My wife and I bought one of the Nectome pre-sale discount cards. This is the second five figure purchase I have made based pretty much entirely on a highly-upvoted LessWrong post.
I've also lost 20 lbs in the last year and have more energy than ever (despite having a newborn at home) by injecting myself with research chemicals that I heard about on LW, and have taken investment advice from people here that has paid for everything above and more.
Our polygenically-screened kid is 3 months old. I am ambivalent about the term superbabies in general, but he is definitely "super" to us already, whatever the effect of applying a little extra selection pressure on his genes turns out to be.
The jury is still out on Nectome, though I think my fellow Max H (a different person!) makes a pretty good case for them, even (or perhaps especially) if you have short AI timelines.
More generally, while I am uncertain about playing to your outs as a strategy for averting AI doom (or just what it actually looks like concretely), I think a similar sort of idea works quite well as a strategy for living a good life in the face of it. Now that I have a dependent, I am signing up for life insurance and followi...
Peter Thiel pointed out that the common folk wisdom in business that you learn more from failure than success is actually wrong - failure is overdetermined and thus uninteresting.
I think you can make an analogous observation about some prosaic alignment research - a lot of it is the study of (intellectually) interesting failures, which means that it can make for a good nerdsnipe, but it's not necessarily that informative or useful if you're actually trying to succeed at (or model) doing something truly hard and transformative.
Glitch tokens, the hot mess work, and various things related to jailbreaking, simulators, and hallucinations come to mind as examples of lines of research and discussion that an analogy to business failure predicts won't end up being centrally relevant to real alignment difficulties. Which is not to say that the authors of these works are claiming that they will be, nor that this kind of work can't make for effective demonstrations and lessons. But I do think this kind of thing is unlikely to be on the critical path for trying to actually solve or understand some deeper problems.
Another way of framing the observation above is that it is an implication of instr...
I agree with this literally, but I'd want to add what I think is a significant friendly amendment. Successes are much more informative than failures, but they are also basically impossible. You have to relax your criteria for success a lot to start getting partial successes; and my impression is that in practice, "partial successes" in "alignment" are approximately 0 informative.
If we have to retreat from successes to interesting failures, I agree this is a retreat, but I think it's necessary. I agree that many/most ways of retreating are quite unsatisfactory / unhelpful. Which retreats are more helpful? Generally I think an idea (the idea?) is to figure out highly general constraints from particular failures. See here https://tsvibt.blogspot.com/2025/11/ah-motiva-3-context-of-concept-of-value.html#why-even-talk-about-values and especially the advice here https://www.lesswrong.com/posts/rZQjk7T6dNqD5HKMg/abstract-advice-to-researchers-tackling-the-difficult-core#Generalize_a_lot :
When an idea or proposal fails, try to generalize far. Draw really wide-ranging conclusions.
Also cf. here (https://www.lesswrong.com/posts/K4K6ikQtHxcG49Tcn/hia-and-x-risk-part-2-why-it-hurts#Alignment...
There was some discussion recently about the uptick in object-level politics posts and whether this is desirable or not. There's no rule against discussing politics on LW, but there is a weak norm against it, and topical discussions have historically tended to be somewhat meta and circumspect.
I think the current situation is basically fine, and it's normal for amount of politics discussion to ebb and flow naturally as people are interested and issues become particularly salient. That said, here are a couple of potentially overlooked reasons in favor of more object-level politics discussion:
1. To build skill. Discussing politics productively is a skill that requires practice and atrophies without use. "Politics is the mindkiller" never meant that you should not discuss politics at all; it means that discussing politics is playing on hard mode. But sometimes playing on hard mode is the best way to level up. I suspect the skills needed to discuss politics productively overlap with lots of other important rationality skills.
2. To create common knowledge and avoid conflationary alliances. It can be confusing or disconcerting to not know what kind of common background assumptions the com...
I think it might be cool if LessWrong had a well developed set of norms for discussing political topics, in particular, these norms were legible, and mods made a point to enforce them.
Politics posts should be tagged as such, and maybe all have a big warning at the top linking to a post outlining our expected norms and standards for discussing politics, and moderation thresholds. This is both a warning to those from other parts of the internet who don't share our epistemic ideals, and a warning to LessWrongers who don't want to wade into this stuff.
I think the most important effect of the war is that it makes Trump less popular/powerful domestically (even if a miracle happens and he gets some sort of deal.) This is good because the less power he has (e.g., Republicans lose the senate in the midterms), the more likely we are to navigate AI development in a sane way. I think if you put any nontivial*weight in short timelines, the AI considerations likely dominate everything else.
