AI: Great, But Somehow Still Not Very Good

There are a lot of use cases for machine learning in the fab, but pitfalls could lie ahead.


In an invited presentation at CS Mantech 2024, Charlie Parker, senior machine learning engineer at Tignis, provides context for the AI hype cycle with a high-level overview of machine learning concepts, then explores how the technology fits into the fab, from inventory management to institutional knowledge capture, but warns that it is worth being aware of the ways in which machine learning models can go wrong and the potential pitfalls that may lie ahead.

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