A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

MIT researchers have developed a new machine-learning-based adaptive control algorithm for autonomous drones. The ...

The diagram below highlights what these steps ... a “test set”, which are respectively used to: Train the machine learning algorithm. Evaluate how well it works on queries it hasn’t seen ...

Over the past few decades, robots have gradually started making their way into various real-world settings, including some ...

discuss some of the most common machine learning algorithms, and explain how those algorithms relate to the other pieces of the puzzle of creating predictive models from historical data.

Systems controlled by next-generation computing algorithms could give rise to better and more efficient machine learning products, a new study suggests. Systems controlled by next-generation ...

It can be relatively cheap to gather a lot of bio-signal data. To teach a machine-learning algorithm to find a relationship between bio-signals and health outcomes, however, you need to teach the ...

20, 2025/––MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), announced that quantum algorithms will be deeply integrated with machine learning to explore practical application ...

The full dataset contained 2,523 compounds and included compounds with both senolytic and non-senolytic properties so as not to bias the machine-learning algorithm. The algorithm was then used to ...