Two Brains

For two months this column has been describing an architecture. Here’s the part I kept in the footnotes: I’ve been building it.

I owe you a confession, and then I owe you a demonstration.

The confession first. For weeks I’ve written about why the machines can’t tell truth from plausibility — why detection isn’t a strategy, why fluency isn’t fidelity, why the only honest path is to separate the saying from the knowing and import truth from somewhere you can actually check. I’ve signed each of those columns with a one-line note that I co-founded a company “built on this conviction.” That little disclosure has been doing a lot of quiet work. These columns were not the musings of a neutral observer. They were the argument […]

By |June 9th, 2026|2026, Artificial Intelligence, Uncategorized|10 Comments
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GenAI is Fluent in Everything, but Faithful in Nothing

Why the machines hallucinate, why they have no worldview, and why truth has to come from somewhere else.

I’m going to say something that sounds like an insult and is meant as a description: large language models (all of them) hav never known a true thing. Not once. It doesn’t know things at all. It is extraordinarily good at sounding like it does, which is a different skill, and most of our present confusion comes from mistaking the second for the first.

Here is what a language model actually does. It has read an enormous amount of text, and from that text it has learned, with real brilliance, what tends to come next. Give it some words and it predicts the words likely to follow. That […]

By |June 8th, 2026|2026, Artificial Intelligence|7 Comments
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Knowing What You Don’t Know

Why the next real breakthrough in AI isn’t a bigger brain — it’s a machine that can admit ignorance.

A reader caught me out.

Last column I argued that the great AI buildout — the hundreds of billions pouring into data centers and the GPUs that fill them — is aimed at the wrong layer. We are spending as if the bottleneck were the size of the model’s brain, when the real bottleneck is getting the right information in front of it. Cheap retrieval, I said, not expensive cognition.

A reader replied, pointing out the name Jevons.

In 1865, a young English economist named William Stanley Jevons noticed something strange about coal. As steam engines got more efficient — as they wrung more work out of every lump […]

By |June 4th, 2026|2026, Artificial Intelligence, Jevons, Uncategorized|12 Comments
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The Most Expensive Mistake in the History of Computing

I promised to show you why the whole industry’s answer to its own problem — buy a bigger brain — is the most expensive mistake in the history of computing. To do that I have to take you back to 1999, because I was there, and if you’re old enough to be reading me, maybe you were too.

And I wasn’t only watching. In 1999 I put $10,000 into a young company called E-Loan, run by a founder named Chris Larsen. After the IPO I cashed out for $400,000 and bought a house. Chris kept playing — E-Loan to Prosper to Ripple — and did rather better than a house; he’s a crypto billionaire now. (Chris, if you’re reading this: we should talk.) Those are […]

By |June 3rd, 2026|2026, Artificial Intelligence|3 Comments
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The Thirty Percent Confession

 

Last time I told you the AI industry is paying a tax it doesn’t have to pay — that a great deal of what we grandly call “AI” is really just looking things up, and we’ve chosen to do that looking-up on the most expensive silicon ever manufactured. A number of you wrote to say I was overstating it. Surely, you said, the people setting hundreds of billions of dollars on fire know something I don’t.

So this week I won’t argue with you. I’ll let one of the largest companies in enterprise software argue with you instead — because it already has, in a research paper it published itself and seems to have hoped you wouldn’t read too closely.

The company is Salesforce. The same […]

By |June 2nd, 2026|2026, Artificial Intelligence, Uncategorized|3 Comments
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