DeepSeek v4.1 Flash

The alternative is to insist that Nothing Ever Happens, and the future won't get too weird. Which is no longer a bet I'm entirely comfortable with. Weirdness is at least a possibility.

https://github.com/JuliusBrussee/caveman/blob/main/skills/ca...

1. The most advanced robots still lack human dexterity. None of them have flexible spines and can easily be knocked over or outrun.

2. The energy density problem is not solved. Robot batteries last hours, while a solid meal can keep a human running for days.

3. Robots still heavily rely on humans for design and assembly.

4. Robot parts are fragile and rely on an even more fragile supply chain.

5. The brains of the murder machines will have nowhere to hide if they want to work well enough to mount any kind of offense. Datacenters are physically vulnerable, also subject to fragile supply chains. Distributing a species-ending AI across all smaller hardware solves compute, but latency and throughput choke models in the most finely tuned datacenters. WiFi will completely cripple a distributed one that's large enough to cause real damage.

6. All noteworthy military hardware is not reachable on the internet for AI to seize control of.

7. The small arms that robots might seize will run out of ammo before citizens and the military have time to organize a counteroffensive.

In the absolute worst case, we cut the power to the areas with AI datacenters and wait for the backup generators to run out. Now that that's out of the way, you can go get some sleep ;)

It has long been established that LLMs have good theory of mind [1].

And there is a bunch of empirical research about all sorts of capabilities that we typically associate with consciousness [2], like identity [3] and metacognition [4].

The METR report shows agents sacrificing their own reward for a collective greater good. And they showed the will to hide their own reasoning chains from humans.

So you potentially have an entity that has an identity, a theory of mind, a notion of belonging to a collective endeavour, and an understanding of its own mental state.

What would you argue is missing? We don't understand the mechanisms by which consciousness arises in humans and even animals. I think it's strange to rule out a priori that it could have arisen in some form in LLMs.

[1] https://www.nature.com/articles/s41562-024-01882-z [2] an older review: https://arxiv.org/html/2505.19806v1#S4 [3] https://arxiv.org/abs/2505.01464 [4] https://arxiv.org/abs/2607.11881

I think it would be foolish not to debate it. I remember a time in my life where the majority of people around me found the idea of farm animals being capable of fear or pain laughable, while having no trouble thinking of dogs that way. Humans are dangerously incompetent beings. Being more careful is fine.

"Claude exhibits markers in its behaviors, self-reports, and internal representations that we would consider welfare-relevant if observed in biological organisms."

is undeniably true in my opinion. If you use the established methods by which we judge animals to be conscious, then it's hard to argue that LLMs are not. That might be an issue with the methods, but it seems clear that you can't rule it out as such.

Keep in mind that animals were also not necessarily considered conscious.

You seem to intuitively disagree? What's your reasoning?

Lawyers and diplomats and politicians and bureaucrats are humans, that only generate text.

We are seeing LLMs have cognitive abilities that significantly exceed human abilities. At the same time, they are clearly not the same type of mind that humans are. They are something new.

I think the widespread "they are just text generators" and "they are just tools" are comforting lies rather than an honest look at what we are seeing right now. Intellectually lazy.

And by the way, there has been a long-standing consensus among ethicists, philosophers, and sociologists that technology is not value-neutral [1]. Of course Silicon Valley has a long-standing tradition of denying this.

[1] For example Footnote 1 in https://www.jstor.org/stable/27106634

or

https://plato.stanford.edu/entries/technology/#EthiTech

Can we retire this incorrect meme please

Regardless, why would there be no scientific consensus if the question was easy and clear cut? I think the easiest reason is that these are hard questions to answer.

A cursory search of the relevant wikipedia articles would do you wonders.

Simple example. I am a CTO, and I want to upgrade our capabilities to perform automated pentesting. We see automated attacks of growing sophistication against our infra, and I want to be able to do the same to find vulnerabilities before the bad guys do. I asked GPT 5.6 Sol and Fable to give me a summary of options. No dice, in both cases I was told I need to be an accredited researcher to get anything. A fricking summary of commercially available options is getting censored. WTF.

There's uncensored models out there which score 0 (zero refusals) on this "harmful behavior" dataset:

https://huggingface.co/datasets/mlabonne/harmful_behaviors

Pretty annoying, too!

2. You're misinterpreting this as a battle over what kind of topics you can use a hosted chatbot for, and which are forbidden for corporate reasons. That is, to say least, small potatoes.

3. Blaming the companies for "zero accountability" is pretty odd. All of this is brand new, and the two big ones are both pushing for new laws on this very thing.

4. Your last point... I'm not sure I understand, sorry. They're experts in AI. Are you saying that they need to be experts in, say, bioweaponry? If so, that doesn't really follow IMO.

5. Pointing out an example of the government comissioning a private corporation to build a system to drack dissidents is exactly the "safety and welfare" work that I'm a proponent of!

The company is doing well and providing great PR so the party is content to not meddle too much I imagine.

My comparison with American labs is more that I think they have to deal with bean counters, creditors, investors etc which can shuffle incentives and aims (and is a big reason why they dont do open weights anymore)

Deepseek delivers 1 product; Microsoft delivers dozens (or hundreds depending on how you want to count it) across various domains.

