An artificial-intelligence algorithm that discovers its own way to learn achieves state-of-the-art performance, including on some tasks it had never encountered before. Joel Lehman is at Lila Sciences ...

When CARL, a Japanese stationery company, was honored with an Honorable Mention in the Red Dot Award: Product Design 2025, few were surprised. This is, after all, the country where even the smallest ...

The Learning Household, a new book by Ken Bain and Marsha Marshall Bain, truly resonated with me because it affirms something I have always believed as a parent: the home should be a place where ...

Researchers have found a way to make the chip design and manufacturing process much easier — by tapping into a hybrid blend of artificial intelligence and quantum computing. When you purchase through ...

Patent applications on artificial intelligence and machine learning have soared in recent years, yet legal guidance on the patentability of AI and machine learning algorithms remains scarce. The US ...

Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field ...

The emergence of using Machine Learning Techniques in software testing started in the 2000s with the rise of Model-Based Testing and early bug prediction models trained on historical defect data. It ...

Background: Fertility preferences refer to the number of children an individual would like to have, regardless of any obstacles that may stand in the way of fulfilling their aspirations. Despite the ...

The year 2024 is the time when most manual things are being automated with the assistance of Machine Learning algorithms. You’d be surprised at the growing number of ML algorithms that help play chess ...

bLaboratory for Clinical Research and Real-World Evidence, Institute for Artificial Intelligence in Medicine, University Hospital Essen, Essen, Germany cInstitute for Artificial Intelligence in ...

Abstract: This paper presents a dynamic selector model for data workload prediction. A main function responsible for selecting the most accurate Machine Learning Algorithm (e.g., Linear Regression, ...