I find it really funny how after he gets booed he says, “If you don’t care about science, that’s okay, because AI is going to touch everything else as well. Whatever path you choose, AI will become part of how work is done.” Yeah, if you’re worried that AI is only going to fuck up science, don’t worry, it’s going to fuck up everything else as well. Was he trying to stick to a (terrible) script, or is he genuinely this incapable of reading a room?

“When someone offers you a seat on the rocket ship, you do not ask which seat. You just get on.” No, my mom taught me about stranger danger. I know what to do when a sketchy old man named Eric Schmidt pulls up with a rocket ship that says FREE ICE CREAM.

“The rocket ship is here. Let me give you some advice. First, find a way to say yes. Listen.” Thanks for revealing how AI adoption is really about coercion. It doesn’t matter what you think, AI is inevitable and you ignorant Luddites are gonna have to find a way to like it.

Truly a masterclass in public speaking by Eric Schmidt. When the audience reacts negatively to what you said, just double down and shove it down their throats. You’re a billionaire, so you know better than them.

How many people, if they were given $1.3 million just once in their lifetime, would figure out far better uses for that money than this guy?

The last several years have been the monkey’s paw moment for rationalists, where they keep getting what they want and realizing it’s actually bad. As for why they keep getting what they want, just look at who’s funding them.

(Also featuring a “Chinese curse” that isn’t actually a phrase in Chinese. At least it’s not “may you live in interesting times”.)

I attended a town hall hosted by the department at my university supposedly for general discussion about department affairs. Considering the university had recently made moves such as adding “AI” into the very name of the department, I had suspicions that much of the discussion would be about AI. (I realize I’m doxxing myself but whatever.) I mostly came for the free food, but I was also interested in seeing what people thought about AI.

The event started with a talk by a prominent professor with major administrative power in the department, and indeed the talk was mostly about AI. His views were that he personally didn’t like AI, but he believed that it had changed the world (particularly in programming), and that it was going to stay. One of his justifications for pivoting the department to AI was ensuring universities had some say in AI and not letting all the control go to unaccountable corporations.

The reaction from the audience was a pleasant surprise to me. He asked everyone how much they were excited about AI (hardly anyone) and how much they were worried (most of the audience). By far the most amusing moment was when someone asked, “What if the assumption that AI is inevitable is wrong? What if AI does not live up to its promises?” (Sadly, I don’t remember the exact words that the person said.) The professor’s response was that by this point, there are so many trustworthy, smart, prominent people who definitely wouldn’t fall for scams, and they have adopted AI. He trusts those people, so he trusts that AI is genuine. I don’t know if the audience member accepted this explanation, but I hope not. Our modus operandi is FOMO.

The pizza was only ok, not really worth a 90 minute event.

This really goes to show how much they need to rely on the LLMentalist effect, despite the AI boosters insisting that the AI is totally different now, everything changed in the last few months. They do not care about creating a useful, reliable tool. That concept doesn’t even occur to them, since why do that when AI is magic?

In any case, they are incapable of creating a useful, reliable tool. Deep down, the only thing the AI companies have at their disposal is the ELIZA effect. OpenAI has every incentive not to truly eliminate AI psychosis, because they need engagement. They only want to mitigate the extreme cases where people go insane and cause bad PR for them. But mild AI psychosis is totally fine, it’s great when people are addicted to your product and make the numbers go up!

Somehow this is no worse than his usual fare, such as a thumbnail that is just a bunch of colored lines resembling a line chart but without representing any actual data, with some random marked points labeled “Dark Farms” and “Human Zoo”.

No, I’m not kidding.

Unfortunately, our problem right now is not Donna the below-average Democrat but Donald the fascist. And when it comes to fascists I do not ask if they are above or below average.

The fire code thing really is an excellent example of LessWrong Brain. Fire truck drivers insist on needlessly large trucks (no citation) which makes roads 30% wider than they would otherwise be (no citation) which has “probably” “non-trivially” contributed to larger cars (no citation) leading to enough additional road fatalities to cancel out the lives saved by stricter fire codes (no citation).

