If you’re like me, you can love technology and still worry about what it’s doing to us.

If that tension feels familiar, this episode is for you.

Today’s guest is Glen Slater, a Jungian psychologist and the author of Jung vs. Borg (as in cyborg).

This book completely blew my mind. It’s officially the most highlighted book in my Kindle.

It explores what increasingly feels like an inevitable trajectory: the deeper merging of human beings and machines, and what happens to the psyche as more of our attention, identity, and inner lives become mediated by technology.

On one hand, it’s one of the more unsettling books I’ve read. On the other, it’s one of the more hopeful, because Glen lays out a path for preserving the best parts of the human experience while using technology to expand consciousness (rather than diminish it).

In this conversation, we get into:

* What Jungian psychology can teach us about the digital age

* Why technology may be disrupting our “inner ecology”; meaning, emotion, imagination, embodiment, and self-knowledge

* Why technology is not neutral and how the tools we build can ultimately reshape us

* The myth of progress and why technological advancement alone does not guarantee human advancement

* Why embodiment may be essential to consciousness

* Whether AI itself could help us become more self-aware

This ended up being one of the most thought-provoking conversations I’ve had.

You’ll leave with a few potential answers to the core question we explore here on Dream Machines: how do we keep advancing technologically without losing the most nourishing parts of the human experience?

A thread we’ll continue to pull, together.

So with that, enjoy my conversation with Glen Slater.

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Today’s episode is brought to you by… Bifrost.AI

Bifrost is a leading simulation and evaluation platform for Physical AI.

It helps robotics teams build high-fidelity simulations, test models against the edge cases that are hard to capture in the real world, and generate perfectly labeled synthetic data along the way.

If you’re building robots and want to understand where your model fails before it reaches the field, visit bifrost.ai.

World models have become one of the most hyped frontiers in AI — and for good reason. The technology is reaching a tipping point, it’s attracting some of the world’s best AI talent, and many believe world models could be the unlock for both AGI and general-purpose robotics.

But ask five people what a “world model” actually is, and you’ll probably get five different answers.

That’s because there isn’t one approach. There’s a whole spectrum of world models being built today, each trying to understand and simulate the physical world in a different way.

To cut through the ambiguity, I sat down with Matthias Niessner, CEO of SpAItial, a London + Munich-based startup building one of the leading world models for physical AI.

In this episode, we cover:

The spectrum of world models — from pixel-first video models, to 3D spatial representations, to systems that learn physics and cause-and-effect in latent space.

Why video models may be hitting a wall — particularly around spatial consistency, long time horizons, and real-time interaction.

How world models are actually trained — including the role of massive video datasets, data curation, multimodal signals, and learned representations.

“Looks right” vs. “behaves right” — and why generating a photorealistic world is very different from generating one that behaves according to real physics.

Why 3D consistency matters — and why a world that changes as you move through it isn’t really a persistent model of the world.

How physics enters the picture — from relatively simple rigid-body dynamics to far harder problems like fluids, deformation, and objects shattering.

The limits of video game data — and why learning from existing physics engines can only get you so close to reality.

World models for robotics simulation — including a future where a photo of a home, factory, or workspace can become a training environment for a robot.

Closing the sim-to-real gap — and why increasingly realistic learned simulations could fundamentally change how robots are trained.

The path to general-purpose robotics — and how better models of the physical world could accelerate the arrival of machines that can operate reliably almost anywhere.

I learned a ton in this episode — and walked away even more optimistic about how quickly we may be approaching general-purpose robotics.

So with that, I bring you Matthias Niessner.

Today’s guest is Will McDonald, co-founder and Chief Product Officer of Miris.

Miris is rethinking how high-fidelity 3D content gets delivered at scale. Their thesis: the future of 3D depends entirely on simplifying distribution.

In that vein… we talk about why pixel streaming falls short, how Miris uses volumetric data instead, and why that matters for everything from e-commerce and gaming to robotics and simulation.

Will and I worked together for many years at AWS, so we also dive into lessons learned from Amazon’s customer obsessed culture, what it gets right, and experience of going from big tech back into startups.

If you care about spatial computing and simulation, and where the 3D internet is heading, this one’s worth the time.

With that I bring you, Will McDonald.

If you want to understand what it takes to get robots out of the lab and into production, this one’s for you.

Today, I’m joined by the cofounders of Bifrost: Charles Wong (CEO) and Aravind Kandia (CTO).

Bifrost is one of the leaders in synthetic data generation and simulation for evaluation. They’ve built some of the most impressive tools I’ve seen to date for helping robotics developers train, test, and deploy autonomy in the real world.

