In practice, it's a little more tricky. AI APIs give mostly human-level reliable results in many cases. But they don't work well 100% of the time, which affects trust in an automated B2B product meant to replace human labor.
There are still applications that aren't meant to replace human labor, just to generate natural language very quickly. I've even seen this done in academia. And also, the API AIs are expected to become more reliable over time.
Reliability is much more possible than it was 1-2 years ago.
There was an article early on I'm trying to find that said the direction of attention was counter-intuitive this time around.
Some of this is in the weeds, but those who have kept up actively trying to use the AI for 12-18 months are often saying and seeing different things because they know what capabilities have arrived while some of us hang on to the understanding from the last time we might have looked at something.
Where I think I see things differently both in what I've been able to show and deliver, is the application of this technology does need to come before, or right along with development of it. This has largely been overlooked so far
Learning how to use something new and pretty different requires trying to use it, see what it can do reliably, and what it's improving at, and helping organizations with $ to fund something they need.
The big one still, is that something that's not possible today, has to be looked at more through a lens of not if, but when. The when has been happening much quicker.
They can get much closer to working well 100% of the time.
Often by not using them at each step, or not wanting a magic wand to figure it all out.
Human labor replacement isn't anything new. Anything simple or repetitive technology in general (including LLMs) will make a dent.
The applications for natural language, or not are quite valid. I had someone in academia approach me for designing a guide to help grade in the personalized style of a professor. The irony was there's ways to do it without LLM that might equal what is posisble today, but what they were asking for was valid.
One of the big issues that's improving is not just API "reliability", but the cost of running things per request off API, or reasonably running som eor part of it locally.
