A.I. accurately predicted the full baseball post-season back in July

UNU seems to get their press releases on here a lot. As far as I can see there's not much "AI" involved, just a UI over the "wisdom of crowds" method of making predictions. In this case, the Cubs were heavily favored all season to win the World Series, had arguably one of the best GMs and managers in baseball, and a raft of all-star players. Goat aside, it was fairly smart money to lean towards them from mid-season on.

Same thing with their Kentucky Derby prediction this year. The swarm literally decided the horses in the exact odds they were going off at (which makes sense since gambling odds by their very nature are "the wisdom of the crowd") and that's how they finished.

This reminds me very much of delta polling, where you survey experts in a field with a complex and unsolvable question, tally the results, send that information back to the experts, and then ask them again. After a few rounds this tends to arrive at what is usually a pretty solid answer.

It is used sometimes in scientific and medical research. An automated tool is pretty neat, but like others said, it doesn't really classify as AI. I'm not sure how much money I would really put down on the bets the site makes, but it is similar in some ways to the scandal that rocked Draft Kings/Fan Duel, where admins were using high-level data to make bets on opposing systems. They did in fact make money.

This reminds me of one of the chapters from "How Not to Be Wrong: The Power of Mathematical Thinking" by Jordan Ellenberg (highly recommended). He describes how "stock brokers" would send out a "free stock prediction" to thousands of email addresses. The prediction would be a simple up/down prediction for a specific stock. The prediction was randomly chosen. But these "brokers" would send an equal number of up and down predictions, ensuring that they got a correct prediction for half of their recipients. They would then throw away half of the emails (the wrong half), and repeat with the remaining half. After ten predictions, there would still be a small number of people remaining for whom they'd sent only correct predictions to (10 in a row, which seems really impressive if you can't see the full picture). They would then contact these few people and offer to keep selling them predictions for a fee.

Stories like this (And Paul the Octopus, who I see was mentioned already) are exactly the same thing. Thousands of people are trying to using deep learning (i.e. stats), or other crazy methods as in this article, to make predictions. Of course every now and then one of them is going to work better than expected. This would be the case even if people were simply using random numbers. But we ignore all the ones that fail and give heaps of attention to the Pauls.

The article mentions "swarm intelligence" that essentially forms a hive-mind. Where is the AI/ML when it seems like it just picks the most popular responses from its many respondents?