…But I’ve also had it clearly tell me in an answer that 2 is an odd number.
This is because it is an excellent language translator and it is trained on the principles of “call & response”
I think what's interesting is that many types of creativity may really just be re-synthesizing "stuff we already know."
So a lot of the negative comments along the lines of, "it can't be creative because it never thinks of anything beyond its training data" don't click with me. I think synthesizing two existing concepts into some third thing is actually a form of creativity.
These nets may not learn the same way we do exactly, and they may not possess the same creative abilities as us — but there's definitely something interesting going on. I for one am taking a Beginner's Mind view of it all. It's pretty fascinating.
I would stop that kind of evolution, as it can be catastrophic, but I know that humanity is not able to stop itself from evolving further.
An 18 year old will have been training for ~160,000 hours on a volume of raw data that is probably far beyond our ability to currently store let alone train an AI with.
As far as training for a specific task, all that training on other matters kicks in to help the human learn or accomplish a “novel” task more rapidly, for example, knowing how to read and interpret the instructions for that task, knowing how to move your appendages and the expected consequences of your physical interactions with a material object. You’re certainly not taking a fetus with a blank slate and getting it to accomplish much at all.
If you are also saying AIs will be a more intelligent species, able to adapt better on Earth than humans, that requires extraordinary evidence. A human could solve complex problems no other species it machine can solve on nothing more than a handful of rice for a week. Where is the similar scale species/machine?
And even then for proper agi it would need to close the loop after inducing an hypothesis with testing.
Meatbags are going to be useful for a while still.
It can translate code from one language to another. Code that it has never seen before. Or between natural language and programming language.
It's certainly not perfect but it is reasoning all right
Its funny how many people will immediately poke holes in it for software development, but two years ago I could not imagine an AI could write code like chatgpt is doing now.
As shown by this post, we're still discovering what's possible with the tools we have now.
Also, human programmers aren't amazing at writing defect free code.
On that thought, does anyone even still use Copilot?
The AI can output a lot of text but can you input a 100000 line code base into it? No you can't. You can't even input 50 lines of code that is already in the data set!
And by failure I mean somethin akin to a blue screen and not that the output was wrong, there was no output!
This is obviously true, and yet we've invented so many things. From the wheel, to control of fire, to farming and animal husbandry, to mathematics, to metallurgy, to physics, to semiconductors, etc.
The interesting question is, was the invention of all those things simply the re-synthesis of "stuff we already know?" If the answer is yes, doesn't that mean we're now on the cusp of a something akin to a singularity? We can now synthesize nearly-unlimited streams of coherent human thought. If we had a way of differentiating the wheat from the chaff, we could analyze what would have been millennia of human output in the proverbial blink of an eye. If human knowledge is just "stuff we already know", then we better buckle up. It's about to be a wild ride.
This is the key to AGI. We need verification systems, they can be a code execution environment, a database of facts, a math symbolic engine, a physical simulation, a game, or real world lab experiments. These verifiers will produce signal that can be used by the language models to improve. The cheaper and faster verification is, the faster we can iterate. Generating ideas is cheap, proof matters.
Just remember AlphaZero a bit - it started from scratch, playing against itself, in a few hours it surpassed human level. Go simulation and verification is trivial. The board is just a matrix. So learning from massive search and verification is a proven path to super-human level.
Here is a related paper:
> Evolution through Large Models
And the space is combinatorial. Most of it is unexplored. It is creativity, but also a form of search.
If you think about it the most creative is random noise. then you apply rules it it to constrain the noise or limit the predictions. And add more rules in layers. so getting the system to produce more creativity is just relaxing the rules at different layers.
Really? This seems like a straw man - I've only seen gobs and gobs of examples showing all the amazing things ChatGPT can do. I have seen some measured comments from real experts helping to explain how ChatGPT works behind the scenes, and this is usually to temper sentiments when folks start going down the "It's sentient!!" route.
This was a lengthy poem that went into the finer details of quantum physics, and it all read as decent poetry.
It might not be "Shakespere" exactly, but it knew in general what I was looking for.
It's also impressive to me that this isn't information that is scraped off some website, like Google. It's actually generating this stuff in real-time and it may have never been seen before, anywhere, ever. That is far beyond anything I've ever encountered.
If it's a lesser form of intelligence, as you imply, then I almost find the results more impressive.
Different != lesser
> Probably, but
Then why even continue speaking if you agree
> our concepts seem to be tied pretty closely to language.
Me: “ChatGPT, explain how an electron orbiting a hydrogen nucleus would behave if classical mechanics held true.”
ChatGPT: “In classical electromagnetism, an electron orbiting a hydrogen nucleus would behave in a similar way to the way a planet orbits the sun, as described in my previous response. The electron would follow an elliptical path around the nucleus, and the force of attraction between the electron and the nucleus would be given by Coulomb's Law.
According to Coulomb's Law, the force of attraction between two charged particles is given by:
F = k * (q1 * q2) / r^2
Where F is the force of attraction, k is the Coulomb constant, q1 and q2 are the charges of the two particles, and r is the distance between them.
In the case of an electron orbiting a hydrogen nucleus, the force of attraction would be the force that keeps the electron in orbit. The electron would be attracted towards the nucleus by this force, but at the same time, it would be moving with a certain velocity, which would cause it to follow a curved path. This path would be an elliptical orbit, with the nucleus at one of the foci of the ellipse.
The electron's orbit would be stable as long as the force of attraction between the electron and the nucleus was strong enough to keep the electron in orbit, but not so strong that it pulled the electron into the nucleus. This balance would be determined by the size of the ellipse and the velocity of the electron. If the ellipse were too small, the electron would be pulled into the nucleus. If the ellipse were too large, the electron would escape from the orbit.
However, we know that this is not actually how an electron behaves in an atom. In reality, electrons do not follow classical orbits around the nucleus. Instead, they follow a more complex pattern described by quantum mechanics. This is because the principles of quantum mechanics are needed to accurately describe the behavior of very small particles like electrons.”
On the surface this looks impressive. Except that the answer about stable orbits is flat out wrong. The electron would spiral into the nucleus, quite quickly, because of Maxwell’s equations: a moving electron radiates electromagnetic energy. This is part of the foundational defense of quantum mechanics. If as you claim, language and concept are so closely tied, surely a language model with billions (trillions?) of parameters is capable of encoding a relational understanding of this magnitude.
https://physics.stackexchange.com/questions/413039/electron-...
> If it’s a lesser form of intelligence I almost find the results more impressive.
You get that you’re saying the least common denominator in conversational intelligence makes you go bzzzzz? That the one thing ChatGPT lacks, critical thinking, does not impress you?
You know, in the 90s, they had these things called tamagotchis… you might be interested.
People keep saying ChatGPT isn't that impressive because it's just "regurgitating knowledge" and has no insight into it, or things along those lines. But I find it insanely impressive that you can specify something like:
"Provide your answer in JSON form. Reply with only the answer in JSON form and include no other commentary."
And it will do exactly that. Or tell it to explain you something "in the style of Shakespere".
I just asked it about quantum physics as Shakespere and got this (plus a lot more):
---
Oh sweet youth, listen closely as I impart
The secrets of the quantum realm, a place of art
Where particles and waves, both small and large
Exist in states both definite and in charge
---
That is really fascinating stuff.