Completion is not the same as only returning the exact strings in its training set.
LLMs don't really seem to display true inference or abstract thought, even when it seems that way. A recent Apple paper demonstrated this quite clearly.
ChairmanMeow
joined 2 years ago
Oh that's probably right actually.
I don't know anymore. But for me that probably means I shouldn't give it a rewatch. If it was any good, I'd remember it better I think.
IIRC not quite? I think he scolded her for getting near those caves. But I don't quite remember.
It's Sith Rey, she encounters her during a vision while training under Luke.
To lower prices presumably.
I understand the sentiment but that's an extremely small subset of people that are inconvenienced, in exchange for a significant reduction in the plastic littering in rivers, seas and oceans.
Skill issue
Kuttenberg sounds really funny in Dutch, it basically translates to "Cunts Mountain".
It's dead simple to Google mate.
And I'm not reinforcing what you said. For your theory to be true, it'd require the absolute silence of that entire crowd of people. They'd all have to be in on it. You really think none of those people would spill the details? Governments can barely keep shit secret once it spreads to 2 people.
Yes, but that's the textbook definition of inflation (being forced to raise wages because the salary becomes less valuable). I'm not sure if that's really the goal here.
I can understand the case for UBI, but so far most trials have been quite small in scope... that means few national effects have been properly observed.
To be fair, if 8% exits the labour market that would have a pretty severe economic effect, no?
Well the thing is, LLMs don't seem to really "solve" complex problems. They remember solutions they've seen before.
The example I saw was asking an LLM to solve "Towers of Hanoi" with 100 disks. This is a common recursive programming problem, takes quite a while for a human to write the answer to. The LLM manages this easily. But when asked to solve the same problem with with say 79 disks, or 41 disks, or some other oddball number, the LLM fails to solve the problem, despite it being simpler(!).
It can do pattern matching and provide solutions, but it's not able to come up with truly new solutions. It does not "think" in that way. LLMs are amazing data storage formats, but they're not truly 'intelligent' in the way most people think.