EETimes - Toward Sustainable Economics of Artificial Intelligence

Recent technology and business media have given much coverage to the expanding use case of machine learning and artificial intelligence, but how much have they talked about economics of AI? At the physical layer, more objects in our lives are embedded with sensors or are sensors. The aim and consequence are to record and quantify more of our physical world, creating vast data sets that make machine learning possible. At the application layer, growing compute power and model sophistication such as dimensionality reduction and manifold learning have helped data scientists tackle messier technical problems than could be addressed even just a few years ago. Meanwhile, the pandemic has heightened the urgency and societal stakes to direct research insights toward practical problem-solving, broadly defined.