On Mathematical Maturity (1) Thomas Garrity

A video about neural networks, function approximation, machine learning, and mathematical building blocks. This is a submission for #SoME3 (0:00) Functions Describe the World (3:15) Neural Architecture (5:35) Higher Dimensions (11:55) Taylor Series (15:20) Fourier Series (21:25) The Real World (24:32) An Open Challenge Links and Content: • On Mathematical Maturity, Thomas Garrity: [VIDEO] • Earth Rotation Loop: [LINK] • Earth Rotation Loop Modeling Shell Surfaces: [LINK] • Fourier Features Paper: [LINK] • Code for mandelbrot/image approximations: [LINK] • Code for line/surface approximations: [LINK]

The above short clip is from the following series: "On Mathematical Maturity (1) Thomas Garrity": [VIDEO] "On Mathematical Maturity (2) Thomas Garrity": [LINK]

I think the more realistic long term victims will be implementation specialists and business analysts. The middlemen who sit between product (developer) and customer. Giving your product the ability to talk & work directly with the customer seems to me a much more valuable activity than covering all the edge cases that would arise during the development of such a solution with an LLM. Remember, everything is a function [0] and LLMs support calling them. The trick is having the skill and domain expertise to establish bounded contexts and prompts that align with realistic product use cases and transition between them cleanly. I know there is a lot of doubt that users would enjoy using a chat interface, but I strongly believe it would be popular as long as it actually works. If it's not well designed and the GUI tools are faster even for a novice, you will have wasted a lot of time/money for nothing. [0] [VIDEO]