The Deep View: Conversations

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. 

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 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