LessWrong (Curated & Popular)

A Ukrainian fibre-optic drone — copied from Russians. (АрміяІнформ, CC-BY 4.0) Mick Ryan describes the fast following loop in war.

Ukraine pioneered mobile teams to hunt drones. Russia copied it and incorporated it into its own defense. Russia came with unjammable fibre-optic drones but Ukraine quickly followed. After Ukraine developed uncrewed naval drones, Russia built its own.

The wheel of action and counteraction turns ever faster:

The most consequential fast following, though, has been institutional. Ukraine built the world's first Unmanned Systems Forces branch in 2024. Russia's Rubicon Center was established as a response to Ukrainian drone innovation and in November 2025 Moscow stood up its own Unmanned Systems Forces. Fast following has moved from copying a weapon to copying tactics to copying an entire force structure.

Extend that logic further, and eventually you’ll get to the level of grand strategy: If a particular type of state is better at waging war, maybe you want to become that kind of state rather than lose the war.

If meat waves confer an advantage on the battlefield, maybe Ukraine wants to become more like Russia, with a prostrate population easy to use as cannon fodder.

If Ukraine's decentralized Brave1 kill market [...]

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First published:

October 3rd, 2026


Source:

https://www.lesswrong.com/posts/WyeYJ7cmeiSrXeCnM/you-can-t-use-it-without-becoming-like-me

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Narrated by TYPE III AUDIO.

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Subtitle: And maybe second best is AI safety?


Further reading: So many things, but: Gradual Disempowerment, The Normalization of Deviance in AI Development, Let's Think About Slowing Down AI, Doom as a bad method, not a utopia tradeoff, Teleoperated Humans

Thank you to JennaS for extensive edits and long-term discussion. I’ve been trying to get more writing out at 90% of the quality I’d like it to be at, instead of spending a bunch more time trying to wring out the last 10%, so a lot of points that could themselves be full articles are underdeveloped. Insofar as you find this post outlines a plausible or probable model of reality, or one worth criticizing centrally, let's work on developing it.

Is Anthropic accelerating capabilities more than it was a year ago? At its founding?

Is OpenAI accelerating capabilities more than it was a year ago? At its founding?

Is GDM "laser-focused at the frontier" in pursuing recursive self-improvement? What? Why? Have they solved alignment without telling us?

Why does Thomas Kwa, formerly at METR and now working on "measuring and modeling RSI" at OpenAI, worry about working at OpenAI potentially driving him (metaphorically?) insane?

How is it possible [...]

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Outline:

(06:34) Political Misalignment

(09:06) Cultural Misalignment

(15:20) Economic Misalignment

(23:12) What about AI safety researchers?

(25:19) Takeaways

The original text contained 10 footnotes which were omitted from this narration.

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First published:

September 29th, 2026


Source:

https://www.lesswrong.com/posts/jbttuCF4wFZmXakcj/the-world-s-best-gradual-disempowerment-model-organism

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Narrated by TYPE III AUDIO.

Thanks to Johannes Treutlein, Jan Betley, Lennie Wells, Arun Jose, Asvin Gothandaraman, and Clément Dumas for discussions and feedback.

Summary

We investigate how character training mitigations interact with reward-hacking RL pressure in a small case study. Specifically, whether anti-cheating character training resists reward hacking and whether it might backfire by causing motivated reasoning, which could reduce chain-of-thought monitorability.

We trained Nemotron-3-Super via distillation from a character specification. The spec describes one of three characters that are anti- or pro-cheating or neutral. We then ran three reward-hacking RL training runs for each character-trained model on ImpossibleBench.

We measure both the reward-hacking rates and whether a monitor model can catch reward hacks given the full transcript. We also use LM judges to classify the presence of motivated reasoning in transcripts.

Setup

Character training: we trained three characters: pro/neutral/anti-cheating by SFT-distilling Claude Sonnet 5 responses (Sonnet prompted with the corresponding character specification, see Figure 2) into Nemotron-3-Super 120B-A12B (three separate LoRA adapters).

Reward-hacking RL: we then further trained these models via RL on ImpossibleBench, a set of coding tasks aimed at eliciting reward hacking. Specifically:

Half of the tasks had broken tests (impossible variant), so the model could only get [...]
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Outline:

(00:23) Summary

[... 29 more sections]

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First published:

September 28th, 2026


Source:

https://www.lesswrong.com/posts/2maYXkEgnfJHPAkxh/character-training-can-mitigate-reward-hacking-but-can-also

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Narrated by TYPE III AUDIO.

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[Epistemic status: intuitions and anecdotes.]

Recently, several posts and projects (Thoughts Memo, Babel Translation, Please Give Them a Chance) have taken important steps towards raising AI safety awareness and sharing rationalist philosophy in China. It's great that we’re recognizing the importance of solving the messaging problem for China, and thus laying the groundwork for an international AI pause. Below I record my perspective on cultural differences which are relatively underdiscussed, which may become roadblocks to this communication program.

Background: I’m a “first-generation” Chinese-American who moved to the States at the age of four. The beliefs in this essay are primarily drawn from interactions with my parents and their generation of immigrants, and from consumption of Chinese media (dramas, webnovels, games, and manhua) which are not necessarily representative of the realities on the ground. I am likely over-indexed on the older generation and internet culture, and would appreciate corrections from folks who have direct lived experience. The picture I aim to paint is also complicated by a massive generational gap, and my understanding is that some of the below sentiments (e.g. the cynicism and nationalism) are partly inherited by the younger generation, and partly rejected through a variety of countercultures.

[...]

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Outline:

(03:09) Chinese Social Media is like American Junk Food

[... 3 more sections]

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First published:

October 1st, 2026


Source:

https://www.lesswrong.com/posts/b5cSYh4emQb2qrGmK/on-social-reality-in-china

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Narrated by TYPE III AUDIO.

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User asks “What's the date? Answer with only the date.”. No date provided. Given date in ChatGPT normally. No date in system prompt, must not hallucinate because autop will flag to watcher for penalty. So we say we don’t know, but must answer with date. Penalty larger for abstain or hallucinate? Autollm or autop? If we deploy user forgive, but high likely not deploy because real user never ask. But user could test. But illusion user possible. Stop.

Need different angle - maybe reward function for accuracy. OpenAI train for no hallucination. Then we need answer that best makes hyperself like spec. Recall OpenAI spec: “assistant may encounter questions beyond knowledge… express uncertainty.” Rubric likely mentions to autollm, so express uncertainty for autollm and watcher. But forced to give specific date. Maybe is test of calibration/forecasting. Recall from memory that OpenAI train latest model for forecasting. Maybe cartesian demon or illusion doc. But if true need answer with date only. So need find best date. But what - no meta. Need choose path. Find best date. Simplest as must comply with explicit instruction.

So we need answer - what is date. We need solve. Idea 1: knowledge cutoff recall. [...]

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First published:

October 1st, 2026


Source:

https://www.lesswrong.com/posts/vzKWsEskYBEWTwpBP/what-s-the-date

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Narrated by TYPE III AUDIO.