University of Tokyo
Assembly Line
AI and lasers light the way to a manufacturing revolution
High-quality data is crucial because AI machine-learning systems need to be trained. A few thousand to a few tens of thousands of data points are often required for the algorithm to start making useful predictions. “We have constructed an all-automated and autonomous data acquisition system, called the Meister Data Generator,” says Yohei Kobayashi, a professor at the University of Tokyo’s Institute for Solid State Physics. “We don’t even need to go to the lab to take data: it keeps working 24 hours a day, 7 days a week.”
The researchers have applied their idea to many laser production processes including, very recently, laser ablation: using a short pulse of light to remove a small amount of material from a surface. In this case, they created a high-quality dataset by firing light pulses of controllable duration at a solid target. A three-dimensional microscope then provided images for the corresponding surface changes at a rate of about one per minute, or a 1,000 data points in a day.
This big-data driven approach is proving very fruitful, and the University of Tokyo collaborators at Kyushu University in Fukuoka are already exploiting the method to serve the semiconductor manufacturing industry.
Rapidus, University of Tokyo plan 1-nm chip tech with French partner
Japanese chipmaker Rapidus and the University of Tokyo are partnering with French research institute Leti to jointly develop basic technology for designing chips using technology in the 1-nanometer range, Nikkei has learned. The partners will begin actively exchanging staff and sharing technology as early as next year. Leti will contribute its expertise in chip components to build an infrastructure for supplying 1-nm products.