skybrian's recent activity
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Comment on Inside Google’s $200bn Wall Street finance machine for Anthropic in ~finance
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Inside Google’s $200bn Wall Street finance machine for Anthropic
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Comment on How accurate have Ed Zitron's AI skeptic predictions been? in ~tech
skybrian Link ParentOn the other hand, the most advanced chips are only made in a few billion-dollar fabs and they're pretty booked. Also, if you don't like the comparison to nuclear weapons, there are other products...On the other hand, the most advanced chips are only made in a few billion-dollar fabs and they're pretty booked. Also, if you don't like the comparison to nuclear weapons, there are other products that are restricted like cruise missiles, machine guns, and prescription medicine.
Also, keep in mind that the goal is to slow things down (a new Moore's law), not to halt progress.
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Comment on How accurate have Ed Zitron's AI skeptic predictions been? in ~tech
skybrian Link ParentYeah, good point. People working on disaster scenario preparations (like Jeff Kaufman is) is something I heartily approve of. I should see if they take donations.Yeah, good point. People working on disaster scenario preparations (like Jeff Kaufman is) is something I heartily approve of. I should see if they take donations.
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Comment on How accurate have Ed Zitron's AI skeptic predictions been? in ~tech
skybrian Link ParentIt definitely won't help with military applications. That would require actual arms agreements, and we don't see anything like that with drones. But limiting civilian access to dangerous tech is...It definitely won't help with military applications. That would require actual arms agreements, and we don't see anything like that with drones. But limiting civilian access to dangerous tech is still helpful.
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Comment on Reasons why robotics is hard in ~tech
skybrian LinkFrom the article: [...]From the article:
In the San Francisco AI scene, there is a widespread belief that robots will soon enter the picture. In parallel with the race to develop broadly capable AI, there is an equally aggressive race to develop broadly capable robots – humanoid machines imbued with physical intelligence. Artificial workers that can cook and clean, fetch and carry… and do everything else, including building more of themselves, leading (in many forecasts) to economic growth best characterized as an “explosion”.
In other words, the thinking goes, AI in the data center will soon subsume all intellectual labor, and AI in humanoid bodies will soon subsume all physical labor. However, there is an important difference: while we can see progress in the intellectual realm, the physical side of AI is mostly confined to test facilities and demo videos. There is no robot equivalent to ChatGPT – nothing that you or I, or even most people in the AI community, can get our hands on.
So we’re stuck with demo videos. Unfortunately, they are a poor tool for assessing progress. We might be seeing the one successful task achieved in 100 attempts. The scenario might have been carefully arranged to avoid challenges the robot isn’t ready for. The video might be edited to make it look like the robot is acting with more speed and reliability than is actually the case. Here’s one very impressive demo… with a suspiciously large number of camera cuts.
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Demos draw attention to the things a robot can already do. The question then becomes: what’s missing? In today’s post, I’ll catalog the technical challenges that will have to be overcome along the road to broadly capable artificial workers. The next time you watch a robot doing something impressive, ask yourself: which of these capabilities has the robot demonstrated, and which challenges might the demo scenario be avoiding?
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Reasons why robotics is hard
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Comment on Want some advice on how to escape my current situation - I [34M] am fed up of my [68F/81M] parents and want out in ~life
skybrian LinkThis is a long shot, but do you know anyone you might consider sharing a place with? Obviously it depends a lot on who it is.This is a long shot, but do you know anyone you might consider sharing a place with? Obviously it depends a lot on who it is.
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Comment on How accurate have Ed Zitron's AI skeptic predictions been? in ~tech
skybrian Link ParentPerhaps of interest: we recently discussed an in-depth article about why many people resist building data centers.Perhaps of interest: we recently discussed an in-depth article about why many people resist building data centers.
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Comment on How accurate have Ed Zitron's AI skeptic predictions been? in ~tech
skybrian Link ParentI think it would still make sense because the impact on the job market can't happen if companies don't have access to the models that have the right skills to do the work they want to automate....I think it would still make sense because the impact on the job market can't happen if companies don't have access to the models that have the right skills to do the work they want to automate. And there are lot of tasks that AI can't do yet.
Yes, there are also lot of jobs that are already at risk, but it would give society time to absorb the impact of the new tech that's already out there without piling on more changes.
