Before the days of AI 2027, he became famous in 2024 for posting one of the original pieces of writing in the line-go-up genre: Situational Awareness. It seems that like any good grifter, he used this opportunity to make money (in this case by starting a hedge fund).

There is something about this picture, a warehouse full of books to be destroyed by Anthropic for training data, that just makes me sick. Knowing that they are destroying books in the abstract is bad enough, but seeing the sheer scale of it makes me viscerally angry.

Karen Hao called her book Empire of AI for a very good reason. The empire has all these noble narratives of bringing civilization and progress to the colonies, but in reality the empire only sees resources to be extracted, repackaged, and sold back to their subjects at a fee. Kudos to those who saw this immediately and fought against it. Shame on those who believed in the narrative of progress, to the point where many of them are collaborators with the empire.

Whenever a smarmy fellow on Linkedin posts about how AI is making so much progress in coding or math, I want them to see this picture. I want them to see the videos of families in tears after a data center takes away their home with eminent domain, and other families who have to deal with the resulting pollution. Go beyond the bloodless math of tokens and instead see for yourself what this all truly costs. I hope it was worth it.

It gets worse. I found another article about the same podcast: Sam Altman says AI won't shorten the workweek because humans secretly enjoy being busy.

"Technology, for a long time, has been promising people that they're going to work less and they're going to have all this leisure," Altman said. "But somehow we never get the promise of the four-hour workweek at mass scale in society," he added. "And I don't expect AI to change that."

"It's like a relative game. People are very focused on how they're doing relative to other people," the CEO said.

"I think we're all going to be much busier than we thought we were supposed to be in a post-superintelligence world. We're still going to complain about it, but secretly we're going to be happy," Altman concluded.

The chuds are all at r/accelerate now. "We're the unapologetically Pro-AI alternative to r/singularity, r/futurology, r/artificial & r/technology which are becoming filled with Luddites, Techno-Decelerationists, Techno-Reactionaries, & Anti-AIs."

Clamuel did another podcast. I don't want to waste my time watching it, but I want to sneer at some choice quotes from news articles breathlessly reporting this stuff as gospel 1, 2

"We are now, like, in the singularity"

Is the singularity in the room with us right now? Even the people on X the Everything (Including CSAM) App aren't so convinced.

Altman said on the podcast that just a decade ago, the so-called singularity still felt like a distant and improbable dream — something he and his colleagues would discuss casually over lunch.

"Now we're actually in the moment that we used to talk about at the lunch table in a very not-serious way," he said. "I've been waiting for this my whole life, and I think it's going to be incredible, hugely positive, awesome for the world."

Do you feel it? Do you feel incredible? Do you feel hugely positive? Do you feel awesome, now that the singularity is here? Oh wait, he's speaking in the future tense again, never mind. Force of habit.

It's also funny how he talks about how positive things are gonna be immediately after the super scary hack done on Hugging Face (really due to incompetence on both sides). Oh no, the AI is gonna kill us all! It's going to be incredible, hugely positive, awesome for the world.

Later in the podcast, Altman criticizes AI leaders who have repeatedly warned that AI is dangerous. He didn't name Anthropic, his primary competition, but its CEO, Dario Amodei, is well-known for making dire predictions about the future in his calls for greater attention to safety.

"I also think some of the alternative visions painted by other companies are quite terrifying," Altman said. "I'm going to make sure that gets pushed against and is not what happens."

At least Clammy realizes that all the doom trolling about how AI will replace and destroy all humans turns out, surprisingly, to lead to overwhelming negative public opinion. But this statement truly reassures me that Scammy has good intentions about AI safety. He will make sure this is pushed against and is not what happens. He wouldn't want another super scary, dangerous hack that just so conveniently turns out to be excellent marketing.

OpenAI CEO Sam Altman says one of his biggest concerns about AI isn't whether it becomes too powerful in and of itself, but that a single company could control that power.

Yeah, it would be really bad for Anthropic to control all the power of AI. It would be a disaster to hand everything over to Anthropic.

"Every time that humanity has traded off its liberty for safety, it's been a long-term net loss," Altman said. "We are going to put this in the hands of people. We're going to empower them. We are going to let society express its ideas and use this technology in the way they want."

Society is expressing its ideas about AI, all right. But I feel like they aren't what he has in mind.

Altman, meanwhile, said preventing such power from becoming overly concentrated has long been central to his vision for AI, even as his company continues to keep its own models closed.

"For so long now, I have felt focused on this singular goal of abundant intelligence and a belief that incredible human prosperity will come from that, as long as we don't have a weird power concentration and kind of a new authoritarianism," he said.

Well, we seem to have a weird power concentration and "kind of" a new authoritarianism, but I don't see any abundant intelligence or incredible human prosperity.

Lots more sneers on the Better Offline subreddit.

