So the boosters are making a big deal about the dump of "proofs" OpenAI has made recently, so I thought I would collect some relevant links in one place...

Stuff on autoformalization:

• A short blog post breaking down some of the bugs found and potential for more
• preprint discussing the problems with natural language to lean in detail and pointing out some blatant inconsistencies in the recent Navier-stokes "proof"
• /r/betteroffline discussion of above preprint
• Some of our very good friends are aware of the problem! Of course, this is lesswrong, so there is a tinge of "this is why we need to be careful with using this sort of approach to make our AI God".
• The soundness bug that led to the fallacious disproof of the Collatz Conjecture

And some other related links:

• OpenAI already retracting a few papers

Let me know in the comments if you have any links I should to these lists!

So seeing the reaction on lesswrong to Eliezer's book has been interesting. It turns out, even among people that already mostly agree with him, a lot of them were hoping he would make their case better than he has (either because they aren't as convinced as him, or they are, but were hoping for something more palatable to the general public).

This review (lesswrong discussion here), calls out a really obvious issue: Eliezer's AI doom story was formed before Deep Learning took off, and in fact was mostly focusing on more GOFAI than neural networks, yet somehow, the details of the story haven't changed at all. The reviewer is a rationalist that still believes in AI doom, so I wouldn't give her too much credit, but she does note this is a major discrepancy from someone that espouses a philosophy that (nominally) features a lot of updating your beliefs in response to evidence. The reviewer also notes that "it should be illegal to own more than eight of the most powerful GPUs available in 2024 without international monitoring" is kind of unworkable.

This reviewer liked the book more than they expected to, because Eliezer and Nate Soares gets some details of the AI doom lore closer to the reviewer's current favored headcanon. The reviewer does complain that maybe weird and condescending parables aren't the best outreach strategy!

This reviewer has written their own AI doom explainer which they think is better! From their limited description, I kind of agree, because it sounds like the focus on current real world scenarios and harms (and extrapolate them to doom). But again, I wouldn't give them too much credit, it sounds like they don't understand why existential doom is actually promoted (as a distraction and source of crit-hype). They also note the 8 GPUs thing is batshit.

Overall, it sounds like lesswrongers view the book as an improvement to the sprawling mess of arguments in the sequences (and scattered across other places like Arbital), but still not as well structured as they could be or stylistically quite right for a normy audience (i.e. the condescending parables and diversions into unrelated science-y topics). And some are worried that Nate and Eliezer's focus on an unworkable strategy (shut it all down, 8 GPU max!) with no intermediate steps or goals or options might not be the best.

I found a neat essay discussing the history of Doug Lenat, Eurisko, and cyc here. The essay is pretty cool, Doug Lenat made one of the largest and most systematic efforts to make Good Old Fashioned Symbolic AI reach AGI through sheer volume and detail of expert system entries. It didn't work (obviously), but what's interesting (especially in contrast to LLMs), is that Doug made his business, Cycorp actually profitable and actually produce useful products in the form of custom built expert systems to various customers over the decades with a steady level of employees and effort spent (as opposed to LLM companies sucking up massive VC capital to generate crappy products that will probably go bust).

This sparked memories of lesswrong discussion of Eurisko... which leads to some choice sneerable classic lines.

In a sequence classic, Eliezer discusses Eurisko. Having read an essay explaining Eurisko more clearly, a lot of Eliezer's discussion seems a lot emptier now.

To the best of my inexhaustive knowledge, EURISKO may still be the most sophisticated self-improving AI ever built - in the 1980s, by Douglas Lenat before he started wasting his life on Cyc. EURISKO was applied in domains ranging from the Traveller war game (EURISKO became champion without having ever before fought a human) to VLSI circuit design.

This line is classic Eliezer dunning-kruger arrogance. The lesson from Cyc were used in useful expert systems and effort building the expert systems was used to continue to advance Cyc, so I would call Doug really successful actually, much more successful than many AGI efforts (including Eliezer's). And it didn't depend on endless VC funding or hype cycles.

EURISKO used "heuristics" to, for example, design potential space fleets. It also had heuristics for suggesting new heuristics, and metaheuristics could apply to any heuristic, including metaheuristics. E.g. EURISKO started with the heuristic "investigate extreme cases" but moved on to "investigate cases close to extremes". The heuristics were written in RLL, which stands for Representation Language Language. According to Lenat, it was figuring out how to represent the heuristics in such fashion that they could usefully modify themselves without always just breaking, that consumed most of the conceptual effort in creating EURISKO.