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Comment on How accurate have Ed Zitron's AI skeptic predictions been? in ~tech
skybrian Link ParentI suspect that’s partly a matter of power: longshoremen controlled ports, which are a choke point, so they were paid off. A similar thing happened for Samsung chip workers. Unions can do it in the...I suspect that’s partly a matter of power: longshoremen controlled ports, which are a choke point, so they were paid off. A similar thing happened for Samsung chip workers. Unions can do it in the construction industry in some cities, unless they have to compete with non-unionized workers.
Many white-collar workers don’t have that kind of leverage.
Also, there will be new firms that just never had that many workers to begin with. Google doesn’t have an army of support staff in call centers like older businesses would have.
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Comment on How accurate have Ed Zitron's AI skeptic predictions been? in ~tech
skybrian Link ParentGovernments don't allow the public to have access to nuclear weapons, though, and already there are restrictions on who can use "cyber" LLM's. The "pacing" thing might be more about how soon the...Governments don't allow the public to have access to nuclear weapons, though, and already there are restrictions on who can use "cyber" LLM's. The "pacing" thing might be more about how soon the public gets access to more advanced models and the society-wide disruptions from that happening too quickly.
But many people become libertarians when their own access is impeded in any way, society be damned.
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Comment on How accurate have Ed Zitron's AI skeptic predictions been? in ~tech
skybrian Link ParentThere's an emerging consensus at least among AI researchers and leadership that AI is improving too fast and there should be an international agreement to keep it from improving too fast. This is...There's an emerging consensus at least among AI researchers and leadership that AI is improving too fast and there should be an international agreement to keep it from improving too fast. This is called "pacing." More here. If we somehow managed that, it would answer the "not a lot of time" problem. Why not make more time?
As you can see from that thread, there's skepticism among people who see the world in populist terms, where an attempt among the elite to gather consensus to do anything constructive must be some kind of conspiracy or cartel.
Given the populists in power, an international agreement does seem unlikely. As we've seen with climate change, international agreements are hard even in favorable conditions.
I don't know how you keep populism from undermining any good idea that comes along. Maybe thing to do is to try to harness it like Mamdani is doing, and then give the populists some of what they want? Sometimes it will be a dumb idea that sounds good, but if it doesn't do much damage then maybe it's not so bad?
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Comment on How accurate have Ed Zitron's AI skeptic predictions been? in ~tech
skybrian Link ParentI think "for many tasks" is doing all the work there? Sure, it's not hard to think of routine office tasks where leading LLM's do as good a job as you or I could do. This is basically playing..."For many tasks, we could say that we’ve already achieved AGI," Huang said. "I think of all of those milestones…they’re kind of senseless at this point."
I think "for many tasks" is doing all the work there? Sure, it's not hard to think of routine office tasks where leading LLM's do as good a job as you or I could do.
This is basically playing around with definitions in a motte-and-bailey kind of way.
I think it's very fair to criticize such rhetoric, but it doesn't justify Zitron's disregard for the facts. The other side hyping things up doesn't justify spreading your own misinformation.
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Comment on How accurate have Ed Zitron's AI skeptic predictions been? in ~tech
skybrian Link ParentI haven’t seen any serious estimate that AGI is six months away. The most aggressive timeline I’ve seen is AI 2027 which was a scenario published in 2025. As the name indicates, they have it...I haven’t seen any serious estimate that AGI is six months away. The most aggressive timeline I’ve seen is AI 2027 which was a scenario published in 2025. As the name indicates, they have it happening in 2027.
So far, the details are wrong but they are often vaguely similar to what happened. The scenario had coding automation in early 2026, very good Chinese models in mid 2026, AI takes some jobs in late 2026.
The job market for junior software engineers is in turmoil: the AIs can do everything taught by a CS degree, but people who know how to manage and quality-control teams of AIs are making a killing.
Seems relatable?
There’s a bit about China “stealing the weights” from a US AI firm, which hasn’t happened, but there have been industrial-scale distilling attacks.
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Comment on How accurate have Ed Zitron's AI skeptic predictions been? in ~tech
skybrian Link ParentIt's vaguely ominous, but I'm wondering what there is to say or do. I think college students and new grads are already worried? It may or may not happen in any given industry and the timing is...It's vaguely ominous, but I'm wondering what there is to say or do. I think college students and new grads are already worried?
It may or may not happen in any given industry and the timing is uncertain. What should people do to prepare when we don't know the impact yet?
Of course there is general-purpose preparation, like setting up an emergency fund and saving what you can.
