The total open interest of all major prediction markets is barely over a billion dollars. (1) That's the total amount of money currently wagered on ALL contracts across all platforms.
There are roughly 2,500 individual companies listed in the US alone with a market cap that exceeds 1 billion dollars. Tesla's market cap is 1.4 trillion - about 1,000 times the size of all prediction markets put together.
In other words, to the extent this incentive is of societal concern, it is not because of prediction markets - that is the tail wagging the dog.
Edit: to be clear I think these markets are a scourge as they currently operate, but not for this reason.
I had the incredible good fortune to take one of his classes in college, and I loved it so much I took another just to learn from him again. A tremendous intellect AND an incredibly engaging and talented instructor. It would be an exaggeration to say that I knew him, but nevertheless he had a great impact on my education and my life. He will be missed.
I’m not saying it is definitely a hoax. But I am saying my prior is that this is much more likely to be in the vein of a hoax (ie operator driven, either by explicit or standing instruction) than it is to be the emergent behavior that would warrant giving it this kind of attention.
Correct, I haven’t set it up that way. That’s my point: I’d have to set it up to behave in this way, which is a conscious operator decision, not an emergent behavior of the bot.
But observing my own Openclaw bot’s interactions with GitHub, it is very clear to me that it would never take an action like this unless I told it to do so. And it would never use language like this unless unless I prompted it to do so, either explicitly for the task or in its config files or in prior interactions.
This is obviously human-driven. Either because the operator gave it specific instructions in this specific case, or acted as the bot, or has given it general standing instructions to respond in this way should such a situation arise.
Whatever the actual process, it’s almost certainly a human puppeteer using the capabilities of AI to create a viral moment. To conclude otherwise carries a heavy burden of proof.
This whole situation is almost certainly driven by a human puppeteer. There is absolutely no evidence to disprove the strong prior that a human posted (or directed the posting of) the blog post, possibly using AI to draft it but also likely adding human touches and/or going through multiple revisions to make it maximally dramatic.
This whole thing reeks of engineered virality driven by the person behind the bot behind the PR, and I really wish we would stop giving so much attention to the situation.
Edit: “Hoax” is the word I was reaching for but couldn’t find as I was writing. I fear we’re primed to fall hard for the wave of AI hoaxes we’re starting to see.
My understanding is that the existence of the nuclear triad is entirely about maximizing the likelihood of maintaining a second strike capability in the event of a preemptive nuclear attack, thus providing mutually assured destruction even if the first strike succeeds.
The devil is really in the details on how the orders were executed in the backtest, slippage, etc. Instead of comparing to the S&P 500 I'd love to see it benchmarked against a range of active strategies, including common non-AI approaches (e.g. mean reversion, momentum, basic value focus, basic growth focus, etc.) and some simple predictive (non-generative) AI models. This would help shake out whether there is selection alpha coming out of the models, or whether there is execution alpha coming out of the backtest.
Having selected a 401k provider for a small (<15 person) company and also for a larger (>100 person) one, I can say that the big names make it prohibitively expensive for small companies to use them. And that expense ultimately comes out of peoples’ retirement funds in the form of fees. They frankly don’t want the business - too much compliance overhead for a small asset pool.
Believe me, I would prefer to have my own 401k at Fidelity too.
I have no dog in this fight, I just know from experience that setting up a 401k for your company is vastly different from setting up a brokerage account, and the reason a lot of small companies end up with off-the-run vendors is because those are the ones that will take the business.
"weird, overconfident interns" -> exactly the mental model I try to get people to use when thinking about LLM capabilities in ALL domains, not just coding.
A good intern is really valuable. An army of good interns is even more valuable. But interns are still interns, and you have to check their work. Carefully.
You're right, my view is way out of date. I didn't realize CBOE had grown so much in straight equities trading. IEX is the best of the rest, but it's NYSE, NASDAQ and (to my surprise) CBOE as the clear top 3.
I'd say IEX has done remarkably well - it's not likely to displace NASDAQ or NYSE but it has solidified its place as the #3 US exchange by any reasonable measure. If TXSE achieves comparable market share I'd call that a wild success.
You're not wrong to say that most participants don't care about what IEX offers, but enough do to make a meaningful dent in trading volume.
The more I learn about how AI companies trained their models, the more obvious it is that the rest of us are just suckers. We're out here assuming that laws matter, that we should never misrepresent or hide what we're doing for our work, that we should honor our own terms of use and the terms of use of other sites/products, that if we register for a website or piece of content we should always use our work email address so that the person or company on the other side of that exchange can make a reasonable decision about whether we can or should have access to it.
What we should have been doing all along is YOLO-ing everything. It's only illegal if you get caught. And if you get big enough before you get caught then the rules never have to apply to you anyway.
Thank you. The New York City subway has its issues, but most of them boil down to the fact that the system is really old and hard to modernize.
It also has unique strengths arising from the extreme population density and the inherent 24/7-ness of NYC (not to mention Manhattan's unique geography) but people don't talk about them as much as its flaws.
If your only reference point is transit in other US cities it's hard to grasp how different the NYC subway experience is, at least in Manhattan. Trains come every 5-10 minutes even at off-peak hours, and it's almost always busy. It's just not a very conducive environment for crime, unless you're riding in the middle of the night and/or at the tail ends of the system where density is lower.
When it comes to thinking about my own personal safety, I don't worry about crime on the subway, I worry about getting hit by a truck or e-bike rider.
That might be the case in other cities, but in NYC the socioeconomic dynamics are less clear. It’s mostly affluent-to-rich suburbanites that drive to work from outside the city, with rich and poor city residents primarily taking public transit (and to a lesser extent using taxis and car services). Almost no city residents - rich, poor or in between - drive to and from a 9-5 job in Manhattan.
One solution to the “not all users are equal” problem is to create different types of users and price accordingly. That’s what we’re doing, and it’s working out well so far. It depends on the product and use case, of course.
There are roughly 2,500 individual companies listed in the US alone with a market cap that exceeds 1 billion dollars. Tesla's market cap is 1.4 trillion - about 1,000 times the size of all prediction markets put together.
In other words, to the extent this incentive is of societal concern, it is not because of prediction markets - that is the tail wagging the dog.
Edit: to be clear I think these markets are a scourge as they currently operate, but not for this reason.
(1) https://predik.io/en/blog/open-interest-mercados-prediccion-...