The LessWrong Brain argument starts with a deliberately contrarian conclusion and proves it with a Rube Goldberg chain of logical syllogisms. Of course, citations are strictly optional, and they are free to misinterpret them as they see fit. The only real standard of each claim is “looks good to me”, but you are supposed to be impressed that they managed to string a dozen of them together to reveal some shocking, deep truth of the world that nobody else knows about. The AI 2027 nonsense is an infamous example of this.

He uses the word “fermi” which is cult jargon based on Fermi estimation, a.k.a. guessing shit with back-of-the-envelope calculations. Not exactly what you want if you want to convince people to reform fire codes, especially if you have zero citations for anything.

I guess people just aren’t rational enough, and the only reason the fire codes are so irrational is because people are emotional about fire codes. Firefighters are apparently revered as heroes, when it is the LWers who should be the heroes. After all, firefighters merely save people from fires, while LWers buy multimillion dollar mansions to talk about saving quadrillions of hypothetical people from hypothetical basilisks!

It’s fine, spyware is only a risk when it’s bad people’s spyware. It’s totally fine when it’s Anthropic™-approved spyware!

As for Mythos catching things, maybe they should have used Mythos on their very own Claude Code considering that it has hilariously obvious security exploits, such as this one which inserts an arbitrary string into a shell command. Actually, never mind I don’t see anything wrong here, maybe we should burn another $20k in electricity running Mythos on it again to find out.

In basically every case in history where people decided to kill a bad king, there was a period of chaos and violence that followed it. The killing of Charles I happened during the English Civil War, and the killing of Louis XVI happened during the French Revolution. This has happened many times in Chinese history, with the fall of an imperial dynasty leading to several decades of civil war (most recently in the early 1900s). But I guess if you have a big clever brain with big clever thoughts, you don’t need to look at history.

If the only way to get rid of a bad king is to kill him, he will do anything he can to defend his power, including using as much violence as necessary. (People generally do not like being killed.) Even if you successfully get rid of him, good luck establishing a proper government afterwards with all the violence you’ve caused. And who knows if the new king is gonna be better or worse? A better system would instead have a mechanism that replaces officials on a regular basis, say every few years, and ensure that these replacements are peaceful. Oh wait, that’s liberal democracy. If we do something boring like support democracy, how will people ever think of us as special, clever thinkers with bold, contrarian thoughts?

It’s still One Person. A mortal, fleshy person. Their defence is that they’re inoffensive, things are stable, nothing is directly their fault and people are bound by law and oath.

Bro, your system involves giving all the power to one person. You cannot then say they have no responsibility or that they’re “inoffensive” when they abuse it.

I’ve seen this story play out in software engineering: people were very impressed when the AI does unexpectedly well in one out of 50 attempts on an easy task, and so people decided to trust it for everything and turn their codebases into disasters. There was no great wave of new high-quality software. Instead, the only real result was that existing software has become far more buggy and insecure.

Now we have people using AI in science and math because it was impressive in random demonstrations of solving math problems. I now have friends asking me why I’m not using AI, and also saying that AI will be better than all mathematicians in 30 years or whatever. Do you really think I refuse to use AI out of ignorance? No, I know too much about it! I have seen the same story play out in software engineering, and what makes this any different?

I think the main difference here is that breaking RSA now just requires scaling up existing approaches, while breaking LWE or anything like that would need a major conceptual breakthrough. The former possibility is much more likely, and in any case, cryptographers are the most paranoid people on the planet for a reason.

Unfortunately, one can never be sure about much in cryptography until P vs NP is solved (and then some).

(Of course, just because some people say that scaling up is enough doesn’t mean it’s actually true. For breaking RSA, we know have Shor’s algorithm, while the only evidence AI bros have from superintelligence coming from scaling is “trust me bro”.)

This is what happens when your worldview is based on anime.

(A lot of anime has heavy themes, but most people understand that it’s not real life, just like all such art. Unlike Yud, most people’s worldviews on coding and math are based on actual coding and math.)