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Comment on How accurate have Ed Zitron's AI skeptic predictions been? in ~tech
skybrian LinkFrom the article: [...] [...] [...] [...] [...] [...] [...] [...]From the article:
I was curious how well the predictions of the most widely cited AI skeptic I've seen (Ed Zitron) have done, so I looked at how his predictions panned out. To disclose my own biases, I've never had a particularly strong pro or anti AI progress position. For example, in 2022, I did a comprehensive look at predictions Futurists made, including well-respected folks like Kurzweil and found them to be generally wrong on both the prediction results as well as the reasoning. On the flip side, in 2015, I wrote about how people were underestimating AI's ability to displace humans in jobs and have repeatedly been on the record as saying that many people are underestimating AI's ability to displace humans from jobs. My position on AI has been extremely boring and is basically, "if something is currently happening, the people who are saying that it's impossible that it will ever happen are probably wrong".
One comment I've seen from a lot of AI skeptics when someone responds to an AI skeptic is that all of the people who are saying that AI isn't fake are self-interested liars. Personally (to my obvious detriment), I have no particular financial interest in AI companies. I own whatever the standard share of them is via boring index funds. I have some seed stage investments, but just due to the timing and what's gotten big, that part of my portfolio is underweight on AI. I don't work at an AI lab or a company that supplies AI labs. I've mentioned being hilariously bad at interviews before, and I did interview at an AI lab a number of years ago and failed the phone screen in a performance that was the kind of performance that must've inspired Jeff Atwood's famous Why Can’t Programmers... Program? where he concludes that there must be a lot of fake programmers out there because nobody could fail a coding interview that badly if they knew how to program. I don't benefit in any particular way if AI does well, except insofar as anyone who holds broad index funds benefits, but I do care about accuracy.
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Because there are quite a few prediction results, let's look at one in detail before the complete list to get an idea of the kind of reasoning Zitron uses. We'll arbitrarily look at this November 2024 talk where Zitron says, among other things, the major tech companies (like Meta and Google) are dying and they're thrashing around on AI because they don't know how to grow.
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Although this wouldn't be in the spirit of Zitron's statement, one could argue that Meta is actually dying, it just hasn't died yet. However, the reasoning in Zitron's argument is incorrect here—the Meta, Google, and Microsoft ecosystems are not dying. Given how fast these companies are growing (in terms of revenue and profit), it doesn't seem that AI is, as Zitron implied, some kind of desperation move they're reaching for because "they don't know how to grow" and are all out of ideas. I don't think it's worth spending this much text on each prediction, but the pattern Zitron used here is illustrative.
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From what I can tell of how people cite Zitron, they cite him as an authority so they can say that this guy who looked at the numbers has made this claim, so their claim is backed up by the numbers. It turns out that if you look at the claims Zitron makes and know anything about the topic, the claims don't make sense, but I don't think that's the point. The point is one can say that someone looked at the numbers. The other point seems to be that this guy is angry2, which is a good way to drive engagement.
But when people bring him up, they're of course not generally citing his anger; they're saying here's this guy who's looked at the numbers and, if you're angry about AI, he's right there with you being angry about AI, and he's got numbers on his side.3 Like I said above, I don't want to go into this level of detail on each claim; this is just an illustrative example about how the claims below look. For any of his posts that I read, while there are numbers thrown around, the numbers don't actually connect to a coherent argument. In many cases, as we saw above, the numbers don't even really support his argument (such as an MAU decline in Facebook causing Meta financial problems which would then cause Meta to spuriously insert AI in places it doesn't belong). I suspect he's relying on people's eyes glazing over when they see numbers and just not thinking about what the numbers mean.
With the predictions below, someone could have the exact same prediction record and have completely reasonable reasons that just didn't pan out. Or someone could be correct in every case and also be wrong because all of their reasons are wrong. Someone like the latter person might have some kind of intuition that they're unable to articulate, or perhaps they're someone who just got lucky. Fortunately for us, we don't have to make this difficult judgement call because Zitron is wrong on the predictions and also wrong on the reasoning.
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If we compare to how futurists did in our analysis of futurists, on style, Zitron relies much more heavily on anger than any of the futurists we looked at. On the quality of reasoning, he was probably about average compared to the futurists. Despite being wrong on roughly everything, he's not more unreasonable than someone like Buckminster Fuller, who suggested we'll be able to send people by radio because atoms have frequencies and radio waves have frequencies so it will be possible to pick up all of our frequencies and send them by radio.
