The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

TrainCheck uses training invariants to find the root cause of hard-to-detect errors before they cause downstream problems, ...

Although they mostly go unnoticed by humans, small earthquakes occur much more frequently than large earthquakes, and knowing ...

For the first time, large language models performed on a par with gold medallists in the International Mathematical Olympiad.

Despite the AI hype, tools are proving valuable for leading-edge chip manufacturing. More aggressive feature scaling and ...

Each year farmers face a massive challenge, losing £3.5 billion worth potatoes due to the unpredictable weather conditions, ...

The more data the machine is exposed to, the better it becomes at performing the task, which is why machine learning is often used for complex problems such as image recognition, natural language ...

Some physicists have been using machine-learning tools since the 1950s, but their widespread use in the field is a relatively new phenomenon. The idea to use a type of machine learning called a neural ...

These systems focus on improving forecast accuracy, efficiency, and extreme weather handling through advanced machine ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

Machine learning can make these calculations using samples of simulated data, a process that takes closer to 24 hours and creates a database that astrophysicists can sample from in a matter of seconds ...