Aki Fujimura, chief executive of D2S, sat down with Semiconductor Engineering to talk about AI and Moore's Law, lithography, and photomask technologies. What follows are excerpts of that conversation. SE: In the eBeam Initiative's recent Luminary Survey, the participants had some interesting observations about the outlook for the photomask market. Fujimura: In the last couple of years, mask revenues have been going up. Prior to that, mask revenues were fairly steady at around $3 billion per year. Recently, they have gone up beyond the $4 billion level, and they're projected to keep going up. Luminaries believe a component of this increase is because of the shift in the industry toward EUV. One question in the survey asked participants, 'What business impact will COVID have on the photomask market?' Some people think it may be negative, but the majority of the people believe that it's not going to have much of an effect -- or it might have a positive effect.

To avoid the computational requirements of online methods, we can use reinforcement learning (RL) instead. In RL, In recent years, major progress has been made to deploy the agent interacts with a simulation environment many autonomous vehicles and improve safety. However, certain times prior to execution, and at each simulation episode common driving situations like merging in dense traffic are it improves its strategy. The resulting policy can then be still challenging for autonomous vehicles. Situations like deployed online and is often inexpensive to evaluate. RL the one illustrated in Figure 1 often involve negotiating with provides a flexible framework to automatically find good human drivers.

Semiconductor Engineering sat down to discuss the issues and challenges with machine learning in semiconductor manufacturing with Kurt Ronse, director of the advanced lithography program at Imec; Yudong Hao, senior director of marketing at Onto Innovation; Romain Roux, data scientist at Mycronic; and Aki Fujimura, chief executive of D2S. What follows are excerpts of that conversation. SE: Machine learning is a hot topic. This technology uses a neural network to crunch data and identify patterns, then matches certain patterns and learns which of those attributes are important. We also have more advanced forms called deep learning.

Semiconductor Engineering sat down to discuss artificial intelligence (AI), machine learning, and chip and photomask manufacturing technologies with Aki Fujimura, chief executive of D2S; Jerry Chen, business and ecosystem development manager at Nvidia; Noriaki Nakayamada, senior technologist at NuFlare; and Mikael Wahlsten, director and product area manager at Mycronic. What follows are excerpts of that conversation. To read part one, click here. SE: Artificial neural networks, the precursor of machine learning, was a hot topic in the 1980s. In neural networks, a system crunches data and identifies patterns.

Aki Fujimura, chief executive of D2S, sat down with Semiconductor Engineering to discuss Moore's Law and photomask technology. Fujimura also explained how artificial intelligence and machine learning are impacting the IC industry. What follows are excerpts of that conversation. SE: For some time, you've said we need more compute power. So we need faster chips at advanced nodes, but cost and complexity are skyrocketing. Fujimura: Moore's Law is definitely slowing down, but I'm confident there will be continued innovation everywhere to keep it going for a while. There's a lot that every discipline of the eco-system is working on to make incremental and breakthrough improvements.