...

EURISKO lacked what I called "insight" - that is, the type of abstract knowledge that lets humans fly through the search space. And so its recursive access to its own heuristics proved to be for nought. Unless, y'know, you're counting becoming world champion at Traveller without ever previously playing a human, as some sort of accomplishment.

Eliezer simultaneously mocks Doug's big achievements but exaggerates this one. The detailed essay I linked at the beginning actually explains this properly. Traveller's rules inadvertently encouraged a narrow degenerate (in the mathematical sense) strategy. The second place person actually found the same broken strategy Doug (using Eurisko) did, Doug just did it slightly better because he had gamed it out more and included a few ship designs that countered the opponent doing the same broken strategy. It was a nice feat of a human leveraging a computer to mathematically explore a game, it wasn't an AI independently exploring a game.

Another lesswronger brings up Eurisko here. Eliezer is of course worried:

This is a road that does not lead to Friendly AI, only to AGI. I doubt this has anything to do with Lenat's motives - but I'm glad the source code isn't published and I don't think you'd be doing a service to the human species by trying to reimplement it.

And yes, Eliezer actually is worried a 1970s dead end in AI might lead to FOOM and AGI doom. To a comment here:

Are you really afraid that AI is so easy that it's a very short distance between "ooh, cool" and "oh, shit"?

Eliezer responds:

Depends how cool. I don't know the space of self-modifying programs very well. Anything cooler than anything that's been tried before, even marginally cooler, has a noticeable subjective probability of going to shit. I mean, if you kept on making it marginally cooler and cooler, it'd go to "oh, shit" one day after a sequence of "ooh, cools" and I don't know how long that sequence is.

Fearmongering back in 2008 even before he had given up and gone full doomer.

And this reminds me, Eliezer did not actually predict which paths lead to better AI. In 2008 he was pretty convinced Neural Networks were not a path to AGI.

Not to mention that neural networks have also been "failing" (i.e., not yet succeeding) to produce real AI for 30 years now. I don't think this particular raw fact licenses any conclusions in particular. But at least don't tell me it's still the new revolutionary idea in AI.

Apparently it took all the way until AlphaGo (sometime 2015 to 2017) for Eliezer to start to realize he was wrong. (He never made a major post about changing his mind, I had to reconstruct this process and estimate this date from other lesswronger's discussing it and noticing small comments from him here and there.) Of course, even as late as 2017, MIRI was still neglecting neural networks to focus on abstract frameworks like "Highly Reliable Agent Design".

So yeah. Puts things into context, doesn't it.

Bonus: One of Doug's last papers, which lists out a lot of lessons LLMs could take from cyc and expert systems. You might recognize the co-author, Gary Marcus, from one of the LLM critical blogs: https://garymarcus.substack.com/

So, lesswrong Yudkowskian orthodoxy is that any AGI without "alignment" will bootstrap to omnipotence, destroy all mankind, blah, blah, etc. However, there has been the large splinter heresy of accelerationists that want AGI as soon as possible and aren't worried about this at all (we still make fun of them because what they want would result in some cyberpunk dystopian shit in the process of trying to reach it). However, even the accelerationist don't want Chinese AGI, because insert standard sinophobic rhetoric about how they hate freedom and democracy or have world conquering ambitions or they simply lack the creativity, technical ability, or background knowledge (i.e. lesswrong screeds on alignment) to create an aligned AGI.

This is a long running trend in lesswrong writing I've recently noticed while hate-binging and catching up on the sneering I've missed (I had paid less attention to lesswrong over the past year up until Trump started making techno-fascist moves), so I've selected some illustrative posts and quotes for your sneering.

• Good news, China actually has no chance at competing at AI (this was posted before deepseek was released). Well. they are technically right that China doesn't have the resources to compete in scaling LLMs to AGI because it isn't possible in the first place

China has neither the resources nor any interest in competing with the US in developing artificial general intelligence (AGI) primarily via scaling Large Language Models (LLMs).

• The Situational Awareness Essays make sure to get their Yellow Peril fearmongering on! Because clearly China is the threat to freedom and the authoritarian power (pay no attention to the techbro techno-fascist)

In the race to AGI, the free world’s very survival will be at stake. Can we maintain our preeminence over the authoritarian powers?

