www.bbc.com/news/articles/c62z54gwd22o
• Nvidia’s US push: https://www.thedeepview.co/p/nvidia-to-produce-500-billion-worth-of-supercomputers-in-the-u-s-for-the-first-time
• Apple’s US push: https://www.apple.com/newsroom/2025/02/apple-will-spend-more-than-500-billion-usd-in-the-us-over-the-next-four-years/

Outline: 
0:00 – Intro 
4:09 – The vulnerability of the AI supply chain
19:13 – Is it realistic to bring production back to the US? 
27:31 – Innovation could plateau 
34:04 – The challenge of navigating uncertainty, even if the tariffs come off

Get The Deep View — your daily source for in-depth, fact-based reporting on artificial intelligence — in your inbox every morning. Subscribe here! (https://www.thedeepview.co/subscribe)

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Artificial intelligence is a complicated topic, bound by a number of complex threads — technical science, ethics, safety, regulation, neuroscience, psychology, philosophy, investment and — above all — humanity. On The Deep View: Conversations, Ian Krietzberg, host and Editor-in-Chief at The Deep View, breaks it all down, cutting through the hype to make clear what's important and why you should care.

I sat down with Dr. Eric Sydell, the founder and CEO of Vero AI, to break down the challenges of oversight, governance and compliance — and the techno-utopia on the horizon — and the ways in which AI can help, hurt, and generally, disrupt everything. 

Episode links: 

• Ethan Molick: https://www.linkedin.com/posts/emollick_if-ai-development-stopped-this-week-we-would-activity-7272747981752176640-nTKX/
• What even is AI: https://www.ibm.com/think/topics/artificial-intelligence
• Sam Altman says we must regulate AI: https://www.thedeepview.co/p/paris-ai-summit-the-smoke-and-mirrors-of-governance
• EU AI Act: https://www.europarl.europa.eu/topics/en/article/20230601STO93804/eu-ai-act-first-regulation-on-artificial-intelligence
• Challenge of AI regulation: https://www.thedeepview.co/p/report-the-misguided-race-to-regulation
• Nurses and AI: https://www.thedeepview.co/p/current-harms-and-the-real-world-impacts-of-algorithmic-decision-making
• Preslav Nakov fact-checking LLMs: https://aclanthology.org/2024.findings-acl.558/

Outline

0:00 – Intro

2:28 – AI for compliance
4:43 – Overcoming reliability problems

10:16 – Toys VS tools
15:54 – Keeping up with the rate of ‘progress’

22:03 – The challenge of regulation: 

28:55 – Balancing AI with the bottom line

34:38 – The problem with ‘Abundance’

43:11 – How to get the good without all the bad

51:17 – Running to and running from technology

55:02 – Looking for optimism

Get The Deep View — your daily source for in-depth, fact-based reporting on artificial intelligence — in your inbox every morning. Subscribe here! (https://www.thedeepview.co/subscribe)

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Artificial intelligence is a complicated topic, bound by a number of complex threads — technical science, ethics, safety, regulation, neuroscience, psychology, philosophy, investment and — above all — humanity. On The Deep View: Conversations, Ian Krietzberg, host and Editor-in-Chief at The Deep View, breaks it all down, cutting through the hype to make clear what's important and why you should care.

I sat down with Dr. Stefan Leichenauer, SandboxAQ's VP of Engineering, to break down the ways in which he’s bringing the two technologies together. 

Check out our breakdown of quantum computing: https://youtu.be/-umrjwGFTRw

Episode links: 

• Quantum sensing: https://www.baesystems.com/en-us/definition/what-is-quantum-sensing
• Sandbox LQMs: https://www.sandboxaq.com/
• Quantum computers: https://www.ibm.com/think/topics/quantum-computing
• Sandbox drug discovery: https://www.sandboxaq.com/solutions/aqbiosim
• Sandbox materials generation: https://www.sandboxaq.com/post/building-better-batteries-with-lqms

Outline

0:00 – Intro

1:36 – How does Sandbox leverage Quantum?

4:35 – What makes a sensor a Quantum sensor? 
8:00 – What would a Quantum computer need to do to be ready for use? 

11:30 – What reliable Quantum computers mean for Sandbox and AI 
15:18 – Sandbox’s Large Quantitative Models 

27:52 – Specialist systems VS generalist systems
35:41 – Black Boxes and LQMS 

37:45 – LQMs and hallucination
41:50 – LQMs and drug discovery
50:00 – The cost associated with LQMs

53:37 – LQMs and materials generation
56:55 – Future outlook  

Get The Deep View — your daily source for in-depth, fact-based reporting on artificial intelligence — in your inbox every morning. Subscribe here! (https://www.thedeepview.co/subscribe)

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Artificial intelligence is a complicated topic, bound by a number of complex threads — technical science, ethics, safety, regulation, neuroscience, psychology, philosophy, investment and — above all — humanity. On The Deep View: Conversations, Ian Krietzberg, host and Editor-in-Chief at The Deep View, breaks it all down, cutting through the hype to make clear what's important and why you should care.