artificial intelligence tagged posts

Researchers train a machine-learning model to monitor and adjust the 3D printing process to correct errors in real-time. A new computer vision system watches the 3D printing process and adjusts velocity and printing path to avoid errors. Training the system in simulation, researchers avoid the costly trial-and-error associated with setting 3D printing parameters for new materials.

Scientists and engineers are constantly developing new materials with unique properties that can be used for 3D printing, but figuring out howto print with these materials can be a complex, costly conundrum.

Often, an expert operator must us...

Huge amounts of data are needed to train machine-learning models to perform image classification tasks, such as identifying damage in satellite photos following a natural disaster. However, these data are not always easy to come by. Datasets may cost millions of dollars to generate, if usable data exist in the first place, and even the best datasets often contain biases that negatively impact a model’s performance.

To circumvent some of the problems presented by datasets, M...

When the human brain learns something new, it adapts. But when artificial intelligence learns something new, it tends to forget information it already learned.

As companies use more and more data to improve how AI recognizes images, learns languages and carries out other complex tasks, a paper publishing in Science this week shows a way that computer chips could dynamically rewire themselves to take in new data like the brain does, helping AI to keep learning over time.

“The brains of living beings can continuously learn throughout their lifespan...

A new study by the Oregon State University College of Engineering shows that machine learning techniques can offer powerful new tools for advancing personalized medicine, care that optimizes outcomes for individual patients based on unique aspects of their biology and disease features.

The research with machine learning, a branch of artificial intelligence in which computer systems use algorithms and statistical models to look for trends in data, tackles long-unsolvable problems in biological systems at the cellular level, said Oregon State’s Brian D. Wood, who conducted the study with then OSU Ph.D. student Ehsan Taghizadeh and Helen M. Byrne of the University of Oxford.

“Those systems tend to have high complexity — first because of the vast number of individual ce...