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A study in PNAS suggests that symmetric structures in nature are preferred because they require less information to encode — they are more compressible.
As physicists are increasingly reliant on artificial intelligence (AI) methods in their research, we ponder the role of human beings in future scientific discoveries. Will we be guides to AI, or be guided by it?
“Girls don’t like physics” is a common refrain, but this perception has not always existed, nor does it occur everywhere in the world today. We call on our readers to fight such unfounded stereotypes.
As artificial intelligence (AI) makes increasingly impressive contributions to science, scientists increasingly want to understand how AI reaches its conclusions. Matthew D. Schwartz discusses what it means to understand AI and whether such a goal is achievable — or even needed.
Venkatesh Narayanamurti and Jeffrey Y. Tsao discuss lessons learned from the success of the great 20th-century industrial research labs and warn against three common misconceptions about the nature and nurture of research.
In the 25 years since the first quantum teleportation experiments, researchers have been pushing the limits both in terms of the distances and the complexity of the quantum states involved.
Sarah Malik explains how quantum random walks can be used to model the cascades of quarks and gluons resulting from the proton–proton collisions at the Large Hadron Collider.
Travelling by train rather than plane when possible is a key way to reduce the carbon footprint associated with conferences. Here are some things we’ve learned about how it works in practice.