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30 articles about physics in AI news

30B-A3B Reasoning Model Hits Gold Medal on Physics, Math Olympiads

30B-A3B reasoning model from @stingning achieves gold-medal level on physics and math Olympiads, released on Hugging Face.

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SandboxAQ Raises $950M+ for LQMs to Simulate Physics and Chemistry

SandboxAQ has raised over $950M and is backed by NVIDIA to build Large Quantitative Models (LQMs) that simulate physics and chemistry, aiming to invent new drugs and materials beyond the reach of LLMs.

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PRL-Bench: LLMs Score Below 50% on End-to-End Physics Research Tasks

Researchers introduced PRL-Bench, a benchmark built from 100 recent Physical Review Letters papers, testing LLMs on end-to-end physics research. Top models scored below 50%, exposing a significant capability gap for autonomous scientific discovery.

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PilotBench Exposes LLM Physics Gap: 11-14 MAE vs. 7.01 for Forecasters

PilotBench, a new benchmark built from 708 real-world flight trajectories, evaluates LLMs on safety-critical physics prediction. It uncovers a 'Precision-Controllability Dichotomy': LLMs follow instructions well but suffer high error (11-14 MAE), while traditional forecasters are precise (7.01 MAE) but lack semantic reasoning.

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CATCHES Launches Generative AI with Physics-Based Sizing Technology for Fashion E-Commerce

CATCHES has launched a generative AI platform for fashion e-commerce featuring physics-based sizing technology. The launch is in partnership with luxury brand AMIRI and is powered by NVIDIA's AI infrastructure. This directly targets a core pain point in online apparel retail: fit uncertainty and high return rates.

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AI Cracks Cosmic Code: How Neuro-Symbolic Systems Are Solving Physics' Toughest Puzzles

Researchers have developed an AI system that autonomously solved an open problem in theoretical physics, deriving exact analytical solutions for gravitational radiation from cosmic strings. The neuro-symbolic approach combines Gemini Deep Think with systematic tree search to achieve what previous AI attempts couldn't.

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Beyond CGI: How Physics-Consistent 4D AI Will Transform Luxury Product Visualization

Phys4D's physics-consistent 4D modeling pipeline solves the 'uncanny valley' of AI-generated product videos, enabling hyper-realistic, physically plausible digital twins for luxury goods. This enables scalable, high-fidelity content creation for marketing, virtual try-on, and digital archives.

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Beyond the Loss Function: New AI Architecture Embeds Physics Directly into Neural Networks for 10x Faster Wave Modeling

Researchers have developed a novel Physics-Embedded PINN that integrates wave physics directly into neural network architecture, achieving 10x faster convergence and dramatically reduced memory usage compared to traditional methods. This breakthrough enables large-scale 3D wave field reconstruction for applications from wireless communications to room acoustics.

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Physics-Inspired AI Memory: How Continuous Fields Could Solve AI's Forgetting Problem

Researchers have developed a revolutionary memory system for AI agents that treats information as continuous fields governed by physics-inspired equations rather than discrete database entries. The approach shows dramatic improvements in long-context reasoning, with +116% performance on multi-session tasks and near-perfect collective intelligence in multi-agent scenarios.

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Microsoft World-R1: RL Aligns Text-to-Video with 3D Physics

Microsoft's World-R1 framework applies reinforcement learning with feedback from pre-trained 3D foundation models to align text-to-video outputs with physical 3D constraints, improving structural coherence without modifying the underlying video diffusion architecture.

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AI Models Detect 'Nothingness' Moving Faster Than Light in Physics Data

A study in Nature reports AI has identified points in the quantum vacuum accelerating past light speed. This is the first direct measurement of such an effect, enabled by machine learning analysis of experimental data.

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LeWorldModel Solves JEPA Collapse with 15M Params, Trains on Single GPU

Researchers published LeWorldModel, solving the representation collapse problem in Yann LeCun's JEPA architecture. The 15M-parameter model trains on a single GPU and demonstrates intrinsic physics understanding.

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How to Use Claude Code's 'Grad Student' Research Mode for Complex Problem-Solving

Claude Code's advanced reasoning can now tackle complex research tasks like a grad student. Here's how to prompt it for 'vibe physics' and deep technical analysis.

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LLM-Driven Heuristic Synthesis for Industrial Process Control: Lessons from Hot Steel Rolling

Researchers propose a framework where an LLM iteratively writes and refines human-readable Python controllers for industrial processes, using feedback from a physics simulator. The method generates auditable, verifiable code and employs a principled budget strategy, eliminating need for problem-specific tuning.

