TOP Tech Podcast

Can you use AI to think better or think more critically? Philosopher Pia Lauritzen says no. The second we give up to the shortcut use AI, we are letting go of the very basic condition that forces us to think.

When we ask if machines can think, the first question should be: why do humans think? Why do we think?

For Pia, it is fairly simple. We think because we know there is something we do not know. We have a problem. There is a gap. A gap between what I know and what I want to know. 

So I have to start thinking. That is why I ask these questions and that is why I put up with this pain in my head of trying to figure something out that I do not know.

The machine does not have that problem. It does not know that it does not know. 

It is like an animal. 

It does not know that it does not know. 

Of course it is a matter of how you understand thinking. But if you consult the old thinkers and not just the engineers and technologists, then you will have a really hard time finding anyone who would say that a machine could ever think. 

And if it cannot think itself, why should it be able to help us think? We are the only ones who know how to do that.

This is the core problem. AI feels helpful. It removes the discomfort of not knowing where to start. It fills the blank sheet. But that discomfort is not a bug. 

That discomfort is the feature. That discomfort is what thinking is.

And it is at this point that I am reminded of the scene in Con Air. Define irony.

Please enjoy the show.

Cheers, 

Mark & Jeremy.

PS: Subscribe so other curious minds like you can find our channel.

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We taught technology to generate music before we taught it how to assign fair credit to musicians. Nicholas Ponari explains why Overtune rejects one-prompt AI music generation in favor of human-in-the-loop creation. 

Unlike platforms trained on scraped catalogs, Overtune’s AI is built on licensed music, starting with ~20,000 loops produced in-house. Producers can submit stems voluntarily, creating a clean foundation for ethical training and attribution.

The platform uses vector-based audio embeddings to measure how much each stem contributes to a generated track. This enables automated attribution and proportional royalty distribution when songs are commercialized. 

Contributions are weighted mathematically, with clear thresholds to credit primary and secondary influences while avoiding excessive fragmentation 

Please enjoy the show.

Cheers,

Mark and Jeremy

PS: Subscribe so other curious minds like you can find our channel.

Other ways to connect with us:
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Email: [email protected]

Marketing funnels don't exist. They never did. The internet just convinced us they were real. Meta, Google, OpenAI and a supporting cast of billionaire sociopaths figured out they could control distribution and black-box your customers.

Hurrah. Humanity forgot to read the small print. 

Now you're running a business where you don't even know who your customer is.

Well here’s the AI-shaped healthcheck: Your customer is OpenAI.

You're paying 3-15% for a digital presence you don't need. It's called the Silicon Valley tax. You're burning money to keep VCs rich while platforms add another layer of black box between you and the people you serve.

The alternative? Network methodology. Someone you know, or someone who knows someone you know. That's it.

Funnels were invented to sell marketing. Networks are how humans actually work. 

We've been doing it since we had prefrontal cortexes.

Everything that's real is analog. 

That's true for business too.

Welcome to the marketing jungle. 

The year is 2026, and if you don’t know who the sucker at the table is… you probably shouldn’t be playing the stakes. 

Please enjoy the reality check.

Cheers,

Mark and Jeremy. PS: Keep thinking on paper. They don’t want you to, that’s why you must. 
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Matt Kinsella runs Infleqtion, a company building quantum computers. The biggest misconception about quantum computing is that it will replace classical computing. It won't. 

Quantum processors will sit above GPUs in data centers the same way GPUs sit above CPUs today. 

NVIDIA just built the bridge to make this work. It's called NVQ Link, and it changes how we think about the future of compute.

NVIDIA announced NVQ Link in October 2024. It's the bridge between quantum computers and classical GPU clusters. Workloads pass seamlessly between them.

Here's how it works in practice. Infleqtion and NVIDIA solved something called the Anderson Impurity Model - a photovoltaic problem in material science. Parts of it were solved on a GPU cluster. Parts that couldn't be solved by GPUs were solved on Infleqtion's quantum computer. 

Then they recombined to give the answer. 

This isn't commercially useful yet. But expand that over time and you could be looking at the future data center. One with three layers. CPUs at the bottom for general computing. GPUs in the middle for parallel processing and AI. QPUs at the top for problems that are quantum mechanical in nature. 

Workloads come in, get chopped up, each piece goes to the part of the stack best suited to solve it. Then results recombine.

This is already happening. Infleqtion just announced a contract with the Army called Sapient Secure AI for PNT - position, navigation, and timing. It runs their quantum-inspired software on NVIDIA's Jetson edge GPUs. 

Small GPUs that don't have much memory. 

The software lets them ingest far more streaming data than normal. Video, speed, inertial motion. Then it recreates what GPS gives you - where you are in the world - by extrapolating from all those signals. Without GPS.

Please enjoy the show.

Cheers, 

Mark & Jeremy.

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What is the value proposition of going into space? What is the killer app? How do we make money? And specifically, looking at space stations and satellites, do the economics actually work?In part one of our Space to Grow book club, we learned how SpaceX reduced launch costs by 97%. Matthew Weinzierl and Brendan Rosseau showed us how NASA gave the keys to private industry. The result was dramatically cheaper access to space.But so what? Who cares? So A bunch of billionaires can go to space for less money than before. What does that mean for you? What does that mean for me?In Part 2, we bring in the skeptics. They ask reasonable questions. Why spend money on hotels on the moon when there are problems on Earth? Why mine asteroids for precious metals when we have problems here? The pursuit of space is inspiring, but inspiration can blind us to reality.Outside of a few obvious existing users like satellites and government science missions, how could the rest of us and organizations benefit from lower costs to orbit? How much of what the optimists see as potential will turn into reality?Please enjoy the show.
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TIMESTAMPS

(00:00⁠) Trailer 
⁠(01:35⁠) No Dust Jackets ⁠
(02:00⁠) Name Jeremy's Astronaut ⁠
(03:52⁠) What Is The Product Market Fit For Space? ⁠
(05:26⁠) Satellites And The Le Chatelier Principle ⁠
(09:00⁠) Planet's Dove Satellites ⁠
(16:38⁠) Satellites For Climate ⁠
(18:28⁠) John Lewis ⁠
(22:30⁠) Ronald Reagan & Carl Sagan ⁠
(26:42⁠) Inflatable ISS Modules