ronald_raygun

5 ms·

1.
Generative Unix CTF for RL(vmax.ai)
1 points by ronald_raygun 4mo ago|0 comments
2.
Should You Select Your Kids with an Algorithm? [video](youtube.com)
1 points by ronald_raygun 1y ago|0 comments
3.
by ronald_raygun 1y ago
Throw some nukes and a war over Taiwan into the mix?
4.
by ronald_raygun 1y ago
Location: Arizona Remote: Yes Willing to relocate: Yes Technologies: Python, sklearn, a/b testing, numpy, pandas, matplotlib, ML, SQL Résumé/CV: https://www.linkedin.com/in/geoffrey-bradway/ email: geoff
5.
by ronald_raygun 2y ago
the term carcinogen is very broad, I think you just mean the bad ones can cause harm (sorry, former CA resident here)
6.
by ronald_raygun 2y ago
geese are excellent gaurdian animals https://en.wikipedia.org/wiki/Guard_goose
7.
by ronald_raygun 2y ago
Well, as the deer die off there are more resources left for the remaining deer, and so it is easier for them to have kids and the birth rates might increase. So it could potentially converge to a predator-prey equilibrium
8.
by ronald_raygun 2y ago
Kids these days are still getting all the shit jobs in the cool science labs.
9.
by ronald_raygun 2y ago
"i would be happy to assist you in rtfm"
10.
by ronald_raygun 2y ago
Well it sounds like an instance of "your keys are always in the last place you look, because then you stop looking"
11.
by ronald_raygun 2y ago
TLDR: breadthfirst
12.
References for graphical models and compuatational graphs?
2 points by ronald_raygun 2y ago|1 comments
13.
by ronald_raygun 2y ago
I agree with this 100%
14.
by ronald_raygun 2y ago
College seems to me to be geographically structured to help you make friends. I remember reading one study that shows basically repeated random interactions with the same person will tend to develop towards making friends with them organica
15.
by ronald_raygun 2y ago
whatever this is https://arstechnica.com/gaming/2021/03/how-to-beat-paper-mar...
16.
by ronald_raygun 2y ago
The Devonian certainly wasnt a wood age
17.
by ronald_raygun 2y ago
I can already change my race. I just check a different box on government forms...
18.
by ronald_raygun 2y ago
von Neumann could do calculus when he was 8. Some people are just born that way
19.
by ronald_raygun 3y ago
Because they are essentially bombs
20.
by ronald_raygun 3y ago
What do you think a serf was?
21.
by ronald_raygun 3y ago
Idk lots of civilizations had slaves (I almost wrote ancient, but slavery didn’t go away until less than 200 years ago, and human trafficking is still a big issue). But compare Rome with say the Spartans, who had an insanely big slave class
22.
by ronald_raygun 3y ago
Wasn’t there an OpenAI paper where they showed that MM multiplication with the numerical imprecision of floats was enough to get general function learning? You might not even need anything else…
23.
by ronald_raygun 3y ago
Sure computes have lots of transistors, but brains have 10s of billions of neurons and only use 12W of power.
24.
by ronald_raygun 3y ago
The more general point is people are asymptomatic growth and assume a never ending exponential, when in reality it’s probably something with a carrying capacity
25.
by ronald_raygun 3y ago
Yeah you could imagine that with a fixed amount of resources that implies a maximum “computational intelligence”. Right now we aren’t close to that limit. But if we get better algorithms, there’s going to be fewer gains as we get towards a
26.
by ronald_raygun 3y ago
Sure, but it seems that with a fixed amount of hardware or operations there is some sort of efficient frontier across all the axes (speed, generalization, capacity, whatever), so there should logically be a point with diminishing returns an
27.
by ronald_raygun 3y ago
Yeah but there are arguments that Moore’s law won’t continue because at a certain point you can’t really get transistors closer without quantum effects messing with them
28.
by ronald_raygun 3y ago
I always found the idea of infinitely self improving AI to be suspect. Let’s say we have a super smart AI with intelligence 1, and it uses all that to improve itself by 0.5. Then that new 1.5 uses itself to improve by 0.25. Then 0.125, etc
29.
by ronald_raygun 3y ago
> You could probably design some degenerate probability distribution that ml-estimation behaves really badly for, but those are not common in practice. Anything multimodal...
30.
by ronald_raygun 3y ago
Another thing to note is that you're multiplying probabilities together. Since each probability is between 0 and 1, youre always shrinking the likelihood with each new data point. When you're doing this kind of analysis, the quest

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