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DeepSeek v4

api-docs.deepseek.com

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Re: DeepSeek v4

#471

Post by hodgehog11 »

pm2r wrote: post #352
hodgehog11 wrote: post #324

Earlier quoted context omitted.

I don't want to give away too much due to anonymity reasons, but the problems are generally in the following areas (in order from hardest to easiest): - One problem on using quantum mechanics and C*-algebra techniques for non-Markovian stochastic processes. The interchange between the physics and probability languages often trips the models up, so pretty much everything tends to fail here. - Three problems in random…

It would be wonderful to have a deeper insight, but I understand that you can disclose your identity (I understand that you work in applied research field, right ? )

Yes, I do mostly applied work, but I come from a background in pure probability so I sometimes dabble in the fundamental stuff when the mood strikes.

Happy to try to answer more specific questions if anyone has any, but yes, these are among my active research projects so there's only so much I can say.

Re: DeepSeek v4

#472

Post by _blk »

dalemhurley wrote: post #326
sudo_cowsay wrote: post #292

Earlier quoted context omitted.

I sometimes wonder if there are any security risks with using Chinese LLMs. Is there?

Theoretically yes. It is entirely possible to poison the training data for a supply chain attack against vibe coders. The trick would be to make it extremely specific for a high value target so it is not picked up by a wide range of people. You could also target a specific open source project that is used by another widely used product. However there is so many factors involved beyond your control that it would not b…

Would be interesting to hook up a much simpler LLM as fact checker to see when errors are introduced.

If I had to place a hidden target it'd probably be around RNGs or publicly exposed services..

Re: DeepSeek v4

#473

Post by khalic »

jari_mustonen wrote: post #239

Open Source as it gets in this space, top notch developer documentation, and prices insanely low, while delivering frontier model capabilities. So basically, this is from hackers to hackers. Loving it! Also, note that there's zero CUDA dependency. It runs entirely on Huawei chips. In other words, Chinese ecosystem has delivered a complete AI stack. Like it or not, that's a big news. But what's there not to like when…

Open weight and open source are not the same

Re: DeepSeek v4

#474

Post by laurentiurad »

jari_mustonen wrote: post #239

Open Source as it gets in this space, top notch developer documentation, and prices insanely low, while delivering frontier model capabilities. So basically, this is from hackers to hackers. Loving it! Also, note that there's zero CUDA dependency. It runs entirely on Huawei chips. In other words, Chinese ecosystem has delivered a complete AI stack. Like it or not, that's a big news. But what's there not to like when…

not a full AI stack. Training still runs on NVIDIA chips.

Re: DeepSeek v4

#475

Post by hodgehog11 »

ant6n wrote: post #96
Aliabid94 wrote: post #14

MMLU-Pro: Gemini-3.1-Pro at 91.0 Opus-4.6 at 89.1 GPT-5.4, Kimi2.6, and DS-V4-Pro tied at 87.5 Pretty impressive

Funny how Gemini is theoretically the best -- but in practice all the bugs in the interface mean I don't want to use it anymore. The worst is it forgets context (and lies about it), but it's very unreliable at reading pdfs (and lies about it). There's also no branch, so once the context is lost/polluted, you have to start projects over and build up the context from scratch again.

Most of these tests are one-prompt in nature. I've also noticed issues with the PDF reader in Gemini which was very frustrating, although it is significantly better now than it was even two weeks ago. On the contrary, now GPT-5 seems to be giving me issues.

In my experience, Gemini is the most insightful model for hard problems (particularly math problems that I work on).

Re: DeepSeek v4

#476

Post by culi »

patshead wrote: post #189
alecco wrote: post #117

Earlier quoted context omitted.

Please don't slander the most open AI company in the world. Even more open than some non-profit labs from universities. DeepSeek is famous for publishing everything . They might take a bit to publish source code but it's almost always there. And their papers are extremely pro-social to help the broader open AI community. This is why they struggle getting funded because investors hate openness. And in China they strug…

DeepSeek's models are indeed open weight. Why do you feel that pointing this out would be considered slander?

I think they were reading GP's comment as a correction. Like "not open-source, just open weight". I'm not sure if their reading was accurate but I enjoyed their high effort comment nonetheless

Re: DeepSeek v4

#478

Post by lanthissa »

chvid wrote: post #322

The incredible arrogance and hybris of the American initiated tech war - it is just a beautiful thing to see it slowly fall apart. The US-China contest aside - it is in the application layer llms will show their value. There the field, with llm commoditization and no clear monopolies, is wide open. There was a point in time where it looked like llms would the domain of a single well guarded monopoly - that would have…

not really, china has gone domestic for everything as soon as it could.

its naive to think they would have stayed on a 'western' stack.

Most of the time 'losing' isn't making a bad choice its being put in a situation where you have no good choices.

Re: DeepSeek v4

#479

Post by computably »

deaux wrote: post #95
madagang wrote: post #39

Earlier quoted context omitted.

Their Chinese announcement says that, based on internal employee testing, it is not as good as Opus 4.6 Thinking, but is slightly better than Opus 4.6 without Thinking enabled.

That's super interesting, isn't Deepseek in China banned from using Anthropic models? Yet here they're comparing it in terms of internal employee testing.

> That's super interesting, isn't Deepseek in China banned from using Anthropic models? Yet here they're comparing it in terms of internal employee testing.

I don't see why Deepseek would care to respect Anthropic's ToS, even if just to pretend. It's not like Anthropic could file and win a lawsuit in China, nor would the US likely ban Deepseek. And even if the US gov would've considered it, Anthropic is on their shitlist.

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