Ok, but so do most humans? So few people actually have true understanding in topics. They parrot the parroting that they have been told throughout their lives. This only gets worse as you move into more technical topics. Ask someone why it is cold in winter and you will be lucky if they say it is because the days are shorter than in summer. That is the most rudimentary “correct” way to answer that question and it is still an incorrect parroting of something they have been told.
Ask yourself, what do you actually understand? How many topics could you be asked “why?” on repeatedly and actually be able to answer more than 4 or 5 times. I know I have a few. I also know what I am not able to do that with.
Few people truly understand what understanding means at all, i got teacher in college that seriously thinked that you should not understand content of lessons but simply remember it to the letter
I don’t think actual parroting is the problem. The problem is they don’t understand a word outside of how it is organized. They can’t be told to do simple logic because they don’t have a simple understanding of each word in their vocabulary. They can only reorganize things to varying degrees.
This is only one type of intelligence and LLMs are already better at humans at regurgitating facts. But I think people really underestimate how smart the average human is. We are incredible problem solvers, and AI can’t even match us in something as simple as driving a car.
Lol @ driving a car being simple. That is one of the more complex sensory somatic tasks that humans do. You have to calculate the rate of all vehicles in front of you, assess for collision probabilities, monitor for non-vehicle obstructions (like people, animals, etc.), adjust the accelerator to maintain your own velocity while terrain changes, be alert to any functional changes in your vehicle and be ready to adapt to them, maintain a running inventory of laws which apply to you at the given time and be sure to follow them. Hell, that is not even an exhaustive list for a sunny day under the best conditions. Driving is fucking complicated. We have all just formed strong and deeply connected pathways in our somatosensory and motor cortexes to automate most of the tasks. You might say it is a very well-trained neural network with hundreds to thousands of hours spent refining and perfecting the responses.
The issue that AI has right now is that we are only running 1 to 3 sub-AIs to optimize and calculate results. Once that number goes up, they will be capable of a lot more. For instance: one AI for finding similarities, one for categorizing them, one for mapping them into a use case hierarchy to determine when certain use cases apply, one to analyze structure, one to apply human kineodynamics to the structure and a final one to analyze for effectiveness of the kineodynamic use cases when done by a human. This would be a structure that could be presented an object and told that humans use it and the AI brain could be able to piece together possible uses for the tool and describe them back to the presenter with instructions on how to do so.
Ok, but so do most humans? So few people actually have true understanding in topics. They parrot the parroting that they have been told throughout their lives. This only gets worse as you move into more technical topics. Ask someone why it is cold in winter and you will be lucky if they say it is because the days are shorter than in summer. That is the most rudimentary “correct” way to answer that question and it is still an incorrect parroting of something they have been told.
Ask yourself, what do you actually understand? How many topics could you be asked “why?” on repeatedly and actually be able to answer more than 4 or 5 times. I know I have a few. I also know what I am not able to do that with.
Few people truly understand what understanding means at all, i got teacher in college that seriously thinked that you should not understand content of lessons but simply remember it to the letter
I don’t think actual parroting is the problem. The problem is they don’t understand a word outside of how it is organized. They can’t be told to do simple logic because they don’t have a simple understanding of each word in their vocabulary. They can only reorganize things to varying degrees.
Some systems clearly do that though or are you just talking about llms?
Just llms
It’s like saying bro, this mouse can’t even type text if I don’t use an on screen keyboard
This is only one type of intelligence and LLMs are already better at humans at regurgitating facts. But I think people really underestimate how smart the average human is. We are incredible problem solvers, and AI can’t even match us in something as simple as driving a car.
Lol @ driving a car being simple. That is one of the more complex sensory somatic tasks that humans do. You have to calculate the rate of all vehicles in front of you, assess for collision probabilities, monitor for non-vehicle obstructions (like people, animals, etc.), adjust the accelerator to maintain your own velocity while terrain changes, be alert to any functional changes in your vehicle and be ready to adapt to them, maintain a running inventory of laws which apply to you at the given time and be sure to follow them. Hell, that is not even an exhaustive list for a sunny day under the best conditions. Driving is fucking complicated. We have all just formed strong and deeply connected pathways in our somatosensory and motor cortexes to automate most of the tasks. You might say it is a very well-trained neural network with hundreds to thousands of hours spent refining and perfecting the responses.
The issue that AI has right now is that we are only running 1 to 3 sub-AIs to optimize and calculate results. Once that number goes up, they will be capable of a lot more. For instance: one AI for finding similarities, one for categorizing them, one for mapping them into a use case hierarchy to determine when certain use cases apply, one to analyze structure, one to apply human kineodynamics to the structure and a final one to analyze for effectiveness of the kineodynamic use cases when done by a human. This would be a structure that could be presented an object and told that humans use it and the AI brain could be able to piece together possible uses for the tool and describe them back to the presenter with instructions on how to do so.