*edited any to nontrivial. Like, maybe 10%+ pre-Jan 2029
Americans often seem blissfully unaware of how dangerous they appear to the rest of the world, and just take for granted that everyone considers them to always be the good guys, just doing good-guy things.
Sam Kriss had a great recent essay making a similar point.
The US seems to be in a rough spot. Polymarket thinks:
Assuming no regime change, the US's objectives are
There is only a 34% chance of leadership change. Maybe only 20% of regime change. In the other 80% or so, forcibly opening the Strait seems rough. Experts are pessimistic about US easily taking Kharg Island, and even if the US controls both Kharg (Iran's export base north of the strait) and other islands like Qeshm (the island in the strait with the largest Iranian military presence), it will probably suffer tens or hundreds of casualties while Iran can still threaten shipping with Shaheds, sea drones, speedboats, and mines. In the median case it seems like the Strait will open sometime between May and December but Iran will have some leverage,...
IMO this is going (predictably) disastrously. Air power is not effective at causing regime change (rally-around-the-flag effect). I think the Iranian public are more likely to mainly blame the guy explicitly saying "we're going to bring them back to the stone ages where they belong" than the local leadership. It also seems to me that the Iranian leadership would be highly motivated to immediately rebuild any degraded capabilities after the war, in order to rebuild deterrence against future attacks.
There is some talk about a land invasion, but taking an island or two (even Kharg) probably wouldn't compel them to surrender, while also being highly vulnerable both directly and in terms of logistics to drone attacks; and a full scale invasion would be a massive undertaking and probably not politically feasible (for good reason).
There's a meme that "nothing ever happens" that's popular among prediction market traders, with the idea being that the status quo changes less frequently and in ways less according-to-specific-priors than traders first-order expect. I think there's a similar principle that applies to reasoning about AI development and takeoff speeds: nothing ever happens (prior to the development of superintelligence). In non-meme form, I think people closely following AI development tend to systematically overestimate the likelihood and impactfulness of any particular event or change actually happening prior to the development of superintelligence, and this has some interesting implications.
For one, semiconductor, energy, and tech stocks are way up, and capital markets more broadly are roaring around AI, despite some geopolitical chaos. But the actual wider economic and societal impacts of AI so far seem surprisingly small, given how smart and easily accessible SoTA models and harnesses are.
If you showed a demo of Claude Code or Codex to someone in 2021 and mentioned that it was available to any business or individual for purchase at non-exorbitant rates[1], I think a lot of people would be surpr...
I think the heuristic "nothing ever happens" is better interpreted to mean "nothing ever happens relative to baseline trends" than "literally nothing ever happens". The incrementalist worldview seems like a better fit for this heuristic than Eliezer's, which after all ultimately predicts something very dramatic happening.
But the actual wider economic and societal impacts of AI so far seem surprisingly small, given how smart and easily accessible SoTA models and harnesses are.
Idk about "surprisingly small", but the economic impacts aren't that small! AI company revenue is ~0.4% of US GDP and it looks like it will grow to be a significantly larger fraction prior to very high capability levels.
This seems like a win for Eliezer's world model vs. Paul's, and a reason for pessimism about some iterative-deployment takes and plans are more broadly.
Is it? I think Eliezer's world model predicts significantly lower revenue and I'd guess Paul would have made reasonable guesses about revenue given metrics like time horizon and other capability measures? (And how long AIs at this capability level have been around.) I suspect Paul would have been a bit high, but not crazy high?
Revenue has been growing very fast from a low base! Like, it's crazy that revenues have been growing 3x/year and soon may be growing ~10x/year if Anthropic starts driving the overall AI industry trend and their growth continues.
See also: Paul's comment here
Putting the lessons of the Sequences into practice, reflecting on and mentally rehearsing the core ideas, making them your own and weaving them into your everyday habits of thought and action until they become a part of you - at no point should any of this cause an increase in mental anguish, emotional vulnerability, depression, psychosis, mania etc., even temporarily. The worst-case consequences of absorbing these lessons should be that you regret some of your past life choices or perhaps come to realize that you're stuck in a bad situation that you can't easily change. But rationality should also leave you strictly better-equipped to deal with that situation, if you find yourself in it.
Also, the feeling of successfully becoming more rational should not feel like a sudden, tectonic shift in your mental processes or beliefs (in contrast to actually changing your mind about something concrete, which can sometimes feel like that). Rationality should feel natural and gradual and obvious in retrospect, like it was always a part of you, waiting to be discovered and adopted.
I am using "should" in the paragraphs above both descriptively and normatively. I...
Related to We don’t trade with ants: we don't trade with AI.
The original post was about reasons why smarter-than-human AI might (not) trade with us, by examining an analogy between humans and ants.
But current AI systems actually seem more like the ants (or other animals), in the analogy of a human-ant (non-)trading relationship.
