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Computer Scientists Prove Why Bigger Neural Networks Do Better
Two researchers show that for neural networks to be able to remember better, they need far more parameters than previously thought.
Quantum Complexity Tamed by Machine Learning
If only scientists understood exactly how electrons act in molecules, they’d be able to predict the behavior of everything from experimental drugs to high-temperature superconductors. Following decades of physics-based insights, artificial intelligence systems are taking the next leap.
Machine Learning Gets a Quantum Speedup
Two teams have shown how quantum approaches can solve problems faster than classical computers, bringing physics and computer science closer together.
Researchers Build AI That Builds AI
By using hypernetworks, researchers can now preemptively fine-tune artificial neural networks, saving some of the time and expense of training.
Computer Scientists Eliminate Pesky Quantum Computations
For years, intermediate measurements made it hard to quantify the complexity of quantum algorithms. New work establishes that those measurements aren’t necessary after all.
Qubits Can Be as Safe as Bits, Researchers Show
A new result shows that quantum information can theoretically be protected from errors just as well as classical information can.
The Year in Math and Computer Science
Mathematicians and computer scientists answered major questions in topology, set theory and even physics, even as computers continued to grow more capable.
What Does It Mean for AI to Understand?
It’s simple enough for AI to seem to comprehend data, but devising a true test of a machine’s knowledge has proved difficult.
Mathematician Hurls Structure and Disorder Into Century-Old Problem
A new paper shows how to create longer disordered strings than mathematicians had thought possible, proving that a well-known recent conjecture is “spectacularly wrong.”