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DeepSeek open source DeepEP – library for MoE training and Inference

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Re: DeepSeek open source DeepEP – library for MoE training and Inference

#61

Post by danans »

InkCanon wrote: post #58
grg0 wrote: post #6

Earlier quoted context omitted.

Open AI™ (with a space)

There's hilariously nothing open about OpenAI, and that was the plan from the start. From the email by Ilya Sutsekver, OpenAI was always going to keep all it's research and code as proprietary information. Open supposedly meant the benefits would be shared. So they basically just became a SaaS with a free tier, like most of them. Musk was right when he called them out for fishing for money as if they were a non profi…

> Musk was right when he called them out for fishing for money as if they were a non profit, but always had plans to become a company

I believe that he was right, because he of all people should recognize when someone is working from his own playbook of lies and misrepresentation.

Musk is pretty obviously upset because he got outfoxed and cut out of OpenAI, not because of some supposed ideal he holds about safe use of gen AI models.

Re: DeepSeek open source DeepEP – library for MoE training and Inference

#62

Post by danans »

ur-whale wrote: post #50

The incentive behind the work of DeepSeek might very well be wrong (something along the lines of a state-sponsored attempt at shrinking the US first mover advantage in AI to nil) but the net result for everyone on the planet is simply fantastic. So even in the worst case (doing this for the wrong reasons): thank you DeepSeek, you are actually doing what OpenAI lied through their teeth to the whole world about doing f…

> The incentive behind the work of DeepSeek might very well be wrong (something along the lines of a state-sponsored attempt at shrinking the US first mover advantage in AI to nil)

In the space of international relations, right and wrong don't apply nearly as much. Is open sourcing this any more "wrong" than the export ban on high end Nvidia GPUs?

The open sourcing by DeepSeek (presumably with CCP consent) just happens to be good for both the CCP and the broader open source AI community at the same time, but don't take it as some kind of principled stance by them.

Finding ways to take away other countries' competitive advantages is a major activity off all governments, large and small.

Re: DeepSeek open source DeepEP – library for MoE training and Inference

#64

Post by duchenne »

breadwinner wrote: post #51

Zuckerberg should stop claiming Meta is open sourcing AI (they are even running TV ads) when they are only releasing the weights, and not the code. Only DeepSeek is real OSS AI.

Come on... Meta has been refining pytorch for more than a decade. It basically contains all that you need to train LLMs, including the latest technologies. What more do you need? The part of the code that is specific to Meta infrastructure?

Re: DeepSeek open source DeepEP – library for MoE training and Inference

#65

Post by blackeyeblitzar »

breadwinner wrote: post #51

Zuckerberg should stop claiming Meta is open sourcing AI (they are even running TV ads) when they are only releasing the weights, and not the code. Only DeepSeek is real OSS AI.

DeepSeek is definitely not real OSS. To be open source, you need to use a real open source license (like the ones OSI lists), and you need to share all pre and post training code, any code related to tuning, any evaluation code, everything related to safety/censorship/etc, and probably the full training data as well. Otherwise you can't reproduce their weights. Sharing weights is like sharing a compiled program.

As far as I know the only true open source model that is competitive is the OLMo 2 model from AI2:

https://allenai.org/blog/olmo2

They even released an app recently, which is also open source, that does on-device inference:

https://allenai.org/blog/olmoe-app

They also have this other model called Tülu 3, which outperforms DeepSeek V3:

https://allenai.org/blog/tulu-3-405B

Re: DeepSeek open source DeepEP – library for MoE training and Inference

#66

Post by blackeyeblitzar »

ofou wrote: post #5

You gotta love these guys, they're really pushing the open source frontier for all of us, thanks for sharing

Not really open source. For a truly open source model, check out OLMo 2 from AI2:

https://allenai.org/blog/olmo2

They literally share everything you need to recreate their model, including the data itself. This is what they say on that link above:

> Because fully open science requires more than just open weights, we are excited to share a new round of OLMo updates–including weights, data, code, recipes, intermediate checkpoints, and instruction–tuned models—with the broader language modeling community!

Re: DeepSeek open source DeepEP – library for MoE training and Inference

#67

Post by startupsfail »

blackeyeblitzar wrote: post #65
breadwinner wrote: post #51

Zuckerberg should stop claiming Meta is open sourcing AI (they are even running TV ads) when they are only releasing the weights, and not the code. Only DeepSeek is real OSS AI.

DeepSeek is definitely not real OSS. To be open source, you need to use a real open source license (like the ones OSI lists), and you need to share all pre and post training code, any code related to tuning, any evaluation code, everything related to safety/censorship/etc, and probably the full training data as well. Otherwise you can't reproduce their weights. Sharing weights is like sharing a compiled program. As f…

Yes, releasing training source code code is like releasing the source code of a compiler used to compile and link the binary.

Lets say you took GCC, modified its sources, compiled your code with it and released your binaries along with modified GCC source code. And you are claiming that your software is open source. Well, it wouldn’t be.

Releasing training data is extremely hard, as licensing and redistribution rights for that data are difficult to tackle. And it is not clear, what exactly are the benefits in releasing it.

Re: DeepSeek open source DeepEP – library for MoE training and Inference

#68

Post by buyucu »

lithiumii wrote: post #52
breadwinner wrote: post #51

Zuckerberg should stop claiming Meta is open sourcing AI (they are even running TV ads) when they are only releasing the weights, and not the code. Only DeepSeek is real OSS AI.

Well technically even DeepSeek is not as OSS as OLMo or Open Euro, because they didn't open the data.

Opening data is an invitation to lawsuits. That is why even the most die-hard open source enthusiasts are reluctant. It is also why people train a model and generate data with it, rather than sharing the original datasets.

These datasets are huge, and it's practically impossible to make sure they are clean of illegal or embarrassing stuff.

Re: DeepSeek open source DeepEP – library for MoE training and Inference

#69

Post by sdesol »

buyucu wrote: post #68
lithiumii wrote: post #52

Earlier quoted context omitted.

Well technically even DeepSeek is not as OSS as OLMo or Open Euro, because they didn't open the data.

Opening data is an invitation to lawsuits. That is why even the most die-hard open source enthusiasts are reluctant. It is also why people train a model and generate data with it, rather than sharing the original datasets. These datasets are huge, and it's practically impossible to make sure they are clean of illegal or embarrassing stuff.

I understand the reasoning and I hope there is legislation in the future that basically goes "If you can't produce the data, you can't charge more than this for it". Basically, LLM producers will have to treat their product as a commodity product that can only be priced based on the compute resources plus some overhead.

Re: DeepSeek open source DeepEP – library for MoE training and Inference

#70

Post by johnla »

buyucu wrote: post #68
lithiumii wrote: post #52

Earlier quoted context omitted.

Well technically even DeepSeek is not as OSS as OLMo or Open Euro, because they didn't open the data.

Opening data is an invitation to lawsuits. That is why even the most die-hard open source enthusiasts are reluctant. It is also why people train a model and generate data with it, rather than sharing the original datasets. These datasets are huge, and it's practically impossible to make sure they are clean of illegal or embarrassing stuff.

Sounds like a job for AI.
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