It's a nice rant that I think will become more common until everyone burns out and one important realization dawns upon them: the corporations doing these things don't really care about your plight, suffering, etc. You can write thousands of books using this kind of tongue-in-cheek-but-really-angry language, and they'll just laugh it off. Felix Reisenberg will make a new post about something he's doing with Claude, Boris will make a tweet and everyone will rush to turn it into LLM-generated images so they can post on their LinkedIn for their bosses to measure their engagement KPIs, and we'll forget about the rants.
So if you are suggesting that life is now meaningless at status quo, it suggests that life will find new meaning....perhaps it will come in the form of a realisation that if corporations are in no ones interest, perhaps the better life is the one fighting against meaninglessness through our own redefinitions of noble pursuits...perhaps the most noble pursuit will become war against companies and executives in a post-modern religious crusade to reclaim some purpose in ones life. Perhaps murder is not a problem when you murder companies
It's the same process that has been running - creation of complexity as a dissipative structure - but now with even less friction. Some say we'll transcend, I think we're spiraling into the language-navel of cartesian dualist logical positivist insanity.
I love the dissipative structure framing. It's the only logical explanation for all of this.
Datacenters in space are visionary -- they are maximally energy rate dense and they expand the area of energy absorption. Might be 100 years too early but that is where we are headed, after we turn all of the available biosphere of earth into computronium, that is.
The only superior technology left would be von Neumann probes.
> Of all the things we could be doing, why are we doing this?
Money. Capitalism. It's all a fucking grift. Always has been.
If you thought AI was going to usher in a post scarcity golden age of infinite wealth where all disease, hunger, want and inequality are solved and everyone gets to live their lives purely for pleasure and intellectual pursuit, where the Eschaton is in their Heaven and all is right in the world, and humanity spreads out amongst the stars as beings of transcendent posthuman machine intellect or some shit you read in a sci-fi book then congratulations, you're the mark.
Proving theorems is one of the main ways that mathematicians turn math into money.
The recent barf-out done by LLM companies is useful if what are you are interested in is an unreadable mess and someone giving you the final answer. You might be able to extract some new "aha!" moments out of it, but we will have to wait and see what happens once people go through it. I would hypothesize the LLM output will be good at hinting at some non-obvious relationships and patterns, but I doubt it will yield anything of substance in its own right.
Historically, proving difficult theorems required mathematicians to sometimes invent new fields, new ways of looking at problems, the discovery of which itself yielded incalculable contributions to both mathematics and other fields. It is this that is the greater contribution of and to mathematics.
> Proving theorems is one of the main ways that mathematicians turn math into money.
Mathematicians working at universities are paid to teach, to engage in the politics and business of government contracting, and only in very rare circumstances to play prestige games on famous problems.
It is unlikely that Congress will decide to slash budget for NSF's MPS directorate on account of AI getting good at proving theorems. That's just not how Congress works.
It is also unlikely that LLMs will be able to do, in the near future, do the sort of applied mathematics that happens in the context of occasional NIH or DoD funding that flows into Mathematics departments, for a variety of complex sociological reasons I'm happy to expound upon.
And it's unlikely Engineering degree programs will stop requiring calculus sequences, since being able to do the computation was has not been the actual point of teaching calc since he late 20th century (if ever).
So, the good news is that I doubt any of this will have much of an effect on the job market for Mathematicians who want to prove theorems for a living. The bad news, of course, is that the job market for Mathematicians who want to prove theorems for a living was already pretty horrendous.
This is pretty much the main point of his frustration.
The world has standardised methods of accounting. Not only do Anthropic and OpenAI avoid using those methods, they both use the same phrase “annualised revenues” to describe two radically different accounting processes.
They’re both also leaking those annualised numbers slowly to the press at irregular intervals, which hints that they’re disclosing new numbers in the days after a big sale lands. So you see “$30bn annualised” because they managed to land a $1bn contract the week before, bumping the annualised figure up by $12bn compared to the start of the previous month, and the end of the next.
Yes, This is the one thing he says that generally resonated with me. A lot of his talking points (harnesses as elaborate rude goldberg machines) read more as exaggerated negative statements supporting a pre-concieved narrative
I tried to make a similar play on Heath Robinson but couldn't make it work. In any case check him out, he's more-or-less the English version of Rube Goldberg. Both a lot of fun.
Zitron complained about a lot of things, one some he was wrong (eg. llm are not useful), on others(eg. "magic accounting" or datacenters ) he has very good points ... but we will see.
He did not say LLMs are not useful, he said they’re valuable for software engineering and could justify a hundred million or billion dollar valuation but not a trillion dollar valuation
This is latests refactor, in older videos he stated more than once that llms are basically crap (and at the time he said that he was probably right, but it was very short sight)
No one has rebutted Ed's points. The only rebuttal is "but look how cool AI is!". He mainly sticks to objective facts about their financial situation, and an honest analysis of that situation is dire, regardless of what you think of AI.
