Unfortunatelly, that’s not how most people think, otherwise there wouldn’t be these ads

Ads via HDMI shouldn’t work if the TV doesn’t have internet connection, by my understanding. So I do not see any problems there.

So, it should be used reasonably, as it should have always been.

It’s quite misleading to say 14 when it’s only March. That said, the drop to 120 last year is still alarming.

I don’t think AI is to blame. They just don’t need those people. I heard big tech hired a lot of people to steal them from smaller businesses, so they could not compete with them. If those employees had been useful to them, they wouldn’t fire them.

What do you even mean? Calculators and LLMs are solving different problems. And there are a lot of calculators and a lot of LLMs. Also, calculator accuracy could be approaching 0% because they all have limited precision and there are infinite numbers. Some of the calculators even can’t correctly answer 0.1+0.2, while most LLMs can do that.

Because guessing correct answer is more successful than saying nothing.

Because it’s so accurate or because it isn’t?

I was surprised that S&P500 gained over last year ~16%, but dollar lost compared to euro ~15℅, so there was no real gain.

Not only 20 years ago.

Source: Takeda, S., Keeley, A.R. & Managi, S. How Many Years Away is Fusion Energy? A Review. J Fusion Energ 42, 16 (2023). https://doi.org/10.1007/s10894-023-00361-z

I wouldn’t blame AI, I would say that overall the US is becoming more and more anti-science overall. Just look how people are against vaccines or flat-earthers. Even academics are leaving US because of funding cuts by the current administration. Schools are in bad shapes…

Fusion is possible. It just needs 20 years of research first.

While I agree with you, most people don’t understand what cloud is and since Microsoft is pushing users to use OneDrive, general user would just turn it on just to get rid of the window.

According to the study, they are taking some random documents from their datset, taking random part from it and appending to it a keyword followed by random tokens. They found that the poisened LLM generated gibberish after the keyword appeared. And I guess the more often the keyword is in the dataset, the harder it is to use it as a trigger. But they are saying that for example a web link could be used as a keyword.