Hi. I went through this journey myself. I have a CS master degree, and always wanted to transition into AI research (focus on probabilistic programming, deep learning and self-play, but also simulation, learning-to-learn, bayesian inference, genetic algorithms). The initial plan was to self-learn machine learning, deep learning and statistics. I did that for 1 year, with the hope of joining on of the big AI labs afterwards. As it's very competitive, I couldn't join one of those labs, and wasn't willing to compromise on that. So I turned to plan B: salvage my ML skills by applying them to crypto trading, and if it works, then I'll have funding to start my own lab.

Plan B worked: in 1 year and 2 months, we turned 40k of our own funds into [redacted]. Today we are a team of 5 and we do $5B of daily volume, around 3% of the global crypto markets. Now the challenge is to start the research division, operate the trading and research in tandem, and create the right incentives: the research converts money into ideas, the trading ideas into money. The research would have two sub-divisions: fundamental and applied to trading.

My motivation for the research is mostly curiosity: I want to de-mystify intelligence (natural or artificial) and reverse-engineer it. When you talk about your lab, I resonate a lot with "watch[ing] the beauty of it". The way I would describe my research agenda is the following: put a bunch of phds in a room, see what happens.

If that sounds interesting, email me at [redacted]