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With a deep passion for physics, Shiraz Minwalla investigates the complexities of black holes, grey galaxies, and beyond.

In a research world defined by scale and AI-driven discovery, small colleges are proving impact isn’t measured in dollars. At places like Wellesley and Bowdoin, close mentorship, collaborative problem-solving, and a readiness to experiment with new tools are shaping the next generation of scientists to navigate a rapidly evolving research landscape.

More scientists are leaving academia, trading tenure-track hurdles for the speed and flexibility of industry. For physicist Elizabeth Frank, that shift meant moving from mapping Mercury to mining the Moon — swapping publication bottlenecks for the fast, interdisciplinary problem-solving of space startups, and using AI to revive data gathered half a century ago.

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.

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.

String theory was once hailed as the “theory of everything” — a unified model of nature built on tiny vibrating strings. But after decades of expansion, the field has evolved beyond its namesake, embracing branes, dualities, and abstract geometry. Some physicists now wonder: is it time to rename the theory entirely?

What is AI? From symbolic logic to large-scale neural networks, we're unpacking how today’s systems learn, generate, and reason alongside the the misconceptions and challenges of applying AI in science and society.

Sloan Foundation president Adam Falk is stepping down this year after seven years leading the iconic organization. He spoke with FirstPrinciples about how the foundation’s philosophy has given it an outsized impact on scientific progress.

Artificial structures surrounding an entire star were thought to be impossible. A new calculation shows that they could be supported by the gravity of a second star.

Astrophysicist Niayesh Afshordi and science communicator Phil Halper explore theories—from black holes birthing universes to the end of cosmic singularities—in a sweeping narrative that challenges the Big Bang orthodoxy.

In 2006, a group of physicists proposed a bold idea: that gravity must be the weakest force in any consistent theory of quantum gravity. Almost twenty years later, this so-called Weak Gravity Conjecture remains unproven, but the research it inspired continues to raise deep questions.

Even Janna Levin, once dubbed the “chillest astrophysicist alive,” is abuzz with energy about “magical” collaborations, both scientific and artistic.

For more than a century, physicists have struggled with an uncomfortable truth: the two pillars of modern physics fundamentally contradict each other.

Scientists are using artificial intelligence and machine learning to tackle dark matter and other cosmic puzzles.

In an era of misinformation, understanding science is essential for informed decision-making. True scientific literacy goes beyond reading or quick online searches—it empowers individuals to think critically, evaluate evidence, and discern credible information from misleading claims.

DARPA has launched the Quantum Benchmarking Initiative to assess whether scalable, fault-tolerant quantum computers can be built within the next decade.