41–50 of 92 posts
Earlier quoted context omitted.
The titel has a typo as the actual article has the title "The Social Edge of Intelligence".
I've corrected the typo now, but I almost let it stand as a testament to my humanity.
I didn't mind that there was a typo.
Generative AI is the average of all human knowledge
While true in some sense, it does have more knowledge than the average person.
If I read thousands of books that explain the details of another civilization in another galaxy, very thoroughly and consistently, but it it just happens to be all made up - did I gain knowledge? More importantly, does what I have in my brain now flip from being fiction to being knowledge if that civilization flipped from not existing to existing? How so, if nothing in my brain, or how I live out the rest of my life, changes in the least, if not a single atom in this galaxy changes (let's ignore that gravity has infinite reach and all that, for the sake of argument)?
If yes, how? What in your definition of knowledge makes that possible?
Earlier quoted context omitted.
While true in some sense, it does have more knowledge than the average person.
With AI, everyone will be average in no time! Internet started it, hopefully LLMs will finish it.
Now with LLMs lowering the average through cognitive offloading and skill atrophy, prepare for it to get a whole lot worse.
I'll say it again: because we do not have any material focus on pragmatic, disagreement structuring effective communications, (people are not taught how to discuss disagreement) not only is our current AI being massively misunderstood, the human population do not have the discrete language skills to even use AI without massive hallucination issues that they are in control, but do not have the language nuanced underst…
Can you state your point more simply?
This in itself is negative, but the ramifications are profound: the landscape of ideas is never realized by a material percentage of the students. And those who could have contributed worthwhile insights have been taught to not contribute.
Earlier quoted context omitted.
Can you state your point more simply?
I hope I'm wrong about this - but they sounded like some breed of utopian leftist mad that an AI not specifically trained on their drivel doesn't agree with their utopian ideas, and they believe that this is solely responsible for The Rapture/The Revolution (TM)/real communism not happening. The use of euphemisms and incredible lack of awareness of using 'hellscape' to describe the first world is a bit of a give-away…
There is a fundamental assumption made about the ability of AI here that I believe is wrong. It assumes that the outputs are lacking because of a limit of ability. I think there is a strong case to make that many of their limitations come from them doing what we have told them to do. Hallucinations are the stand out example of this. If you train it to give answers to questions, it will answer questions, but it might…
> I think there is a strong case to make that many of their limitations come from them doing what we have told them to do. Hallucinations are the stand out example of this. If you train it to give answers to questions, it will answer questions, but it might have to make up the answer to do so. This isn't not knowing that it does not know. This is doing the task given to it regardless of whether it knows or not. Are y…
This is not a problem in the ability of the system, it is a problem of how to construct training for such a task.
To provide training examples where it answers it does not know the answer only when it does not know the answer. You need training examples where it says it doesn't know when it does not contain that knowledge, but it provides an answer when it does know the answer.
To create such an example, you need to know in advance what the model knows and what the model does not know. You can't just have a database of facts that it knows, because you also need to count things that it can readily infer.
Any model that can reliably give the sum of any two 10 digit integers should be able to answer so. You can't list every possible number that a model knows how to add. That is just the tiniest subset of the task you would have to do because you have to determine every inferrable fact, not just integers. Adding to the problem is that training on questions like this can add to the knowledge base to the model either from the question itself or by inductively figuring out the answer based upon the combination of the question and the fact that it was not expected to know the answer.
A completely different training system would have to be implemented. There is research on categorising patterns of activations that can determine a form of 'mental state' of a model. A dynamic training approach where the answer that the model is expected-to-give/rewarded-for-giving is partially dependent on the models own state could be achieved through this mechanism.
Generative AI is the average of all human knowledge