It is surprising how many exceptionally strong mathematicians have started working for OpenAI and Anthropic. These people would have easily become professors at top universities if they stayed in academia. I think many mathematicians, especially the competitive ones at the top, have a "progress at any cost" attitude (and I'm sure the paychecks helped). As for the results, you still need good mathematicians to sift through all the output to identify that the proofs are valid.

I would honestly be positive about universities developing their own specialized math AI (in an ethical manner) to help mathematicians get these kinds of results, but right now, AI is inseparable from these evil companies. Thankfully, I believe this is a likely outcome in the future because the AI companies will one day implode.

From what I've seen, most prompts are in plain English. I suppose the part where the AI parses the statement correctly is much easier than the part where it boils a couple lakes in the process of bashing its head against the wall trying millions of different combinations of random shit from the literature to slap together a proof. For one of the big results (cycle double cover), the prompt specified that the AI could use 64 subagents and was required to not give up for at least 8 hours. The tokenmaxxers would be proud, we didn't need that forest anyway. Thank god math doesn't have a CTO to look at the expense reports.

Among the three big results I've looked at (unit distance problem, cycle double cover, Jacobian), two were counterexamples and one of them had a short 3 page proof using ideas from the 1970s. The Jacobian conjecture is an extreme case because a single counterexample is enough (for unit distance, you technically need a family of counterexamples), and it is easy to check with very basic computations. It is telling that all of these announcements came from OpenAI or Anthropic employees, who presumably have unlimited access to their AI. Nobody really knows how many resources they spent on this, or what else they tried. Nobody really seems to care about this question, either.

I think there is a phenomenon where supposedly hard questions are much easier than expected, because by chance nobody found the right approach for a while, and eventually it becomes famous as a "hard problem" which makes nobody want to attempt it.

What I'm more worried about is many people starting to use AI to try and prove small lemmas for them in their projects. Of course, a $200/mo subscription is absolutely necessary to them. This honestly feels like a repeat of Claude Code back in February. The software engineers eventually realized that AI is absurdly expensive after the AI companies realized that spending $14000/mo to service a $200/mo subscription is a bad idea. If the AI vendors couldn't squeeze money out of rich software companies, what exactly are they gonna get out of poor mathematicians and universities? Also, there is the cognitive decline caused by overuse of LLMs that has yet to set in.

I think a serious possibility is that AI generated papers flood the zone with uninteresting incremental results that are eventually meaningless and full of mistakes. Right now, math is full of smart, dedicated people, so at least major results are reviewed carefully. But as AI alarmism drives away many honest people from the field, the remaining mathematicians will be burdened with far more work to review, and their cognitive faculties will be eroded by LLM use. Despite 4 years of development, $3 trillion of debt, mountains of stolen data, all the agents and harnesses and loops and other expensive tricks, as well as the advantages of Lean in math research, LLMs still hallucinate.

I believe this is happening with software, but at least there are objective consequences for screwing up there (guy gets his home directory deleted, email is sent on a guy's behalf without permission, small business gets every customer subscription cancelled). But nothing bad happens if there is a mathematical mistake in a paper and nobody catches it. One could say to just provide a Lean proof, but there is still the issue of making sure the Lean code actually matches the content of the paper. Exactly what force will correct things?

Still, I don't think this is the most likely possibility. The AI companies are extremely unsustainable financially, and it's not like they're very popular. Once they collapse, I believe there will be a re-evaluation of how LLMs should be used in research. If they are used (let alone trained), someone is going to have to pay the bills.

In the end, we have to ask ourselves the question of why one does math. To me, math is not really a field where you memorize trivia. The real value comes from being able to think abstractly and rigorously from first principles, and from understanding why something is true rather than just knowing it is true. It is another aspect of your ability to reason as a free human. A few dedicated people go into math research, but your skills can easily go to many places. If you're starting undergrad, you have plenty of time to see how this all pans out before making a decision.

Here's A Taxonomy of Omnicidal Futures Involving Artificial Intelligence by Critch and Tsimerman, which approvingly cites our favorite AI 2027. Nobel disease is still a thing (I think the rationalist beliefs are quite pervasive among mathematicians).

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.

“California is, I believe, the only state to give health insurance to people who come into the country illegally,” Kauffman said nervously. “I think we probably should not be providing that.”

“So you’d rather everyone just be sick, and get everyone else sick?” another reporter asked.

“That’s not what I’m saying,” said Kauffman.

“Isn’t that effectively what happens?” the reporter countered. “They don’t have access to health care and they just have to get sick, right?”

Kauffman contemplated that one for a moment. “Then they have to just get sick,” he said. “I mean, it’s unfortunate, but I think that it’s sort of impossible to have both liberal immigration laws and generous government benefits.”

Do I need to comment on this one?