DeepSeek announced its new R1 model on January 20. They released a paper on how R1 was trained on January 22. Over the weekend, the DeepSeek app became the number-one download on the Apple App Stor…
Is the R1 model better than all existing models? Well, it benchmarks well. But everyone trains their models to the benchmarks hard. The benchmarks exist to create headlines about model improvements while everyone using the model still sees lying slop machines. No, no, sir, this is much finer slop, with a bouquet from the rotting carcass side of the garbage heap.
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This crash doesn’t mean AI sucks now or that it’s good now. It just means OpenAI, and everyone else whose stock dipped, was just throwing money into a fire. But we knew that.
Slop generators are cheap now, and that’s a sea change — but the output is still terrible slop, just more of it.
this bares repeating. I’ve seen quite a few people declare that DeepSeek fixes all of the issues with LLMs as a technology, but that just isn’t true. a DeepSeek LLM is still an unreliable plagiarism machine with no known use case trained on massive amounts of stolen data, even if OpenAI and other American ghouls were the ones who did the theft in the first place.
there’s a small victory in that Altman and friends were exposed very publicly as lying grifters, and that’s worth celebrating. but it’s very important to not get swept up in a hype wave, especially one crafted by people who are much more competent at managing public opinion than Altman & co. from what I understand: no, this thing isn’t meaningfully open source. no, you can’t run the good version at home. sure, it performs great at the benchmarks we know were designed to be cheated. yeah, DeepSeek LLMs are probably still an environmental disaster for the same reason most supposedly more efficient blockchains are — perverse financial incentives across the entire industry.
but hey, good news for the boy genius Prompt Engineer at your company: he gets to requisition another top end gaming PC, absolutely drowning in RGB, to run the shit version of DeepSeek on. maybe in a couple months he can spin switching from OpenAI’s rentseeking to a DeepSeek LLM startup’s slightly cheaper rentseeking into a mild pay bump.
e: see david’s reply, I’m wrong about not being able to run the full version at home — but you need $6000 of fairly specific hardware and it’s molasses slow
yeah, DeepSeek LLMs are probably still an environmental disaster for the same reason most supposedly more efficient blockchains are — perverse financial incentives across the entire industry.
the waste generation will expand to fill the available data centers
oops all data centers are full, we need to build more data centers
ah, I stand corrected! the figures I was looking at previously were for doing it at acceptable speeds in a data center.
can you imagine the intensity of the RGB in the boy genius Prompt Engineer’s new $6000 custom top end gaming PC with server components? maybe they’ll have the LLM slowly plagiarize them a Python script that turns on more RGB when the GPU’s under load.
SoftBank, one of the big backers behind Stargate, is notorious for WeWork-level funding disasters — but five days from floating the idea to the crash might be a new record.
I must've read the words "Jevon's Paradox" a hundred times today, I didn't realize that many people had their livelihood predicated on NVidia going to the moon forevermore.
Aside from stitching together a bigger and bigger trenchcoat, has open AI done anything else? Just goes to show how vacuous LLMs are if this is what it takes to catch up/outpace them.
Like, it's not even THAT much better. I mean, not so much so that everyone should flood it lmao. The main plus was no restriction on tokens used, but that's useless when it's getting overloaded all the time.
I would say it's just barely noticeably better than the free tier of GPT. Which makes it a little annoying to go back but w/e.