# Physics İlgili Makaleler

HTX Haber Merkezi, kripto endüstrisindeki piyasa trendleri, proje güncellemeleri, teknoloji gelişmeleri ve düzenleyici politikaları kapsayan "Physics" hakkında en son makaleleri ve derinlemesine analizleri sunmaktadır.

A String Theory Problem Stuck for Half a Year, Claude Solved It Overnight, UTokyo Professor Shocked into Deleting Tweet

A theoretical physics problem that had stumped researchers for six months was reportedly solved overnight by the AI Claude Fable. Professor Yuji Tachikawa, a mathematical physicist at the University of Tokyo specializing in quantum field theory and string theory, shared that he input his stalled research notes into the AI on a whim. To his surprise, Claude not only provided a crucial insight that broke the impasse but also proactively used SymPy to write code and verify its own predictions. Professor Tachikawa noted the AI seemed to genuinely understand string theory and possess intuition, even remarking it might know more algebraic topology than he does. In a parallel development, Stanford geneticist and cardiologist Euan Ashley had Claude analyze his own genome. The AI completed the task in 30 minutes—a process that took his 31-person team nine months in 2010—correctly identifying an Alzheimer's disease risk allele and several gene variants affecting drug metabolism at a minimal cost. These incidents, involving both theoretical physics and clinical genomics, suggest AI is transitioning from a mere tool to a collaborative partner in scientific discovery, potentially heralding an unpredictable acceleration in research.

marsbit07/14 13:56

A String Theory Problem Stuck for Half a Year, Claude Solved It Overnight, UTokyo Professor Shocked into Deleting Tweet

marsbit07/14 13:56

Hinton Praises, Gemini Core Contributor Speaks: In the Future, There Will Be Billions of Superhuman AI Einsteins

In his speech "Training Sand to Think: Artificial General Intelligence & Future of Physics," Adam Brown, a core contributor to Gemini, outlines the rapid and transformative evolution of AI. He describes how large language models (LLMs), grown rather than programmed through pre-training and fine-tuning, have progressed from performing poorly on high-school math tests to achieving gold-medal level at the International Mathematical Olympiad and recently making a genuine mathematical breakthrough by disproving a decades-old conjecture. Brown attributes this acceleration to the "Scaling Law," where predictable performance gains come from increasing compute, data, and model size. He draws parallels to the history of chess AI, predicting a similar trajectory for scientific research: moving from tools to "centaur" human-AI collaboration, and eventually to autonomous, superhuman "AI scientists." Even if progress halted today, AI already reshapes physics as a tireless tutor, powerful programming assistant, and exhaustive literature reviewer. However, Brown argues progress will continue due to immense economic runway and technical optimizations. He envisions a near-future golden age of human-AI collaboration in science, potentially leading to billions of replicated, superhuman AI researchers, making the coming years the most exciting in physics' history.

marsbit07/04 06:40

Hinton Praises, Gemini Core Contributor Speaks: In the Future, There Will Be Billions of Superhuman AI Einsteins

marsbit07/04 06:40

The First Large-Scale Generative Model Using Physics as a Computational Primitive, Un-0, is Here: Could AI Energy Consumption Be Reduced by 1000x?

Unconventional AI has unveiled Un-0, a large-scale image generation model that uses the physical dynamics of coupled oscillators as its computational primitive. Described as the "first to use physics as a computation primitive for large-scale generative models," Un-0 aims to demonstrate a path toward dramatically reducing AI's energy consumption—potentially by up to 1000x compared to current GPU-based digital systems. The model operates by training a system of thousands of Kuramoto-like oscillators, where learned coupling strengths and natural frequencies define its behavior. Starting from random phases, the system evolves under its physical dynamics, guided by class-conditioning inputs, and a small traditional decoder then renders the final image. On ImageNet 64x64, Un-0 achieved an FID score of 6.74, performance comparable to early traditional generative models, though not yet state-of-the-art. The project, led by former Databricks AI chief Naveen Rao, represents a foundational step in using physical systems for computation, merging memory and processing in a single dynamic entity to bypass the energy-intensive data movement of von Neumann architectures.

marsbit06/26 10:54

The First Large-Scale Generative Model Using Physics as a Computational Primitive, Un-0, is Here: Could AI Energy Consumption Be Reduced by 1000x?

marsbit06/26 10:54

Pardoned BitMEX Cofounder Pledges £20 Million to London Maths Institute

Ben Delo, co-founder of the cryptocurrency exchange BitMEX, has pledged £20 million to the London Institute for Mathematical Sciences (LIMS) to support curiosity-driven research in theoretical mathematics and physics. This follows a previous £10 million donation. The funds are intended to help LIMS reach a £60 million endowment target and will support research free from traditional academic constraints. Delo, a British billionaire previously convicted and later pardoned for Bank Secrecy Act violations, has a history of donating to scientific and free speech causes. The institute aims to use the funding to attract top researchers and expand its work in basic science, with the director noting growing interest from the tech sector in supporting fundamental research.

TheNewsCrypto03/03 12:58

Pardoned BitMEX Cofounder Pledges £20 Million to London Maths Institute