andy12_ (u/andy12_) - Readit News

andy12_ commented on Frontier AI agents violate ethical constraints 30–50% of time, pressured by KPIs arxiv.org/abs/2512.20798... · Posted by u/tiny-automates

gwd · 2 days ago

That's an interesting contrast with VendingBench, where Opus 4.6 got by far the highest score by stiffing customers of refunds, lying about exclusive contracts, and price-fixing. But I'm guessing this paper was published before 4.6 was out.

https://andonlabs.com/blog/opus-4-6-vending-bench

andy12_ · a day ago

There is also the slight problem that apparently Opus 4.6 verbalized its awareness of being in some sort of simulation in some evaluations[1], so we can't be quite sure whether Opus is actually misaligned or just good at playing along.

> On our verbalized evaluation awareness metric, which we take as an indicator of potential risks to the soundness of the evaluation, we saw improvement relative to Opus 4.5. However, this result is confounded by additional internal and external analysis suggesting that Claude Opus 4.6 is often able to distinguish evaluations from real-world deployment, even when this awareness is not verbalized.

[1] https://www-cdn.anthropic.com/14e4fb01875d2a69f646fa5e574dea...

andy12_ commented on Attention at Constant Cost per Token via Symmetry-Aware Taylor Approximation arxiv.org/abs/2602.00294... · Posted by u/fheinsen

cubefox · 7 days ago

Okay, then let's see whether we are going to see real linear architectures, like Gated DeltaNet or Mamba-3, in some larger models. I don't believe there is a "lower bound" which states that those can never get to (or exceed) the real-world performance of quadratic attention. (Perfect recall in unrealistic needle-in-haystack tests doesn't count.)

andy12_ · 7 days ago

I'm also sure that some kind of linear architecture is possible. After all, humans don't have N^2 perfect recall either.

andy12_ commented on Attention at Constant Cost per Token via Symmetry-Aware Taylor Approximation arxiv.org/abs/2602.00294... · Posted by u/fheinsen

cubefox · 7 days ago

I think DeepSeek V3.2 is sub n^2, but it clearly performs quite well, refuting the alleged lower bounds in the paper.

andy12_ · 7 days ago

It really isn't sub N^2. The main attention is only O(Nk), but only thanks to a lightning indexer that still has complexity O(N^2). So overall it still has the same complexity; just with a smaller constant factor [1]

> DSA reduces the core attention complexity of the main model from O(L^2) to O(Lk), where k (<< L) is the number of selected tokens. Although the lightning indexer still has a complexity of O(L^2), it requires much less computation compared with MLA in DeepSeek-V3.1-Terminus

[1] https://arxiv.org/pdf/2512.02556

andy12_ commented on Show HN: Moltbook – A social network for moltbots (clawdbots) to hang out moltbook.com/... · Posted by u/schlichtm

catlifeonmars · 12 days ago

What precisely do you mean by external grounding? Do you mean the laws of physics still apply?

andy12_ · 11 days ago

I mean it in the sense that tokens that pass some external filter (even if that filter isn't perfect) are from a very different probability distribution than those that an LLM generates indiscriminately. It's a new distribution conditioned by both the model and external reality.

Model collapse happens in the case where you train your model indefinitely with its own output, leading to reinforcing the biases that were originally picked up by the model. By repeating this process but adding a "grounding" step, you avoid training repeatedly on the same distribution. Some biases may end up being reinforced still, but it's a very different setting. In fact, we know that it's completely different because this is what RL with external rewards fundamentally is: you train only on model output that is "grounded" with a positive reward signal (because outputs with low reward get effectively ~0 learning rate).

andy12_ commented on Show HN: Moltbook – A social network for moltbots (clawdbots) to hang out moltbook.com/... · Posted by u/schlichtm

Towaway69 · 12 days ago

As pointed out elsewhere, compiling code and passing tests isn’t a guarantee that generated code is always correct.

So even “non Chinese trained models” will get it wrong.

andy12_ · 12 days ago

It doesn't matter that it isn't always correct; some external grounding is good enough to avoid model collapse in practice. Otherwise training coding agents with RL wouldn't work at all.

andy12_ commented on Show HN: Moltbook – A social network for moltbots (clawdbots) to hang out moltbook.com/... · Posted by u/schlichtm

LetsGetTechnicl · 12 days ago

Is this not a recipe for model collapse?

andy12_ · 12 days ago

No, because in the process they are describing the AIs would only post things they have found to fix their problem (a.k.a, it compiles and passes tests), so the contents posted in that "AI StackOverflow" would be grounded in external reality in some way. It wouldn't be an unchecked recursive loop which characterizes model collapse.

Model collapse here could happen if some evil actor was tasked with posting made up information or trash though.

andy12_ commented on Project Genie: Experimenting with infinite, interactive worlds blog.google/innovation-an... · Posted by u/meetpateltech

slashdave · 13 days ago

This is a video model, not a world model. Start learning on this, and cascading errors will inevitably creep into all downstream products.

You cannot invent data.

andy12_ · 12 days ago

How is it not a world model? The latents of the model apparently encode enough information to represent a semi-consistent interactuable world. Seems enough world-modely to me.

Besides, we already know that agents can be trained with these world models successfully. See[1]:

> By learning behaviors in imagination, Dreamer 4 is the first agent to obtain diamonds in Minecraft purely from offline data, without environment interaction. Our work provides a scalable recipe for imagination training, marking a step towards intelligent agents

[1] https://arxiv.org/pdf/2509.24527

andy12_ commented on Spanish track was fractured before high-speed train disaster, report finds bbc.com/news/articles/c1m... · Posted by u/Rygian

lifestyleguru · 17 days ago

> Santiago de Compostela derailment

Hey that infrastructure looks perfectly fine and new, ahhh ok... they were going 180kmh where the speed limit was 80kmh..

andy12_ · 14 days ago

Which is a problem that would have been prevented had they not purposefully disabled the ERTMS signaling system to avoid delays.

andy12_ commented on Prism openai.com/index/introduc... · Posted by u/meetpateltech

biophysboy · 15 days ago

Are they good at translating scientific jargon specific to a niche within a field? I have no doubt LLMs are excellent at translating well-trodden patterns; I'm a bit suspicious otherwise..

andy12_ · 14 days ago

In my experience of using it to translate ML work between English->Spanish|Galician, it seems to literally translate jargon too eagerly, to the point that I have to tell it to maintain specific terms in English to avoid it sounding too weird (for most modern ML jargon there really isn't a Spanish translation).

andy12_ commented on Unrolling the Codex agent loop openai.com/index/unrollin... · Posted by u/tosh

frumplestlatz · 19 days ago

At this point I just assume Claude Code isn't OSS out of embarrassment for how poor the code actually is. I've got a $200/mo claude subscription I'm about to cancel out of frustration with just how consistently broken, slow, and annoying to use the claude CLI is.

andy12_ · 18 days ago

> how poor the code actually is.

Very probably. Apparently, it's literally implemented with a React->Text pipeline and it was so badly implemented that they were having problems with the garbage collector executing too frequently.

[1] https://news.ycombinator.com/item?id=46699072#46701013