In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...

One would imagine that an AI capable of solving the hardest Olympiad problems would naturally produce novel scientific ...

From autonomous cars to video games, reinforcement learning (machine learning through interaction with environments) can have ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

In an interview with Technology Networks, Dr. Daniel Reker discusses how machine learning is improving data-scarce areas of ...

Overview: Structured online platforms provide clear, step-by-step learning paths for beginners.Real progress in data science comes from hands-on projects and co ...

Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...

Interview Kickstart today announced the launch of its Advanced Machine Learning Program, a specialized interview preparation track designed for engineers and data professionals preparing for machine ...

By transforming movement into data, Timothy Dunn is reshaping how scientists can study behavior and the brain.

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

Here's the case for constraint-aware intelligence in the AI 2.0 era.

AI is not yet the success that it should be, so two dozen enterprises will disclose their move toward a crucial new paradigm – hybrid AI – at a 2026 conference.