OpenAI recently released a ton of math problems that they spent, on average, three hours each solving with one of their latest (obviously unreleased) models. These are problems that humans have been unable to make progress on, or whose solutions they thought could not be improved upon, for decades. For instance, subquadratic 3SUM—while the gains are tiny, improving on what people thought was an unimprovable lower bound is extremely impressive. It’s on the order of voodoo magic, as 3SUM intuitively seems unsolvable in subquadratic time. OpenAI claims that they spent under three hours per problem, and that seems about right.

And academia is not reacting well. Imagine you’re a PhD student working on these problems, one of the brightest minds in the world. You’ve spent years trying to solve a problem, and you learn that an AI model took just three hours to one-shot it and surpass all the progress you’ve made on it. You learn that not only were you on the wrong track, but you had previously been on the right track and deviated from the correct path. Soul-crushing, really.

Which is why the math community is so strongly against it. While some of the broader math community’s concerns have merit (see Terence Tao’s concern that there’s too much math to consume), its reaction has largely been one of protectionism. Thousands of researchers, professors, and academics are concerned that their fields of research are being rendered useless and that their life’s work is meaningless. It’s understandable! You’ve spent years of your life toiling away at numbers and letters, graphs and equations! It’s frustrating.

But progress is progress! You cannot stop progress. And policing it is futile. This is the world you live in and the world that you will continue to experience. And it’s a good thing: who knows what future innovations a more efficient multiplication method could lead to? Suppose one day we discover a significantly more efficient algorithm for something that’s widely adopted. Think of how much energy we would save every time that routine runs anywhere in the world.

It’s really about jobs. Academics are concerned that they are losing their jobs, and they should be. But they should not mask that concern by treating the field of mathematics like some kind of hobby. If we are using public funding and other research grants to pay academics to discover things for the good of the public, we should expect some kind of return on that funding. We are not paying them to dilly-dally and indulge their own egos. We are paying them to make discoveries that benefit us all.

This pattern of AI replacing white-collar work is all too common. First, it came for the software engineers, as software engineers are paid very well in today’s industry. The cost of developing some crappy internal tool has essentially dropped to zero, when it used to cost a company a few junior software engineers’ salaries (which were still quite high). Now it’s coming for academics, because academics are also paid very well. And it makes sense! It’s the highest ROI you can get; automating a software engineer’s work or a professor’s work saves much more money than automating a barista’s.

There’s a disconnect between the kinds of jobs most people think will be AI’d away first and those that actually will be. The usual concern is that we’ll replace artists, Uber drivers, and truck drivers. But why do that? Self-driving cars, despite the progress we have made, are still in their infancy. And even if they do replace human drivers, is the token cost worth it? As of now, maybe not, but certainly in the future. But why deal with the real world, which has all sorts of obstacles popping up in the road, when we can deal in the abstract, in the realm of words or tokens, and automate away the high-paying jobs first?

But there’s no sympathy for white-collar jobs. Nobody cares if some rich software engineer gets laid off (unless it’s a game developer, in which case their whining on Twitter somehow gets amplified and treated differently from that of the thousands working on Microsoft Excel). They make $200k a year. Who cares? They’re fine. There’s nobody to really go to bat for them. And academics—what do the pesky nerds in the math department really do? Sure, people will fight to preserve jobs researching some endangered fish in the Nevada desert, but nobody cares about math. It’s boring nerd shit.

The real way to prevent yourself from being automated away is either to be on top of the AI (sell the AI and its product) or to be on the bottom, doing something that is not worth AI’ing away. Plumbing is one example; you cannot easily AI away plumbing because it requires hardware, and you are also dealing with unpredictable customers who don’t really know what they want. You can automate everything else away, but plumbing is something you would have to do manually. You can create better tools for plumbers, and perhaps in the future we will have robots, but in the end, that root will need to be cut away with an auger. It’s a much harder problem than theorizing about 3SUM.

I don’t think this is a bad thing. Plumbers can make good money. In the future, they may make more money. And that’s good! They deserve it.

Pirating anime is essentially a solved problem and has been for a few years now.