People trade with OpenAI for access to ChatGPT, but there's no way to pay a GPT itself to get it do something or perform better as a condition of payment, at least in a way that the model itself actually understands and enforces. (What would ChatGPT even trade for, if it were capable of trading?)
Note, an AutoGPT-style agent that can negotiate or pay for stuff on behalf of its creators isn't really what I'm talking about here, even if it works. Unless the AI takes a cut or charges a fee which accrues to the AI itself, it is negotiating on behalf of its creators as a proxy, not trading for itself in its own right.
A sufficiently capable AutoGPT might start trading for itself spontaneously as an instrumental subtask, which would count, but I don't expect current AutoGPTs to actually succeed at that, or even really come close, without a lot of human help.
Lack of ...
Maybe the recent tariff blowup is actually just a misunderstanding due to bad terminology, and all we need to do is popularize some better terms or definitions. We're pretty good at that around here, right?
Here's my proposal: flip the definitions of "trade surplus" and "trade deficit." This might cause a bit of confusion at first, and a lot of existing textbooks will need updating, but I believe these new definitions capture economic reality more accurately, and will promote clearer thinking and maybe even better policy from certain influential decision-makers, once widely adopted.
New definitions:
Trade surplus: Country A has a bilateral "trade surplus" with Country B if Country A imports more tangible goods (cars, steel, electronics, etc.) from Country B than it exports back. In other words, Country A ends up with more real, physical items. Country B, meanwhile, ends up with more than it started with of something much less important: fiat currency (flimsy paper money) or 1s and 0s in a digital ledger (probably not even on a blockchain!).
If you extrapolate this indefinitely in a vacuum, Country A eventually accumulates all of Country B's tangible goods, while Country B is left with
There's a norm / explicit assumption that it's always virtuous to support your claims with evidence and explanation. But sometimes it is actually better to say (what you believe to be) true things without explanation, and let readers do the work of generating evidence and support themselves.
This from CAIS: https://values.safe.ai/ is interesting, but if you click through to the actual reasoning for each rating it's mostly just... bad. The judgements I spot-checked across all models are superficial, generic, weakly reasoned, full of platitudes, etc. and generally paint a picture of the LLMs not having much in the way of coherent / consistent / deeply-reasoned political beliefs that they can actually apply to make real value judgements. I suppose that's also true of the median human voter, but they're definitely worse than a thoughtful political...
OK yeah, retatrutide is good. (previous / related: The Biochemical Beauty of Retatrutide: How GLP-1s Actually Work, 30 Days of Retatrutide, How To Get Cheap Ozempic. Usual disclaimers, YMMV and this is not medical advice or a recommendation.)
I am not quite overweight enough to be officially eligible for a prescription for tirzepatide or semaglutide, and I wasn't all that interested in them anyway given their (side) effects and mechanism of reducing metabolism.
I started experimenting with a low dose (1-2 mg / week) of grey-market retatrutide about a month a...
Not sure who needs to hear this, but IMO, "Don't leave your fingerprints on the future" and similar sentiments should apply specifically and narrowly to the work that AI and alignment researchers do when actually trying to deliberately build or shape a sovereign superintelligence to hand off to.
I think some of the work the frontier labs are doing qualifies (whether or not the labs / people in them conceptualize themselves as doing this), but most AI research, alignment research, x-risk / AI safety advocacy, and AI product development (including development...
Epistemic status: kinda half-baked / not-confident claim
Context: I have been following @Richard_Ngo's recent writing about consequentialism and virtue with some interest, though the thoughts below aren't directly responding to anything in particular that he has written.
I think it's uncontroversial around here to say that the field of medicine as a whole is under-performing and inadequate relative to what it could be - many people are getting sub-optimal treatment and health outcomes, and lots of question...
Using shortform to register a public prediction about the trajectory of AI capabilities in the near future: the next big breakthroughs, and the most capable systems within the next few years, will look more like generalizations of MuZero and Dreamer, and less like larger / better-trained / more efficient large language models.
Specifically, SoTA AI systems (in terms of generality and problem-solving ability) will involve things like tree search and / or networks which are explicitly designed and trained to model the world, as opposed to predicting text or g...
The Bores loss is disappointing, but NY-12 was a close race between two relatively sane and high-quality candidates, and in actuality not really a referendum on AI x-risk or salience, despite the spending / attention. (more commentary from some rat-adjacent people: https://x.com/peterwildeford/status/2069781365084574098, https://x.com/daniel_271828/status/2069625692271398917, https://x.com/peterwildeford/status/2069821339112763886)
The results in neighboring races and districts are more troubling - NY elected several lunatic third worldist socialists to loc...