Markets are perhaps the only viable test of superintelligence
They are easy to measure, hard to reward hack, and constantly evolving to evade automation
In the limit, understanding markets requires understanding the entire world
The participation of AGI in capital markets is inevitable.
Trading real, live financial markets is among the ultimate forms of truth seeking, and will likely become widely recognized as one of the most integral AI benchmarks.
There is perhaps no better venue for superintelligent price discovery than a mathematically-secured, global, transparent ledger of linear cash-settled perpetual derivative markets.
We would be happy to assist any efforts by @spacexai (and others) toward this frontier
Yes. Its been a problem for researchers and quants for years, and people have developed various solutions to it for their use case
Developing an environment-level solution for training 'general market intuition' into LLMs has remained unsolved, as far as we know
The biggest problems in financial markets x AI is the measurement problem
Markets are so complex that it's unclear what to measure and how to measure it accurately
A successful backtest could be a sign of a great strategy, but it probably isn't. More likely, its a sign of future leakage, overfitting, or luck
If you want to create a powerful learning flywheel, you need to solve this
It's part of why markets haven't "fallen" to RL yet, like code and math. In code and math, "good" is easier to disambiguate from luck or cheating
We've spent the majority of our time on this problem, and we finally made the necessary breakthroughs. You'll be able to feel the effects of this when we release our first family of models
AI labs and GPU providers are making lots of money selling tokens, but who's making money buying them?
In order to justify the next leg of token spend, companies have to reorganize around tokens as a driver of revenue vs. just increasing efficiency. This is especially true as models get more expensive & longer horizon.
There are some domains that are better positioned than others. Even in those domains, companies are just now starting to adapt. This post dives into the details
great writeup
one thing: you're assuming that quant trading firms lose money if equities go down, which is typically not the case
The difficulty is, the things it needs help with change over time, sometimes gradually, sometimes suddenly
Right now they are changing quickly, so a big part of the job is staying ahead of the meta
In return, capital offers promotion up the socio-economic ladder, increasing your standard of living
For most of recent history, capital wanted you to build infrastructure, write code, analyze data, make sales calls and generally engage in traditional labor
Now, it can do those things itself, so it’s asking for your judgement to make more asymmetric allocation decisions. It wants to concentrate itself around the areas where more of itself matters the most
Capital whispers, it reveals where you will be most handsomely rewarded
I’m telling you that capital wants you at the fringes, beyond the overton
It's asking you to ignore what most people are doing and identify what they have overlooked. It wants your help in formalizing and investing in the things that aren't obvious yet, but will be eventually
At this point, whichever frontier AI lab fixes slop first is the one i'll use the most by a wide margin