EDA Challenges Machine Learning

Over the past few years, machine learning (ML) has evolved from an interesting new approach that allows computers to beat champions at chess and Go, into one that is touted as a panacea for almost everything. While there is clearly a lot of hype surrounding this, it appears that machine learning can produce a better outcome for many tasks in the EDA flow than even the most seasoned architects and designers can generate. EDA companies have been investing in this technology and some results are being announced. But developers and users appear to be taking it slow for a couple of reasons. First, results are non-deterministic and nobody is quite sure how to assess the risks associated with that.