I am getting into trading on my own (my main job was in machine learning and I studied math in university). I've also come to a similar conclusion that you pretty much have to model these "manipulations" on top of the statistics/Brownian-motion-driven behavior of any security. I am currently working on a hybrid model for something on Polymarket but it's not yet sophisticated. Do you have any resources that you can point me to that expand on this very idea of adding human behavior to financial modeling?
Without giving away my exact strategies, I'm also an ML engineer and I'll just say that ML is in 90% of cases the wrong tool, whereas simple regressions and scatter plots will unearth loads of statistical anomalies if you know where to look. You want to find anomalous behavior then hone in on how to make them your counterparty.
ML can help you optimize things after that, but locating diamonds in a soup of noise is not really where ML shines.
Perhaps this is by design. Cruise had a failsafe system that detected a collision and decided to pull over but by pulling over it dragged a person underneath the car (or something close to this scenario). Maybe this dumb failsafe was designed not to repeat Cruise's mistakes?
Certainly a better way to handle this would have been to pull over. I think stopping where ever it happened to be is only acceptable if the majority of sensors fail for some reason
I was there. I encountered multiple stopped Waymos in the street. It was annoying, but not dangerous. They had their lights on. Any driver following the rules of the road would get around them fine. It was definitely imperfect, but safe. Much safer than the humans blowing through those very same intersections.
When I was a young man, I worked at a restaurant, and the lights went off.
I being the hero I was, wanted to keep the show running, bought some candles, ovens worked fine, water worked fine (for now). I wanted to charge cash. But eventually big boss came and shut us down since light wasn't coming.
And he was right, cooking and working under those conditions is dangerous for the staff, but also for the clients, without light you cannot see the food, cannot inspect its state, whether stale, with visible fungi, etc...
Yes, the perfect worker would still operate under those conditions, but we are not perfect, and admitting that we only can provide 2 or 3 nines, and recognizing where we are in that 0.01% moment, is what keeps us from actually failing so catastrophically that we undo all of the progress and benefits that the last bit of availability would have allowed us.
> but also for the clients, without light you cannot see the food, cannot inspect its state, whether stale, with visible fungi, etc...
...I have to say, I'm pretty skeptical of this one. I've eaten in lots of dark restaurants, sometimes lit pretty much just by candles on the table. Seems to work fine.
But if you're just interested in doing some machine learning on it, then it's all about how much RAM and not really how fast. I used to use my gaming laptop to do a lot of local ML
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