- cross-posted to:
- fuck_ai@lemmy.world
- cross-posted to:
- fuck_ai@lemmy.world
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I’m sorry but this says nothing about how they lied about the training cost - nor does their citation. Their argument boils down to “that number doesn’t include R&D and capital expenditures” but why would that need to be included - the $6m figure was based on the hourly rental costs of the hardware, not the cost to build a data center from scratch with the intention of burning it to the ground when you were done training.
It’s like telling someone they didn’t actually make $200 driving Uber on the side on a Friday night because they spent $20,000 on their car, but ignoring the fact that they had to buy the car either way to get to their 6 figure day job
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
banned from use by government employees in Australia
So is every other AI except copilot built into Microsoft products. Government employees can’t use chatgpt directly. So this point is a bit disingenuous.
Even if they greatly underreported costs and their services are banned: the models are out there, open source and way more efficient than anything Meta and OpenAI could produce.
So it’s pretty obvious that the tech giants are burning money for mediocre output.
I’m very confused by this, I had the same discussion with my coworker. I understand what the benchmarks are saying about these models, but have any of y’all actually used deepseek? I’ve been running it since it came out and it hasn’t managed to solve a single problem yet (70b param model, I have downloaded the 600b param model but haven’t tested it yet). It essentially compares to gpt-3 for me, which only cost OpenAI like $4-9 million to train (can’t remember the exact number right now).
I just do not see the “efficiency” here.
what if none of it’s good, all of it’s fraud (especially the benchmarks), and having a favorite grifter in this fuckhead industry is just too precious
well, it’s free to download and run locally so i struggle to see what the grift is
fuck off promptfan
i haven’t seen another reasoning model that’s open and works as well… it’s LLM base is for sure about GPT-3 levels (maybe a bit better?) but like the “o” in GPT-4o
the “thinking” part definitely works for me - ask it to do maths for example, and it’s fascinating to see it break down the problem into simple steps and then solve each step
the “thinking” part definitely works for me
[bites tongue, tries really hard to avoid the obvious riposte]
I’m sure the next AI will be the ethical, uncensored, environmentally sustainable one…
wait, 2021 was when crypto was still a thing vcs poured money into, so that might be yet another case of crypto to ai pivot
Jesus you still think AI is comparable to crypto? What year are you in 2022?
off you fuck
mods, offer him a battle he has no chance of winning
ai is pushed by the same people as crypto, uses the same resources as crypto, captures attention of the same libertarian-brained vcs wanting to build their neofeudal empires, gives result equally as useless, unwanted and aggressively pushed by people that bought into it, not to mention crimes against environment, logic, abuse of workforce or general waste of everyone’s time and attention. but nOo iTs CoMpLeTeLy dIfFeReNt tHiS tImE
Is that the whale mini boss from Dive Man’s stage in MegaMan 4?
sure is!
I’m still just impressed you can teach whales communism
Pretty standard for AI -except for the first part
