[gwern]

> And even if it is good enough, once you're shelling out thousands of dollars a year in research costs, does that give you any remaining alpha?

That's precisely why you would want to make a startup to get investment now rather than self-fund and bootstrap. That alpha isn't going to last forever, especially because everyone has access to the frontier LLMs, which keep getting better, and will eventually beat your fancy harness or specialized finetune.

And also, perhaps more importantly, so you can start developing an alternative to prediction markets and become the new PM; as Scott notes, with superforecaster AI, it's unclear why you really need Kalshi or Manifold or anyone else, with all their fees and overhead. Leave them to the degens, and carve off the socially useful part to do much more efficiently - tokens are cheaper than transactions! This is the big prize, but you need to start now before someone else does it better or commoditizes it.

[kennywinker]

> I met an AI superforecaster startup founder who told me his AI had turned $35 into $2 million on Kalshi over seven months

Ok… assuming you can’t use that $2mil for some reason, simply take out a $10k line of credit and you’ll have $571 million in 7 months.

If you have the 2mil, congrats you’re 7 months away from $114B - you’re now one of the top 20 richest people in the world.

If this was truely the money printing machine they are saying it is, they would not be talking about it.

[ffitch]

from the article:

  I asked the guy who turned $35 into $2 million in seven months on Kalshi whether, in another seven months, he would be able to 100,000x his money a second time to $200 billion. Unsurprisingly, he said no - there’s only so much easy money on Kalshi, and his AI had already taken it all (also, other people with similar AIs are starting to fight him for it!)

[kennywinker]

So this stuff is only as useful with a steady supply of people making less intelligent bets. You don’t have to sell me on it being bullshit, but you are.

[ffitch]

The article is not about this stuff being useful for making money off of prediction markets.

[chucksmash]

Any given trade also has a capacity. A mispricing opportunity can only absorb so much investment before it's no longer mispriced.

A particular trade that can 2x $20k won't be able to do the same for $20 billion.

It's why RenTech capped their Medallion Fund and closed it to outside investment.

If there's only a billion dollars sloshing around on Kalshi, you can't expect to put $1 trillion into bets and take $2 trillion out.

[danaris]

But if these "superforecasters" can forecast just about anything accurately—which seems to be the claim—then they're not limited to any one claim, or even a small subset of them. They can place bets on everything and expect to win most of the time.

This doesn't pass the smell test.

[kennywinker]

Stock market’s got plenty to spare

[Tenoke]

1. The liquidity is not infinite to compound that easily.

2. The alpha dries up with more players, even in the year or whatever since that founder started.

[gwern]

You're attacking a strawman. No one is claiming that you can pull off that multiplier at arbitrary amounts arbitrary amounts of times. And 7 months is plenty of calendar time for those arbitrages to disappear, given the attention on the area and the rapid rate of development. (Warren Buffett can't pull off his early trades now either, doesn't mean he was stupid or grifting in taking early investment.)

[kennywinker]

So you agree this stuff isn’t useful?

[gwern]

Wow, I obviously do not agree with that, and since you're trying to put words in my mouth and false dichotomies, I think that's the last question of yours I will be answering.

[kennywinker]

I was specifically responding to your comment by pointing out that you’re describing something that is valuable now but will be of less and less value as the market adapts. If you think that’s a good investment, that’s your business, of course.

[jimbokun]

The article covers the purpose for prediction markets after super human predictors: to deal with bias or ulterior motives trained into the models.