>cloud computing will continue to see decreases in costs cloud computing costs much more than on prem; it's available on demand, which is why it's attractive t

>cloud computing will continue to see decreases in costs cloud computing costs much more than on prem; it's available on demand, which is why it's attractive to some companies. For everyone else it's an outsourcing play that unlocks capex for revenue generation. >Quantum computers might play a role in increasing computational power in the next decade. Nope. No chance. Best case is that QC will provide improved molecular simulations in 10-20 years. But that will be a very specialised result. >Right now a lot of AI research is low hanging fruit recently made available with advances in CPU and GPU. After the advances dry up maybe more fundamental research will produce much better results with our current technology. 100%, but the key word is maybe. One problem I anticipate is that the current skill set of grad students and the current management mind set in academia and commercial research is not well fitted to the kind of fundamental research that includes maybe and risk. I think that a more likely turn is that there will be a focus on how to better exploit the tech for data science and ML that we have. Currently we're pretty hit and miss and also the results are rather unpredictable and brittle. When did you last find an ML project on Github with unit tests?