Since gravity is the curvature of spacetime, quantizing gravity would mean quantizing spacetime (or quantizing geometry) also, which would lead to their being smallest units of space and time, perhaps somewhere around the Planck length and Planck time.
The complexity that comes from the zero-cost abstractions promoted by both C++ and Rust here isn’t in performance (not runtime nor compiletime) but in programmer reasoning and refactoring.
This reminds me a bit of a Clojure library called Plumbing (formerly Graph): https://github.com/plumatic/plumbing. It also let you create a DAG for structured computation. It was used for a web service, at that time.
Unfortunate name for a product, I can't find anything called Dynamic on DDG, only dynamic things with a lowercase d. Do you have a link to the project?
Research into belief perseverance shows that even when people are shown overwhelming evidence contradicting one of their beliefs that they dig in their heels and stick to the belief anyway. [1]
There's also Frank Lunz's observation that many people form opinions based solely on the emotive content of the words (Russell conjugation [2]) they're presented with, regardless of the facts. [3]
Libraries like this enable differentiable programming, which lets you backprop through more than just neural networks. For instance, people have built a differentiable raytracer and plugged a physics engine into reinforcement learning to accelerate training.
Does graphic performance indicated ML training performance (to a certain degree)? Is it fair to say that if graphically it performs better, the ML training will be better with the proper software support?
