The translated papers would feature modern notation and visual diagrams.
Use Claude or Codex to rewrite Yurii Nesterov’s papers in notations, diagrams that current practitioners of deep learning understands.
I think this by itself may lift optimization education for frontier model developers.
Positive users agree notations are a fair bottleneck in optimization theory and support using AI to rewrite Nesterov papers, while negative users report safety filters blocking the effort.
@_arohan_ Probably the same treatment for OR on the applied side. Take the old papers on queues, scheduling, routing, inventory, allocation, etc and rewrite them in terms of agents, GPUs, tokens, evals, rollouts, traces, PRs, and human review. AI productivity is just optimization.
Use Claude or Codex to rewrite Yurii Nesterov’s papers in notations, diagrams that current practitioners of deep learning understands.
I think this by itself may lift optimization education for frontier model developers.
@_arohan_ wait so notations are the bottleneck for getting practioners into optim theory? thats actually a fair point
@_arohan_ triggered a safety filter on Fabel. No can do. 🥶
@_arohan_ (im underwater)
"a weird quantum shape or just a drunk scribble"
@_arohan_ making theory digestible for the applied crowd is usually where the bottleneck lives
curious which paper u d start with
The translated papers would feature modern notation and visual diagrams.
Use Claude or Codex to rewrite Yurii Nesterov’s papers in notations, diagrams that current practitioners of deep learning understands.
I think this by itself may lift optimization education for frontier model developers.
