Mentioning neural ODE doesn't make sense here, as this is unrelated. Basically any implementation of transformer uses residuals, but you're not really training a neural ODE here.
Also consider getting rid of the em-dashes. I don't know if you mostly vibe-coded this or not, but the README is pretty clearly AI generated.
Good, coding harnesses should be open source and LLMs should be treated as commodities. Minimize switching costs for consumers, and let people understand how they're interacting with the context and the LLM outputs.
The industry has been moving the wrong direction with Claude Code staying closed (despite multiple times leaking the source code!) and the open source Gemini CLI being deprecated in favor of closed source Antigravity CLI.
is this the ChatGPT finance features they launched in May? it keeps asking me to integrate my finance data, but I have doubts about how useful it would actually be (not to mention some distrust about how well they would actually protect my data).
The interesting part is they chose to go with a normalizing flow approach, rather than the industry standard diffusion model approach. Not sure why they chose this direction as I haven’t read the paper yet.
As with many startups (especially ones with high burn rates) OpenAI is risky. It could take down SoftBank and its data center vendors. 6% of nvidia’s revenue is not that concerning, as I’m sure they can find other buyers for those GPUs. But I really don’t buy the argument that OpenAI is the gen AI industry. If they ceased to exist tomorrow, the tech/genAI industry would just trundle along. At this point the tech is quite commodotize.
Also consider getting rid of the em-dashes. I don't know if you mostly vibe-coded this or not, but the README is pretty clearly AI generated.