In terms of the style of reasoning, of the futurists reviewed, he's probably closest to Kurzweil, in that he uses numbers to give a kind of aura of credibility, but if you know something about the topic he's discussing or look at the numbers, the reasoning falls apart. Zitron's reasoning isn't worse than Kurzweil's, who (for example) continually made new predictions of extremely fast progress that didn't pan out (such as, in 2001, predicting unbounded lifespans by 2011). Continually predicting that AI progress will stop for reasons that are incorrect is just taking the flip side of the bet on progress. Instead of having infinite progress, we're going to have no progress. Every time that prediction is proven wrong, you can just make another similar prediction and then move the date forward a bit. Michał Zalewski (lcamtuf) has some thoughts on why this happens:
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I'm curious what people do after being on the wrong side of a set of failed predictions about progress like this. For the futurists, even the ones who were nearly completely wrong (which was every single one reviewed here), they can still make some kind of case like "a quarter of the things I said would happen happened, it just took two to twenty times longer than I expected" and if they're not so stuck on accuracy, they can round this up to "the things I said would happen happened", which is often what they've done. That seems to have served them well as nobody really cares to look at the details anyway.
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Amazingly, following the series of incorrect predictions Ehrlich made in and after writing The Population Bomb in 1968, he followed this up with The Population Explosion in 1990 and has continued saying that we have global overpopulation that is causing or will cause a dire crisis unless we cut worldwide population. He has said the same thing this century and even this decade. It appears the only reason he's not saying that today is that he died earlier this year.
If I didn't look it up, I would've guessed that his recent position would be something like "well, I got some things wrong, but it was only due to these actions that were inspired by my work that crisis was averted", not "just you wait, the crisis is happening now and I'm about to be proven right"; in 2015, referring to his incorrect 1968 book, he said "[m]y language would be even more apocalyptic today". That's the pattern we've seen from Zitron, but I wouldn't have guessed that the one person I looked up would've kept that up for 50 more years. Maybe we'll get 50 more years of Zitron predicting the end of AI progress.
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BTW, a funny thing about Gemini hitting 500M users being "so unrealistic that someone at Google should have been fired, and that someone is Sundar Pichai" is that Zitron has also (incorrectly) said that Google doesn't know how to grow, and that as a result they're shoving AI everywhere. Dennis Snell pointed out that, if Zitron takes his own statement seriously, Google can make Gemini's user numbers go to any number it wants by doing the exact thing Zitron said they would do, sticking AI everywhere.
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That last sentence really sums up Zitron's position. "There are so many guys to be mad at the moment". In this talk, he throws in this jab at Andreesen and blames Andreesen for Meta, Google, and Microsoft pursuing growth. In reality, if Marc Andreesen had never existed, Meta, Google, and Microsoft would almost certainly still be trying to grow so we of course cannot actually blame Andreesen for these companies trying to grow. There's just this thing that he says is bad, and in his usual style, he pulls some person and says they're the evil villain that's to blame for this, and then moves on to the next non sequitur.
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How accurate have Ed Zitron's AI skeptic predictions been?
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Comment on The 2026 Hugo Award winners! in ~books
skybrian Link ParentI’ve read it. It’s a long, uneven, wide-ranging book covering a lot of history, only vaguely related to science fiction or fantasy, but still pretty great and recommended. I think it got an award...Inventing the Renaissance by Ada Palmer
I’ve read it. It’s a long, uneven, wide-ranging book covering a lot of history, only vaguely related to science fiction or fantasy, but still pretty great and recommended. I think it got an award because Ada Palmer is both a historian and a science fiction author.
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Comment on Be careful about what you want (gifted link) in ~life
skybrian (edited )LinkThis is great. Mixed motives should be acknowledged more often, in a positive way. Few people are saints. Too often, we see the opposite: shallow accusations of hypocrisy. If you advocate for...In other words, if I’m going to be really driven, I need to harness both selfless and selfish motivations. I don’t scorn mixed motives; I live by them. I think a lot of us live this way.
This is great. Mixed motives should be acknowledged more often, in a positive way. Few people are saints.
Too often, we see the opposite: shallow accusations of hypocrisy. If you advocate for something that also benefits yourself or your organization, this is seen as a reason to dismiss the whole argument. An extreme form of this is dismissing things as “marketing” based on convoluted logic to show that, despite all appearances, an argument is somehow self-serving.
We should be able to acknowledge that people are often “talking their book,” while also being open to ideas that might still be right. Self-interest is a good reason to be somewhat suspicious and cross-check, but it's not proof that an argument is wrong.
https://archive.is/h6ysi
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