So? Tell me his data is wrong, and then I'll care. His primary "prediction" is that it's a bubble and will crash. And he has lots of empirical facts regarding Anthropic, OpenAI, and all the related companies' actual financial situation. Him being wrong on different predictions does not change the fact that Anthropic and OpenAI are in massive debt and do not have the revenue to handle it, and that a huge percentage of the stock market is being propped up by AI. As he himself says, I really hope nothing bad happens, but the financials are to dire to ignore.
His "facts" are not facts, he makes stuff up, miss-states things constantly, and is financially illiterate. Whenever I read anything he writes I'm constantly face-palming because it's basically all rubbish.
He's anti-tech, anti-AI, incredibly biased, and just honestly full of bile.
And yes, I'm saying his data is wrong, his interpretation of the data is wrong, and his conclusions are wrong.
>For example, when Timothy B. Lee looked at a spreadsheet that Zitron used to create a projection of Anthropic's revenue, he found
>He doesn't count February 1-10, counts March 1-10 twice, counts August 21-October 21 as one month instead of two, and doesn't count October 21-November 1. [another commenter notes that his spreadsheet also contains February 30] ... Ed claims he tried to compute Anthropic's revenue for 2025 and came up with $3.6 billion, suggesting some funny business [but the numbers work out once you fix the errors]
from the above link. Personally I agree it's a bubble and there will likely be some sort of crash. But Ed is way to pessimistic on the underlying technology.
And bubbles and crashes are kind of inevitable with any hot new tech given human nature trying to pile in and get rich quick. It's a bit like prediting it'll rain one day.
The reason why B.C. became a thing is because the art of drafting died from CAD. The attention to detail, the minutae of walking the reader through a highly sophisticated thing was replaced by short-form video explanations. His work is very much a callback to the days of old. So too, is his turn to be relegated to a relic of his time.
Also, it's hand coded WebGL. It's smooth, faultless and has no peers.
> So too, is his turn to be relegated to a relic of his time.
No, it'll be tasteful artifact, not a relic. Records, fountain pens and automatic watches did not die. They are used by people who discern things, and no, none of these things have to be expensive (i.e. Neither Seiko 5, nor Lamy Safari are expensive, yet they are as dependable as their 100x expensive brethren).
> But what is the incentive for contractors to participate, and how does it overcome the enormous disincentive of "You are training your replacement"?
They don't need an army of contractors to do this. They just need a few, much like the AI labs that have a handful of SME staff for each particular subject to guide the corpus of data. See mathematics example.
It is not about knowing if someone can be bought. It's knowing just how much is just enough to buy them.
And then you have individuals whose pride is more than enough. See Terence Tao for a great example of a Useful Idiot.
I'm seeing a lot of surprised people on this thread. Have a look at the more recent YC batches of startups. Count all the non-AI ones, and subtract from total. And don't pretend to not know what the end game of something like YC is here. And YC is not the only one.
One company doesn't need to do everything. But 100-1000 smaller companies, each taking on a piece of every-day work that people are paid to do and replacing it with AI, is definitely doable and can pay very well if deployed at scale. It doesn't have to be perfect all the time either - just cheap, fast, and good enough. As it always has been.
You didn't really think they are training vision models so they can just drive your car around, or that they are training robots to perform physical tasks so they can just use them in factories, did you?
You’re almost right but missing an entire category of startup: “egocentric” data. A lot of the most high revenue startups right now are, essentially, recruitment agencies for frontier labs to get video of skilled workers. OpenAI and others are spending billions per year with the various startups. We aren’t witnessing specialized startups training for specific sectors, we are witnessing training startups trying to hoover as much video as possible.
Personally, I’m not convinced these startups have much life in them. They’re popular right now because they are low effort as there is a huge demand from the frontier labs, but a year from now, there’ll be more than enough data.
There are at least a dozen in YC and probably hundreds in total.
I think a lot of the founders of such companies know that their companies have an expiry date and no viable exit strategy.
Probably the strategy is making as much money as possible while there's demand from the AI labs and then the founder will figure out their next steps with a bit more money in their accounts.
There will not be, they will find that the videos submitted are all of noise quality after the training starts, and then they would need videos of certain, specific actions that were basically not recorded. and it will go on and on for quite a long time.
>It'll likely need a whole host of bloody wars for that.
Out of curiosity who are we killing or getting killed by? What amount of brainwashing will it take to get all these rubes to kill eachother to make the 1% richer?
> What amount of brainwashing will it take to get all these rubes to kill eachother to make the 1% richer?
I suppose whatever the amount is we reached it a while ago, given the number of people who have died for oil prices or to distract from this or that domestic political situation.
Pro-capitalist governments (cycle of corruption choosing the winners, revolving door between politics and business)
Human and robotic military conscripted to fight
Capitalists
Capitalists' workers paid enough to not be "worker class"
The other side:
Union supporters
Workers rights advocates
Socialists/communists
People who lost jobs/poverty class
Workers abused more than "average"
We have seen these types of wars before, and in the USA. Our own worker rights and union history was horrendously bloody. Even had the US military killing strikers and union folks. It's also where the private military, The Pinkertons, came from.
And prior to 1940s with FDR, there was a strong Socialist and Communist groups pushing for their respective changes. FDR appeased some of the demands with his reforms. And those reforms were credited to the success of the late 50's and 60's.
reply