At the intersection of artificial intelligence and fundamental physics, the NSF Institute for Artificial Intelligence and Fundamental Interactions (IAIFI) is preparing scientists to learn, think and understand at the deepest levels. In its latest week-long Summer School program, students explored frontier challenges through lectures, tutorials, and collaborative hackathons, testing how AI can shape the future of physics, and how physics can push the boundaries of AI.

At Columbia University, quantum breakthroughs emerge from a culture of shared labs, ideas, and materials. What began as informal collaboration has become a scalable model for cross-disciplinary science that powers advances in programmable quantum systems.

Z.ai's new open-source model and Harmonic's math-native chatbot highlight contrasting strategies for AI reasoning, while a new wave of increasingly specialized benchmarks invites us to rethink how we measure progress.

From prompt injection to physics simulators and open reasoning models, recent news shows that AI isn’t just accelerating science, it’s reshaping how it works. The question now, is will it deepen inquiry, or erode the principles on which credibility in science is built?

A new kind of network is emerging. One that could enable ultra-secure communication, safeguarded by the laws of physics. As the race to build a quantum internet accelerates, nations are vying for digital sovereignty and want to be the first to build the unbreakable internet.

She’s one of the internet’s sharpest scientific voices: equal parts physicist, critic, and communicator. In this candid conversation, Sabine Hossenfelder reflects on AI, the flood of low-impact theory papers, and how a scientific culture ripe for reform could finally be ready for change.

Hidden prompts buried in preprints show how easily large language models (LLMs) can be manipulated, exposing a deep vulnerability in science’s quality-control system. As artificial intelligence (AI) becomes part of the scientific review process, traceability and transparency must become new norms, not afterthoughts.

The Flatiron Institute stands out for its bold model: full-time scientists, open-source tools, and a mission to accelerate discovery through computation. Its success across fields—from astrophysics to neuroscience—reflects the power of that approach.

Large language models have advanced dramatically in recent years, yet when physicists gave them an undergraduate-level test, even the best models were only correct on around one out of every three questions. The new PhysUniBench benchmark exposes how far AI still has to go in mastering fundamental science.