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DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via RL

arxiv.org

111–120 of 1001 posts

Re: DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via RL

#111

I've always been leery about outrageous GPU investments, at some point I'll dig through and find my prior comments where I've said as much to that effect. The CEOs, upper management, and governments derive their importance on how much money they can spend - AI gave them the opportunity for them to confidently say that if you give me $X I can deliver Y and they turn around and give that money to NVidia. The problem wa…

The results never fell off significantly with more training. Same model with longer training time on those bigger clusters should outdo it significantly. And they can expand the MoE model sizes without the same memory and bandwidth constraints.

Still very surprising with so much less compute they were still able to do so well in the model architecture/hyperparameter exploration phase compared with Meta.

Re: DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via RL

#112
post #53
post #35

Reddit's /r/chatgpt subreddit is currently heavily brigaded by bots/shills praising r1, I'd be very suspicious of any claims about it.

You can try it yourself, it's refreshingly good.

Agreed. I am no fan of the CCP but I have no issue with using DeepSeek since I only need to use it for coding which it does quite well. I still believe Sonnet is better. DeepSeek also struggles when the context window gets big. This might be hardware though.

Having said that, DeepSeek is 10 times cheaper than Sonnet and better than GPT-4o for my use cases. Models are a commodity product and it is easy enough to add a layer above them to only use them for technical questions.

If my usage can help v4, I am all for it as I know it is going to help everyone and not just the CCP. Should they stop publishing the weights and models, v3 can still take you quite far.

Re: DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via RL

#114

I've always been leery about outrageous GPU investments, at some point I'll dig through and find my prior comments where I've said as much to that effect. The CEOs, upper management, and governments derive their importance on how much money they can spend - AI gave them the opportunity for them to confidently say that if you give me $X I can deliver Y and they turn around and give that money to NVidia. The problem wa…

Latest GPUs and efficiency are not mutually exclusive, right? If you combine them both presumably you can build even more powerful models.

Of course optimizing for the best models would result in a mix of GPU spend and ML researchers experimenting with efficiency. And it may not make any sense to spend money on researching efficiency since, as has happened, these are often shared anyway for free.

What I was cautioning people was be that you might not want to spend 500B on NVidia hardware only to find out rather quickly that you didn't need to. You'd have all this CapEx that you now have to try to extract from customers from what has essentially been commoditized. That's a whole lot of money to lose very quickly. Plus there is a zero sum power dynamic at play between the CEO and ML researchers.

Re: DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via RL

#115

The US Economy is pretty vulnerable here. If it turns out that you, in fact, don't need a gazillion GPUs to build SOTA models it destroys a lot of perceived value. I wonder if this was a deliberate move by PRC or really our own fault in falling for the fallacy that more is always better.

It’s not just the economy that is vulnerable, but global geopolitics. It’s definitely worrying to see this type of technology in the hands of an authoritarian dictatorship, especially considering the evidence of censorship. See this article for a collected set of prompts and responses from DeepSeek highlighting the propaganda: https://medium.com/the-generator/deepseek-hidden-china-polit... But also the claimed cost i…

have you tried asking chatgpt something even slightly controversial? chatgpt censors much more than deepseek does.

also deepseek is open-weights. there is nothing preventing you from doing a finetune that removes the censorship. they did that with llama2 back in the day.

Re: DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via RL

#116

Earlier quoted context omitted.

China is actually just one person (Xi) acting in perfect unison and its purpose is not to benefit its own people, but solely to undermine the West.

Can't tell if sarcasm. Some people are this simple minded.

Ye, but "acting in perfect unison" would be a superior trait among people that care about these things which gives it a way as sarcasm?

Re: DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via RL

#117
post #16

Earlier quoted context omitted.

With $5.5M, you can buy around 150 H100s. Experts correct me if I’m wrong but it’s practically impossible to train a model like that with that measly amount. So I doubt that figure includes all the cost of training.

It's even more. You also need to fund power and maintain infrastructure to run the GPUs. You need to build fast networks between the GPUs for RDMA. Ethernet is going to be too slow. Infiniband is unreliable and expensive.

You’ll also need sufficient storage, and fast IO to keep them fed with data.

You also need to keep the later generation cards from burning themselves out because they draw so much.

Oh also, depending on when your data centre was built, you may also need them to upgrade their power and cooling capabilities because the new cards draw _so much_.

Re: DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via RL

#118

I've always been leery about outrageous GPU investments, at some point I'll dig through and find my prior comments where I've said as much to that effect. The CEOs, upper management, and governments derive their importance on how much money they can spend - AI gave them the opportunity for them to confidently say that if you give me $X I can deliver Y and they turn around and give that money to NVidia. The problem wa…

Agree. The "need to build new buildings, new power plants, buy huge numbers of today's chips from one vendor" never made any sense considering we don't know what would be done in those buildings in 5 years when they're ready.

>in 5 years

Or much much quicker [0]

[0] https://timelines.issarice.com/wiki/Timeline_of_xAI

Re: DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via RL

#119

The US Economy is pretty vulnerable here. If it turns out that you, in fact, don't need a gazillion GPUs to build SOTA models it destroys a lot of perceived value. I wonder if this was a deliberate move by PRC or really our own fault in falling for the fallacy that more is always better.

Seeing what china is doing to the car market, I give it 5 years for China to do to the AI/GPU market to do the same.

This will be good. Nvidia/OpenAI monopoly is bad for everyone. More competition will be welcome.

Re: DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via RL

#120
post #35

Reddit's /r/chatgpt subreddit is currently heavily brigaded by bots/shills praising r1, I'd be very suspicious of any claims about it.

The amount of astroturfing around R1 is absolutely wild to see. Full scale propaganda war.

I would argue there is too little hype given the downloadable models for Deep Seek. There should be alot of hype around this organically.

If anything, the other half good fully closed non ChatGPT models are astroturfing.

I made a post in december 2023 whining about the non hype for Deep Seek.

https://news.ycombinator.com/item?id=38505986

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