Online algorithms are designed to make decisions sequentially, without complete knowledge of future inputs. In many real-world applications—from scheduling and resource allocation to network ...

Adaptive systems were supposed to simplify decision-making. Instead of hard-coded rules, engineers built models that could learn from data, respond to change, and improve over time. That promise still ...

New research shows that people recognize more of their biases in algorithms' decisions than they do in their own -- even when those decisions are the same. Algorithms were supposed to make our lives ...

In this Artificial Intelligence podcast with Lex Fridman, computer scientist Donald Knuth discusses Alan Turing, Neural networks, machine learning and other AI topics from ant colonies and human ...

Machine learning is hard. Algorithms in a particular use case often either don't work or don't work well enough, leading to some serious debugging. And finding the perfect algorithm–the set of rules a ...