Contrast with real creativity (what people can do but machines currently cannot) where you conjecture something completely new.
For example, Copernicus conjecturing the idea that the Earth revolves around the Sun. No machine learning model would have gotten there because it would have been trained on a bunch of data that said the Earth was the center of the universe.
The image is new, it did not previously exist. It is a creation, a very vague idea of a few words that was created in full realization.
So it sees like the only difference between the "Not creativity" that Dall-E is doing and "Real Creativity" that humans do is tht humans are the ones doing it?
I agree there's this concept of expanding the frontiers of human aesthetic capability that has slow-marched from cave paintings till post-modernism. That there are a very few artists that invent completely new styles that the rest of us copy and remix. It's questionable that Dall-E can do that, but I'm also not sure that it can't do that.
The differentiator is whether the result is worthy to look at for humans, that's all.
In case of the OP, you forget that the human had to predict that the combination of two would be interesting for other humans, and then construct the prompt, possibly selecting the best pictures. That's who did most of the work here, and it was effortless for the neural network of a human. Could DALL-E analyze the world autonomously without human intervention at all? No, it's an open loop system.
Novelty hinges on the ability to conceptualize things, not the execution. Sure, DALL-E 2 shows a glimpse of conceptualization internally as it works with compressed descriptions (concepts, abstractions) of things it draws. But it's super limited and not flexible enough to create new ideas, it doesn't have either short-term or long-term memory, it doesn't change, it has all knowledge about Kermit and Blade Runner pre-baked, and so on. You have to re-train it from scratch every time you want it to remember something truly new, there's no feedback loop to do that. Human ability is still much more powerful.
DALL-E 2 is almost at the point where it can supplement the human conceptualization with AI execution, though. Possibly in a couple iterations it will be there, with more believable results. In very limited cases, of course - as it's temporally unstable (it makes a totally new image each time), cannot correct the output from new details provided by a human (like a professional concept artist could), etc.
If the Twitter user claimed that the text prompts themselves were generated by asking GPT-3 for "An interesting sequence of text prompts to feed an image generation AI" or something like that, I would have believed them.
Presumptively, I imagine it's harder to create a model that generates images matching a certain human-language input prompt than to create an image generation model with no language component and have it pick its own scenarios internally. I don't think the former is done to palm off "most of the work" to humans, but rather because people want an easy way to see create own ideas so there's more demand for it.
> You have to re-train it from scratch every time you want it to remember something truly new, there's no feedback loop to do that.
As far as I'm aware, this isn't true. Deep learning is perfectly compatible with fine-tuning an existing model using new data. OpenAI/MS have been doing this with Codex to improve it based on Copilot telemetry and code from new languages/libraries.
Copernicus got his idea after gathering a lot of data, explicitly and implicitly, training his internal model of the world.
I fail to see what the difference is between 99% of existing "creativity," which is essentially arranging existing ideas into novel combinations, and what DALLE2 does.
Creativity is a very vague word, I'm sure we can come up with definitions of it that let humans keep sole domain over it. But breakthroughs often come from combining domains and concepts, very very rarely do we ever jump out of one local maxima into another, and I'm not even convinced that Copernicus counts as that. There's a reason why there are so many examples of the same breakthrough happening in multiple places in the world independently - innovation is a slow gradual collaborative process and not plateaus waiting for men of genius to have a spark of inspiration.
Also I'm not convinced that a computer couldn't have discovered the earth revolves around the sun - it's hard to make machine learning jump out of local maxima, but it does happen, and I can see some hidden layers becoming far more efficient at predicting outcomes by stumbling across a model that centered the sun. That being said - there likely are examples of things that computers couldn't have theoretically figured out the model for, but I'm hard pressed to think of one.
Call it moving goalposts, no true Scottsman, the AI effect, whatever. The behavior is as follows: an argument over whether an ill-defined attribute is possessed by a computer is defended or attacked with useless semantics since nobody can agree on what any of the words mean anyway.
Creativity, intelligence, consciousness.
It doesn't matter what you say, you cannot define these concepts with the same clarity you use to defend that the concept is missing.
Saying there is no creativity because its just a neural net extrapolating from data is like saying there's no god because its all just atoms: what is god and why would the existence of atoms have anything to do with it.
Learn from Wittgenstein: Worüber man nicht sprechen kann, darüber muss man schweigen.
