Icebox
Ideas I thought about and did not build.
None of these are secret and none of them are coming. If one of them is your kind of problem, take it — I would rather it existed than stayed mine.
Poker bot for online play
A serious poker agent built on counterfactual regret minimisation, in the line of the Libratus and Pluribus work. A direct application of the CFR material I am working through, and one of the cleaner testbeds for imperfect-information games.
Autonomous garbage collection
An autonomous driving stack under a robotic arm, collecting garbage without a crew. Smaller machines would take what the truck cannot reach: alleyways, loose litter, the places a route misses.
Autonomous park cleanup
Robots that clear litter from national and state parks without supervision. The same platform — navigation, perception, autonomy over unstructured ground — carries over to surveying and aid distribution, which is where it gets interesting beyond cleaning.
Volunteer distributed training network
A voluntary network of machines donating compute to train deep learning models, gathering game data as it goes. Stragglers, verification and bandwidth are the real problem here, not the model.
Multi-agent learning for finance
Several learning agents interacting inside a market, rather than one model predicting a series. It depends on the order book work: without a believable simulator there is nothing for the agents to learn against.
Pre-flop-only poker simulator
Eight players, pre-flop betting, then a random runout to settle the pot. Stripping out every post-flop decision isolates pre-flop strategy, which makes it a clean testbed for regret minimisation before taking on the full game.
Work through an autonomous robotics textbook
Read an autonomous robotics textbook properly and build the projects in it. It is the prerequisite for both cleanup ideas — neither is a software problem I can reason my way through without the fundamentals.
AI tutor for the MCAT
A tutor that builds a study plan from a student's own practice performance instead of handing everyone the same schedule. The hard part is not the model — it is showing the plan actually moves scores.
Betting lobbies for mini-games
Lobbies where players join and bet on short mini-games, starting with toy games and growing toward larger ones as the format proves itself. The engineering is tractable; the regulation is the actual project.
Fundamental quantitative finance projects
PCA, linear regression, the one-fund theorem, covariance analysis — implemented rather than read about. These are the pieces every later finance project quietly assumes you already have.
RNNs for financial forecasting
Recurrent models over financial time series for forecasting and analysis. The honest version of this spends most of its effort on why the naive baseline is so hard to beat.
ARC Raiders resource-farming bot
An agent that farms resources in ARC Raiders with nobody at the keyboard. The perception and control problem is the appealing part; the terms of service are why it sits here.