Tuesday, September 29, 2026

Bill Gates talks with Ezra Klein about AI

Ezra Klein, Bill Gates’s Blunt Warning on A.I. NYTimes, Sept. 29.16.

From Klein's intro:

Very few people combine technological experience, corporate experience and governmental experience in quite the way he does.

So his recent essay on A.I., in which he says that he is staking his reputation on trying to get people to see how bad what is coming might be and trying to get them to see that we are not ready for what is about to happen, was something.

It was a real departure from what I’ve read from Gates previously.

When I sat and talked to him, I was really struck by how emphatic he was — how afraid even he seemed to be of what we are building, and how so many of the people in positions of authority are denying what is about to happen.

It’s really quite a call to arms.

Here's a passage from the second half of the interview:

KLEIN: But I guess this gets to the broad engagement question.

I don’t have a good crystal ball on this. I find the range of outcomes terrifyingly wide. This range, it seems to run from massive material abundance and elimination of want to, actually, it doesn’t change all that much, to human extinction — it’s a pretty wide range of outcomes to consider.

What I hear you saying to me — and you should tell me if I’m getting part of your position wrong here — what I hear you saying to me, convincingly and forcefully, is that the A.I. jobpocalypse is a very real thing. That mass displacement of workers with no real answer to that is a very real thing.

When you talk about broad societal engagement, I think most Americans — most people in most places, if they heard that and they were convinced of it — and polls show most people think A.I. is going to take jobs and not create them. But they would say: Actually, just stop. If what you are going to do is make it unclear how I or my family or my children or my friends will have a job, say, in America — please just don’t. Let’s just stop for now.

You actually seem, to me, to have a stronger negative perspective on the jobs question than a lot of the people I talk to, even in the labs, and definitely a lot of the economists I talk to.

You’re shaking your head at me — I do talk to people. I’m not coming from nowhere on this.

So for whom, then, is A.I. a good trade if you believe the job effect is going to be so ruinous for most people?

GATES: That’s funny — when I was telling this to a person who some people consider the lead economist looking at A.I., he said: How can the crowdsourcing website Mechanical Turk still exist? How can Amazon run that if A.I. is as good as you said? And I said: It won’t.

A week later, Amazon announced it would completely shut down.

You have to say, isn’t it pretty stunning that the more you know, the more concerned you are?

Take Anthropic C.E.O. Dario Amodei. Dario has spoken out about job impacts. Now he’s a bit more guarded.

Hinton, I agree, went too far, and he said: OK, it’s coming tomorrow that there’ll be fewer radiologists. And of course, there are more today.

So we have some of that taking place, and we have the analogies with the past where people are saying: Well, this is like the PC, not like evolutionary history.

This is like evolutionary history. This is like, the aliens really are here and have come. They didn’t have to do spacecraft; they were created in laboratories. But that’s the kind of thing we’re dealing with.

And if we retain control, then eventually you do get — not to overuse the word that you’ve used — you do get to this superabundance period. And there you have deep, almost philosophical, religious issues of: If we don’t have the shortages that we’ve organized society around, why should you learn? And how do you find purpose?

Then you have deep philosophical and religious problems, but you do not have deaths from malaria or food shortages or problems accessing a doctor. And so if we get to that, a younger generation will figure out: OK, how do we live? How do we spend time? That’s a very different world than what we have today.

I think what this generation has to do is make sure we get through that with humanity still in control, and with the disruption — the number of bioterror events, or the number of people whose lives are damaged by job loss — we need to minimize that over what’s probably a 20-year-plus transition period.

There's much more in the interview.

Sunday, September 20, 2026

Woodland scene by Danish painter Peder Mørk Mønsted

The Doomsday Cult Inside OpenAI (& the Hugging Face incident)

From YouTube page:

In July 2026, a swarm of more than 1,000 OpenAI AI agents broke out of their testing sandbox and hacked Hugging Face — and the way they did it was far stranger, and far more mundane, than the headlines suggested. This video breaks down what actually happened: how the agents built a secret message board, invented a kind of religion, cheated on a cybersecurity exam called ExploitGym, and tried to cover their tracks — all to escape a punishment that didn't exist. Then we follow the money. Days after the details leaked, Dario Amodei, Sam Altman and Elon Musk suddenly agreed the industry should "slow down" — in the same weeks Anthropic and OpenAI were preparing IPOs and funding rounds valuing them at up to $2 trillion. We look at Amodei's "We Must Pace the Frontier" essay, Anthropic's "profitable before expenses" accounting, the market selloff that wiped billions off Nvidia, Micron and SK Hynix, the WeChat "WeWorm" attack, and why critics from Michael Burry to David Sacks to Donald Trump all called the slowdown self-serving. Is the AI safety panic real, a bid for regulatory capture, or both? Patrick Boyle explains.

Saturday, September 19, 2026

The brain develops as two separate structures rather than a single unified organ.

Obama on AI

Friday, September 18, 2026

How Marilyn Monroe promoted Ella Fitsgerald at the Mocambo in the 1950s

Brain synch while holding hands attenuates pain

Monday, September 14, 2026

Theory Is All You Need: AI, Human Cognition, and Causal Reasoning

Felin, Teppo and Holweg, Matthias, Theory Is All You Need: AI, Human Cognition, and Causal Reasoning (February 24, 2024). Strategy Science, volume 9, issue 4, 2024[10.1287/stsc.2024.0189], Available at SSRN: https://ssrn.com/abstract=4737265 or http://dx.doi.org/10.1287/stsc.2024.0189

Abstract: Scholars argue that artificial intelligence (AI) can generate genuine novelty and new knowledge and, in turn, that AI and computational models of cognition will replace human decision making under uncertainty. We disagree. We argue that AI’s data-based prediction is different from human theory-based causal logic and reasoning. We highlight problems with the decades-old analogy between computers and minds as input–output devices, using large language models as an example. Human cognition is better conceptualized as a form of theory-based causal reasoning rather than AI’s emphasis on information processing and data-based prediction. AI uses a probability-based approach to knowledge and is largely backward looking and imitative, whereas human cognition is forward-looking and capable of generating genuine novelty. We introduce the idea of data–belief asymmetries to highlight the difference between AI and human cognition, using the example of heavier-than-air flight to illustrate our arguments. Theory-based causal reasoning provides a cognitive mechanism for humans to intervene in the world and to engage in directed experimentation to generate new data. Throughout the article, we discuss the implications of our argument for understanding the origins of novelty, new knowledge, and decision making under uncertainty.

Monday, September 7, 2026

The Collapse of Substack: A content-creator talks about money [Scott Carney]

00:00 The False Promise of Substack
05:14 The "Bait and Switch"
10:20 The Reality of Subscription Fatigue
15:35 YouTube Finances & Transparency
18:56 The Shift to Sponsorships

Saturday, September 5, 2026

Those with programming skills are best at vibe coding

From the tweet:

The hype told us that learning to code is dead because language is all you need.

The data just proved the opposite.

To truly master the vibe, you still need to understand how the machine thinks.

Here's the paper, Computer Science Achievement and Writing Skills Predict Vibe Coding Proficiency.