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The Best Qubits for Quantum Computing Might Just Be Atoms
In the search for the most scalable hardware to use for quantum computers, qubits made of individual atoms are having a breakout moment.
How Chain-of-Thought Reasoning Helps Neural Networks Compute
Large language models do better at solving problems when they show their work. Researchers are beginning to understand why.
Physicists Finally Find a Problem That Only Quantum Computers Can Do
Researchers have shown that a problem relating to the energy of a quantum system is easy for quantum computers but hard for classical ones.
New Breakthrough Brings Matrix Multiplication Closer to Ideal
By eliminating a hidden inefficiency, computer scientists have come up with a new way to multiply large matrices that’s faster than ever.
How Selective Forgetting Can Help AI Learn Better
Erasing key information during training results in machine learning models that can learn new languages faster and more easily.
Never-Repeating Tiles Can Safeguard Quantum Information
Two researchers have proved that Penrose tilings, famous patterns that never repeat, are mathematically equivalent to a kind of quantum error correction.
How Quickly Do Large Language Models Learn Unexpected Skills?
A new study suggests that so-called emergent abilities actually develop gradually and predictably, depending on how you measure them.
Scientists Find Optimal Balance of Data Storage and Time
Seventy years after the invention of a data structure called a hash table, theoreticians have found the most efficient possible configuration for it.
How to Build an Origami Computer
Two mathematicians have shown that origami can, in principle, be used to perform any possible computation.