It comes close. The author doesn't want to learn the math and study the thing. Why? By implication, because they're over 35 and don't want to learn new stuff anymore.
It's possible for me to learn enough math to download a huggingface model and start from tokenizing my prompt and convert them to token embeddings and add position embeddings and go through 32 layers of softmax+mlp with layernorm and write out the equation that would compute each intermediate floating number until it tells me the probabilities of each output token so I can sample a token and continue the sentence autoregressively. Computing any one of these 100 billion 16-bit floating point multiplications? I can either compute them in decimal or check out the IEEE754 fp16 format and compute in binary manually, or maybe draw a circuit with AND and NOT gates if given enough time.
These are the low level operations. From a higher level mathematical standpoint? I can prove to you analytically how a SGD optimizer on a convex surface will converge to the global minimum at an exponential rate, starting from either set theory or dependent type theory and the construction of real numbers from sets of rational numbers.
The author posed it as a question. It's not about want as much as able. No matter how much I wanted (at 58) to understand the inner working of a LLM, it's beyond me, just like becoming a fighter pilot.
However, even though I don't program, nothing in his list prior to AI is beyond me yet, if I wanted to learn it. I am happy being a 25 years Linux power user who climbed the Emacs learning curve to use org-mode and then gradually added email,rss, irc, web, and gopher modalities to it.
Why? By implication, because they're over 35 and don't want to learn new stuff anymore.
It seems you are both missing the point of article, and jumping on a stereotype.
Said point being: while the author clearly does like learning new stuff, and rolling up his sleeves to deal with all the fiddly bits -- AI is categorically different. In that the complexity is simply off the page compared to most (choosing my words carefully) technologies one is used to geeking out on. And that even experts in the field admit they don't really understand it.
(That, and the sheer resources required to do something interesting, the perpetual lock-in with the sociopathic entities that provide said resources, etc).