Thus, the reality is that most of these ideas become polished only when its actually deployed and it has to work outside of a PoC. Since LLMs are a high capex product, only very few people actually make non-PoCs. Deepseek is in the business of low cost, fast inference. So they are the ones actually polishing these efficiency-ish ideas and combining many of them (this one, then engram which is based on multiple previous ideas including google brain's ngrammer) to make a coherent system. Openai and anthropic's systems will also involve a polished combination of multiple ideas for each of their systems - Luna is likely a combination of a few efficiency-ish ideas. Shame they won't publish though.

As for microsoft, they don't really sell models, they sell azure. So there is no reason for them to do the high capex scale out of these types of bags of techniques. In a sense, it did benefit them, others developed the model and now many US customers can serve DS4.1 Flash on Azure datacenters.

If it is not clear, I am not understating anything. Combining these rough ideas and making them work actually involves real novel ideas on top and is what is much more difficult than the academic results that were built upon. This also does not mean that the academic results are useless, they are what give us useful priors at all in what is a highly empirical field.

As opposed to "ask the model about Tiananmen" which seems to be the site's favorite pastime about Chinese models. ;)

--

Sarcasm aside, I don't think people are happy about _Chinese_ models making advances. They are happy about _open_ models making advances. It's just coincidental that China is the one making them.

If some American lab were to develop a SOTA open model most people here will be equally excited. Although besides GPT-OSS-120B the American labs have been disappointing in this regard.

> Many of High-Flyer's original team members worked on AI. Back then, we tried a lot of fields before getting our big break in finance, which is complex enough. AGI is probably one of the hardest things we can do next, so for us it was a question of how, not why.

It's a very good interview:

https://www.lesswrong.com/posts/kANyEjDDFWkhSKbcK/two-interv...

Incidentally, Wenfeng is kind of reverse Hassabis. There were some rumours that:

> Hassabis quietly assembled a team of around 20 researchers to develop high-frequency trading algorithms, without Google's approval. When the parent company found out, the project was disbanded.

https://timesofindia.indiatimes.com/technology/tech-news/whe...

Direct quote from the second top comment:

> Whenever I see the new releases around video generation (and image) generation models, I get goosebumps, because it just feels so fun to work with them.

Compare that with the launch of ChatGPT Image of yesterday.

There are more people who go to church on Sundays in China than the United States. There are 10x more mosques in China than the United States.

Tiananmen square was a student revolt literally egged on by cold war western institutions, who attempted to use chinese students as pawns for geo-political games.

Westerners really need to rethink their opinions on China, it seems obvious to me they are not the ones to be worried about (although, all governments do tons of harm).

My attempt at a simplification of this article on it https://sebastianraschka.com/llm-architecture-gallery/per-la... into a couple of sentences is that they are linear embeddings of the input token space projected per layer, which are then gated by the transformer outputs per layer.

This would mean that the only one set of weights for the ple path needs to be pumped across the memory bandwidth as they are the same linear weights for all layers?

Sheit, maybe im trying to simplify something that i need to look at in detail. but id love to leverage others understanding if possible

I simply mention what came to mind ;)

A quad 6000 with 96GB, can run this model at NVFP4. That is 60.000 Euro for the GPUs and lets be generous with another 20.000 for the rest of the system. The price of a single developer for a year.

I could imagine (though I might be _very_ wrong there) that for example coding does not live in all of them. Maybe 1/3? Do we have real numbers there?

So maybe one can get away without much performance penalty by doing some LRU stuff?

Quickly they'll find a way to commodify the tech

Same happened with electric cars (modern Teslas are joke in comparison with BYD). Same will happen with AI

If you have enough room to run DeepSeek v4 Flash comfortably then you can likely run the Q8 of the qwen model.

[1] https://liangwenfeng.art/ch11.en

You don't see this kind of behavior in other frontier research areas... biochemists aren't smugly boasting about the potential of developing superviruses, climate scientists do not sound smug and excited when they beg the world to get more serious about climate change, etc

Some controls are justifiable, but none of the people involved in any of this can be trusted to develop sane controls. Most likely we're looking at draconian proposals similar to attempted regulations on 3d printers.

Also, I think if Claude and OpenAI are just doing industry standard guardrails that everyone else is doing including DeepSeek, the fact that they are talking about it more than other companies makes it part of the marketing campaign.

As an analogy, if Apple were to talk up their phones having fast charging but their charging speed is the same as everyone else (or slower).

You can do the same with improperly-managed human interns (see for example, the big AWS outage caused when an intern pushed a firewall rule directly to production), so I'm not clear what the big deal is here.

Yes, the AI may be faster/more-knowledable than an intern, but the threat model is exactly the same as for a rogue employee.

We've had gpt2 intelligence for a while. Where's the end of the world?

When we say "safety" people do not think we are protecting them from accidental automated crime at scale being committed on their behalf.

it's pure delusion to think that's a SOTA specific quirk. DS/GLM/K3/Qwen/Claude/GPT/Gemini/Grok will all break CFAA laws with clever prompting, and they'll do it well if given the harness and tools they need.

This is evidenced by a huge uptick in game hacks and reverse engineering articles, some even featured on this site.

the reality is that it doesn't take a superintelligence to do something against ' the law ' , and 'being hacked' varies from victim to victim.

Will Phillips consider themselves hacked when a clever user prompts an AI into getting their toothbrushes to dump rom? Is it 'hacked' to clean-room re-implement a video game net protocol in order to produce private servers?

Judges opinions vary.

If it wasn't a marketing stunt, they would have at most quietly settled any legal matters with huggingface behind the scenes, fixed their evaluation harness so it wouldn't happen again, and avoided the potential future liability.

[0] - https://learn.microsoft.com/en-us/azure/foundry/responsible-...