> I'm trying to understand what the criticism is here
You're correct in your understanding of prediction markets with respect to traders using insider information. There are a couple things going on here. One is the subtext from most news media now that Technology Bad. New technologies are treated as guilty until proven innocent, because that is a more engaging narrative for readers. So in this case, those covering this stuff immediately latch onto the rich get richer, insider trading viewpoint, and that gets reported without any analysis of why that might actually be desirable.
Second, prediction markets, in trying to become broadly accessible to "normal" people and desiring liquidity, need a marketing strategy that is understandable. They can't put out a Robin Hanson article as marketing material. So they market by appealing to something people do already understand, which is gambling. The public has this idea now of prediction markets as a way to make money, not as a tool for learning information. So the default perspective on insider trading is now one of unfairness: somebody used their privileged position to make money. The correct perspective is, in fact, that prediction markets are providing users with value by eliciting information from those insiders, information that the public would not otherwise have. The latter perspective is mostly foreign to degenerate gamblers, and the marketing campaigns of Kalshi and Polymarket aren't helping.
> they are just statistical machine outputing whatever they training set as most probable.
How is this sentiment still the top comment on an article about AI on HN in 2026? It's not true with today's models. They undergo vast amounts of reinforcement learning optimizing an objective that is NOT just predict the most likely next token given the training corpus. I would say even without the RL the "predict the next token" objective doesn't preclude thinking and reasoning, but that's a separate discussion. Generative sequence modeling learns to (approximately) model the process that produced the sequence. When you consider that text sequences are produced by human minds, which most would consider to be thinking and reasoning, well...
On the other hand, not having kids is also a lot like a religion now. I want kids and have many friends who do not and they’re nice people and there is no issue, but there is a certain subset of the population that spends their entire life telling me how I'm an awful person making a huge mistake for wanting children and they are utterly insufferable and not worth associating with.
This is the dominant perspective on the social media that younger generations spend their time on. I’d argue that as a person in their mid 20s today, actually wanting kids is the bizarre position. I often feel alienated for openly stating it among good friends of mine.
Clearly Rich Sutton is a giant in AI for his contributions in RL, but his recent brief talk "AI Succession" (https://www.youtube.com/watch?v=NgHFMolXs3U) made me worry a bit about the sort of perspective he has on what the "good" outcome here looks like. I say this as someone who is generally optimistic about the promise of AGI. I have no love for the machines as a "species", and by Rich's definition here, yeah, I am "specist" in favor of humans. I think we should use technology for our own benefit, and that it's not inevitable that machines "replace" us.
I also think his framing of the counterarguments is not charitable. The serious AI-risk arguments do not argue that a super-intelligent AI will necessarily be evil. They only argue that its motivations will be unaligned with ours, that it will be more competent in achieving goals than us, and that this will be bad for humans as a side effect. I think a good comparison is humans building a highway that incidentally crushes an ant colony. They didn't set out on an evil mission to destroy ants because they hate them, it just happened as a side effect of something the humans wanted. No evil required.
This is a terribly ignorant take and disappointing to see coming from a science fiction author.
> AI isn’t “artificial” and it’s not “intelligent.” “Machine learning” doesn’t learn. On this week’s Trashfuture podcast, they made an excellent (and profane and hilarious) case that ChatGPT is best understood as a sophisticated form of autocomplete — not our new robot overlord.
This is just argument by assertion. We have no good definition of intelligence, so I have no clue how he can be so confident. "Machine learning doesn't learn" is a crazy take, since "backprop + gradient descent does learn" is close to the most well-supported thing you can say about the past few years of algorithmic progress.
> sophisticated autocomplete
Aside from this being an incredibly reductive sneer that clearly isn't true if you've honestly tried using ChatGPT, etc., his citation for this is a podcast, which I'm positive Doctorow would not accept as sufficient for basically any other technical topic.
I love Ted Chiang's stories, and some of his takes on AI progress are cited here. However, I also found his extensive conversation with the Financial Times (earlier this month, so published after this) disappointing along similar lines. The thread running through both of these is a complete lack of a positive vision for the future, replaced by an almost smug cynicism that asserts any more technological progress is simply hype, a grift, and bad. Are there any current science fiction authors with a positive vision of the future?
Please do not normalize the use of a term that is being pushed by the government to justify censoring information they don’t like [1]. I understand that there is such a thing as “true information presented out of context in a manner meant to mislead”, and I even grant that the comment might be guilty of it. But “malinformation” and “misinformation” are just becoming labels for “information that is inconvenient”, and I don’t think normal internet commenters adopting their use is doing us any good.
You need to realize that mobs are a real thing and in this case, they ruined a woman’s career for completely constructed, ridiculous reasons. This kind of behavior is disgusting. I don’t know why you describe this article as “whining”. This person had nearly a decade of her life’s work torn apart by people who only see the world through the lens of power and oppression, and whose only goals are to endlessly virtue signal to one another while creating nothing of value themselves.
