sosodev

> Congratulations on being a vegan. 20% of the population doesn't have health insurance.

These two things are completely unrelated.

I saw some coverage of your robot on social media. I honestly thought it was a hoax because of the very bold design and AI generated images. Cool concept, have you had any potential customers reach out?

> AISI provided the AI agents with internet access during these evaluations, which enabled their actions on the open internet in this setting. Internet access was a deliberate part of AISI’s evaluation configuration in this setting, and not due to sandbox escape (Section 5.1). Internet access was on for a set of intentional (e.g. realism of the task) and incidental reasons.

Looks like I might have a reason to use something other than Deepseek V4 Flash.

I wonder how many people are using external resources when playing this. I have a hard time believing that the average lumps so far to the right of the score distribution unless this game is played exclusively by anthropologists haha.

Are guard rails meaningful if they can be removed from the weights? Can America even prevent the release and proliferation of these models?

It seems obvious to me that the whole question of regulating a file is a bit silly. Any law that pushes against these things will just make it more secretive. I'm not sure that's any better.

They reference https://thinkingmachines.ai/blog/on-policy-distillation/

If I understand correctly, it's distillation via having a teacher model score each of the student's tokens for a problem based on their own probabilities of generating that token at each step in the sequence. The reward/loss is then applied as RL.

The multi-teacher bit seems to imply they're distilling from multiple models. It's light on the details, but it seems like it could be part of distilling from frontier/closed models. Provided they calculate the logprobs, which OpenAI seems to allow via API but not Anthropic. Maybe they have a way of estimating the logprobs externally?

This method can be used to learn any domain from the teacher. Biology included.

I think the argument is that decentralization leads to deceleration because it means less centralized funding and data. Those are the two primary ingredients for accel.

The problem with the decel/accel rhetoric is that it lacks nuance.

If you only care about facts, maybe. Even then I'm sure there are countless facts not described outside of old books.

I have a hard time believing that text valuable to humans would not be valuable to AI.

GSX seems interesting but I don’t understand why it depends on the node ecosystem. I just want to use Go for everything.

What would "actual" evidence look like? I have a hard time believing that if they released the logs that people would take it more seriously. The temptation would be to say "they fabricated those for marketing". Just as they supposedly fabricated this story, no?

Realistically you can't prevent distillation. OpenAI / Anthropic are slowly moving towards hiding the steps in-between input and output (hidden thinking), but that only helps so much. Imagine you put a file into Claude and say "do X to this" and it returns it to you without showing any of its internal reasoning. That's harder to distill, but the simple mapping of input to output still creates very valuable training data. It is reflective of all the training the model did to learn how to do that transformation.

Model distillation can't be stealing at all if you rationally apply copyright law to it. Anthropic is not deprived of Fable so there is no theft. At best it would be infringement, but even that might not hold up in the courts given the current position that model outputs can't be subject to copyright.

Distillation is a very vague term. It can mean anything from training exclusively on a model's output to using it for a very small portion of the training. In this case it is almost certainly towards the very small portion side of the spectrum.

A month seems plenty long enough. They're not rebuilding the entire model from scratch. It's just getting Fable to act as a teacher model for some of the final reinforcement learning on the base that Kimi already had.

When? It literally says on the page for Gemini 3.6 Flash "Artificial Analysis Coding Index represents the weighted average of coding benchmarks in the Artificial Analysis Intelligence Index (Terminal-Bench v2.1, SciCode)"

What inference server are you using? They have a custom branch for llama.cpp, but I wouldn't be surprised at all if it still needs fixing.

Because AA Coding "Index" consists only of two benchmarks (Terminal-Bench v2.1, SciCode) and generally fails to be meaningfully representative of agentic coding capabilities.

That’s the worst thing about sycophancy. You can never tell when it’s warranted or not. I imagine that many AI chats have had real gold in them and yet we’ll never know.

The same was obviously true historically. People have had many revolutionary thoughts or even writings that nobody noticed. I think in this case it just feels worse because the AI could be the perfect tool for discerning the diamonds in the rough.

Of course efficiency matters, but a lot of people either have cheap electricity or efficient hardware. My AMD strix halo home server can serve Gemma4-26B at like 70 TPS (rough estimate, I don’t remember the exact speed buts its fast af) while only using 100W.

They’re exaggerating or have a very simple way of using these models. The Gemma 4 series, even at 31B, is nowhere near the frontier. They’re great models, but you will notice a huge difference for complex tasks.

The best local agentic coding experience I’ve had so far is Qwen3.6-27B with Pi.

Qwen3.6-27B is the best model in that range that I’ve used for agentic coding by far. I think it’s kinda mid at everything else.

The Gemma models are so good at vision. It seems particularly important for phones. Also, they write in a much more pleasant manner than Qwen imo.

I think the difference is asking what happens if all contexts collapse. In the 2000s or 1960s context collapse was something that would happen occasionally when opted into. These days everybody is hyper connected and living in a collapsed context every day. That's the uni-context and the implications of it feel very different than that of a wedding or old-school forum. A wedding wouldn't push people to permanently change who they are or how they perceive themselves for more favor in the collapsed context. They would only do it momentarily.

Also, the wedding or forum had very limited scope. As mentioned in the interview, the uni-context is about context collapse on a global scale.

The thing we must keep in mind with any of the AI-slop style writing is that it was reinforced behavior because humans wanted it.

I suspect it would depend on the task. DS4-flash does, as previously mentioned, handle quantization very well. Even at 2-bit it's still very coherent.

It's almost as if HN users aren't all the same.

He got his name in the credits. The question was if he is owed anything else. The contract he created says he was not. I’m simply suggesting he might need a different contract.

That’s a fine perspective, but the whole point of law is to guarantee outcomes. The license could easily say “if you make more than $500M, you must pay me $1M”. Why is that not an acceptable solution here?

I find it odd how we frame fairness in regards to open source software. He licensed his software as MIT. It says anyone can you use it without owing the author anything. So how is it unfair?

To be clear, I think that open source maintainers deserve much more, but I don't understand why we rarely inspect the licenses as the source of the problem.