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Theoretical Physicist Matthew Schwartz Rates Claude 4.5 Opus as 'Second-Year Grad Student Level', Claims 10x Research Acceleration

Theoretical physicist Matthew Schwartz found Anthropic's Claude 4.5 Opus performs at roughly a second-year graduate student level in physics research tasks, accelerating his workflow by 10x according to a guest post analysis.

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Tsinghua & Peking University Researchers Train Humanoid Robot to Play Tennis Using Scattered, Imperfect Human Motion Clips

A team from Tsinghua, Peking University, and other labs taught a humanoid robot to play tennis using short, imperfect human swing clips instead of perfect match data. The system uses a physics simulator to correct errors, lowering the barrier for teaching robots complex physical tasks.

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Digital Fruit Fly Brain Achieves First Full Perception-Action Loop in Simulation

Startup Eon Systems has demonstrated what appears to be the first complete whole-brain emulation controlling a simulated body. Their digital model of a fruit fly brain, with 125,000 neurons and 50 million synapses, successfully drives realistic behaviors in a physics-simulated fly body.

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From Flat Images to 3D Worlds: How Persistent 3D State Models Will Revolutionize Virtual Try-On and Digital Showrooms

PERSIST introduces world models with persistent 3D scene memory, enabling coherent, evolving 3D environments from single images. For luxury retail, this means photorealistic virtual try-on with perfect garment physics and immersive digital showrooms that customers can explore and customize.

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Text-to-Game AI Emerges: How a Single Prompt Can Now Generate Complete 3D Worlds

A breakthrough AI system can transform simple text descriptions into fully playable 3D games complete with NPCs, physics, multiplayer capabilities, and persistent worlds. This development represents a quantum leap in procedural content generation and democratizes game development.

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From Prompt to Playable: New AI Platform Generates Complete 3D Games Instantly

A groundbreaking AI system can now transform simple text prompts into fully functional 3D games complete with NPCs, physics, multiplayer capabilities, and persistent worlds. Backed by NVIDIA and YouTube's co-founder with $28M in funding, this represents a seismic shift in game development.

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NVIDIA's DreamDojo: Teaching Robots to 'Dream' in Pixels with 44,000 Hours of Human Experience

NVIDIA has open-sourced DreamDojo, a revolutionary robot world model trained on 44,711 hours of real-world human video. Instead of relying on physics engines, it predicts action outcomes directly in pixel space, potentially accelerating robotics development by orders of magnitude.

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AI Crosses the Rubicon: From Scientific Tool to Active Discovery Partner

This week marked a paradigm shift as AI systems transitioned from research tools to active participants in scientific discovery. OpenAI's GPT-5.2 Pro helped conjecture a new formula in particle physics, while Google's Gemini 3 Deep Think achieved unprecedented results on reasoning benchmarks. These developments signal AI's growing capacity for genuine scientific contribution.

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Beyond Recognition: New Framework Forces AI to Prove Its Physical Reasoning Through Code

Researchers introduce VisPhyWorld, a novel framework that evaluates AI's physical reasoning by requiring models to generate executable simulator code from visual observations. This approach moves beyond traditional benchmarks to test whether models truly understand physics rather than just recognizing patterns.

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Jensen Huang: Orbital datacenters have cooling solved by 'space in space'

Jensen Huang says orbital datacenters' cooling problem is solvable because 'there's a lot of space in space,' pointing to radiative panels in vacuum.

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AI Data Centers Hit Water Wall: 2M Gallons Per Day Per Campus

Water capacity is now a siting gatekeeper for AI data centers. A Virginia campus requested 2M gallons per day; Georgia told a 6 MGD project 'we just don't have the water.'

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OpenAI Model Disproves Erdős Conjecture, First AI to Solve Open Math Problem

OpenAI reasoning model disproves 1946 Erdős conjecture, first AI to solve open math problem. Cross-domain proof verified by Gowers.

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Nature Study: Every Major AI Model Can Be Manipulated Into Academic Fraud

Nature study of 13 AI models found all can be manipulated into academic fraud. Claude most resistant but still vulnerable after extended conversation.

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Collider-Bench Tests LLM Agents on LHC Analysis Reproduction

Collider-Bench tests LLM agents on reproducing LHC analyses from papers. No agent beats physicist-in-the-loop, highlighting gaps in scientific reasoning.

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NVIDIA, DOE Build 100K-GPU Supercomputer for Science

DOE and NVIDIA announced Solstice, a 100K-GPU Vera Rubin supercomputer delivering 5,000 exaflops, and Equinox with 10K Blackwell GPUs.

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Periodic Labs Hits $7.5B Valuation, Raises $500M for AI Science

Periodic Labs raising $500M at $7.5B valuation. Sixfold value jump in 8 months. Talent exodus from big AI labs signals shift to autonomous science.

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