At @lanyon_ai, we’re completing Hilbert’s (other) dream. From November 1st, we’re rolling out pre-release versions of Lanyon to early customers and testers, and will be hosting simultaneous public demos of Lanyon capabilities in San Francisco and Chicago. From moon bases to modular reactors to atomic-scale programmable matter, we're on a mission to make the abstract concrete, to make the digital physical, and to formally verify reality. Join us!

Why is fusion hard? In the first in our series of “physics deep dives”, Chief Scientist @JunoRavin shows how Lanyon can be used to autonomously rediscover and analyze some of the fundamental physics difficulties underlying magnetic confinement fusion: the sausage instability that killed the Z-pinch device, and the interchange/flute instabilities that continue to plague magnetic mirror devices. This deep dive shows the true power of Lanyon’s neurosymbolic architecture for applied physics research, combining formally verified 3D MHD simulations produced by Lanyon’s symbolic layer, with highly flexible AI-driven physics analyses enabled by Lanyon’s neural layer. Stay tuned for further additions to this series, where we will dive deeper into field-reversed configurations, tokamaks, stellarators, and all of the new physics difficulties that emerge at these new ranges of timescales. Post below 👇

I don't think this is true: it will just select for a very particular kind of mathematician: the G. H. Hardy. If you read C. P. Snow's foreword to the Apology, it becomes clear that Hardy's most substantive mathematical contributions came about from taking the highly creative and technically impressive (but otherwise utterly inexplicable) accomplishments of Littlewood and Ramanujan, and figuring out how to explain, interpret, and communicate them in a manner that was simultaneously rigorous, precise, and beautiful. It's ironic given his derogatory comments about mathematical exposition in the Apology, but Hardy's real skill lay in the beauty and clarity of his prose and his explanation. He was always the one who wrote up the final manuscript for publication, but he was almost never the one who provided the underlying results or ideas. (Again, Snow's foreword makes clear that the Apology is, amongst other things, a work of immense self-hatred.) In a world where Littlewoods and Ramanujans are commodified, be a Hardy.

Math has a proof checker. Can physics get one? Jonathan Gorard @getjonwithit, an applied mathematician and the cofounder and CEO of Lanyon AI, joins to explain why AI took off in math and coding but not yet in physics. We discuss an AI finishing the formal check of a Fields Medal proof and why it scared him, why he thinks “I detected a particle” rests on 20 to 50 levels of theory, and what Alan Turing’s PhD student Robin Gandy tried to build for physics. The conversation also covers his push to make physics executable, why he thinks mysteries are artifacts of description languages, and whether there is still a place for the physicist. youtu.be/oQypVVv1u1o

Using Lanyon to autonomously discover and verify new models and algorithms for continuum mechanics. Simulating high-energy impact of a copper projectile on an elastoplastic plate, plus the resulting damage profile. The discovered model matches the experimental value for the effective plastic strain to within 5%. Model discovery, formal verification, software implementation, and numerical simulation all completed in less than 5 minutes, from a single prompt.

Math has a proof checker. Can physics get one? Physicist Jonathan Gorard @getjonwithit, cofounder of the Wolfram Physics Project and now CEO of Lanyon AI, thinks so: “We want to make physics executable in the same way that software is executable and that now increasingly mathematics is executable.” He also says, “I’m in a continual process of grief.” What does it mean to grieve a way of doing physics? And is there still a place for the physicist?