Let’s not conflate knowledge with intelligence though. GPT-4 simply isn’t intelligent.
"Here is a random string of 32 characters:
a8Jk5pYr0Dm9Nc1Vz8Qf2Bt6Hg3Lw4Uo"
I’ve tested this with a wide variety of number inputs and it’s performance is highly variable. Error also increases linearly with strong length.
does a 4 year old have intelligence?
Logic, arithmetics, algebra, precisely following steps of an algorithm - those are not skills one "kinda" just "gets" at some point, they're trained by deliberate practice, by solving lots and lots of problems specifically constructed to exercise those skills.
Point being, get GPT-4 through school, and then compare with adult performance on math-adjacent tasks. Or at least give it a chance by prompting it to solve it step-by-step as a problem, so it can search closer to the slice of latent space that encodes for relevant examples of similar problems and methods of solving them.
Anecdote: admittedly, I'm autistic as are the people I know, so maybe that's not a good sample. I struggle with a lot of basic shit even as an adult. Oh god, I empathize with the hypothetical GPT5.
GPT4 will produce stuff, but only if prodded to do so by a human.
I recently asked it to help me write some code for a Garmin smartwatch. The language used for this is MonkeyC, of which there isn't a huge amount of examples on the internet.
It confidently provided me with code, but it was terrible. There were gaps with comments suggesting what it should do, bugs, function calls that didn't exist, and many other problems.
I pointed out the issues and GPT4 kept apologising and trying new stuff, but without any improvement. There wasn't any intelligence there; the model had just intuited what a program might look like from sparse data, and then kept doing the same thing. It didn't know what it was doing; it just took directions from me. It couldn't suggest ideas when it couldn't map to a concept in memory.
A human with an IQ of 80 would know if they didn't know how to code in MonkeyC. If they thought they did, they'd soon adjust their behaviour when they realised they couldn't. They'd know where the limit of their knowledge was. They wouldn't keep trying to guess what functions were available. If they didn't have any examples in memory of what the functions might be like, they might come up with novel workarounds, or they'd appreciate what program I was trying to write and suggest a different approach.
Presumably we'll make progress on this at some point, but I think it'll take new breakthroughs, not just throwing more parameters at existing models.
What makes it even more frustrating is to iterate, you constantly have to keep it updated with any changes you made outside of chatgpt.
Don't get me wrong, it's pretty useful but it is far from a silver bullet. Getting that last 20% (or even 30%) is going to be a lot of work...
What does a phrase like "GPT-4 scores 90th percentile on the Uniform Bar Exam" mean to you, regarding whether humans can easily surpass its knowledge and reasoning?
https://www.forbes.com/sites/johnkoetsier/2023/03/14/gpt-4-b...
Absolutely nothing, because of construct validity. Those tests measure things that have shown to correlate with abilities of concern in humans, and so are, for their purposes, valid for humans.
This hasn’t been demonstrated for LLMs, and the assumption that construct validity can be assumed without being established is begging the question: it is presuming not only that LLMs are general intelligences, but thaf they are general intelligences structurally similar to human intelligences such that the proxy measures for cognitive capacities work similarly.
I suppose, when GPT-4 writes correctly working code that does what you want on the first try, this says absolutely nothing about its cognitive capacity, because, after all, it's just a proxy measurement for the underlying generative process. (Yes, obviously the cognition is _different_ from what happens in humans. That does not mean that... it isn't intelligence?)
It says something about its ability to write code. Beyond that... its impossible to say.
We simply don’t have the information about generative AI models to be able to generalize from limited proxies about them; psychometry is not transferrable from humans to them — or at least, we have neither evidence nor a strong theoretical reason to think it should be.
The intelligence of something is inconsequential. What truly matters is its ability to convincingly imitate intelligence.
In that sense, because we are making progress on producing an indistinguishable imitation... you might as well say we are making progress on an actual sentient intelligence.
….
in my 42 years on this planet I don't think i've made any novel discoveries.