Learning from data and information has led to impressive achievements in recent years, especially considering recent advances in artificial intelligence (AI). Computer algorithms are capable to successfully learn in many domains, including human language, ranging from speech recognition to accurate translations, real-time pattern recognition from images, self-driving vehicles, and so on. The key enabler has been the availability of large amounts of data as well as ubiquitous and scalable computation and software. The aim of this proposal is to achieve enhanced motion control performance by learning in high-tech systems, including wafer scanners, a domain that is expected to highly benefit from AI advancements.
|Effective start/end date||1/01/20 → 1/10/25|
Funded in part by
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