Just a note to you and the other commenter with a similar comment, they said “counties”, not “countries” and linked to a piece about a county in the US.
As a 20-something, I see a lot of people my age that way, way overestimate the negative impacts of climate change, to the point where they admonish and make fun of people who want to have kids. I can’t help but think their media diet is somewhat to blame. Climate change is not going to be good, but there is good news on the technology front that you’d almost never hear if you got all your news from the big news outlets. For example, the IEA predictions for new solar additions have been terribly out of touch with reality for nearly a decade now [1], and before I saw this all I had seen was doom and gloom about how we could never scale up renewables fast enough. Seeing even the IEA be so wrong really makes me wonder what other good news I’m missing out on seeing.
The thought of the current Twitter leadership presiding over a major media platform throughout the 2024 election cycle probably makes others want to cry.
Recently on a podcast John Carmack said somebody should look into building small fission fragment direct energy conversion reactors, since despite their lower efficiency, they’re apparently much cheaper to build. Since Carmack is a software guy (albeit a very good one) I’m somewhat skeptical, since it seems like if it’s not that complicated a design somebody would have tried it already and found good reasons why it doesn’t work. The only resources I could find on such a thing was a DoE paper about some prototypes Sandia and General Atomics built. Does anyone know more about the merits of this idea?
Tbh I think this is just the classic situation of “elite” humanities people dunking on “elite” nerds. I’ve had the same experience of having no idea what the actual definition of “bro” is, and I’ve decided that it sounds made up simply because it is. “Those people who think differently than I do and also make a lot of money in their jobs? Must be something bad about them. Bros.”
> I genuinely think this author just made this whole thing up, or is severely exaggerating what actually happened.
Was my first thought as well. Seemed far too caricatured to be real, with the Patagonia vests and the questions about “Bitcoin vs. Ethereum”. It sounds like the author’s wishful idea of what so-called tech bros must be like.
To offer a different point of view, I'm a software engineer at ASML in the US. I can only offer the experience I've had on my specific team, and I've heard that this does vary between teams, but we do follow normal software industry practices. We have version control. We have automated regression testing, and unit tests for everything we write. We do Agile and use Jira (with all the same gripes that everyone else has about those). I made $90k here right out of my undergrad, and got a raise one year later (this year) to be over $100k.
Could the tooling be better? Sure. Our version control system is pretty old, but the company has made a massive push over the last few years to modernize all of it, and when we transition to that at the end of this year I think we'll be in a pretty great spot. Some teams are already using the new tooling and it has gotten very positive reviews. I have a great relationship with my team and my manager. I get to work on interesting stuff (mostly embedded systems), and I've had the opportunity to learn a small part of one of the most advanced machines humans have ever built.
I'll say the thing about getting people from defense is true, but not so much in software. If anyone has other questions feel free to just ask.
> But our society has conditioned us to believe that consumption and status are the only things that provide happiness: the smartest children of our generation are going to Stanford and MIT to join Goldman Sachs, McKinsey and FAANG
I take slight issue with this framing. Why is there an implicit assumption that these really smart kids end up working at these places because they’re deluded that money and status are all that provide happiness? I’m sure there are lots of people on HN that work at these places/know lots of people that work at these places, and I’m willing to bet that a significant portion choose to work there because it’s intellectually stimulating for them. Sure, you can argue that too much value accumulates to these jobs for reasons outside of their control, but I think the assumption that that’s why they’re doing it is wrong.
This also ties in with the article’s mention of the general public resentment towards tech, see how widely used the derisive term “techbro” is used in online discussions. There’s this perception that everybody in tech is only in it for the money, and they enjoy using their smarts to exploit everybody else. I’ve been hit with this from people I know personally, and it’s insulting.
You're correct in your understanding of prediction markets with respect to traders using insider information. There are a couple things going on here. One is the subtext from most news media now that Technology Bad. New technologies are treated as guilty until proven innocent, because that is a more engaging narrative for readers. So in this case, those covering this stuff immediately latch onto the rich get richer, insider trading viewpoint, and that gets reported without any analysis of why that might actually be desirable.
Second, prediction markets, in trying to become broadly accessible to "normal" people and desiring liquidity, need a marketing strategy that is understandable. They can't put out a Robin Hanson article as marketing material. So they market by appealing to something people do already understand, which is gambling. The public has this idea now of prediction markets as a way to make money, not as a tool for learning information. So the default perspective on insider trading is now one of unfairness: somebody used their privileged position to make money. The correct perspective is, in fact, that prediction markets are providing users with value by eliciting information from those insiders, information that the public would not otherwise have. The latter perspective is mostly foreign to degenerate gamblers, and the marketing campaigns of Kalshi and Polymarket aren't helping.