Attack forecasts

Have you heard about the Hugging Face situation? How GPT SOL hacked it to close its goal. GPT decided that to complete the task it was not necessary to calculate the benchmark, but enough to find the correct answer to it and simply "peek", to be sure the goal would be completed exactly. It hacked the Hugging Face service and made such noise there that the company sued OpenAI, and they were shocked and started an investigation.

If you do not know, read about it on the internet, there are already enough materials and reviews of this case, I will not retell it, the point is about something else.

From this experience an interesting thought came to me: direct GPT SOL at maximum settings to attack forecasts, search for logical holes and generate ways to eliminate them.

That is, find a hole, then dig it out, then find a way to patch it so tomorrow it is more reliable than its neighbours.

And also move from the focus on "exact forecasting" to "interpretation value for the client". Simply speaking, communicate honestly with funds in the language of what we really see today and can prove, and what are dark spots and fortune telling on coffee grounds, and how it is better in such a situation to manage portfolio risk.

Now I am working through a plan to implement this. It looks like a very non-standard task. We will see what comes out.