Over the past 60 years, starting with the original Turing Test, people have kept setting up tests that would show us computers were truly intelligent, but then when some computer passes the test, nobody cares. After going over a bunch of these, Siskind writes:
Now we hardly dare suggest milestones like these anymore. Maybe if an AI can write a publishable scientific paper all on its own? But Sakana can write crappy not-quite-publishable papers. And surely in a few years it will get a little better, and one of its products will sneak over a real journal’s publication threshold, and nobody will be convinced of anything. If an AI can invent a new technology? Someone will train AI on past technologies, have it generate a million new ideas, have some kind of filter that selects them, and produce a slightly better jet engine, and everyone will say this is meaningless. If the same AI can do poetry and chess and math and music at the same time? I think this might have already happened, I can’t even keep track.
So what? Here are some possibilities:
First, maybe we’ve learned that it’s unexpectedly easy to mimic intelligence without having it. This seems closest to ELIZA, which was obviously a cheap trick.
Second, maybe we’ve learned that our ego is so fragile that we’ll always refuse to accord intelligence to mere machines.
Third, maybe we’ve learned that “intelligence” is a meaningless concept, always enacted on levels that don’t themselves seem intelligent. Once we pull away the veil and learn what’s going on, it always looks like search, statistics, or pattern matching. The only difference is between intelligences we understand deeply (which seem boring) and intelligences we don’t understand enough to grasp the tricks (which seem like magical Actual Intelligence).
I endorse all three of these. The micro level - a single advance considered in isolation - tends to feel more like a cheap trick. The macro level, where you look at many advances together and see all the impressive things they can do, tends to feel more like culpable moving of goalposts. And when I think about the whole arc as soberly as I can, I suspect it’s the last one, where we’ve deconstructed “intelligence” into unintelligent parts.
I am most interested in the last one. As a materialist, I do not think there is anything magical about intelligence. It must arise from physical/electrical/chemical stuff going on in our brains. It must, therefore, be simulatable with a big enough computer. And whenever we do understand something our brains are doing, it turns out that there are a lot of subroutines doing fairly simple things that add up to something bigger.
The higher mental activity that I have thought the most about is of course writing. I have a strong sense that the words I type out when I am trying to write fast are emerging from multiple subsystems, one of which does exactly what LLMs do: predicting the next word from those that come before. I am one of the writers whose prose appears in my brain as a rhythm of sounds before the words form, after which some other module chooses words that fit the rhythm but convey the meaning; what brings me to a halt is when the modules clash. At that point, some more conscious module has to intervene to sort things out. This feels amazing when it happens right, words just pouring out of me, but I never have any sense that they are emerging from a deep and true soul. I have a module that remembers how millions of sentences from thousands of books go, and it takes elements from that training data to fit the story I am trying to tell. To the extent that this works well, it is pretty close to automatic.
Apparently when writers take questions from the public, the most common one is, "Where do you get your ideas?" I find this utterly unmysterious. Like an LLM, writers have a huge set of training data: other stories, their own lives, things they have read about in the news. If you went through the average long novel with enough knowledge of the writer's life and a big enough computer you could probably trace the source of every element. The secret to "creativity" is 1) know a diverse set of things, and 2) combine them in interesting ways. I find that this is particularly true when writers are trying to be intensely personal, as in their memoirs; there is nothing in the average memoir that has not been in a hundreds memoirs already.
LLMs can mimic much human behavior because there is nothing magical about what humans do.
2 comments:
The thing is, "data" and "experience" are not the same. Neither are "words" and "concepts".
"Language learning models" are simply predictive models that predict what the next word in a sentence might be. The only way they "learn" is by randomly piecing together words they doesn't actually understand, and then comparing the results with sentences created by humans (which they also don't understand), and seeing how close of a match was made, and discarding the result if it doesn't meet a certain threshold.
You might argue that people learn via a similar mechanism, trying a word where it doesn't belong, and being corrected - but you'd be discounting the conceptual element, and the meanings that people understand attach to different words, and the human ability (even at incredibly young ages) to intuit meanings on their own and be correct a shocking amount of the time, without having to try every possible permutation of usage.
A toddler doesn't learn by using every word they know in sequence, and rejecting millions of attempts based on being told by an outside source that they were wrong. They do an awful lot of intuiting, and an awful lot of contextual judgement. If a child hears a word said, even when it's not directed toward them, they don't just add it to a list of words to randomly try in random situations - they recognize that the word got said in a certain context, and has some kind of meaning associated with that context, and they puzzle it over and apply reasoning to it (even if sometimes flawed reasoning), and come to a decision on how to use it, and then try it out to confirm. It doesn't take a kid a million attempts to learn what a word means - a lot of the time, they can figure it out in about two or three, which is astonishing if you stop to think about it.
If computers had to "learn" via trial and error at the speed that we humans are able to conduct trial and error, we'd say they have no intelligence whatsoever, because they'd be producing completely wrong answers all the time.
But the bigger issue is that computers don't have any ability to intuit anything, or any ability to decide anything for themselves (even wrongly). They are logic gates, processing binary code, carrying out their programming. They don't have a conception of reality, because they don't experience reality. They have no senses with which to experience the world. They don't have bodies that exist in three dimensions with which to interact with physicality. They don't have billions of neurons collecting data about the environment. They don't know what "hot" is, or what "up" is, or what anything else is, because they haven't experienced anything. They don't "think", they just perform functions that sometimes produce results which can mimic human behaviors deceptively.
But deceiving people is not that hard. In fact, it's not the machine doing the deceiving - it's us, deceiving ourselves. Remember, humans will frequently apologize if they accidentally walk into a trash can. We have a very powerful drive to anthropomorphize even the most unliving of things, to say nothing of unintelligent. We look at plumbing fixtures on a bathroom sink and think, "Heh - it's a silly face!". We're easy to fool.
G. Veloren's observation about children is on point. My 3 year old grandson, since he began to talk, regularly repeats what someone has just said to him, as though he's committing it to memory in his word bank. And his communication is clear, his vocabulary varied, and his sentence structure already demonstrating skill in constructing compound and complex sentences. (This last is partially explained by the conversations of his nearest adults, all of whom have facility in using language... I'm a retired English teacher, and my daughter has always been an avid reader and in her own work as a designer of training materials must be conscious of communication skills)
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