I think that an obvious bot can still manipulate users. Fb has infinite resources with which to test this stuff prior to roll out. They skittish do it if it didn’t work for them.

I disagree.

Lemmy is also a link aggregator which works in a similar way to reddit, but it has it’s own history, culture, and quirks.

Sure, things will happen on Lemmy which are reminiscent of reddit because they’re both link aggregators, but to say lemmy “is” reddit is very reductive.

Even pizza shops with their own drivers. I’d usually prefer to go get it myself so it’s as fresh as possible.

Even in places with good infrastructure and generally non-murderous drivers it still gets very sketchy.

The majority of drivers just havent ridden a bike since they were 3, and just don’t understand that you’re part of the traffic, as though you can magically just slip around between all the cars.

Yeah, still not convinced.

I work in a field which is not dissimilar. Teaching customers to email you their requirements so your LLM can have a go at filling out the form just seems ludicrous to me.

Additionally, the models you’re using require stupid amounts of power to produce so that you can run them on low power machines.

Anyhow, neither of us is going to change our minds without actual data which neither of us have. Who knows, a decade from now I might be forwarding client emails to an LLM so it can fill out a form for me, at which time I’ll know I was wrong.

If I’m brutally honest, I don’t find these use cases very compelling.

Separate fields for addresses could be easily solved without an LLM. The only reason there isn’t already a common solution is that it just isn’t that much of a problem.

Data ingestion from email will never be as efficient and accurate as simply having a customer fill out a form directly.

These things might make someone mildly more efficient at their job, but given the resources required for LLMs is it really worth it?

I suspect that this is “grumpy old man” type thinking, but my concern is the loss of fundamental skills.

As an example, like many other people I’ve spent the last few decades developing written communication skills, emailing clients regarding complex topics. Communication requires not only an understanding of the subject, but an understanding of the recipient’s circumstances, and the likelihood of the thoughts and actions that may arise as a result.

Over the last year or so I’ve noticed my assistants using LLMs to draft emails with deleterious results. This use in many cases reduces my thinking feeling experienced and trained assistant to an automaton regurgitating words from publicly available references. The usual response to this concern is that my assistants are using the tool incorrectly, which is certainly the case, but my argument is that the use of the tool precludes the expenditure of the requisite time and effort to really learn.

Perhaps this is a kind of circular argument, like why do kids need to learn handwriting when nothing needs to be handwritten.

It does seem as though we’re on a trajectory towards stupider professional services though, where my bot emails your bot who replies and after n iterations maybe they’ve figured it out.

I think there’s specific industrial problems for which AI is indeed transformative.

Just one example that I’m aware of is the AI-accelerated nazca lines survey that revealed many more geoglyphs that we were not previously aware of.

However, this type of use case just isn’t relevant to most people who’s reliance on LLMs is “write an email to a client saying xyz” or “summarise this email that someone sent to me”.

I just sync a folder with syncthing and use native markdown editors.

On a desktop I like zettlr. On android I like zettel notes. Both have zettelkasten features which is pretty much just a way to link to other files.

I’m trying… I’m trying real hard to be the shepherd ringo.

This is a really valid point, especially because it’s not only faster but dramatically cheaper.

The thing is, summaries which are pretty terrible might be costly. If decision makers are relying on these summaries and they’re inaccurate, then the consequences might be immeasurable.

Suppose you’re considering 2 cars, one is very cheap but on one random day per month it just won’t start, the other is 5x the price but will work every day. If you really need the car to get to work, then the one that randomly doesn’t start might be worse than no car at all.