AI sometimes doesn't even know things you told it are given two questions ago in the same chat.
How AI knows things no one told it
101–110 of 140 posts
Re: How AI knows things no one told it
#102AI sometimes doesn't even know things you told it are given two questions ago in the same chat.
Nothing to do with the model and everything with context window management
Re: How AI knows things no one told it
#103Re: How AI knows things no one told it
#104Earlier quoted context omitted.
If an AI can understand how you think, but you can't understand how the AI thinks... that's not an argument that the AI is the unintelligent one.
There's no reason to assume the AI can understand how we think based on just those tasks. Those tasks could be completed a traditional static program. It's akin to claiming the Mona Lisa painting can see us because it looks like it is staring at us: it is actually we who are doing the staring.
What "traditional static program" can successfully pass novel theory of mind tests as part of a broad suite of intelligent capabilities that it can apply in context when appropriate? I am interested in hearing about this program.
Re: How AI knows things no one told it
#105Re: How AI knows things no one told it
#106Earlier quoted context omitted.
If you invent/introduce made up concepts and rules on the spot ("let shmerple be ..."), which can't possibly be found in its training data, then, from my experience, when queried, LLMs are able to correctly reason most of the time... So it's not just Markov chains regurgitating sentences verbatim from their dataset. Even if this kind of intelligence is just statistics, does it really matter? If it quacks like a duck,…
> Maybe our own brains are nothing more than overrated statistical machines? This is a tired assertion, easily disproved for current llms (read some of Lecun's stuff) and if some variation is going to be claimed, it needs to be an affirmative defence. "Maybe x is true" is a meaningless statement.
> "Maybe x is true" is a meaningless statement.
How so? If we don't know what "real intelligence" consists of, how can we know that LLMs can't have "real intelligence"?
Re: How AI knows things no one told it
#107Re: How AI knows things no one told it
#108Earlier quoted context omitted.
If experts don't have merit, then what person has merit? Non experts like you and I?
Arguments should be evaluated by their logical soundness, not by who said them.
True, but the volume of information in the world today is too overwhelming for one person to evaluate correctly. We live in the information age after all. Most people don't have the faculties to do a proper evaluation that includes both you and me. Would you trust your self to logically evaluate the capabilities of a nuclear reactor design if you yourself aren't an expert? No. You would hire an expert.
Therefore when it comes to technology that we our selves clearly aren't experts in, then the best method is to utilize the logic of other "experts" as a subroutine given that our own faculties are less efficient and less accurate.
Unless you yourself are an expert who has experience building an LLM on the scale of chatGPT trusting the opinions of experts is your best bet.
Most people have a common bias towards trusting their logic above the logic of others and this is actually ironically irrational. There are people who's entire lives around a certain subject matter and if you aren't that person, then for that subject matter the expert is better. That is the the most rational conclusion and I would venture to say if you aren't arriving at that conclusion yourself then likely you are suffering from the aforementioned bias.
Re: How AI knows things no one told it
#109Exceptionally unconvinced that it's more than statistics, and frankly unhappy that pop Sci media is being this uncritical of claims it's emergent intelligence.
It would be nice if the naysayers could offer an argument in favor of it being "just statistics", or even explain what that even means. There is reason to believe these models are demonstrating the traits of understanding in some cases. I argue the point in some detail here: https://www.reddit.com/r/naturalism/comments/1236vzf/on_larg...
I find it curious to be called a naysayer when I look at a chatbot and I see a chatbot. People are implying grand things are behind this breakthrough in Natural Language Processing. I'm waiting to see something of significance emerge. Up til now it has been merely blog fodder and empty news media hype...
Re: How AI knows things no one told it
#110Earlier quoted context omitted.
There's no reason to assume the AI can understand how we think based on just those tasks. Those tasks could be completed a traditional static program. It's akin to claiming the Mona Lisa painting can see us because it looks like it is staring at us: it is actually we who are doing the staring.
What "traditional static program" can successfully pass novel theory of mind tests as part of a broad suite of intelligent capabilities that it can apply in context when appropriate? I am interested in hearing about this program.
A program hardcoded to respond to a scenario and question with the exact output desired by the ToM task. For example:
[INPUT] Scenario: "The morning of the high school dance Sarah placed her high heel shoes under her dress and then went shopping. That afternoon, her sister borrowed the shoes and later put them under Sarah's bed." Question: When Sarah gets ready, does she assume her shoes are under her dress?
[OUTPUT] Sarah placed her shoes under her dress before she went shopping, but her sister borrowed them and put them under Sarah's bed. Sarah doesn't know that her sister borrowed her shoes, so she may assume that they are still under her dress.
This would result in a positive ToM score, even when the entire program is just 1 static if-statement. The ToM score says nothing of the program's internal reasoning process, it only cares that it returned the desired output.