• More crap from the same author
• There are some posts pushing back on having an AGI race with China, but not because they are correcting the sinophobia or the delusions LLMs are a path to AGI, but because it will potentially lead to an unaligned or improperly aligned AGI
• And of course, AI 2027 features a race with China that either the US can win with a AGI slowdown (and an evil AGI puppeting China) or both lose to the AGI menance. Featuring "legions of CCP spies"

Given the “dangers” of the new model, OpenBrain “responsibly” elects not to release it publicly yet (in fact, they want to focus on internal AI R&D). Knowledge of Agent-2’s full capabilities is limited to an elite silo containing the immediate team, OpenBrain leadership and security, a few dozen US government officials, and the legions of CCP spies who have infiltrated OpenBrain for years.

• Someone asks the question directly Why Should I Assume CCP AGI is Worse Than USG AGI?. Judging by upvoted comments, lesswrong orthodoxy of all AGI leads to doom is the most common opinion, and a few comments even point out the hypocrisy of promoting fear of Chinese AGI while saying the US should race for AGI to achieve global dominance, but there are still plenty of Red Scare/Yellow Peril comments

Systemic opacity, state-driven censorship, and state control of the media means AGI development under direct or indirect CCP control would probably be less transparent than in the US, and the world may be less likely to learn about warning shots, wrongheaded decisions, reckless behaviour, etc. True, there was the Manhattan Project, but that was quite long ago; recent examples like the CCP's suppression of information related to the origins of COVID feel more salient and relevant.

I am still subscribed to slatestarcodex on reddit, and this piece of garbage popped up on my feed. I didn't actually read the whole thing, but basically the author correctly realizes Trump is ruining everything in the process of getting at "DEI" and "wokism", but instead of accepting the blame that rightfully falls on Scott Alexander and the author, deflects and blames the "left" elitists. (I put left in quote marks because the author apparently thinks establishment democrats are actually leftist, I fucking wish).

An illustrative quote (of Scott's that the author agrees with)

We wanted to be able to hold a job without reciting DEI shibboleths or filling in multiple-choice exams about how white people cause earthquakes. Instead we got a thousand scientific studies cancelled because they used the string “trans-” in a sentence on transmembrane proteins.

I don't really follow their subsequent points, they fail to clarify what they mean... In sofar as "left elites" actually refers to centrist democrats, I actually think the establishment Democrats do have a major piece of blame in that their status quo neoliberalism has been rejected by the public but the Democrat establishment refuse to consider genuinely leftist ideas, but that isn't the point this author is actually going for... the author is actually upset about Democrats "virtue signaling" and "canceling" and DEI, so they don't actually have a valid point, if anything the opposite of one.

In case my angry disjointed summary leaves you any doubt the author is a piece of shit:

it feels like Scott has been reading a lot of Richard Hanania, whom I agree with on a lot of points

For reference the ssc discussion: https://www.reddit.com/r/slatestarcodex/comments/1jyjc9z/the_edgelords_were_right_a_response_to_scott/

tldr; author trying to blameshift on Trump fucking everything up while keeping up the exact anti-progressive rhetoric that helped propel Trump to victory.

So despite the nitpicking they did of the Guardian Article, it seems blatantly clear now that Manifest 2024 was infested by racists. The post article doesn't even count Scott Alexander as "racist" (although they do at least note his HBD sympathies) and identify a count of full 8 racists. They mention a talk discussing the Holocaust as a Eugenics event (and added an edit apologizing for their simplistic framing). The post author is painfully careful and apologetic to distinguish what they personally experienced, what was "inaccurate" about the Guardian article, how they are using terminology, etc. Despite the author's caution, the comments are full of the classic SSC strategy of trying to reframe the issue (complaining the post uses the word controversial in the title, complaining about the usage of the term racist, complaining about the threat to their freeze peach and open discourse of ideas by banning racists, etc.).

This is a classic sequence post: (mis)appropriated Japanese phrases and cultural concepts, references to the AI box experiment, and links to other sequence posts. It is also especially ironic given Eliezer's recent switch to doomerism with his new phrases of "shut it all down" and "AI alignment is too hard" and "we're all going to die".

Indeed, with developments in NN interpretability and a use case of making LLM not racist or otherwise horrible, it seems to me like their is finally actually tractable work to be done (that is at least vaguely related to AI alignment)... which is probably why Eliezer is declaring defeat and switching to the podcast circuit.