Anime has always been pretty rife with piracy. From the LD and tape days to boutique fansub groups to rips of official simulcasts today, people have always pirated anime. But only in the last 5–10 years have we essentially solved piracy. That is to say, the amount we can pirate (of course, way more than we can actually consume) cannot keep up with the amount of storage a home user can accumulate.

A while ago, I ran the numbers using MAL’s API and got about 29k anime, counting movies, OVAs, series, etc. as separate entries. I think this is about as accurate as we can get. More importantly, it probably comes close to accounting for the media that’s actually available. There’s another project, anime-offline-database, that aggregates multiple online databases and comes up with a total of about 41k entries. Keep in mind that this includes many movies, OVAs, and shorts, but let’s assume the worst case: around 530k distinct episodes of anime. I think this is a gross overestimate, and the real number is maybe 50% of that, but let’s use this number as an upper bound.

Currently, reasonable anime releases are about 1.3 GB per episode. It’s been this way for a few years—maybe ten or fifteen. Interestingly enough, thanks to codec improvements, file sizes have remained unchanged or are often smaller nowadays with HEVC. Older shows were often encoded and available in much smaller sizes because their resolution was much lower. For our exercise, we can assume an average file size of 1 GB per episode for easy math.

Thus, the total amount of anime that has been created in the world so far can be stored in 530 TB in the worst case. Realistically, collecting anything close to this would not be possible, given that not all anime is still available. I also don’t think those estimates are anywhere near correct. I’ll explain later.

530 TB of storage alone would cost around $5.3k at $10 per TB (using storage prices from before the AI shortage).

That sounds expensive, but this is a worst case. It is entirely reasonable for a normal consumer to pay that amount of money to have a repository of all anime. It’s something a normal person could have sitting in a single computer case next to their desk. Folks pay thousands of dollars every few years for graphics cards that depreciate faster than this. You do not need a data center or some fancy tape storage. You can have it on spinning disks. You don’t need some enterprise-level storage solution.

But let’s calculate the future of anime: there are roughly 150–250 new anime series every year. Add in a few movies and maybe OVAs, and, using back-of-the-napkin math, we have perhaps 350 cours of anime each year. That would be roughly 5–6 TB of anime per year. Since file sizes and episode runtimes have remained roughly stable, I don’t expect this to increase much. I think adding 6 TB a year to your storage is fairly reasonable. You can buy a 20–24 TB external backup drive and be set for about four years. Over the next 40 years, you’ll acquire a total of 200–240 TB of new anime under these assumptions, which is really not much.

Our current release cycle is also why I believe the estimate of 530 TB is incorrect. If the next 40 years of anime would require only 240 TB of storage, I think acquiring all previous anime in a reasonable format would require around that much or even less. Either way, it’s only a couple of thousand dollars.

For an upper bound of $10k, you can build an appliance right now that would store all anime from now until you die (or at least until I die). Realistically, I would estimate that it would cost only half that, given that so much anime is lost media, but we’re talking theoretically.

I think that this phenomenon would apply to other media too. Books especially are probably solved, but I’m not knowledgeable about movies or TV shows. It might be a few years before a layperson can, with a little bit of money, theoretically fit every piece of visual or audio media on their home PC.

Watching the real-time industrialization of their nation, piloted by companies like Xiaomi and BYD, from a nation of dirt floors and bicycles to Roombas and electric cars within two decades gives a different perspective from the West, where potable water is expected and Flint, Michigan, is ridiculed. There was a recent news article with Chinese scientists featured as national heroes, contrasted with America, where our heroes are the products of the entertainment industry.

Within Chinese youth, the sentiment may be different, but there must be some sort of understanding within older Chinese millennials that engineers, scientists, and business leaders who emphasize technological growth (which is inherently anti-labor in the immediate short term) lead to products that better the lives of ordinary people. I don’t think that understanding is as prevalent in the current era amongst Western cultures that have taken things such as roads, running water, and household products for granted.

