3,593 karma · joined July 30, 2007
I'm applying multi-agent reinforcement learning to AI Safety. I want to ensure that Artificial Intelligence will benefit human society rather than hurt it. I'm addressing both short-term consequences of existing AI tools such as LLMs and long-term existential risk imposed by the potential development of Artificial General Intelligence.
I propose to solve the problem of AI Safety by improving the social behavior of AI agents. Most AI research is focused on getting AI agents to solve bigger and more complex problems in the most efficient way possible; my research is focused on achieving cooperation, reciprocity and teamwork between AI agents.
My strategy is to distill lessons from the study of animal and human societies and apply them to AI agents.
Read more about my research here: https://r.rachum.com
I hope that this upgrade will fix some of these problems. I'll probably take a few years before I upgrade my AHK scripts.
This is far from the truth. The main usage of most open-source projects isn't as code, but as a product. The median user of an open-source project wants to think about the project as little as possible. They want to be as unaware as possible of the code that makes up the project. They're happy to add the project to their `requirements.txt`, add a few lines to import and use it and then never think about it again.
(Sorry, I'm a bit grumpy.)
The problem with this plan is corporate politics. Say that OP takes on this challenge. He makes a plan and carefully and patiently executes it. Say that in six months he's already fixed 30% of the problem, and by doing do he meaningfully improved the team's productivity.
The executives are happy. The distaster was averted, and now they can ask for more features and get them more quickly, which they do.
Congratulations, OP. You are now the team lead of a mediocre software project. You want to continue fixing the code beyond the 30%? Management will be happy for you to take it as a personal project. After all, you probably don't have anything to do on the weekend anyway.
You could stand strong and refuse to improve the infrastructure until the company explicitly prioritizes it. But then why would that job be better than just taking a random position in a FAANG company? The code quality will be better and so will the pay.
It's pretty interesting to read the personal story of a researcher who made it to one of the top AI labs in the world.
However, Python's dataclasses have great features and I wouldn't want to give them up. What would be ideal is a solution for caching the generated code of dataclasses.
If you want to go that route, there's no reason for there to be more than one language on Earth.
Any attempt to research linguistics should respect the fact that people want to be different from each other, and see that as a valid reason.
"PySnooper is a poor man's debugger. If you've used Bash, it's like set -x for Python, except it's fancier."
https://news.ycombinator.com/item?id=19717786 PySnooper: Never use print for debugging again