gay blue dog
That’s the opposite of what I’m saying. Deepseek is the one under scrutiny, yet they are the only one to publish source code and training procedures of their model.
this has absolutely fuck all to do with anything i’ve said in the slightest, but i guess you gotta toss in the talking points somewhere
e: it’s also trivially disprovable, but i don’t care if it’s actually true, i only care about headlines negative about AI
“the media sucks at factchecking DeepSeek’s claims” is… an interesting attempt at refuting the idea that DeepSeek’s claims aren’t entirely factual. beyond that, intentionally presenting true statements that lead to false impressions is a kind of dishonesty regardless. if you mean to argue that DeepSeek wasn’t being underhanded at all and just very innocently presented their figures without proper context (that just so happened to spurn a media frenzy in their favor)… then i have a bridge to sell you.
besides that, OpenAI is very demonstrably pissing away at least that much money every time they add one to the number at the end of their slop generator
consider this paragraph from the Wall Street Journal:
DeepSeek said training one of its latest models cost $5.6 million, compared with the $100 million to $1 billion range cited last year by Dario Amodei, chief executive of the AI developer Anthropic, as the cost of building a model.
you’re arguing to me that they technically didn’t lie – but it’s pretty clear that some people walked away with a false impression of the cost of their product relative to their competitors’ products, and they financially benefitted from people believing in this false impression.
i think you’re missing the point that “Deepseek was made for only $6M” has been the trending headline for the past while, with the specific point of comparison being the massive costs of developing ChatGPT, Copilot, Gemini, et al.
to stretch your metaphor, it’s like someone rolling up with their car, claiming it only costs $20 (unlike all the other cars that cost $20,000), when come to find out that number is just how much it costs to fill the gas tank up once
i can admit it’s possible i’m being overly cynical here and it is just sloppy journalism on Raffaele Huang/his editor/the WSJ’s part. but i still think that it’s a little suspect on the grounds that we have no idea how many times they had to restart training due to the model borking, other experiments and hidden costs, even before things like the necessary capex (which goes unmentioned in the original paper – though they note using a 2048-GPU cluster of H800’s that would put them down around $40m). i’m thinking in the mode of “the whitepaper exists to serve the company’s bottom line”
btw announcing my new V7 model that i trained for the $0.26 i found on the street just to watch the stock markets burn