Neural network AI is simple. So… Stop pretending you are a genius

1. "but that complexity comes from repetition and a random number generator" - Most of the complexity comes from trying to solve non-convex optimization problems via SGD. "Repetition" doesn't make sense unless you're talking about vectorization (you're not), and an rng has little relevance.

2. "Congrats! You took the above code, and looped the loop again." - sure, if that were true then people would have trained deep neural networks in the 90s. Instead we needed researchers (see? geniuses) to invent batch normalization, highway networks, CNNs, dropout, etc. Also, that's not an "recursive neural network", that's a recurrent one.

3. "So you trained a neural network using Nvidia GPUs and moved it to the phone…" - this entire section makes so little sense I don't know where to start. Neural networks are, for the most part, robust to small rng differences - that's why they have surprising generalizability. I have no idea what this guy is trying to say about phones and GPUs though.

4. "What it does well is help you visualize what is happening in those 11 lines" - well, that's not the point, but I'm starting to understand that this guy doesn't get it.

5. "Building a neural network with 1 trait for every word in the English language would require a network that used as much computing power as all of Google." - I'm just going to let that one sit there.

...

"There is neural network code in my tool box."; sure, you sound like you've imported Tensorflow before (possibly?). But maybe before dismissing an entire field you should figure out how any of it works.

What's the point of this? That he's as smart as people who build AI? This person, Brandon Wirtz, needs to work on his self-confidence, not just intelligence.

This is just condescending vitriol.