I think LLMs will be like the steam powered toys of Ancient Rome: a curiosity that implies greater utility, but ultimately requires too many other discoveries to be made first in order to be put into practice.
How else can I get such a fast turnaround on new James Bond novels that include my pet green conure parrot Teansy as a pivotal character?
That is a serious question.
Also, I have really enjoyed playing with math concepts with GPT. It doesn't always get things right, but it's very much like riffing with another mathematician. It can pick up on new concepts, find pro and or con examples for them, etc. Pull in related concepts I hadn't thought of, or had never heard of.
Absolutely wonderful for initial or casual exploration of new ideas.
There is something fun about pushing GPT to grasp something complex it didn't understand immediately, too. Like mentoring an interesting student.
Despite the bittersweet of knowing its hard won understanding will evaporate in short order.
It never had an “understanding”, you just pushed an LLM conversation into a state where it would give higher quality answers.
Like I said, most of these applications of GPT currently just seem like a toy. Until GPT can be put to work to tackle problems that only an AI could do, we won’t really see anything from GPT that couldn’t have been done before by simply talking to a human.
You realize humans on call, ready to completely focus on what I want, are expensive right?
Having a "human-like" entity I can chat with about interesting little problems in math, economics, governance and ethics is really helpful.
I use the word "understanding", because it's so clear when it does, and when it doesn't.
I am not implying it is conscious or aware. Simply that it has represented something in a robust enough way to be able to chat about it from different perspectives consistently.
Another helpful thing is getting pushback from the model when it thinks I am wrong. I have to explain myself better, or occasionally discover I am the one making a mistake. Beautiful!
The limit is the limit of the chat length. There is a sense of accomplishment to explain a problem to another entity, until it understands, and then together establish some interesting results. The day I get to have an entity whose memory accumulates all the details of all the problems I am (we are?) working on will be a GREAT day.
I’be given up using them for now because I mostly I don’t know how to trust what it’s giving me, I’m not good with that.
But I have to be honest when I do receive good results I find in promoting it to give me a good result much more than I realise. Same with other programmers I’ve seen using it as well.
This trust problem has been solved for humans in the past because humans have some responsibility over the outcomes of their work, and there are incentives to ensure you do the right things and not make errors. Your reputation and job depend on it.
An AI has no such sufficient motivation, nor does it care. It’s gonna die anyway by the end of the prompts.
How else can I get such a fast turnaround on new James Bond novels that include my pet green conure parrot Teansy as a pivotal character?
That is a serious question.
Also, I have really enjoyed playing with math concepts with GPT. It doesn't always get things right, but it's very much like riffing with another mathematician. It can pick up on new concepts, find pro and or con examples for them, etc. Pull in related concepts I hadn't thought of, or had never heard of.
Absolutely wonderful for initial or casual exploration of new ideas.
There is something fun about pushing GPT to grasp something complex it didn't understand immediately, too. Like mentoring an interesting student.
Despite the bittersweet of knowing its hard won understanding will evaporate in short order.