Maybe my analogy is a little bit too silly and too obvious, but I think wanting a humanoid robot (rather than one designed in a way that is best suited for the purpose) could be somewhat akin to wanting a mechanical horse rather than a car. On the one hand, this may sound like a reasonable idea if saddles, carriages, stables and blacksmiths are already available. On the other hand, the mechanical horse is going to be a lot slower than a car and a lot more uncomfortable to ride. Also, it is still going to need charging stations or gas stations (since it won’t eat oats) and dedicated repair shops (since veterinarians won’t be able to fix it). Also, its technology might be a lot more complex and difficult to fix than that of a car (especially the early models).

I guess both chatbots and humanoid robots are basically about the fantasy of automating human labor away effortlessly. In the past, most successful automation probably required a strong understanding of not just the tech, but also the tasks themselves and often a complete overhaul of processes, internal structures etc. In the end, there was usually still a need for human labor, just with different skill sets than before. Many people from the C-suite aren’t very good at handling these challenges, even if they would want to make everyone believe otherwise. This is probably why the promise of reaping all the rewards of automation without having to do the work sounds compelling to many of them.

the reason is they’re selling sci fi dreams of robot servants even though these dreams are lies.

We’ve seen the same with chatbots, I guess. Objectively speaking, they perform worse at most tasks than regular search engines, databases, dedicated machine learning-based tools etc. However, they sound humanoid (like overly sycophantic human office workers, to be more precise), thus the hype.

What purpose is this tool even supposed to serve? The most obvious use case that comes to mind is employee monitoring.

It’s also very difficult to get search results in English when this isn’t set as your first language in Google, even if your entire search term is in English. Even “Advanced Search” doesn’t seem to work reliably here, and of course, it always brings up the AI overview first, even if you clicked advanced search from the “Web” tab.

I guess the question here really boils down to: Can (less-than-perfect) capitalism solve this problem somehow (by allowing better solutions to prevail), or is it bound to fail due to the now-insurmountable market power of existing players?

Somehow makes me think of the times before modern food safety regulations, when adulterations with substances such as formaldehyde or arsenic were common, apparently: https://pmc.ncbi.nlm.nih.gov/articles/PMC7323515/ We may be in a similar age regarding information now. Of course, this has always been a problem with the internet, but I would argue that AI (and the way oligopolistic companies are shoving it into everything) is making it infinitely worse.

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.

I have been thinking about the true cost of running LLMs (of course, Ed Zitron and others have written about this a lot).

We take it for granted that large parts of the internet are available for free. Sure, a lot of it is plastered with ads, and paywalls are becoming increasingly common, but thanks to economies of scale (and a level of intrinsic motivation/altruism/idealism/vanity), it still used to be viable to provide information online without charging users for every bit of it. Same appears to be true for the tools to discover said information (search engines).

Compare this to the estimated true cost of running AI chatbots, which (according to the numbers I’m familiar with) may be tens or even hundreds of dollars a month for each user. For this price, users would get unreliable slop, and this slop could only be produced from the (mostly free) information that is already available online while disincentivizing creators from producing more of it (because search engine driven traffic is dying down).

I think the math is really abysmal here, and it may take some time to realize how bad it really is. We are used to big numbers from tech companies, but we rarely break them down to individual users.

Somehow reminds me of the astronomical cost of each bitcoin transaction (especially compared to the tiny cost of processing a single payment through established payment systems).