In this episode, we discuss:

* what most teams still get wrong with simulation

* why real-world data alone is not enough

* why evaluation is becoming the real bottleneck

* how the best teams are closing the infamous sim-to-real gap

* where simulation will be in 5-10 years

These guys are two of the sharpest founders building in robotics right now — and they’ve been at it long before the physical AI hype train. I think you’ll find their insights super valuable and rich with signals from the frontlines.

With that, enjoy this episode with Charles and Aravind.

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This was the most unique and fun episode I’ve done in a while, and it starts in a very unexpected place…

With the art of clowning.

Strange I know, but stick with us, because we quickly connect that world to technology, robotics, and why it holds surprisingly powerful lessons for this moment in time; especially if we want to design intelligent, embodied systems that humans actually want to engage with.

Our guest today is Pasquale D’Silva, CEO of The Illusion of Life, a company building characters and personalities into robots to make them interesting, fun, warm, and worthy of trust.

This all starts with their partnership with Boston Dynamics, where they’ve taken the Spot robot dog and turned it into a character with a real personality, called Spark.

In this chat, we talk about the relationship between humans and machines, and explore all kinds of crevasses, including trust, presence, emotional intelligence, and why artists—not just engineers—may be the key to building joyful, human-centered robots.

If you’re curious about the future of human–machine interaction, you’re gonna love this one. It will stretch your imagination in all the best ways.

So with that, enjoy this episode with Pasquale D’Silva.

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What if machines could learn the world the way humans do?

Not by crunching data and predicting tokens, but by understanding the world and how it works?

Imagine a robot that doesn’t just see a chair, but understands it— its purpose, its relationship to the table, the way you might pull it closer before sitting down.

That’s the world Matt Miesnieks is building.

Matt is the CEO of Primate.AI, a new kind of physical AI company rethinking how machines perceive and interact with reality. His team is exploring what happens when perception stops being a math problem and starts becoming an act of intuition.

Before founding Primate, Matt helped shape the modern era of spatial computing. He co-founded 6D.AI, the company that pioneered the AR Cloud—a real-time 3D map of the world that made digital content persistent in physical space. 6D.AI was later acquired by Niantic, creators of Pokémon Go, where its technology now powers their next generation of AR experiences.

Now, with Primate.AI, Matt’s taking his biggest swing yet: building machines that perceive reality the way we do—not through pixels, but through concepts, memory, and innate understanding.

If 6D.AI gave AR its eyes, Primate.AI is giving machines a mind.

In this conversation, we explore the future of embodied intelligence, what comes after language models, and why understanding the world like a human may be the only real path to AGI.

Today’s guests are building one of the most ambitious startups in the entire spatial computing industry.

The company is called RP1, and we’re sitting down with co-founders Sean Mann and Dean Abramson.

On its face, RP1 is the world’s first true metaverse browser, trying to do for spatial computing what browsers like Mosaic and Internet Explorer did for the web.

But that’s just the tip of the iceberg.

Beneath the surface, RP1 is so much more... They’re building all the infrastructure and protocols required for a truly spatial internet—one where immersive, persistent digital worlds stream on demand, where physical and virtual environments seamlessly merge, and where millions of users can interact in one, shared world, not a bunch of silo’d virtual experiences.

In this episode, we dive into what RP1 actually is, how it scales to millions of users, and why they believe app stores must die.

We also unpack their vision for the core backbone of this future, a Spatial Fabric—a kind of real-time, distributed protocol for the metaverse that manages everything from identity and maps to avatars and live services.

This one’s technical, philosophical, and wildly ambitious. Let’s get into it.

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This interview is with Alvin Graylin — one of the boldest voices out there today on AI, reimagining civilization in the age of intelligence.

Alvin is the best-selling author of the book, Our Next Reality, which is a super thought provoking exploration of how immersive tech and artificial intelligence are going to reshape every layer of society.

Prior, Alvin spent over a decade on the front lines of the XR industry—building and leading HTC’s VR business in China, and serving as Chairman of the Virtual World Society.

Today, Alvin's on a new mission: to help humanity navigate the AI transition—researching, writing, and evangelizing ways to ensure AI serves a greater good and unlocks an age of abundance.

And While Alvin is an optimist, he’s also a realist—and he’s clear that this transition won’t be smooth unless we get a few critical things right.

We talk about…

* The real risks of AGI—not just killer robots, but unaligned incentives, unchecked power, and job displacement.

* His call for an “AI Bill of Rights,” and why the U.S. and China must shift from competition to cooperation—perhaps through what he calls a CERN for AI. (worth checking out the link to AI Bill of Rights here)

* And finally, we explore XR—not as a form of escape, but as a tool for empathy, education, and rewiring human behavior at scale.

This conversation is expansive, urgent, and radical. Let’s get into it. Enjoy.