Yeah, you're right, I was conflating the excusing bit.
I haven't worked with serious ML engineers, but having worked in large webdev there's usually a team involved in these projects, including senior none devs who would ensure the correct checks and balances are in place before go live. Does this not happen in ML projects? (of course there are always exceptions and unknowns that will slip through, I don't know if that was the case here, or something else)
> Yeah, you're right, I was conflating the excusing bit.
No worries. :)
> Does this not happen in ML projects?
Consistently? No. At the level of e.g. OpenAI/Anthropic? It is mandatory. These are not just research labs, they're product (ChatGPT, Claude) companies. These American companies have done a reasonable job at hiring for all sorts of skillsets to keep things well rounded.
Perhaps DeepSeek hasn't learned this lesson yet... Or, well - it could be far more complicated than that. Speculating is only so useful with so little information.
I haven't worked with serious ML engineers, but having worked in large webdev there's usually a team involved in these projects, including senior none devs who would ensure the correct checks and balances are in place before go live. Does this not happen in ML projects? (of course there are always exceptions and unknowns that will slip through, I don't know if that was the case here, or something else)