looks like its just setting some events, these two lines should clear the anti-select and the anti-right click respectively if pasted into the debug console:

document.body.onselectstart = undefined
document.oncontextmenu = undefined

Thats how its supposed to work and in practice it kinda does, but the people with the money want positive results and the people doing the work have to do what they can to stay alive and relevant enough to actually do the work. Which means that while most scientists are willing to change their minds about something once they have sufficient evidence, gathering that evidence can be difficult when no one is willing to pay for it. Hard to change minds when you can’t get the evidence to show some preconceived notion was wrong.

Yeah, seems weird that simple “it downloads torrents” client gets a D. It gets the job done, is easy to figure out, and doesnt fuck about with features I would never touch. Maybe thats not enough for a power user but for me its exactly what I want.

(but then why is Tixati in B, seems to have mostly downsides?)

Outside of the costs of hardware, its just power. Running these sorts of computations is getting more efficient, but the sheer amount of computation means that its gonna take a lot of electricity to run.

they know it’s impossible to do

There is some research into ML data deletion and its shown to be possible, but maybe not on larger scales and maybe not something that is actually feasible compared to retraining.

While you are overall correct, there is still a sort of “black box” effect going on. While we understand the mechanics of how the network architecture works the actual information encoded by training is, as you have said, not stored in a way that is easily accessible or editable by a human.

I am not sure if this is what OP meant by it, but it kinda fits and I wanted to add a bit of clarification. Relatedly, the easiest way to uncook (or unscramble) an egg is to feed it to a chicken, which amounts to basically retraining a model.

Always has been. The laws are there to incentivize good behavior, but when the cost of complying is larger than the projected cost of not complying they will ignore it and deal with the consequences. For us regular folk we generally can’t afford to not comply (except for all the low stakes laws that you break on a day to day basis), but when you have money to burn and a lot is at stake, the decision becomes more complicated.

The tech part of that is that we don’t really even know if removing data from these sorts of model is possible in the first place. The only way to remove it is to throw away the old one and make a new one (aka retraining the model) without the offending data. This is similar to how you can’t get a person to forget something without some really drastic measures, even then how do you know they forgot it, that information may still be used to inform their decisions, they might just not be aware of it or feign ignorance. Only real way to be sure is to scrap the person. Given how insanely costly it can be to retrain a model, the laws start looking like “necessary operating costs” instead of absolute rules.

Best weight loss method, laziness.

My vote for Biden was an anything but trump vote, but given Biden’s current record as president he has my vote again.

Still not my first choice but we live in a first past the post voting system so gotta take what you can get.

The real AI, now renamed AGI, is still very far

The idea and name of AGI is not new, and AI has not been used to refer to AGI since perhaps the very earliest days of AI research when no one knew how hard it actually was. I would argue that we are back in those time though since despite learning so much over the years we have no idea how hard AGI is going to be. As of right now, the correct answer to how far away is AGI can only be I don’t know.

Five years ago the idea that the turing test would be so effortlessly shattered was considered a complete impossibility. AI researchers knew that it was a bad test for AGI, but to actually create an AI agent that can pass it without tricks still was surely at least 10-20 years out. Now, my home computer can run a model that can talk like a human.

Being able to talk like a human used to be what the layperson would consider AI, now it’s not even AI, it’s just crunching numbers. And this has been happening throughout the entire history of the field. You aren’t going to change this person’s mind, this bullshit of discounting the advancements in AI has been here from the start, it’s so ubiquitous that it has a name.

https://en.wikipedia.org/wiki/AI_effect