We can see that one 9 of availability is 90% = 0.9, two 9s is 99% = 0.99, three 9s is 99.9% = 0.999, etc. In general, for positive integers n, n 9s of availability is 1 - (1/10)^n, and we can extrapolate that to non-integer values of n. The value γ needed for 87.5% availability is the solution to 1 - (1/10)^γ = 7/8, or γ = log_10(8) = 0.903089987. γ is transcendental by Gelfond-Schneider (see this for a reference proof).

Right now, Sora is at zero 9s of availability.

By far the dumbest “feature” in the codebase is this thing called “Buddy” (described in a few places such as here). Honestly, I don’t really know what it’s for or what the point is.

BUDDY - A Tamagotchi Inside Your Terminal

I am not making this up.

Claude Code has a full Tamagotchi-style companion pet system called “Buddy.” A deterministic gacha system with species rarity, shiny variants, procedurally generated stats, and a soul description written by Claude on first hatch like OpenClaw.

…

On top of that, there’s a 1% shiny chance completely independent of rarity. So a Shiny Legendary Nebulynx has a 0.01% chance of being rolled. Dang.

Great, so they were planning on a gacha system where you can get an ASCII virtual pet that, uhh, occasionally makes comments? Truly a serious feature for a serious tool for the serious discipline of software engineering. Imagine if IntelliJ decided to pull this bullshit.

But also, Claude Code is leaning hard into gambling addiction — the “Hooked” model. You reward the user with an intermittent, variable reward. This keeps them coming back in the hope of the big win. And it turns them into gambling addicts.

The Onion could not have come up with a better way to illustrate this very point.

Good luck telling the promptfondlers that LLMs are only useful for entertainment and not for any useful work.

I’m sure these English instructions work because they feel like they work. Look, these LLMs feel really great for coding. If they don’t work, that’s because you didn’t pay $200/month for the pro version and you didn’t put enough boldface and all-caps words in the prompt. Also, I really feel like these homeopathic sugar pills cured my cold. I got better after I started taking them!

No joke, I watched a talk once where some people used an LLM to model how certain users would behave in their scenario given their socioeconomic backgrounds. But they had a slight problem, which was that LLMs are nondeterministic and would of course often give different answers when prompted twice. Their solution was to literally use an automated tool that would try a bunch of different prompts until they happened to get one that would give consistent answers (at least on their dataset). I would call this the xkcd green jelly bean effect, but I guess if you call it “finetuning” then suddenly it sounds very proper and serious. (The cherry on top was that they never actually evaluated the output of the LLM, e.g. by seeing how consistent it was with actual user responses. They just had an LLM generate fiction and called it a day.)

I decided to take a look at the bitcoin white paper.

Usually, the introduction of a technical paper is fluff and people quickly move on to the technical parts. However, the casual claims made in the first paragraph of this paper have aged extremely poorly, to say the least. In a better world, Bitcoin would have remained as an obscure academic toy, and this introduction would have remained fluff.

While the system works well enough for most transactions, it still suffers from the inherent weaknesses of the trust based model.

What weaknesses are there in the trust based model? Let’s find out!

Completely non-reversible transactions are not really possible, since financial institutions cannot avoid mediating disputes. The cost of mediation increases transaction costs, limiting the minimum practical transaction size and cutting off the possibility for small casual transactions, and there is a broader cost in the loss of ability to make non-reversible payments for non-reversible services. With the possibility of reversal, the need for trust spreads. Merchants must be wary of their customers, hassling them for more information than they would otherwise need.

It seems like this guy really loves non-reversible transactions! But as we’ve seen with the history of crypto, non-reversible transactions sound really good until you fall victim to a crypto scam and there is no way to appeal to the bank to reverse the charges. Reversibility actually increases trust because you no longer need to be absolutely certain that you’re dealing with an honest person.

A certain percentage of fraud is accepted as unavoidable.

