I have written about one of Max Tegmark’s ideas already - the Mathematical Universe Hypothesis - and in doing so I admitted he sits at the top of my favourite physicists list. That post was about a single claim. This one is about the man, and about the thing I find more interesting than any individual theory of his: the through-line. Tegmark has spent a career moving steadily inward, from measurable cosmology toward the deepest possible questions about what reality is, and the move never feels like a physicist losing the plot and drifting into metaphysics. It feels like someone following the maths until it runs out of floor. ...

When I wrote about Donald Hoffman, I was working through one half of a question I keep saying I have not settled: whether consciousness is fundamental, there from the start as part of the floor of reality, or computational, something that switches on once a physical process organises information in the right way. Hoffman is the most serious case I have found for the fundamental side, and I gave it a fair hearing because I genuinely find it compelling. ...

In Why Is There Something Rather Than Nothing? I admitted to an instinct I have never quite been able to shake: that the laws of physics are discovered rather than invented, and that mathematics might be genuinely fundamental - not a human language we lay over reality, but part of the bedrock. I said that if we ever reach base reality, maths is the thing most likely to get us there. I left it as a feeling. This post is me taking that feeling and seeing how far a serious physicist has been willing to push it. ...

When I wrote about Yampolskiy’s Personal Universes recently, I left a thread hanging. The question underneath that whole post - the one I said I genuinely had not settled - was whether consciousness is fundamental, there first with the universe as something it experiences, or whether it is computational, something that switches on once a process gets complex enough. I said I had only recently started reading my way into the fundamental side, mostly through Donald Hoffman. This is me pulling on that thread properly. ...

First, the thing this is all in service of. The AI alignment problem is the challenge of making a powerful AI system reliably pursue what we actually want it to pursue - getting its goals, values, and behaviour to line up with human intentions, and to stay lined up even as the system becomes more capable than the people supervising it. It sounds simple and is not: we struggle to state our own values precisely, those values conflict between people, and an AI optimising hard for a slightly-wrong objective can produce outcomes nobody asked for. The multi-agent version - aligning one system with all of humanity at once, rather than a single person - is harder still, and it is the specific version Personal Universes is trying to dodge. ...

The “is the software engineer dead” genre has been running long enough that you can predict most of the takes before you read them. The interesting interviews are the ones where the person being interviewed is in a position to know something the rest of us do not. Boris Cherny, the creator of Claude Code at Anthropic, is one of those people. Sky News got him in front of three charts and asked him to react. ...

For most of the last few years, the “AI and cybersecurity” conversation has been a vibes argument. One side said the models would soon write novel exploits at scale. The other side said the models were still tripping over basic shell commands and could not be trusted to hack anything more dangerous than a CTF box. The honest answer was that nobody had hard numbers, so the debate stayed stuck on intuition. ...

TL;DR - The last month gave producers three things worth paying attention to. Superbooth 2026 in Berlin put neural audio processing into a hardware pedal for the first time and handed Buchla a $999 entry point. The AI music legal picture kept moving, with a fresh lawsuit against Suno and a still-pending Sony ruling expected this summer. And the tooling caught up quietly, with Ableton Live 12.4 and REAPER 7.73 shipping solid point releases. Here is what actually changed - and what is just noise. ...

“Are we living in a simulation?” is one of those questions that sounds like late-night dorm-room talk and then turns out to have a serious literature behind it. The honest short answer to “how likely” is that nobody knows, and that the question may not even have a clean numerical answer. But that is not a reason to wave it away. The reasons we cannot confidently put a number on it are themselves interesting, and they tell us something real about the limits of probability, the nature of consciousness, and what counts as science. ...

TL;DR Recursive self-improvement (RSI) is the idea of an AI that improves its own ability to improve - each round producing a smarter system that does the next round better. It is the engine behind every “intelligence explosion” story since I.J. Good described it in 1965 The narrow version is already real. Systems like AlphaEvolve and the AI Scientist measurably improve algorithms, code, and even research output - including, in AlphaEvolve’s case, the infrastructure that trains the models themselves The leap people fear is different: improving an algorithm is not the same as improving general intelligence. Nothing in 2026 has crossed that line, and the gap is structural, not just a matter of scale Four bottlenecks decide whether RSI runs away or fizzles: compute, data, verification, and diminishing returns. Each is a hard physical or informational limit, not a temporary engineering nuisance The realistic picture is steady, human-paced acceleration - AI assisting AI research - not an overnight takeoff. METR’s time-horizon data shows fast but smooth exponential progress, which is exactly what a bottlenecked process looks like It still deserves serious safety attention, because a slow takeoff is the one we can actually govern There is a particular shape of argument that has haunted artificial intelligence since before the field had a settled name. It goes like this: build a machine slightly better than humans at designing machines, and it will design a machine better than itself. That machine designs a better one. The loop tightens, each turn faster than the last, and intelligence runs away from us in an afternoon. ...