The 2026 Nobel Prize for Physics "We built it, and we'll see what comes," Francis Halzen told me back in 2007. IceCube was his Field of Dreams. Today, the dreamer and the instrument win the Nobel Prize in Physics. I visited the South Pole in 2007 to observe IceCube being built and wrote about it in The Edge of Physics. An excerpt from the book: IceCube has turned the icy wastes of Antarctica into a neutrino physicist’s field of dreams. “Everybody thinks something will be seen at a cubic-kilometer scale,” said Halzen. “I’m not responsible for what is emitting neutrinos in the universe. We developed the technique, we built it, and we’ll see what comes.” IceCube is venturing into the unknown. It’s a discovery instrument, not unlike the proposed Square Kilometre Array or the Large Hadron Collider near Geneva, Switzerland. These behemoths will serve physics for decades, peering through the mists of time to let us glimpse our very beginnings. Edward Wilson, who accompanied [Robert Falcon] Scott to the South Pole and died with him on the way back to McMurdo, might as well have been speaking about the IceCube scientists when he penned these words during his brief sojourn in Antarctica: And this was the thought that the Silence wrought As it scorched and froze us through For the secrets hidden are all forbidden Till God means man to know, We might be the men God meant should know . . .

"We built it, and we'll see what comes," Francis Halzen told me back in 2007. IceCube was his Field of Dreams. Today, the dreamer and the instrument win the Nobel Prize in physics. I visited the South Pole in 2007 to observe IceCube being built and wrote of an entire chapter on it in The Edge of Physics. An excerpt:

When I started as a science writer/journalist in 2000, I'd have been happy to write one book. So, it's a bit surreal to be starting work on my fifth. My publisher, @DuttonBooks, just announced that I'll be writing WHERE MACHINES THINK: The Search for the Geometries of Intelligence. It's a follow-up to WHY MACHINES LEARN, but focusing on the math of generative AI models, from Boltzmann machines to Transformer-based LLMs, via GANs, VAEs, diffusion models, and the like, and maybe onward to AIs that incorporate world models. Another thing I could not have foreseen: the appetite for unfiltered math in a semi-popular account of machine learning and AI. We can cut through so much of the hype and hysteria around AI by paying attention to the math.

Finally bought the entire 4-volume set of Leonard Susskind's Theoretical Minimum series. The first of these, on classical mechanics, was the inspiration for Why Machines Learn, along with @stevenstrogatz's Infinite Powers. They gave me the courage and desire to write a "popular" science/math book, without shying away from the hard stuff (equations/theorems/proofs).

Anthropomorphizing aside, should we be legitimately concerned over the “emergence” of unforeseen capabilities in groups of interacting agents? My Substack piece: wheremachinesthink.substack.…

There has been, somewhat justifiably, much hand-wringing over the use of overly anthropomorphic language in describing the incident. But linguistic choices shouldn’t detract us from trying to understand what actually happened. Did the interactions of hundreds of agents, with each agent potentially unlikely to successfully attack Hugging Face on its own, make possible a considerably complex, and unanticipated, behavior? Depending on your persuasion, the answer is either an emphatic yes or an equally emphatic no. But a whole lot of us are in the middle—wary of moneyed interests, wary of naysayers, and their respective echo chambers. Maybe we can take a step back and look at some prior research that helps make sense of such claims. My latest Substack piece: wheremachinesthink.substack.…