HedyL

Or like the radium craze of the early 20th century (even if radium may have a lot more legitimate use cases than current-day LLM).

New reality at work: Pretending to use AI while having to clean up after all the people who actually do.

If I'm not mistaken, even in pre-LLM days, Google had some kind of automated summaries which were sometimes wrong. Those bothered me less. The AI hallucinations appear to be on a whole new level of wrong (or is this just my personal belief - are there any statistics about this?).

Most searchers don’t click on anything else if there’s an AI overview — only 8% click on any other search result. It’s 15% if there isn’t an AI summary.

I can't get over that. An oligopolistic company imposes a source on its users that is very likely either hallucinating or plagiarizing or both, and most people seem to eat it up (out of convenience or naiveté, I assume).

Maybe us humans possess a somewhat hardwired tendency to "bond" with a counterpart that acts like this. In the past, this was not a huge problem because only other humans were capable of interacting in this way, but this is now changing. However, I suppose this needs to be researched more systematically (beyond what is already known about the ELIZA effect etc.).

Somehow, the "smug" tone really rubs me the wrong way. It is of great comedic value here, but it always reminds me of that one person who is consistently wrong yet is somehow the boss's or the teacher's favorite.

Officially, you can’t. Unofficially, just have one of the ferrymen tow a boat.

Or swim back. However, the bot itself appears to have ruled out all of these options.

At first glance it seems impossible once N≥2, because as soon as you bring a boat across to the right bank, one of you must pilot a boat back—leaving a boat behind on the wrong side.

In this sentence, the bot appears to sort of "get" it (not entirely, though, the wording is weird). However, from there, it definitely goes downhill...

Turns out that being a proficient liar might be the key to success in this attention economy (see also: chatbots).

Of course, there are also the usual comments saying artists shouldn't complain about getting replaced by AI etc. Reminds me why I am not on Twitter anymore.

It also strikes me that in this case, the artist didn't even expect to get paid. Apparently, the AI bros even crave the unpaid "exposure" real artists get, without wanting to put in any of the work and while (in most cases) generating results that are no better than spam.

It is a sickening display of narcissism IMHO.

With LLMs not only do we see massive increases in overhead costs due to the training process necessary to build a usable model, each request that gets sent has a higher cost. This changes the scaling logic in ways that don’t appear to be getting priced in or planned for in discussions of the glorious AI technocapital future

This is a very important point, I believe. I find it particularly ironic that the "traditional" Internet was fairly efficient in particular because many people were shown more or less the same content, and this fact also made it easier to carry out a certain degree of quality assurance. Now with chatbots, all this is being thrown overboard and extreme inefficiencies are being created, and apparently, the AI hypemongers are largely ignoring that.

It's quite noteworthy how often these shots start out somewhat okay at the first prompt, but then deteriorate markedly over the following seconds.

As a layperson, I would try to explain this as follows: At the beginning, the AI is - to some extent - free to "pick" how the characters and their surroundings would look like (while staying within the constraints of the prompt, of course, even if this doesn't always work out either).

Therefore, the AI can basically "fill in the blanks" from its training data and create something that may look somewhat impressive at first glance.

However, for continuing the shot, the AI is now stuck with these characters and surroundings while having to follow a plot that may not be represented in its training data, especially not for the characters and surroundings it had picked. This is why we frequently see inconsistencies, deviations from the prompt or just plain nonsense.

If I am right about this assumption, it might be very difficult to improve these video generators, I guess (because an unrealistic amount of additional training data would be required).

Edit: According to other people, it may also be related to memory/hardware etc. In that case, my guesses above may not apply. Or maybe it is a mixture of both.