Capitalism is sadly doing exactly what it's designed to do there's just a lot of propaganda to mislead you such as the infamous trickle down economics idea
So why can it often output correct information after it has been corrected? This should be impossible according to you.
It generally doesn't. It apologizes then will output exactly, very nearly the same thing as before, or something else that's wrong in a brand new way. Have you used GPT before? This is a common problem, it's part of why you cannot trust anything it outputs unless you already know enough about the topic to determine it's accuracy.
No, LLMs understand a tree to be a complex relationship of many, many individual numbers. Can you clearly define how our understanding is based on something different?
And did you really just go "nuh huh its actually in binary"? I used the collection of symbols explanation as that's how OpenAI describes it so I thought it was a safe to just skip all the detail. Since it's apparently needed and you're unlikely to listen to me there's a good explanation in video form created by Kyle Hill. I'm sure many other people have gone and explained it much better than I can so instead of trying to prove me wrong which we can keep doing all day go learn about them. LLMs are super interesting and yet ultimately extremely primative.
We understand a tree to be a growing living thing, an LLM understands a tree as a collection of symbols. When they create output they don't decide that one synonym is more appropriate than another, it's chosen by which collection of symbols is more statistically likely.
Take for example attempting to correct GPT, it will often admit fault yet not "learn" from it. Why not? If it understands words it should be able to, at least in that context, no longer output the incorrect information yet it still does. It doesn't learn from it because it can't. It doesn't know what words mean. It knows that when it sees the symbols representing "You got {thing} wrong" the most likely symbols to follow represent "You are right I apologize".
That's all LLMs like GPT do currently. They analyze a collection of symbols (not actual text) and then output what they determine to be most likely to follow. That causes very interesting behavior, you can talk to it and it will respond as if you are having a conversation.
That wasn't my intention with the wonky autocorrect sentence. The point of that was to point out LLMs and my auto correct equally have no idea what words mean.
I mean plain old autocorrect does a surprisingly good job. Here's a quick example, I'll only be tapping the middle suggested word.
I will be there for you to grasp since you think your instance is screwy. I think everybody can agree that sentence is a bit weird but an LLM has a comparable understanding of its output as the autocorrect/word suggestion did.
A conversation by definition is at least two sided. You can't have a conversation with a tree or a brick but you could have one with another person. A LLM is not capable of thought. It "converses" by a more advanced version of what your phones autocorrect does when it gives you a suggested word. If you think of that as conversation I find that an extremely lonely definition of the word.
So to me yes, it does matter
"Chatting". LLMs don't have any idea what words mean, they are kinda like really fancy autocorrect, creating output based on what's most likely to occur next in the current context.
Alternatively as both floats (32 bit) and doubles (64 bit) are represented in binary we can directly compare them to the possible values an int (32 bit) and a long (64 bit) has. That is to say a float has the same amount of possible values as an int does (and double has the same amount of values as a long) . That's quite a lot of values but still ultimately limited.
Since we generally use decimal numbers that look like this 1.5 or 3.14. It's setup so the values are clustered around 0 and then every power of 2 you have half as many meaning you have high precision around zero (what you use and care about in practice) and less precision as you move towards negative infinity and positive infinity.
In essence it's a fancy fraction that is most precise when it's representing a small value and less precise as the value gets farther from zero
I mean Bitwarden wants to make money. 10$ a year to not have to mess about with self hosting (however beneficial that might be) is a pretty good deal.
That's the majority of people?? Looks like the most recent number is 64% of people with 20% on Safari and the remaining ~17% split among the rest with Firefox (3%) not even beating Edge (5%)
Yeah dude this was quite nice compared to my experiences on Reddit. Might have come off too strong from all my time there.
Not decaying. The Nazis were always fascist they put on a front of being progressive to ganrner support which worked quite well as we can tell from history. By the time it became obvious they weren't really progressive they were already in power.