The quote is a judgement about what can be logically achieved through discourse, and what cannot (and should not). He draws this boundary to separate the things we can reason about and the things that fall beyond reason and so cannot be reasoned about at all. If you cannot reason about something, you should not bring it up in (philosophical) discourse.
He does this to settle philosophical debates around, for instance, mystical subjects that were fought over to exist or not exist. The conclusion for him is: we do not have the logical tools and concepts to reason about the problem, so we should stop wasting time talking about it.
It's not about lack of knowledge or intelligence, its about acknowledging the limits of reason and discourse, and forgoing any conclusions made beyond those limits. It's a pursuit of truth.
At least, this is how I understand it, I'm not a philosopher.
But there is nothing about understanding the difference between human and machine intelligence that is forbidden by any reason or logic that I am aware of.
Certainly there is a lot we don’t know about that topic. But unless that knowledge is specifically blocked by logic or the laws of physics, it is knowable. The only thing missing is the knowledge required to understand it.
The only source of knowledge is conjecture and criticism, and discussion with others is a great tool for that process. The more the better.
So unless you believe we know all there is to know about a topic right now, there is always the possibility that some new knowledge could help us get closer to the objective truth about it. And it’s guaranteed that new knowledge will come from creative new ideas and criticism of existing ideas.
Saying something is unknowable is akin to believing in a mysterious god creator, or fairies. But more importantly, it is a way to stop or limit the progress of our understanding of the universe. It’s like when parents say “because I said so”. It shuts down discourse and understanding and leads to closed societies.
Again, the quote is not about avoiding or ignoring valid logical discourse, criticism, hypotheses, or any other logically coherent verbalization. The quote says that if the words are ambiguous, don't use them in logical arguments. Meaningless here does not mean hypothetical or conjectural or wrong, but simply ill-defined. This interpretation leaves plenty of room for everything you have described and are afraid would be criticized by the quote.
So, to get back to why I brought it up: creativity is an ill-defined concept in the context of logical reasoning, and so should not be used in logical reasoning as if it was an attribute that we can empirically or theoretically judge any entity to be in possession of.
This is why all replies to the above comment get lost in semantics: what is creativity? This is ill-defined, and hence based on your personal preference you may arrive freely at any conclusion you wish. Hence using the word "creativity" during a logical argument or truthful statement is guaranteed to produce conflict when multiple interpreters are present. Multiple logical interpreters can never be in conflict about purely logical reasoning, this is why we can have math.
Again, this is NOT saying that anything is unknowable, it is simply saying that whatever creativity is, or is composed of, is not clearly defined. This means it cannot be knowable or unknowable until it is clearly defined, and specifically only if done so in a rigorous enough definition to use it during reasoning.
To get back to your last point: doing what I described above is specifically to further the progress of our understanding of the universe, and specifically to attain new knowledge and understanding, because it cuts down on the discourse that does not contribute to that goal. It's the difference between arguing about whether machines have creativity and building DALL-E.
I am 100% sure Copernicus was not the first to suggest a heliocentric system, but he was the one who put enough energy into proving it and defend that theory.
Such a cute point of view, completely wrong but cute. Please go find the original images of Kermit in Blade Runner and WallE that were just copied here.
>For example, Copernicus conjecturing the idea that the Earth revolves around the Sun. No machine learning model would have gotten there because it would have been trained on a bunch of data that said the Earth was the center of the universe.
If the model were trained on actual observations of planetary trajectories it would trivially recreate keplers laws, newtons laws etc.
I never said copying existing images, I said it’s using what already exists for inspiration. That is not the same as creativity.
I want to see what Dall-E comes up with when you ask it to create something new. Maybe “a new type of animal” or “an apartment building made to withstand radiation”. Basically anything that it can’t use existing images and ideas to create. Hell, I’d like to see someone ask GPT-3 for a prompt that Dall-E would fail at and pit them against each other.
The point is a human could come up with those trivially. I think this system would struggle. Because it’s not capable of creating anything new, only combining things that already exist.
This is the flaw in your thinking. Humans are doing the same thing, I don't know why some people think the brain is so magical. We live in a materialist reality and to think the brain is anything other than a complex computer is farcical.
Should be easy to prove.
"Renner stresses that although the algorithm derived the formulae, a human eye is needed to interpret the equations and understand how they relate to the movement of planets around the Sun."