The technology is becoming more complex every year, opening the door to new scientific discoveries and innovations, but with one big drawback: there is more data than ever, and turning it into something useful becomes more difficult with more available data. The Department of Energy wants to help solve this problem by financing machine learning and research of AI could “automate scientific discovery.”
The funds come from the US Department of Energy (DOE), who say it will divide the money among five research projects developing AI algorithms and learning machines adapted to scientific efforts. These algorithms will be, the goal is to analyze huge amounts of data from various sources and use it to offer ideas or even making new scientific discoveries.
aw data can come from various sources: observational studies, scientific experiments and even simulations. RNs and ML systems developed through these projects may be able to use the data for, among other things, to predict an extreme weather event, will provide dynamic information on power grids, form conclusions about the space and physics, etc.
The Department of Energy has its own interest in these algorithms; The agency has scientific user facilities that generate tons of data to analyze. It is not reasonable that humans are sort by scientists such amounts of information in search of breakthroughs, ideas and discoveries.
In a statement on its new funding initiative, the DOE Office of Associate Director of Science for Research Scientific Computing Advanced Barbara Helland said:
Disruptive technology changes occur in applications, algorithms, architectures and computing ecosystems high performance. These projects explore potentially impact approaches in AI and machine learning to help and automate the scientific discovery and analysis of data for problems increasingly complex