Hi, I have a few questions that I’m hoping will help me clarify some of the fundamental definitions. I totally get that these are problematic questions in the absence of consensus around these terms—I’m hoping to have a few people weigh in and I don’t mind if answers are directly contradictory or my questions need to be re-thought.
If it turns out that LLMs are a path to the first “true AGI” in the eyes of, say, the majority of AI practitioners, what would such a model need to be able to do, and at what level, to be considered AGI, that GPT-4 can’t currently do?
If we look at just “GI”, rather than “AGI”, do any animals have GI? If so, where is the cutoff between intelligent and unintelligent animals? Is GPT-4 considered more or less intelligent than, say, an amoeba, or a gorilla, or an octopus etc?
When we talk about “alignment”, are today’s human institutions and organisations aligned to a lesser or greater extent we would want AGI aligned? Are religions, governments, corporations, organised crime syndicates, serial killers, militaries, fossil fuel companies etc considered aligned, and to what extent? Does the term alignment have meaning when talking about individuals, or groups of humans? Does it have meaning for animal populations, or inanimate objects?
If I spoke to a group of AI researchers of the pre-home-computer era, and described a machine capable of producing poetry, books, paintings, computer programs, etc in such a way that the products could not be distinguished from top 10% human examples of those things, that could pass entrance exams into 90% of world universities, could score well over 100 in typical IQ tests of that era, and could converse in dozens of languages via both text and voice, would they consider that to meet some past definition of AGI? Has AGI ever had enough of a consensus definition for that to be a meaningful question?
If we peer into the future, do we expect commodity compute power and software to get capable enough for an average technical person on an average budget to build and/or train their own AGI from the “ground up”? If so, will there not be a point where a single rogue human or small informal group can intentionally build non-aligned unsafe AGI? And if so, how far away is that point?
Apologies if these more speculative/thought-experimenty questions are off the mark for this thread, happy to be pointed to a more appropriate place for them!
It is important to remember that our ultimate goal is survival. If someone builds a system that may not meet the strict definition of AGI but still poses a significant threat to us, then the terminology itself becomes less relevant. In such cases, employing a ‘taboo-your-words’ approach can be beneficial.
Now lets think of intelligence as “pattern recognition”. It is not all that intelligence is, but it is big chunk of it and it is concrete thing we can point to and reason about while many other bits are not even known.[1]
In that case GI is general/meta/deep pattern recognition. Patterns about patterns and patterns that apply to many practical cases, something like that.
Obvious thing to note here: ability to solve problems can be based on a large number of shallow patterns or small number of deep patterns. We are pretty sure that significant part of LLM capabilities is shallow pattern case, but there are hints of at least some deep patterns appearing.
And I think that points to some answers: LLM appear intelligent by sheer amount of shallow patterns. But for system to be dangerous, number of required shallow patterns is so large that it is essentially impossible to achieve. So we can meaningfully say it is not dangerous, it is not AGI… Except, as mentioned earlier there seem to be some deep patterns emerging. And we don’t know how many. As for the pre-home-computer era researchers, I bet they could not imagine amount of shallow patterns that can be put into system.
I hope this provided at least some idea how to approach some of your questions, but of course in reality it is much more complicated, there is no sharp distinction between shallow and deep patterns and there are other aspects of intelligence. For me at least it is surprising that it is possible to get GPT-3.5 with seemingly relatively shallow patterns, so I myself “could not imagine amount of shallow patterns that can be put into system”
I tried Chat GPT on this paragraph, like the result but felt too long:
Intelligence indeed encompasses more than just pattern recognition, but it is a significant component that we can readily identify and discuss. Pattern recognition involves the ability to identify and understand recurring structures, relationships, and regularities within data or information. By recognizing patterns, we can make predictions, draw conclusions, and solve problems.
While there are other aspects of intelligence beyond pattern recognition, such as creativity, critical thinking, and adaptability, they might be more challenging to define precisely. Pattern recognition provides a tangible starting point for reasoning about intelligence.
If we consider problem-solving as a defining characteristic of intelligence, it aligns well with pattern recognition. Problem-solving often requires identifying patterns within the problem space, recognizing similarities to previously encountered problems, and applying appropriate strategies and solutions.
However, it’s important to acknowledge that intelligence is a complex and multifaceted concept, and there are still many unknowns about its nature and mechanisms. Exploring various dimensions of intelligence beyond pattern recognition can contribute to a more comprehensive understanding.
