For years, the guiding assumption of artificial intelligence has been simple: an AI is only as good as the data it has seen. Feed it more, train it longer, and it performs better. Feed it less, and it ...

Leaders love AI because it makes knowledge instantly reusable—drafts, code, analysis on demand. A recent study uses a formal model to show what happens when “good-enough” answers become essentially ...

An AI agent reads its own source code, forms a hypothesis for improvement (such as changing a learning rate or an architecture depth), modifies the code, runs the experiment, and evaluates the results ...

To bridge the gap between a code-driven AI model and language-based AI agent, the researchers set up an environment that allows the agents to interact with weather models and data via code. The AI ...