I'm going to take the time to illustrate here, how I can see LLMs affecting human speech through existing applications and technologies that are (or could) be made both available and popular enough to achieve this. We're far enough down the comment chain I can reply to myself now right?

So, we can all agree that people are increasingly using LLMs in the form of chatgpt and the like, to acquire knowledge/information. The same way as they would use a search engine to follow a link to that knowledge.

Speech-to-text has been a thing for at least 3 decades (yeah it was pretty hopeless once, but not so much now). So let's not argue about speech vs text. People already talk to Google and siri and whoever else to this end, llms. Pale have their responses read out via tts.

I remember being blown away watching a blind sysadmin interacting with a Linux shell via tts at rates I couldn't even understand the words in 1998. How far we've come. I digress, so.

We've all experienced trouble getting the information we're looking for even with all these tools. Because there's so much information, and it can be very difficult to find the needle in the haystack. So we constantly have to refine our queries either to be more specific, or exclude relationships to other information.

This in turn, causes us to think about the words we were using to get the results we want, more frequently because otherwise we spend too much time on recursion.

In turn, the more we do this, and are trained to do this, the more it will bleed into human communication.

Now look, there is absolutely a lot of hopium smoking going on here, but damn, this could have everlasting impact on verbal communication. If technology can train people - through inaccurate/incorrect results to think about the communication going out when they speak, we could drastically reduce the amount of miscommunication between people by that alone.

Imagine:

get me a chair

wheels out an office chair from the study

no I meant a chair for at the kitchen table

Vs

get me a chair for at the kitchen table

You can apply the same thing to human prompted image generation and video generation.

Now.. We don't need llms to do this, or know this. But we are never going to achieve this without a third party - the "llm", and whatever it's plugged into - because the human recipient will usually be more capable of translating these variances, or employ other contexts not as accessible via a single output as speech or text.

But if machines train us to communicate out better (more accurately, precisely and/or concisely), that is an effect I can't welcome enough.

Realistically, the machines will learn to deal with us being dumb, before we adapt.

e: formatting.