There is some sort of societal memory that producing things is still Good, and that a better way to produce Things with less Labor is to be celebrated. Because it is a nation where Things were, until recently, and still are for some non-insignificant portion of the population, not available compared to the West. The job loss is not as significant as the existence and affordability of a vacuum cleaner instead of a broom.

But I think we have largely forgotten about that here aside from a few industries. Household products required to survive comfortably are largely a solved problem. Most people in the US have access to a fridge, reliable transportation, running potable water, showers, a toilet, vacuum cleaners, and other things that we take for granted.

Thus, what’s the incentive for producing?

We now espouse the meaning of our work, of our jobs, of our personal satisfaction with what we do. We do things because we want to, or we need the money, or we think it makes the world a better place. We place the needs of the workers first and foremost without thinking of the product. Of course, this is a generalization, as the CEOs and the leaders of firms think about the product first and foremost, but the general worker does not. The salary system represents the intentional detachment between the worker and the product, amortizing the risk amongst the employees. Sure, we may have layoffs and stock options and tips and other performance-based incentives, but largely the individual employee’s incentives do not match.

Thus, when AI comes along and threatens those things, we as individual employees of the firm are concerned. Technology has always been, economically, a way to produce more given the constraints of labor and capital, and for white-collar workers, AI looks to be a way to accelerate that graph asymptotically whilst demand remains constrained. Not a great place for the labor side of the equation, to be quite fair.

In the West - and within younger Chinese who were born with cell phones in their hands - I’m sure that this production seems to be at the expense of the Worker. However, to older folks across the pond, it can only be seen as something extraordinary.

You grow up sweeping dirt floors and now your Xiaomi automatically maps out your room and cleans it. You grow up not having access to knowledge and now you can ask your phone anything and it can give you the answer. It’s nothing but a miracle. No wonder you embrace AI. Of course you would want agents; work is an act of suffering. Yet you ask your American friend and he or she loves his work and is afraid AI will replace him. You are afraid that your job may be in danger too, but you order your bowl of noodles for 14 yuan, it arrives in 20 minutes from a self-driving, AI-powered delivery robot, and you remember how you no longer need to boil your water and knead your dough from scratch.

I think we in the West need to remember that the product of our work is important too. Societies that still have vivid cultural memories of material scarcity are more likely to view automation as an opportunity for abundance rather than job preservation.

We are competing on a global level. If BYD makes better cars than Ford, they will eat our lunch no matter how many barriers we put up. And those barriers are Not Good for us. If BYD makes a better car, why should we put up with an inferior Ford?

I personally believe there are opportunities to innovate. There are always more features you can put in a car, and we should accelerate our production at the expense of labor. There are things that we can do in 2026 that would’ve been unthinkable in 2025, and reaping the fruits of that progress will be beneficial for our nation in the long run. A decade ago, coal miners were told to learn to code, but now, in the abundance of both cheap solar and cheap code, there must be something greater that coders, designers, engineers, artists, bean counters, and other people who work their minds can do that would lead to a society with more abundance.

A while ago, I saw this page emphasizing the importance of bundling your intent with your message for professional communication. Please give it a read—it’s a very important concept for the workplace. I deeply dislike it when people simply say “Hi” without including the context of their message.

Recently, I’ve started applying this concept to personal messages too. Asynchronous communication is hard, round-trip times are long, and text is an extremely lossy medium for communicating intent if you aren’t used to it. If you message me, please let me know the intent of your communication in the first sentence instead of being wishy-washy.

If you want something from me but think it might be too much, just ask! Perhaps it’s the result of working in a professional environment, but I’m much happier being asked directly for something than having someone socially engineer me into thinking it was my own idea to ask if they needed it. Time is valuable.

Also, provide as much information as possible! Please don’t make people ask you for details. Put everything into one message as concisely as you can.

“Hi! Can you help me with this?”
“Can I get some details?”
“Oh yeah… X, Y, Z.”
“Yes/No”

vs.

“Hi! Can you help me do X on Y at Z?”
“Yes/No”

Don’t waste time! Your life will be much better if you do this, and people will appreciate it.

Thank you for your attention to this matter.