md2020

> 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.

This comment violates several HN guidelines. Take your anger elsewhere.

> 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.

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?

Can you elaborate on why the increasing accuracy of these measurements indicates that the universe is metastable?

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.

Nobody said the causes the foundation is funneling money to are Democrat causes, though. They’re something entirely different.

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.

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?