[ishtiaqrahman]

GREAT QUESTIN!

My theory is that since LLMs (Large Language Models) are the ultimate generalists when it comes to knowledge, they "know" a decent amount about every single topic and concept known to the entire human race. I do not believe there is a single human alive today who possesses knowledge about so many different subjects. For example, a physicist may know 100 times more about physics and mathematics than an LLM, but the LLM probably knows a decent amount about 10,000 more disciplines (like plant biology) that the physicist has little to no understanding of.

I believe this multidisciplinary ability makes LLMs uniquely qualified to pick stocks based on the millions of variables that may impact stock prices.

For example, one of the most successful strategies I deployed was when I asked GPT-4 to come up with the attributes of a hypothetical "most investable stock on the NYSE and NASDAQ based on current market conditions." Once it generated the attributes, I used another instance of GPT-4 to find me a stock that matched these attributes. It came up with NVIDIA. The actual prompt I used was more detailed, but you get the idea.

[ungreased0675]

So… an LLM doesn’t actually “know” anything. It’s not actually calculating any of the variables that affect stock prices.

Have you double checked GPT-4s work? The stock most matching the pre-defined attributes really was Nvidia?