Hi, I have a few questions that I’m hoping will help me clarify some of the fundamental definitions. I totally get that these are problematic questions in the absence of consensus around these terms—I’m hoping to have a few people weigh in and I don’t mind if answers are directly contradictory or my questions need to be re-thought.
If it turns out that LLMs are a path to the first “true AGI” in the eyes of, say, the majority of AI practitioners, what would such a model need to be able to do, and at what level, to be considered AGI, that GPT-4 can’t currently do?
If we look at just “GI”, rather than “AGI”, do any animals have GI? If so, where is the cutoff between intelligent and unintelligent animals? Is GPT-4 considered more or less intelligent than, say, an amoeba, or a gorilla, or an octopus etc?
When we talk about “alignment”, are today’s human institutions and organisations aligned to a lesser or greater extent we would want AGI aligned? Are religions, governments, corporations, organised crime syndicates, serial killers, militaries, fossil fuel companies etc considered aligned, and to what extent? Does the term alignment have meaning when talking about individuals, or groups of humans? Does it have meaning for animal populations, or inanimate objects?
If I spoke to a group of AI researchers of the pre-home-computer era, and described a machine capable of producing poetry, books, paintings, computer programs, etc in such a way that the products could not be distinguished from top 10% human examples of those things, that could pass entrance exams into 90% of world universities, could score well over 100 in typical IQ tests of that era, and could converse in dozens of languages via both text and voice, would they consider that to meet some past definition of AGI? Has AGI ever had enough of a consensus definition for that to be a meaningful question?
If we peer into the future, do we expect commodity compute power and software to get capable enough for an average technical person on an average budget to build and/or train their own AGI from the “ground up”? If so, will there not be a point where a single rogue human or small informal group can intentionally build non-aligned unsafe AGI? And if so, how far away is that point?
Apologies if these more speculative/thought-experimenty questions are off the mark for this thread, happy to be pointed to a more appropriate place for them!
It is important to remember that our ultimate goal is survival. If someone builds a system that may not meet the strict definition of AGI but still poses a significant threat to us, then the terminology itself becomes less relevant. In such cases, employing a ‘taboo-your-words’ approach can be beneficial.
Now lets think of intelligence as “pattern recognition”. It is not all that intelligence is, but it is big chunk of it and it is concrete thing we can point to and reason about while many other bits are not even known.[1]
In that case GI is general/meta/deep pattern recognition. Patterns about patterns and patterns that apply to many practical cases, something like that.
Obvious thing to note here: ability to solve problems can be based on a large number of shallow patterns or small number of deep patterns. We are pretty sure that significant part of LLM capabilities is shallow pattern case, but there are hints of at least some deep patterns appearing.
And I think that points to some answers: LLM appear intelligent by sheer amount of shallow patterns. But for system to be dangerous, number of required shallow patterns is so large that it is essentially impossible to achieve. So we can meaningfully say it is not dangerous, it is not AGI… Except, as mentioned earlier there seem to be some deep patterns emerging. And we don’t know how many. As for the pre-home-computer era researchers, I bet they could not imagine amount of shallow patterns that can be put into system.
I hope this provided at least some idea how to approach some of your questions, but of course in reality it is much more complicated, there is no sharp distinction between shallow and deep patterns and there are other aspects of intelligence. For me at least it is surprising that it is possible to get GPT-3.5 with seemingly relatively shallow patterns, so I myself “could not imagine amount of shallow patterns that can be put into system”
I tried Chat GPT on this paragraph, like the result but felt too long:
Intelligence indeed encompasses more than just pattern recognition, but it is a significant component that we can readily identify and discuss. Pattern recognition involves the ability to identify and understand recurring structures, relationships, and regularities within data or information. By recognizing patterns, we can make predictions, draw conclusions, and solve problems.
While there are other aspects of intelligence beyond pattern recognition, such as creativity, critical thinking, and adaptability, they might be more challenging to define precisely. Pattern recognition provides a tangible starting point for reasoning about intelligence.
If we consider problem-solving as a defining characteristic of intelligence, it aligns well with pattern recognition. Problem-solving often requires identifying patterns within the problem space, recognizing similarities to previously encountered problems, and applying appropriate strategies and solutions.
However, it’s important to acknowledge that intelligence is a complex and multifaceted concept, and there are still many unknowns about its nature and mechanisms. Exploring various dimensions of intelligence beyond pattern recognition can contribute to a more comprehensive understanding.