161–170 of 278 posts
AI is adequate for art. It is NOT suitable for engineering. Not unless you build a ton of handrails or manually verify all the code and logic yourself.
Earlier quoted context omitted.
You may not take it seriously, and I may not take it seriously, but it takes one person to read this seriously, convince another person to invest, and then hire a third person and tell them, "make it so", for the joke to no longer be a joke.
If somebody putting a few millions into making this widespread were enough to make it a problem, then software development would already be doomed and we would better start learning woodwork right now.
Or about launching a Docker container implementing a single, short-lived CLI command.
Or about all the other countless examples of ridiculously complicated and/or wasteful solutions to simple problems that become industry standards simply because they make it easier to do something quickly - all of them discussed/criticized regularly here and elsewhere, yet continuing to gain adoption.
Nah, our industry values development velocity much more than correctness, performance, ergonomics, or any kind of engineering or common sense.
And you will almost immediately run into the fundamental problem with current iterations of GPT - You can not trust it to be correct or actually do the thing you want, only something that resembles the thing you want. The description in this link puts some really high hopes on the ability of AI to simply "figure out" what you want with little input. In reality, it will give you something that sorta kinda looks like w…
I keep hearing this assertion, that GPT can be wrong, therefore it’s an unworkable technology. But it’s a bad comparison. LLMs aren’t trying to be computationally correct like a calculator or something, the value is in their ability to semantically process a question. The other issue is assuming that the existing way of doing things is always correct. Engineers frequently get things wrong. If an AI model can complete…
Because this is incredibly shortsighted and also fundamentally misunderstands the return data of an LLM.
Earlier quoted context omitted.
I keep hearing this assertion, that GPT can be wrong, therefore it’s an unworkable technology. But it’s a bad comparison. LLMs aren’t trying to be computationally correct like a calculator or something, the value is in their ability to semantically process a question. The other issue is assuming that the existing way of doing things is always correct. Engineers frequently get things wrong. If an AI model can complete…
And even if the AI model is only 75% correct, if it can generate the output near instantly and give that as a starting point, that's great. There's a reason why templates, wizards, and samples are so popular -- after servicing of code, the hardest part is probably getting started with it.
Art is where an approximation is fine and you can fill the holes with "subjectivity", but engineering is where missing a bolt on a bridge could collapse the whole thing. AI is adequate for art. It is NOT suitable for engineering. Not unless you build a ton of handrails or manually verify all the code and logic yourself.
Art is where an approximation is fine and you can fill the holes with "subjectivity", but engineering is where missing a bolt on a bridge could collapse the whole thing. AI is adequate for art. It is NOT suitable for engineering. Not unless you build a ton of handrails or manually verify all the code and logic yourself.
* If you want a medical device, it's a problem.
* If you want a fun game or piece of social media, it's probably not.
Over time, we'll know the contours a lot more. A lot of engineering came about purely empirically. We'd build a building, and we'd learn something based on whether or not it fell down, without any great theory as to why.
I suspect deep language models might go the same way. Once a system works a million times without problems, the risk will be considered low enough for life-critical applications.
(And once it's in all life-critical applications, perhaps it will decide to go Darknet on us. With where deep learning is going, the Terminator movies seem less and less like science fiction.)
Would love to get me a bot that will automatically write test coverage and mocks for me.
Earlier quoted context omitted.
>We clearly won't reach AGI with the current LLM approaches, for example. Have any evidence to back this up? Scaling laws seem to show we aren't near a plateau and it's not clear what kind of capability GPT-4,5 or 6 may have.
They’ve already been trained on orders of magnitude more text than a human being ever sees or hears in their entire life, without approaching human intelligence. What text is left to train them on?