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Also, the game theory that gives us insight into voting systems, telling us the current system leads to a 2 party system, did not exist when the US constitution was written.

They were removed from MAINTAINERS, which is what identifies the people responsible for maintaining a piece of code, a subsystem of Linux, not the credits, which is encoded in the git commit history.

A very similar situation to that analysed in this paper that was recently published. The quality of what is generated degrades significantly.

Although they mostly investigate replacing the data with ai generated data in each step, so I doubt the effect will be as pronounced in practice. Human writing will still be included and even curation of ai generated text by people can skew the distribution of the training data (as the process by these editors would inevitably do, as reasonable text could get through the cracks.)

Trump supports Russia and Israel, the dems support Israel. If you pick Trump, both groups pay the price. Depending on who you pick one group will pay the price or not, one group will pay the price no matter what; yet for this group (the Palestinians) the degree to which will probably differ, I suspect Trump may be worse given that he avoids supporting a ceasefire at all and tells the Israeli government to finish what they started. People from Palestine state the same: Trump would be worse, but neither choice would support them.

Neat idea. This could be refined by adding a git hook that runs (rip)grep on the entire codebase and fails if anything is found upon commit may accomplish a similar result and stop the code from being committed entirely. Requires a bit more setup work on de developers end, though.

These models have so many parameters that, while insufficient to memorize all text it has ever seen, it can end up memorizing some of the content. It is the difference between being able to recall a random passage versus recalling the exact thing you need. Both allow you to spill content verbatim, but one is problematic while the other can be helpful.

There are techniques to allow it it 'read on demand', but they are not part of the core model (i.e. the autocmpletion model / LLM) and are tacked on top of it. For example, you can tie it search engine, which Microsoft's copilot does, and is something which I don't think is enabled for ChatGPT by default. Or allow it to query a external data bank (Retrieval Augmented Generation).

Do keep in mind that in Europe there are often required checks whether a car is 'roadworthy', in Norway this seems to be a biannual check: so you cannot really skip maintenance to the extent that that would be a huge factor.

I am not sure whether AI will make the creation of asset flips much easier though, given that store bought assets are already being dropped into a 'game' already.

You may be able to get more granularity by decoupling Google TV volume from the TV's own volume. To do this, you need to disable HDMI CEC control over volume in the remote's settings.

An hypothesis has to be falsifiable though.

KeepassXC is multiplatform. (Also: KeepassDX is quite nice as an an Android app for Keepass databases.)

For those taking this route: do note that the map data is downloaded from their servers. So don't forget to make a small donation to offset the server costs if you are able to!