I think this is false. My general opinion of computer scientists and engineers (especially in silicon valley) lack the scientific training that one gets in other disciplines like in physics or other hard sciences. Psychology, linguistics, cognitive science and neuroscience has generated a rich diverse experimental data in the past 50 years, and now is the prime time for a theory to emerge to connect everything. To make what I’m saying clearer, you needed Newtonian mechanics, Maxwell and Plank and Coulomb to develop and discover the science of electricity and atoms in order for us to engineer the silicon transistor. Without the original scientific knowledge, building such devices would have been impossible. This machine learning, ai, deep learning and this obsession with benchmarks are, in my opinion, a hinderance to AGI
bumby|5 years ago
Theory is required for understanding, not for discovery. They are two different things. What gets a lot of scientists and statisticians worked up is how ML can outperform traditional models without always being interpretable. It’s like claiming the Wright brothers couldn’t build a flying machine without having a thorough understanding of the mechanics of flight. I can improve performance of my car by remapping the fuel without necessarily understanding the nuances of optimizing enthalpy. There’s levels of understanding, and they may not correlate completely to effectiveness. To that extent, it’s more engineering than science