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The Computer Scientist Who Builds Big Pictures From Small Details
To better understand machine learning algorithms, Lenka Zdeborová treats them like physical materials.
When Data Is Missing, Scientists Guess. Then Guess Again.
Across the social and biological sciences, statisticians use a technique that leverages randomness to deal with the unknown.
How ‘Embeddings’ Encode What Words Mean — Sort Of
Machines work with words by embedding their relationships with other words in a string of numbers.
Novel Architecture Makes Neural Networks More Understandable
By tapping into a decades-old mathematical principle, researchers are hoping that Kolmogorov-Arnold networks will facilitate scientific discovery.
With ‘Digital Twins,’ The Doctor Will See You Now
By creating digital twins of patients, Amanda Randles wants to bring unprecedented precision to medical forecasts.
Will AI Ever Have Common Sense?
Common sense has been viewed as one of the hardest challenges in AI. That said, ChatGPT4 has acquired what some believe is an impressive sense of humanity. How is this possible? Listen to this week’s “The Joy of Why” with co-host Steven Strogatz.
What Is Machine Learning?
Neural networks and other forms of machine learning ultimately learn by trial and error, one improvement at a time.
How AI Revolutionized Protein Science, but Didn’t End It
Three years ago, Google’s AlphaFold pulled off the biggest artificial intelligence breakthrough in science to date, accelerating molecular research and kindling deep questions about why we do science.
Game Theory Can Make AI More Correct and Efficient
Researchers are drawing on ideas from game theory to improve large language models and make them more consistent.