HN user
Isn't this the same as saying "utility regulators delaying connecting new power to the grid hiked electricity prices on the public by $23B?"
When my apples are expensive, I don't generally grumble about all the demand from pie makers. If they demand more apples, new suppliers should come in to restore the price, right?
I can ask an agent to add OAuth, you can ask one to add caching, and somebody else can ask one to rebuild the database from first principles and make the UI pink. Each change can be reasonable in isolation.
But this is just bad vibecoding? This would be bad if humans did it too. With agents or humans, you need to coordinate.
When I know something is (primarily) AI generated, I lose interest.
The exception is when it's about a niche I care about, e.g. an analysis of opening trends of early world chess champions. I'll read AI on that for an hour.
My sense is that, for most writing, it's fundamentally interpersonal, the information is about the author as much as it is about the world.
Maybe this flood of slop will cause people to care more about the substance of the writing, not the perspectives of the writing.
Is it possible GPT-5.6 is not a very aligned model?
People have been making claims about the commoditization of llms since chatGPT, and they've been wrong every time as quality and prices and differentiation have increased.
But Scott's point is more: why even have markets? Once you have the superforecasting available on the questions you care about, why do you need to publish it for everyone to also react to?
Almost by definition, once AI forecasters are in the market, they won't (all) be beating the market.
But why evaluate AI forecasters by beating the market? Do we evaluate deep learning by whether hedge funds make money from it in the markets? These things have far, far more utility outside of finance.
Doesn't this argument prove too much? Why does AlphaSense sell their company research instead of using it to trade themselves? Why do people work on open source time series forecasting packages instead of quietly using them to trade?
Indeed they are! It's funny, in Sept 2024 I and others wrote about how the AI Superforecasters _weren't_ here, despite several claims that they were: https://www.lesswrong.com/posts/uGkRcHqatmPkvpGLq/contra-pap...
Yeah, a great developer I know showed me how he could use it to get a safe dev container for Claude Code, in a way that wasn't doable with Docker.
Fair point.
Is this the trend? There have been various points where one of Anthropic or OpenAI was substantially ahead. Sure, many times they're close, but now doesn't seem like one of them.
Based on my conjecture that Anthropic is ahead on AI research, and that OpenAI doesn't know how to make Fable-class models.
I'm going to pre-register my prediction that GPT-5.6 Sol is significantly behind Claude Fable 5, as evaluated by general consensus once time has passed for people to get familiar with both.
If it's helpful, I'm still holding at July 9 as my median date that Fable gets re-released to Americans, the news of the last 24 hours didn't update the model meaningfully.
People forget that Meta already did this years ago, before prediction markets became the next big consumer trend for them to chase.
The app was called Forecast, and launched in June 2020. (Around the same time that Kalshi and Polymarket launched, actually!) It was framed as a way to make the comments and activity on Facebook actually productive rather than toxic, and build expert reputation signaling mechanisms.
I think they sunset it after about a year.
You mean chatgpt style AI won't help them with those skills?
If a human parent or teacher can help with skills like reading, an AI system can too, once it's trained and designed to do so. (How good are humans at teaching reading anyway?)
Yes, I have, but comments are still useful. Don't you think this is an overcorrection?
It is refreshing but perhaps actually not warranted this time?
I mostly study web research, and Opus 4.7 was a regression on BrowseComp compared to Opus 4.6, which has been born out by my usage.
Opus 4.8 is now much better than either 4.7 or 4.6, and having it search the web is one of the primary use cases of chatbots.
What's a definition of AGI you would use, for either time, tasks, value, or job descriptions?
I linked elsewhere in a comment, Metaculus has AGI forecasts.
You can also now use AI forecasters like FutureSearch [1] (disclaimer: I work there), which are competitive with the best humans / teams of humans. And since you aren't depending on a human crowd, you can ask any variation of AGI questions with any definition, even ask conditional questions.
Thank you! Tok me a few hours, without Claude Code I don't think I would have even attempted this.
It's been a big problem for a while. The big Metaculus question about AGI has depends on the game "Montezuma's revenge" (!), and there have been many debates about this going back to at least 2020: https://www.metaculus.com/questions/3479/date-weakly-general...
Author here, I agree, I'd be happy if admins want to change the title of this submission to the title of the piece.
Author here, I drew on this from AI 2027. Yes, a very-expensive AGI, e.g. $1 million / day to simulate a smart human, would be a huge deal. But it would have meaningfully different effects than a cheap one.
Here's one definition AI 2027 used [1]: "Superhuman coder (SC): An AI system for which the company could run with 5% of their compute budget 30x as many agents as they have human research engineers..."
I see a lot of comments like this is the blocking of prediction markets about politics, war, etc.
It's important to remember that ~80% of activity Polymarket and ~90% of Kalshi, by volume, are sports. These are effectively sports betting websites with prediction markets on the side.
Snake oil is a bit strong, no? I would agree that the burden of proof is on multi-agent systems to show they are outperforming single-agent systems.
On my own evals I have seen this, though the improvement may not have been worth the extra cost.
I like this, though it does leave me feeling more nervous when I really don't know how I'd solve the problem, still requires trust.
It would have to be an incredibly tiny tax, no?
What was your use case?