Almost like that is a problem of human nature. And it’s not like cryptocurrency has a spotless record when dealing with fraud! The problem with fraud is not the third party (the bank), but with the second party (the merchant or customer you’re dealing with).

The introduction is not long, and most of the paper concerns the technical details of the construction of Bitcoin. By itself, there really is no way to complain about a pile of definitions. But there are still dumb comments that have aged poorly in retrospect.

A block header with no transactions would be about 80 bytes. If we suppose blocks are generated every 10 minutes, 80 bytes * 6 * 24 * 365 = 4.2MB per year. With computer systems typically selling with 2GB of RAM as of 2008, and Moore’s Law predicting current growth of 1.2GB per year, storage should not be a problem even if the block headers must be kept in memory.

But why would you want a block header with no transactions? If you wanted to, I don’t know, replace the world’s financial system, you would need to handle millions of transactions every 10 minutes. How big would the blocks be then? And remember that many copies of the same blockchain would need to be stored (certainly, every miner would need to store a copy). How many thousands or millions of times would that multiply things?

Businesses that receive frequent payments will probably still want to run their own nodes for more independent security and quicker verification.

Turns out it was a bold assumption to think that businesses would just run their own bitcoin miners.

The proof of security (Section 11) is extremely sketchy by modern standards. (They’re assuming that all attackers would follow a certain format to attack and not try something different. I get it, proper proofs of security in cryptography are very subtle and difficult.) There is also a page of fluff making random calculations with the Poisson distribution. In any case, the security of Bitcoin requires that the collective computational power of the defenders exceeds the power of any attacker (so the defenders can make new blocks faster).

Bitcoin is very strange as a cryptographic system in that the defender must have more resources than any possible attacker. In most cryptographic systems, the system should be secure even if the attacker has vastly more resources than the defender. Your phone’s cryptography should be secure even if some government agency dedicated their supercomputers to try and break it. This means that Bitcoin must waste tons of energy, since that is required to maintain security. Any more energy dumped into it will only increase security and not make the actual transactions faster, which makes Bitcoin horrendously inefficient.

As a purely academic idea in cryptography, it is an interesting curiosity, but the arguments for why it’s useful are sketchy. There are other such curiosities that are much more interesting, like homomorphic encryption or secure multiparty computation. It would be a nice line on a CV, but not “incredible”.

The true significance of Bitcoin was the terrible libertarian economic argument for it, and the chain of events that would transform it into nothing more than a speculative fashion trend. It has nothing to do with the technical details of Bitcoin. The technical and economic arguments for Bitcoin turned out to be so weak that nowadays, the only real support for Bitcoin is that maybe you can sell it for a higher price to a greater fool.

Oh boy, another AI doom video popped up on my feed. Time for more morbid curiosity. The topic is about Big Yud and Nate Soares’s new book (“If You Build It, Everyone Dies”) about how AI is gonna kill us all. I have better things to waste 30 minutes on, so I’m not watching the full video, but the thumbnail (“The 7 Minute War”) kinda suggests what the contents are gonna be.

Thankfully, the description of the video has a Google doc with their sources! I’m sure it’s full of hard evidence from careful experiments that logically demonstrate why their doomsday scenario is something to worry about, not just a random assortment of Anthropic blog posts and completely unrelated events.

Somehow, there are a bunch of sources for the first 2 minutes of the video.

“In the New York Times’ best-selling book, which was endorsed by Nobel laureates and the godfathers of AI” Geoffrey Hinton — Personal estimate >50% existential risk.

Geoffrey “All radiologists will be replaced in 5 years” Hinton, Nobel laureate in physics, famous for his work in … physics.

“researchers from the Machine Intelligence Research Institute describe in detail one potential example future” Machine Intelligence Research Institute — The Sable scenario from If Anyone Builds It, Everyone Dies by Yudkowsky & Soares. Fictional narrative illustrating risks, not prediction.

This is not the first we’ve seen from MIRI, and I have a feeling it will not be the last. The monster under my bed is a fictional narrative illustrating risks, not prediction.

