> Seems like I am engaged in the ice trade and they are about to invent the refrigerator.

The way I like to look at it is that I'm engaged in the ice trade and they are about to invent everything else that will end mine and every other current trade. Which leaves me with two practical options: a) deep despair. b) to become a Jacks of all trades, master of none, but oftentimes better than a master of one. The Jacks can, for now, capitalize in the thing that the Machines currently lack, which is agency.

IMO Computer Science doesn't have enough mathematics in the core curriculum. I think more CS students should be double majoring or minoring in Physics and/or Math. The skills you gain in analyzing problems and constructing models in Physics, finding truth/false values and analyzing problems in math, and the algorithmic skills in CS really compliment each other.

Instead of people "hacking" university education to make them purely fotm job training centers. The real hack would be something that really drills down at the fundamentals. CS, Math, Physics, and Philosophy to get an all around education in approaching problems from fundamentals I think would be the optimal school experience.

Don't despair. The key to becoming proficient in advanced subjects like this one is to first try to understand the fundamentals in plain language and pictures in your mind. Ignore the equations. Ask AI to explain the topic at hand at the most fundamental level.

Once the fundamental concepts are understood, what problem is being solved and where the key difficulties are, only then the equations will start to make sense. If you start out with the math, you're making your life unnecessarily hard.

Also, not universally true but directionally true as a rule of thumb, the more equations a text contains the less likely it is that the author itself has truly grasped the subject. People who really grasp a subject can usually explain it well in plain language.

I guess I have the opposite experience. I have a post-graduate level of mathematical education and I am dismayed at how little there is to be gained from it, when it comes to AI/ML. Diffusion Models and Geometric Deep Learning are the only two fields where there's any math at all. Many math grads are struggling to find a job at all. They aren't outclassing programmers with their leet math skillz.

AI makes it easier to catch up. :)

The big thing that made it all click for mathematics was that I stopped thinking about mathematics the way that it was taught to me and I started thinking about it the way that it naturally felt correct to me

So in my specific case I stopped thinking about mathematics as: how to interpret a sequence of symbols

But instead I decided to start thinking about it as “the symbols tell me about the multidimensional topological coordinate space that I need to inhabit

So now when I look at a equation (or whatever) my first step is “OK how do I turn this into a topology so that I can explore the toplogical space the way that a number would”

Kind of like if you were to extend Nagle’s “what it’s like to be a bat” but instead of being a bat you’re a number

[dead]