https://pcpartpicker.com/list/XpFtXR
That setup would currently run for around $1730? Without investing into a monitor, or any peripherals like keyboard, mouse, etc and picking a relatively cheap psu/case/cooler combo.
Maybe I misunderstood but seems a far cry from €850.
Additionally, while technically imbued with ‘meaning’, even the number 420 itself is somewhat meaningless and was originally used to delineate those who knew from those who don’t. It’s just that it got famous enough that we now almost all know.
In that sense I would argue it filled more or less the same function as 67.
I was going to say, I think the perpetuation of leetspeak and most of its use falls squarely into the millennial generation’s early 90s into the early 2000s.
As far as I know that’s generally what is often done, but it’s a surprisingly hard problem to solve ‘completely’ for two reasons:
The more obvious one - how do you define quality? When you’re working with the amount of data LLMs require as input and need to be checked for on output you’re going to have to automate these quality checks, and in one way or another it comes back around to some system having to define and judge against this score.
There’s many different benchmarks out there nowadays, but it’s still virtually impossible to just have ‘a’ quality score for such a complex task.
Perhaps the less obvious one - you generally don’t want to ‘overfit’ your model to whatever quality scoring system you set up. If you get too close to it, your model typically won’t be generally useful anymore, rather just always outputting things which exactly satisfy the scoring principle, nothing else.
If it reaches a theoretical perfect score, it would just end up being a replication of the quality score itself.
I see the misunderstanding, didn’t consciously see the ‘used’ hardware in your post above. That makes a lot more sense!