Step 1, abandon the concept of "first principles." First principles don't exist for most areas of study outside of pure mathematics, and for newer fields like AI they haven't been established yet so you'd just be hamstringing yourself.
Step 2: The steps above are a good plan for learning about traditional AI, and the traditional approaches, which were based on an attempt to model human thought processes. Machine learning was what the industry turned to in the early 2000s because we didn't have the hardware capabilities then to meaningfully model neural networks. We do now, but machine learning has taken over so there's very little research into modeling neural networks...about the same as there was when I was an undergrad.
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Step 1, abandon the concept of "first principles." First principles don't exist for most areas of study outside of pure mathematics, and for newer fields like AI they haven't been established yet so you'd just be hamstringing yourself.
Step 2: The steps above are a good plan for learning about traditional AI, and the traditional approaches, which were based on an attempt to model human thought processes. Machine learning was what the industry turned to in the early 2000s because we didn't have the hardware capabilities then to meaningfully model neural networks. We do now, but machine learning has taken over so there's very little research into modeling neural networks...about the same as there was when I was an undergrad.