Note that “real world truth” is something you can never accurately map with just your senses.
No model of the “real world” is accurate, and not everyone maps the “real world truth” they personally experience through their senses in the same way… or even necessarily in a way that’s really truly “correct”, since the senses are often deceiving.
A person who is blind experiences the “real world truth” by mapping it to a different set of models than someone who has additional visual information to mix into that model.
However, that doesn’t mean that the blind person can “never understand” the “real world truth” …it just means that the extent at which they experience that truth is different, since they need to rely in other senses to form their model.
Of course, the more different the senses and experiences between two intelligent beings, the harder it will be for them to communicate with each other in a way they can truly empathize. At the end of the day, when we say we “understand” someone, what we mean is that we have found enough evidence to hold the belief that some aspects of our models are similar enough. It doesn’t really mean that what we modeled is truly accurate, nor that if we didn’t understand them then our model (or theirs) is somehow invalid. Sometimes people are both technically referring to the same “real world truth”, they simply don’t understand each other and focus on different aspects/perceptions of it.
Someone (or something) not understanding an idea you hold doesn’t mean that they (or you) aren’t intelligent. It just means you both perceive/model reality in different ways.
LLMs are criminally simplified neural networks at minimum thousands of orders less complex than a brain. Nothing we do with current neural networks resembles intelligence.
Nothing they do is close to understanding. The fact that you can train one exclusively on the rules of a simple game and get it to eventually infer a basic rule set doesn’t imply anything like comprehension. It’s simplistic pattern matching.
No, and that definition has nothing in common with what the word means.
Autocorrect has plenty of information encoded as artifacts of how it works. ChatGPT isn’t like autocorrect. It is autocorrect, and doesn’t do anything more.
It’s fine if you think so, but then it’s a pointless argument over definitions.
You can’t have a conversation with autocomplete. It’s qualitatively different. There’s a reason we didn’t have this kind of code generation before LLM’s.
I am not sure of the relevance of the oppressed classes and with the object of duping the latter is the cravings of the oppressed classes and with the object of duping the latter
Yeah, totally. Repeating the same nonsensical sentence over and over is also how I converse. 🙄
ChatGPT will never understand. LLMs have no capacity to do so.
To understand you need underlying models of real world truth to build your word salad on top of. LLMs have none of that.
Note that “real world truth” is something you can never accurately map with just your senses.
No model of the “real world” is accurate, and not everyone maps the “real world truth” they personally experience through their senses in the same way… or even necessarily in a way that’s really truly “correct”, since the senses are often deceiving.
A person who is blind experiences the “real world truth” by mapping it to a different set of models than someone who has additional visual information to mix into that model.
However, that doesn’t mean that the blind person can “never understand” the “real world truth” …it just means that the extent at which they experience that truth is different, since they need to rely in other senses to form their model.
Of course, the more different the senses and experiences between two intelligent beings, the harder it will be for them to communicate with each other in a way they can truly empathize. At the end of the day, when we say we “understand” someone, what we mean is that we have found enough evidence to hold the belief that some aspects of our models are similar enough. It doesn’t really mean that what we modeled is truly accurate, nor that if we didn’t understand them then our model (or theirs) is somehow invalid. Sometimes people are both technically referring to the same “real world truth”, they simply don’t understand each other and focus on different aspects/perceptions of it.
Someone (or something) not understanding an idea you hold doesn’t mean that they (or you) aren’t intelligent. It just means you both perceive/model reality in different ways.
https://thegradient.pub/othello/
LLMs are neural networks and are absolutely capable of understanding.
LLMs are criminally simplified neural networks at minimum thousands of orders less complex than a brain. Nothing we do with current neural networks resembles intelligence.
Nothing they do is close to understanding. The fact that you can train one exclusively on the rules of a simple game and get it to eventually infer a basic rule set doesn’t imply anything like comprehension. It’s simplistic pattern matching.
Does AlphaGo understand go? How about AlphaStar?
When I say LLM’s can understand things, what I mean is that there’s semantic information encoded in the network. A demonstrable fact.
You can disagree with that definition, but the point is that it’s absolutely not just autocomplete.
No, and that definition has nothing in common with what the word means.
Autocorrect has plenty of information encoded as artifacts of how it works. ChatGPT isn’t like autocorrect. It is autocorrect, and doesn’t do anything more.
It’s fine if you think so, but then it’s a pointless argument over definitions.
You can’t have a conversation with autocomplete. It’s qualitatively different. There’s a reason we didn’t have this kind of code generation before LLM’s.
Adversus solem ne loquitor.
If you just keep taking the guessed next word from autocomplete you also get a bunch of words shaped like a conversation.
Yeah, totally. Repeating the same nonsensical sentence over and over is also how I converse. 🙄