Think of it less like a static tool, and more like a human helper, where the same holds.
That said, I can't wait for LLMs to stop being AI and start being just another tool. Anything cursed with the "AI" label seems to go through this mess. In the earlier AI cycles, rules engines were considered "human-ish" and got hyped up, but today we just see then as just another tool available to us, and we're better off for it.
From a horse's perspective, the internal combustion engine is just another tool for making scary noises and powering horse trailers to take me on fun horse adventures. So ... perhaps.
ChatGPT was obedient with the grill-me technique, just wrote a plan. Yesterday it started jumping to implementation. Why?
It's a very very bizarre way to use a computer.
Personally, I just don't. I'll use and prompt the LLMs the way that feels natural to me and move on with my life. Maybe I don't always get completely optimal results from them, but im also not spending half my day pleading with the computer to do a task.
The most important thing to be aware of in my opinion would be that Claude is better at UI design, and leaves a lot more comments in the code.
Other than that the results seem similar, at least functionally. I do not usually review the code style.
With humans it's actually good and worthwhile to create and strengthen connections. With an LLM, that's psychosis.
I don't think LLMs are people in any sense, at least as they're constructed now -- but they very much have what we would call "culture" and "personality" in suitably alien forms.
This is not the same as, e.g., feelings, experience, or humanity, or actual opinions or ideas (versus essentially "distilled vibes") and I feel that AI will more and more force us to confront that (including if new AIs are ever developed that may have the latter, as well!)
And if humans are anything, they are tool users.
Can be both. Use of some tools like LLMs might be more inducing psychosis than others like plain compilers or hammers.
>And if humans are anything, they are tool users.
To the point of self-destruction sometimes.
I really don't get it. Why the fact that it outputs words is so goddamn important for everybody? How does it suddenly make you so emotionally vulnerable? Does my brain work in a different way than the rest of humanity? Can't you disregard what's irrelevant? Is every programmer suddenly a trump supporter that has no ability to recognize empty words? To recognize lies about emotions and facts?
Words are just input. Mostly garbage. Emotion inducing words are garbage 10 times more often than any other. I could expect romance reader to be affected, or somebody with iq 70. But how the caste of some of the most technical people ever is afraid of catching psychosis just because they might read some words?
When we built the idea that anthropomorphising is wrong, we meant when doing it for rocks or trees or thunders or deer or some such.
We communicate with other humans using voice and three dimensional hand gestures. To use computers and early phones we had to learn to operate new input devices: keyboards and mice. Later with touchscreens we moved to two dimensional hand (finger) gestures. We're barely making voice commands work with our devices just recently.
Then, a large number of humans are figuratively tethered to their desks because the devices need power and stable internet connection. Mobile devices break this relationship a bit but you still need to charge them and be close to some sort of access point. In any case, the devices encourage sitting in one place for hours at time.
And this is just computers and smartphones. Humans adapted their entire lifestyles and transformed the landscape to cater to cars.
Was it? Think first about what it replaced. Lots of manual computation in bookkeeping and financial sectors. Telegrams and snail mail moved to email. Typesetting in books and magazines became easier and widely available,…
If there’s one thing that you can’t say about computers is that they’re limited.
The context was that technology should evolve to fit the humans [not the other way around]. And if contemporary technology didn't have limitations, it would be correct.
But it did and humans had to adapt to the computers. Humans had to develop and learn special languages so they could communicate with computers to do all those useful things you mentioned. Why? They were limited in understanding (or parsing) human languages. It took us decades before we could talk to computers in human languages. We're getting pretty close - especially in the past few years - but there's still some friction.
You may need to revisit your computation theory courses. Computers are the embodiment of a mathematical model and thus the inputs and outputs are formalized.
Do you just hold a pen and words are written automatically? Do you just hover your hands over a piano and have the moonlight sonata played? No, you have to do precise mechanical movements because that’s how the output is realized.
There’s no such things as words, sentences, keywords, statements at the computer level. What it does is symbol manipulation. You provide it a string of symbols, the rules for the manipulation, and it will provide a string of symbols as the output.
What symbols, what rules, are completely arbitrary . We just found that {1,0} are all that we needed as the set of symbols and that Context-Free Grammar is perfect for specifying the rules.
We still need to encode everything down to binary (ascii, unicode, bcd, floating points, pixel formats, PCM,…) and use a programming language (as defined by a grammar) to get the computer to do anything. Inference is made possible by those two mechanisms. It’s not a new computation model.
Realising this made me respect the "I" in "AI" a bit more seriously.
Maybe we need better reviewers then?
This presumes that the labs themselves know how well their models perform. But all they have are overtuned benchmarks and hype vibes.
Admittedly, yes, there's some overlap there.
They would have to admit 'seen it in the training data' as a factor, and that opens a can of worms.
They do not test how models perform when used interactively, like most of us do.