OpenAI Furious DeepSeek Might Have Stolen All the Data OpenAI Stole From Us
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Tamaleeeeeeeeesssssss
hot hot hot hot tamaleeeeeeeees
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Right—by “take it down” I meant take down online access to their running instance of it.
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You made me look ridiculously stupid and rightfully so. Actually, I take that back, I made myself look stupid and you made it obvious as it gets! Thanks for the wake up call
If I understand correctly, the model is in a way a dictionary of questions with responses, where the journey of figuring out the response is skipped. As in, the answer for the question "What's the point of existence" is "42", but it doesn't contain the thinking process that lead to this result.
If that's so, then wouldn't it be especially prone to hallucinations? I don't imagine it would respond adequately to the third "why?" in the row.
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To add a tiny bit to what was already explained: you do actually download quite a bit of data to run it locally. The "smaller" 14b model I used was a 9GB download. The 32b one is 20GB and being all text, that's a lot of information.
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I suspect that most usage of the model is going to be companies and individuals running their own instance of it. They have some smaller distilled models based on Llama and Qwen that can run on consumer-grade hardware.
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Imagine if a little bit of those so many millions that so many companies are willing to throw away to the shit ai bubble was actually directed to anything useful.
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Someone should just an make AiPU. I'm tired of all GPUs being priced exorbitantly.
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but does running the program locally allow you to better control the information that it trains on?
in a sense: if you don't let it connect to the internet, it won't be able to take your data to the creators
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You know what else isn’t privacy friendly? Like all of social media.
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Chinese GPUs are not far behind in gflops. Nvidia advantage is CUDA, drivers, interconnection clusters.
AFAIU, deepseek did use cuda.
In general, computing advances have rarely resulted in using half the computers, though I could be wrong at the datacenter/hosting level at the maturity stage.
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Okay, but then why would anyone make non-AiPUs if the tech is the same and they could sell the same amount at a higher cost?
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You kind of get it, it's not really a dictionary, it's more like a set of steps to transform noise that is tinted with your data, into more coherent data. Pass this input through a series of valves that are all open a different amount.
If we set the valves just perfectly, the output will kind of look like what we want it to.
Yes, LLMs are prone to hallucinations, which isn't always actually a bad thing, it's only bad if you are trying to do things that you need 100% accuracy for, like specific math.
I recommend 3blue1browns videos on LLMs for a nice introduction into how they actually work.
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Now I'm imagining "these guys" are named Nicky Mouse
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you don't know what you are talking about and you are too stupid to figure out why here lol
git gud!
