You may see a lot of press reports about scientific discoveries but the reality is that in the last 20 years, science has been stagnating. In the first two decades after the end of World War II a lot was spent in basic science and results were heaped for half a century. That is how we ended to have the boom of Silicon Valley in the 1990s with computer technologies and data communications ushering in the Information Age with the Internet spreading everywhere. But in the last 30 years, not only for R&D budgets, the "R" of Research got smaller and the "D" of Development got bigger, but we are now seeing the "D" itself cannot get bigger much because the "R" of basic research has become so small and basically used for bureaucracy and public relations that there is nothing new in the horizon whether we look at Physics, Chemistry or Biology and all focus is on streamlining scientific and technological work to make it cheaper by exporting it overseas at the expense of reducing it to some commodity work and not doing real basic research. Need to add that just throwing money at science cannot fix the problem. NSF and similar agencies must reinvent themselves. Their evaluations of promising basic science work must not be based on what some people whose expertise is in public relations or community work tell them, and neither should they look at immediate Development results of Research projects to support it, which has proven time and again to be extremely short-sighted.
Deep learning models should be used to decide which basic science projects have the potential to push the envelop in science and technology and to support such endeavors. In other words, the support of science itself should be done scientifically using AI and not be based on lobbying and public relations.

Hoping for a democratic and secular futurist republic in Iran,
Sam Ghandchi, Editor/Publisher
December 10, 2017