alt Hacker NewsFine, if you don't like the piano analogy:
Most people suck at falconry. If you practice at falconry you'll get better at it.
Falcons certainly aren't deterministic.
> it's not like there this huge secret to using them - after all they use natural language as their primary interface
That's what makes them hard to use! A programming language has like ~30 keywords and does what you tell it to do. An LLM accepts input in 100+ human languages and, as you've already pointed out many times, responds in non-deterministic ways. That makes figuring out how to use them effectively really difficult.
> We are discussing if I should replace the magnificent supercomputer already placed in my head by mother nature or God or Aliens or whatever you believe in, for a very shitty, downgraded version 0.0.1 of it sitting in someone's datacenter
We really aren't. I consistently argue for LLMs as tools that augment and amplify human expertise, not as tools that replace it.
I never repeat the "country of PhDs" stuff because I think it's over-hyped nonsense. I talk about what LLMs can actually do.
> Falcons certainly aren't deterministic.
Well falcons are not deterministic and are trained to do something in the art of falconry, yes. Still I fail to see an analogy here as it is the falcon gets trained to execute a few specific tasks triggered by specific commands. Much like a dog. The human more or less needs to remember those few commands. We don't teach dogs and falcons to do everything do we ? Although we do teach specific dogs do to specific tasks in various domains. But no one ever claimed Fido was superintelligent and that we needed to figure him out better.
> That's what makes them hard to use! A programming language has like ~30 keywords and does what you tell it to do. An LLM accepts input in 100+ human languages and, as you've already pointed out many times, responds in non-deterministic ways. That makes figuring out how to use them effectively really difficult.
Well yes and no. The problem with figuring out how to use them (LLMs) effectively is exactly caused by their inherent un-predictability, which is a feature of their architecture further exacerbated by whatever datasets they were trained on. And so since we have no f*ing clue as to what the glorified slot machines might pop out next, and it is not even sure as recently measured, that they make us more productive, the logical question is - why should we, as you propose in your latest blog, bend our minds to try and "figure them out" ? If they are un-predictable, that means effectively that we do not control them, so what good is our effort in "figuring them out"? How can you figure out a slot machine? And why the hell should we use it for anything else other than a shittier replacement for pre-2019 Google? In this state they are neither augmentation nor amplification. They are a drag on productivity and it shows, hint - AWS December outage. How is that amplifying anything other than toil and work for the humans?