Comment by jstummbillig

Exactly this. The perfect example is Google Assistant for me. It's such a terrible service because it's so indeterministic. One day it happily answers your basic question with a smile, and when you need it most it doesn't even try and only comes up with "Sorry I don't understand".

When products have limitations, those are usually acceptable to me if I know what they are or if I can find out what the breaking point is.

If the breaking point was me speaking a bit unclearly, I'd speak more clearly. If the breaking point was complex questions, I'd ask simpler ones. If the breaking point is truly random, I simply stop using the service because it's unpredictable and frustrating.

> When they have sex, people expect to ejaculate and feel good, not have their intercourse morph into a drag race with a clown half-way though.

speak for yourself

Ways to start my morning...reading "When they have sex, people expect to ejaculate and feel good, not have their intercourse morph into a drag race with a clown half-way though."

Stellar description.

This thing of 'look, nobody cares about the details really, they just care about the solution' is a meme that I think will be here forever in software. It was here before LLMs, they're now just the current socially accepted legitimacy vehicle for the meme.

In the end, useful stuff is built by people caring about the details. This will always be true. I think in LLMs and broadly AI people see an escape valve from that where the thinking about the details can be taken off their hands, and that's appealing, but it won't work in exactly the same way that having a human take the details off your hands doesn't usually work that well unless you yourself understand the details to a large extent (not necessarily down to the atoms, but at the point of abstraction where it matters, which in software is mostly about deterministically how do the logic flows of the thing actually work and why).

I think a lot of people just don't intuit this. An illustrative analogy might be something else creative, like music. Imagine the conversation where you're writing a song and discussing some fine point of detail like the lyrics, should I have this or that line in there, and ask someone's opinion, and their answer is 'well listen, I don't really know about lyrics and all of that, but I know all that really matters in the end is the vibe of the song'. That contributes about the same level of usefulness as talking about how software users are ultimately looking for 'solutions' without talking about the details of said software.

Most of us actually drive a car to get somewhere. The car, and the driving, are just a modality. Which is the point.

Sadly, this is not true of a (admittedly very small) number of individuals.

I feel like this is the point where we start to make jokes about Honda owners.

Christine didn’t end well for anyone.

...so that you can get to the supermarket for food, to meet someone you love, meet someone you may or may not love, or to solve the problem of how to get to work; etc.

Your ancestors didn't want horses and carts, bicycles, shoes - they wanted the solutions of the day to the same scenarios above.

But do you want to drive, or do you want to be wherever you need to be to fuck?

Even if it purred real nice when it started up? (I’m sorry)

Weird kink

Food -> 'basic needs'... so yeah, Shelter, food, etc. That's why most of us drive. You are also correct to separate Philia and Eros ( https://en.wikipedia.org/wiki/Greek_words_for_love ).

A job is better if your coworkers are of a caliber that they become a secondary family.

No, but the average user is capable of describing what they want to something trained in interpreting what users want. The average person is incapable of articulating the exact steps necessary to change a car's oil, but they have no issue with saying "change my car's oil" to a mechanic. The implicit assumption with LLM-based backends is that the LLM would be capable of correctly interpreting vague user requests. Otherwise it wouldn't be very useful.

There would be bookmarks to prompts and the results of the moment would be cached : both of these are already happening and will get better. We probably will freeze and unfreeze parts of neural nets to just get to that point and even mix them up to quickly mix up different concept you described before and continue from there.

I think they're suggesting that some problems are trivially solvable by humans but extremely hard to do with code - in fact the outcome can seem non-deterministic despite it being deterministic because there are so many confounding variables at play. This is where an LLM or other for of AI could be a valid solution.

Why sell to a company when you can replace it?

I can speculate about what LLM-first software and businesses might look like and I find some of those speculations more attractive than what's currently on offer from existing companies.

The first one, which is already happening to some degree on large platforms like X, is LLM powered social media. Instead of having a human designed algorithm handle suggestions you hand it over to an LLM to decide but it could go further. It could handle customizing the look of the client app for each user, it could provide goal based suggestions or search so you could tell it what type of posts or accounts you're looking for or a reason you're looking for them e.g. "I want to learn ML and find a job in that field" and it gives you a list of users that are in that field, post frequent and high quality educational material, have demonstrated willingness to mentor and are currently not too busy to do so as well as a list of posts that serve as a good starting point, etc.

The difference in functionality would be similar to the change from static websites to dynamic web apps. It adds even more interactivity to the page and broadens the scope of uses you can find for it.

You might end up with ai trying to get information from ai, which saves us the frustration..

knows where we’d end up?

On the other hand the logs might be a great read.