Forget the grade. Impress your profs. Let them learn from you. For example, you could work on analog computers (look it up). The early AI systems were all anal

Forget the grade. Impress your profs. Let them learn from you. For example, you could work on analog computers (look it up). The early AI systems were all analog, using motors on "volume knobs" to adjust the weights. Analog is MUCH faster than digital. You could probably train an analog neural net "at movie speeds" because it all happens in parallel. Analog weights are trivial (capacitors), backprop is just differentiation which analog does trivially. Function inversion just involves putting the function in the feedback loop of an op-amp. A board with 100x100 mini-caps would be dirt cheap and would have 10,000 "weights". Besides being "up to speed on AI NNs" you would also be breaking new ground (well, really old ground but nobody remembers anything before last year). Imagine talking the department into an "analog AI lab" in cooperation with the EE dept and you get to be "the person". Heck, now you've nearly "joined the department" rather than being a student. Think of college as a big company that lets you do ANYTHING. Profs have to prove themselves to get tensure. Students have to "get good grades" and "learn to hack the FAANG interviews so they can be a 'good cultural fit (aka grade hackers)". But YOU are at college as a "free agent" and can use all the resources to excel at what you love. Imagine having 4 years at a company with the resources of a college that lets you do ANYTHING. You will never have it this good again. Forget the grade.