Probabilistic Artificial Intelligence
15 comments
·March 10, 2025abhgh
I came across this a few days ago, and my excuse to give it a a serious look is that Andreas Krause has some deep and interesting research in Gaussian Processes and Bandits [1].
[1] https://scholar.google.com/scholar?start=10&q=andreas+krause...
trostaft
It's Krause, he's one of the biggest researchers in the field. At least based on the other work of his I've read, he's a good writer too. This ought to be a worth while read.
thisisauserid
Gemini 2.0 Experimental 02-05 sees this as "only" 107K tokens.
Handy if you want help breaking this down.
'Laplace Approximation is a "quick and dirty" way to turn a complex probability distribution into a simple Gaussian (bell curve).
It works by finding the highest point (mode) and matching the curvature at that point.
It's fast and easy, but it can be very inaccurate and overconfident if the true distribution doesn't look like a bell curve.'
dcreater
As a layman in this field, I have no idea the contact it significance of this work. Can someone better informed inform us?
cubefox
Apparently they don't discuss language models at all.
jacob019
This is great. Is it available as a printed book?
falcor84
From a brief search I see that it isn't (or it least not yet), but seeing how well-formatted the pdf is, and the fact that it's CC-licensed, you could print it yourself, or perhaps talk with them to organize a batch.
Though I personally prefer to read these sorts of books directly from pdf, and am grateful to them for sharing it on arxiv.
mnky9800n
I wonder if one could organize an arXiv print service that binds and prints and ships with a unique cover and such.
Also it should use LLMs and the blockchain.
But this would be nice there are a number of papers and such that if you could submit an arXiv link to a print service I would probably buy a copy. I wonder why no one does it.
woolion
Aren't you describing Lulu but for the very niche case of arxiv publications that are small books but not published as books? I think you could do it in a weekend with their API.
brador
Interesting separation and distinction between noisy inputs, noisy processing and noisy chains.
I think we’ll need a GUI for the models to democratize interpretability and let even gamers explore them. Basically to train another model, that will take the LLM and convert it into 3D shapes and put them in some 3D world that is understandable for humans.
Simpler example: represent an LLM as a green field with objects, where humans are the only agents:
You stand near a monkey, see chewing mouth nearby, go there (your prompt now is “monkey chews”), close by you see an arrow pointing at a banana, father away an arrow points at an apple, very far away at the horizon an arrow points at a tire (monkeys rarely chew tires).
So things close by are more likely tokens, things far away are less likely, you see all of them at once (maybe you’re on top of a hill to see farther). This way we can make a form of static place AI, where humans are the only agents