spectrums_coherence

Gemini AI baked into every layer of the operating system.

LOL

most likely copied from PDF, thus the line break is copied properly.

I use searched image, trace them, credit them in my slides and writing. It really doesn’t take that much time and effort…

Is the same effect achievable by a local program in user space/container confinement?

I certainly cannot inspect every program I have to run. In fact, most of the modern program have a deep supply chain, and I cannot make sure that there is no point on the supply chain that want to get root :(

I believe they are higher dimensional string diagrams. Maybe called n-diagrams? They are used in higher homotopy and higher category theory, I believe. But not entirely sure.

https://arxiv.org/pdf/2305.06938

EDIT: Found it! they are called surface diagram, which are generalization of string diagram to 3-categories https://golem.ph.utexas.edu/category/2010/03/modeling_surface_diagrams.html https://ncatlab.org/nlab/show/surface+diagram

Still not sure what the proof is talking about though :(

But from the conclusion it looks like some sort of natruality condition, where the morphisms are slided around except beta.

EDIT AGAIN: got in touch with my string diagram contact. Here is the paper https://arxiv.org/pdf/0807.0658

Note the conclusion at the bottom, the proof on the right and the axiom on the left doesn’t seem to be related.

The proof on the right is Theorem 6; the equality at bottom is in section 3.4, where the proof is omitted because “follows from definition”; the axiom on the left is HM1 and HM2 on page 19.

LLM is very good at programming when there are huge number of guardrails against them. For example, exploit testing is a great usecase because getting a shell is getting a shell.

They kind of acts as a smarter version of infinite monkey that can try and iterate much more efficiently than human does.

On the other hand, in tasks that requires creativity, architecture, and projects without guard rail, they tend to do a terrible job, and often yielding solution that is more convoluted than it needs to be or just plain old incorrect.

I find it is yet another replacement for “pure labor”, where the most unintelligent part of programming, i.e. writing the code, is automated away. While I will still write code from scratch when I am trying to learn, I likely will be able automate some code writing, if I know exactly how to implement it in my head, and I also have access to plenty of testing to gaurentee correctness.

A lot of these request and code are at least partially reviewed or generated by AI. I think this article is talking about AI generating ads when writing the request, the review, and/or the code.

I doubt any of these ads are trickling down to product as long as the maintainer is mildly careful.

I see you don’t run electron app in flatpaks :)

I think it is accessed through xdg-protal, and the usage tracking and permission etc. likely happen at that layer.

The xdg-desktop-portal project is adding an age verification portal (flatpak/xdg-desktop-portal#1922) that needs a data source for the user’s age. userdb already stores personal metadata (emailAddress, realName, location) so birthDate is a natural fit.