Regardless of skill level for-profit GenAI/LLM AI has a terrible economical (funding focus), political (regulatory capture), social (dataset clean up, PR floods on FLOSS projects, spam & scam) and ecological (GPU deprecation pace, data centers) impact.
So… even if somehow a person is so skilled they finally find good use for models hosted by Anthropic, OpenAI, etc then unfortunately they can’t disentangle it from all the negative externalities.
Let’s say your org providing, idunno, coding to control illumination for a smart facility.
Let’s say the lighting doesn’t work, and as a result some one slips and dies. Let’s say it’s 50/50 of the code is at fault or not.
Your org is now looking at liability in a wrongful death lawsuit.
Even if you can argue that it was being used wrong, it’s still going to cost your org more than it would have to pay some one who’s a proper coder to do it.
That’s the whole point I’m making. A “proper coder” can leverage a model without turning it lose on a whole code base and saying “just fuck my shit up”.
You write the logic for a panel and you need to add a centered button in a UI? Done. You need to grab the proper tar flags for data repackage and transport? Done. You need to actually devise a scalable framework for an finite state machine capturing failure modes? Hooray, you now have time to just focus on that, it’s a bad use case for a LLM. This is what you pay real people for.
All laying the ground work for future endeavors which hopefully address those shortcomings. The box is open and it’s unlikely to close, but I agree these models can’t continue to suck as much as they do to make in the long term and be viable without changes.
Even more unpopular: beyond a certain skill level AI starts to look like a feature again too.
But it’s windows so there’s no saving that turd no matter how much you polish it at this point.
Regardless of skill level for-profit GenAI/LLM AI has a terrible economical (funding focus), political (regulatory capture), social (dataset clean up, PR floods on FLOSS projects, spam & scam) and ecological (GPU deprecation pace, data centers) impact.
So… even if somehow a person is so skilled they finally find good use for models hosted by Anthropic, OpenAI, etc then unfortunately they can’t disentangle it from all the negative externalities.
Another negative is liability.
Let’s say your org providing, idunno, coding to control illumination for a smart facility.
Let’s say the lighting doesn’t work, and as a result some one slips and dies. Let’s say it’s 50/50 of the code is at fault or not.
Your org is now looking at liability in a wrongful death lawsuit.
Even if you can argue that it was being used wrong, it’s still going to cost your org more than it would have to pay some one who’s a proper coder to do it.
That’s the whole point I’m making. A “proper coder” can leverage a model without turning it lose on a whole code base and saying “just fuck my shit up”.
You write the logic for a panel and you need to add a centered button in a UI? Done. You need to grab the proper tar flags for data repackage and transport? Done. You need to actually devise a scalable framework for an finite state machine capturing failure modes? Hooray, you now have time to just focus on that, it’s a bad use case for a LLM. This is what you pay real people for.
All laying the ground work for future endeavors which hopefully address those shortcomings. The box is open and it’s unlikely to close, but I agree these models can’t continue to suck as much as they do to make in the long term and be viable without changes.