A HANDS-ON APPROACH TO SCIENTIFIC ARTIFICIAL INTELLIGENCE PROGRAMMING

The field of scientific artificial intelligence is fascinating. The possibility that artificial intelligence can make predictions—whether using experimental or synthetic data, or relying solely on the differential equations that govern the phe-nomena under study—is, quite simply, fascinating. The challenge is for this artificial intelligence to be truly predictive in an engineering sense: that the pre-dictions it makes can be verified and validated, so that industry can ultimately place its trust in the benefits this new discipline can bring.
It is the task of engineers, physicists, and mathematicians to turn this family of techniques into the tool that industry needs right now. The responsibility lies with us, and it begins with training a new generation of researchers in the field who will, no doubt, bring this to a successful conclusion.