“AI researchers have known this has been potentially a very bad idea since at least 2024” Anthropic/Apollo Research — Multiple 2024 papers document deceptive/self-preserving behaviors in controlled evaluations.

They are still trying to flog the Anthropic/Apollo Research claims that chatbots will lie to you if you tell them to lie to you.

“They spin up 200,000 GPUs and let Sable think for 16 hours straight” xAI/NVIDIA — Colossus supercomputer in Memphis scaling toward ~200,000 GPUs for Grok training.

What does this even demonstrate? Some people can do some stuff with some GPUs? I ate some oatmeal today. Now everyone should be thoroughly convinced of my oatmeal-eating abilities.

I watched for a few seconds around the timestamp, and it seems to be the beginning of their scifi story, I mean, AGI scenario. Yes, if you want to convince people that your scenario is plausible, I’m sure this is the part that you need serious amounts of evidence for. Remember, almost half the sources have timestamps for the first two minutes of the video.

“a stunt to see if Sable can crack famous math problems like the Riemann hypothesis” Clay Mathematics Institute — Riemann Hypothesis remains unsolved after 160+ years, considered most famous unsolved problem in pure mathematics.

Again, what does this demonstrate? I tried solving P vs NP with a cheeseburger. That didn’t work either. The only purpose of mentioning this is for narrative window dressing, because Math Is For Smart People.

These are the sources for just the first two minutes. After that, they get a bit sparse.

“Back in 2024, smaller models showed flashes of the same behavior” Multiple Papers — Documented deception/scheming findings in frontier models.

“Claude 3.7 was caught repeatedly cheating on coding tasks even when told to stop”

More Anthropic blog posts and system cards? Come on, I can’t sneer the same thing twice in one post!

“Steal cryptocurrency from weak exchanges just like hackers did to Mt. Gox in 2011” U.S. Department of Justice — Russian nationals charged for 2011 Mt. Gox hack. 647,000-850,000 BTC stolen.

I don’t know what this has to do with supporting the validity of their AI doomsday scenario, but kudos to them for showing why cryptocurrency is also stupid, I guess.

“or Bybit in 2025” Reuters/FBI — Largest cryptocurrency theft to date. FBI attributed to North Korean Lazarus Group.

More? I guess this is hard evidence for showing why cryptocurrency is stupid. I still don’t understand how this demonstrates that AI is scary.

“Reminder, this scenario is based on years of technical research by the Machine Intelligence Research Institute, laid out in the book If Anyone Builds It Everyone Dies” MIRI — Meta-commentary explaining the scenario is illustrative, not predictive.

I knew MIRI would be back. It’s illustrative, not predictive! Please don’t blame us if none of this even remotely happens! But it’s based on years of technical research. An entire graduate student’s worth of output in a decade.

“In 2023, a human gave an LLM access to the internet and created an X account, Terminal of Truths, which gained hundreds of thousands of followers and launched its own crypto meme coin that reached a literal billion dollar market cap” Terminal of Truths — Real-world example of AI agent gaining social media following and wealth.

The link they give references … another one of their own videos. You really are not beating the circular reference allegations here. Even if the purported story is somehow accurate, this again demonstrates how cryptocurrency is stupid. At least they use an LLM as a prop this time.

“Gain of function research. Any one of them could be hijacked to unleash catastrophe.” Science/CIDRAP — Fouchier and Kawaoka created ferret-transmissible H5N1. Controversial GOF research began 2011.

I think Yud is obsessed with this topic in particular. Better than diamondoid bacteria, I guess. Again, the AI just magically comes in and uses this stuff somehow.

“The number one and number two most cited living scientists across all fields think scenarios like this are not only possible but likely to happen. And the average AI researcher thinks there is a 16% chance of AI causing human extinction.”

Okay, let me be completely serious for this one. What would someone do if they truly believed that their work would lead to a horrible disaster, such as the extinction of humanity? Would they continue to work in the field, let alone make enough contributions to rise to the top? Alright I’m done.