Can you give me the scoop on Python, the language? I see things like this project, and it seems very impressive, but being an outsider to the language, I don't "get" it. More specifically: I'm curious to hear thoughts on a) what made this difficult prior to now (with Python), b) why Python is useful for this, and c) what are your thoughts on Python itself?
To add some more context:
I know a lot of developers who work with Python (Flask); Some love it, some hate it (as with any language). My experience has been mainly via homelab/OSS tools that all seem to embrace the language. And yet while the language itself seems very straight forward and easy to use, my experience with the Python _ecosystem_ (again, as an outsider) has been... difficult.
Python 2 vs 3, virtual environments, libraries for each version, etc. It feels as though anytime I've had to use it outside a pre-built Docker container, these issues result in throwing spaghetti at the wall trying to figure out how to even get it working at all. As a PHP/Go dev, it's one of the languages for which I could see myself having a real interest, but this has so far made me hesitant (and I don't want to be).
a) simple b) limited
The language really took off when developers took this simple limited language and pushed it to its very limits using C extensions. The data science explosion opened up the language to a very wide user base.
So to answer your 3 questions: a) Python is not a fast language by any means. There is a lot of overhead in every function call that makes it almost impossible for low latency/real-time use cases. b) I don't think Python is particularly the best language for this. This is just a demonstration of someone building their own custom toolchain to show what is possible with just pure Python. The author has highlighted why they think this is interesting on the website. c) I keep thinking Python will go away soon, and we will see a much better alternative. But the reality is Python is entrenched deeply just like JavaScript. Lot of smart people are putting in a lot of effort to make it better. Personally the ecosystem and packaging story does not annoy me much, but the lack of proper threading (GIL) has hurt my projects more than once.
For your particular pain point, the current community recommended solution is to use uv (https://github.com/astral-sh/uv). There were several detours (pip, pyenv, pipenv, poetry etc.) the community took before they got behind this.
But I have to say, his views on LLMs seem a little premature. He definitely has a unique viewpoint of what "general intelligence" is, which might not apply broadly to most jobs. I think "interviews" them like they were a guest on his podcast and bases his judgement on how they compare to his other extremely smart guests.
Does anyone have a source? If true then this defense of Tesla that we see now is even more bizarre.
https://nitter.net/WholeMarsBlog/status/1889098514061492517#...
The whole thing is funny cause the guy who is so vehemently defending Tesla and FSD despite totaling his car, is being targeted by Tesla fanboy accounts for being a fraud. Twitter is really bottom of the barrel garbage.
Very glad to hear no pedestrians got hit. Really hope the driver takes some kind of lesson away from this experience.
If I didn't know better, I think they are trying to farm engagement.
It's been around for a while now, are there any 3rd party reliable studies showing how good polymarket markets are at predicting events?
There was one investor from France I believe who bet heavily on Trump winning almost $28M. After election it was revealed he had some private polling done, which informed his decision.
It doesn't answer the question you posed, but I believe these markets could highlight some inefficiencies that conventional mainstream information cannot capture.