$SNPS CEO Sassine Ghazi says he is not worried about AI models bypassing commercial EDA tools end to end without their participation, because these models are not static and constantly need to learn and retrain. Accuracy and determinism are essential for autonomous chip design workflows, and customers will not invest hundreds of millions of dollars without confidence it will work. He views this as a significant demand opportunity for their software across training and inference rather than a threat, with Synopsys proactively engaged with customers on building these autonomous workflows. "I don't need to go back or go as far as 10 years ago. You're right around 2017 we introduced and invested and saw great results with centered around reinforcement learning. If you look at the last three years, the focus was around Copilot generative AI move to agents. Right now we're talking about autonomous designs. As you start looking at an autonomous workflow, the most important thing is accuracy and determinism. Customers will not invest hundreds of millions of dollars in a product without having the confidence that it is going to work. The portfolio we have with the sign off leadership is essential to building these autonomous workflows. We are participating with our customers on how to achieve an autonomous workflow. It's not like it's happening without our participation. We're proactively engaged with them to re-engineer how they're looking at the future of engineering with AI being the center of that evolution. I am not worried at all that at some point that model can do the end to end without our participation. Because you have to remember these models are not static. They're constantly changing. They constantly need to learn. So the opportunity is the opposite. It's not a threat. It's a significant demand for our software to train to inference to constantly enable that faster design to deal with the complexity. And we're at the center of it."