Using Machine Learning In Fabs

Amid the shift towards more complex chips at advanced nodes, many chipmakers are exploring or turning to advanced forms of machine learning to help solve some big challenges in IC production. A subset of artificial intelligence (AI), machine learning, uses advanced algorithms in systems to recognize patterns in data as well as to learn and make predictions about the information. In the fab, machine learning promises to provide faster and more accurate results in select areas, such as finding and classifying defects in chips. Machine learning also is used in other process steps, but there are still some challenges to deploy it. It has been used in computing and other fields for decades. It first appeared in semiconductor production in the 1990s. Some saw it as a way to help automate the steps for some manually-driven fab equipment. Over time, machine learning has made staggering progress in computing and elsewhere.