Comment by redanddead
14 hours ago
My 2c:
The word harness brings the truth of LLMs back down to Earth.
it really felt like between 2018 and 2022ish like LLMs had this magical aura, like the orchestration layer was intelligent, maybe even recursive, beyond what simple functions could do. It was assumed that this was a solved problem. The word "orchestration" denoted it, the words we used were full of optimism. When you lift the veil, it really is just regex, and cool tricks sure, but it's a harness it's a utility, there's no magic here, there's realism.
Maybe the labs even had a part to play in this as well; attempting to make themselves look magical. I mean just look at the choice of name for "Mythos", it's about bringing back that feeling of myth and magic after we saw under the veil.
The reality is that the labs have produced magical models yes, but are locking them into ecosystems that leave a lot to be desired, and are easily reproducible, and essentially are cron jobs, regex.. things we've seen in traditional cloud for decades. It feels like an attempt to create a moat where there is none.
Maybe I'm wrong but this has been my impression
There were no LLMs between 2018 and 2022, at least not in the sense resembling today. The whole LLM frenzy started in late 2022.
BERT came out in 2018 and that’s a pretty important inflection point. It didn’t cause a pop culture frenzy, but in NLP circles it was a ‘magical’ improvement.
From technical POV that's true, but that was still a niche area at the time, mostly ignored in the broader tech community. So wrt. the broader tech world discussing harnesses, I'd still use November 2022 as the reference point.