22 ms·

Is DALL-E 2 ‘gluing things together’ without understanding their relationships?

224 points by Hard_Space 4y ago

andybak 4y ago
I'm a big Dall-E fan but this is no surprise to anyone who's used it for more than 5 minutes. It was one of the things highlighted by Google when they announced Imagen as a differentiator: https://imagen.research.google https://imagen.research.google The article touches on this but the headline is slightly deceptive.
- causi 4y ago
  Imagen would be amazing for an "Images Against Humanity" game where you score points by generating the funniest picture.
  - Zircom 4y ago
    Absolutely stealing this idea, look forward to being credited for the idea in the future show hn post :P
- andybak 4y ago
  (Incidentally - I want to make it clear I don't mean "Dall-E has no understanding of the elements and it's just a fancy image search/compositor" - there are results that absolutely require some semantic "understanding". It's just there are limits and spatial understanding is one of the weak spots)
vannevar 4y ago
I'm sure it is, but "gluing things together" coherently in response to a text prompt is a stupendous achievement. It's not AGI, but it's miles ahead of where we were even a few years ago and opens the door to automating a class of jobs I don't think anyone back then believed could be automated, short of AGI.
- danielmorozoff 4y ago
  Where do you see DALLE automating away jobs?
  - robertlagrant 4y ago
    There was a post on here recently on how someone designed their logo by asking DALL-E a load of questions. The rationale could be that it might not remove that job, but it would certainly be a powerful tool for a logo designer to take on way more clients, thus driving down the cost of logo design.
    - odessacubbage 4y ago
      i feel like this boils down to a client-side misunderstanding of where graphic designers actually spend the majority of their time. i'd actually argue that working from spec or even a crude doodle on the back of a napkin is a lot easier than dealing with a client who is married to a poor design that DALL-E puked out for them. one of the most important things about the sketch phase is to be able to iterate without too many assumptions while also being able to recognize and play upon the strengths of individual drawings. this is not a time consuming process but it also isn't something you want to rush anymore so than you'd want to rush the plastic surgeon performing your nose job. depersonalizing the design process in favor of volume does not particularly serve anyone and, moreover, it responds to a need that i don't really think exists. this is not to say that i don't think these kinds of image generators are without uses, but right now we are still in the phase where people are being impressed by graphical fidelity[which was already incredibly cheap] rather than usefulness. imo this stage of ai will primarily work well for tasks that benefit from randomness while also being relatively low stake in the overall production pipeline. training a network to generate typefaces or to randomize npc portraits for an open world game is precisely the sort of area where 'gluing things together' can potentially provide more benefits than headaches.
      - robertlagrant 4y ago
        I was saying a designer could use it for first draft ideas, not their client.
BiteCode_dev 4y ago
Amusingly, I get creative new ideas when I glue things together and ignore what I thought I understood about their relationships.
- TremendousJudge 4y ago
  Happens to me too -- it's a great way to make new things. However, the "creation" I'd argue happens when you look at the pile of random stuff and generate a new understanding, and decide that it is valuable. The difference between trash and art only exists in the head of the artist. Same thing happens with DALL-E output, really.
pera 4y ago
Interesting, DALL-E Mini / Craiyon actually generates a pretty accurate result for "a monkey touching an iguana" (at least semantically): https://i.imgur.com/Oq62gQI.png https://i.imgur.com/Oq62gQI.png
- affgrff2 4y ago
  Maybe it's in the training data? At least some special kind of monkey (human) touching some lizard is.
  - johndough 4y ago
    https://rom1504.github.io/clip-retrieval/?index=laion5B&useMclip=false&query=monkey+touching+iguana&back=https%3A%2F%2Fknn5.laion.ai https://rom1504.github.io/clip-retrieval/?index=laion5B&useM... There seem to exist several pictures of marmoset monkeys touching iguanas, but DALL-E mini shows macaque monkeys. This makes me believe that DALL-E mini has at least some generalization capabilities.
- walrus01 4y ago
  imgur is providing a prompt before viewing this image "this image may contain erotic imagery, are you over 18, etc". i certainly hope not...
IceMetalPunk 4y ago
Now, let's be critical of possible reasons for this. It's important to remember two things: 1) Any NN has zero experience with the world beyond its training data. Things that seem obvious to us from our experience are not obvious to a system that has never experienced those things. And 2) DALL-E 2 was trained on image-caption pairs scraped from the internet, basically. So it's quite possible the reason it doesn't understand things like "X under Y" very well is that its training set doesn't have a lot of captions describing positional information like that, as opposed to any failure in the architecture to even potentially understand these things.
burlesona 4y ago
Slight side tangent but reading this article it hit me how much this generation of work may be reinforcing English as the global language for generations to come. It seems like we are headed towards a phase of technology where learning how to feed well-crafted prompts into the AI system will be a highly valuable productivity skill. And since the major AI systems seem to be built around English, that would make English fluency even more valuable than it already is. I’m sure that’s obvious to non-native speakers who have worked hard to master English, I just hadn’t thought of it before. Less likely but still interesting, I wonder if the way we’re building these models will at some point begin to layer on top of each other such that English as it is used now becomes something deeply embedded in AI, and whether that will evolve with the spoken language or not. It’s funny to imagine a future where people would need to master an archaic flavor of English to get the best results working with their AI helpers.
- affgrff2 4y ago
  But the same work is also removing the language barriers at the same time with really good translation tools. I rather guess being fluent in English will be not as important as it is now. Edit: the same work = transformer based language models
- mtlmtlmtlmtl 4y ago
  Also worth noting that the internet has massively accelerated the importance of English already. As an ESL speaker who grew up on the internet, Norwegian was more or less useless to me outside school and family. Most of my time was spent on the internet, reading and writing lots of English. Norwegian wikipedia is pretty much useless unless you don't know English. That's still true today for the vast majority of articles, but back then was universally the case. There were Norwegian forums, but with a population of just 4 million and change at the time, they were never as interesting or active as international/American forums and IRC channels. In fact I'd say Norwegian is only my native language in spoken form, whereas English feels more natural to me to write and read. Doesn't help that Norwegian has two very divergent written forms, either. I even write my private notes in English, even though I will be the only one reading them.
- Ajedi32 4y ago
QuadmasterXLII 4y ago
My intuition is that DALL-E is more a demonstration of how hard image synthesis is for humans, than how intelligent the algorithm is. The image generation models have orders of magnitude fewer parameters than the large language models.
adamsmith143 4y ago
Why is there this obsession with systems or algorithms having "understanding"? No one thinks these things have internal states equivalent to "understanding". "Understanding" or not you can't deny the capability of these systems.
chpatrick 4y ago
I think "understanding" is a super vague word.
- i_am_toaster 4y ago
  Bingo. This is also a fair comparison to how todays politics works in a nutshell. Overload a word with a vague context and people immediately attribute their own perspective to come to a conclusion that conflicts with an opposing argument. Relating back to this headline, using “understanding” creates lots of messages with differing views because everyone has their own take on the word. If instead you said something like, “DALLE fakes understanding of concepts to create new images,” I bet you’d get even closer to the “political message board” style of comments because you are now taking an objective position (yes/no,true/false,good/bad) on a subjective word (understanding).
IIAOPSW 4y ago
I have a phrase I'd like to coin in contrast to AI. "Artificial Bullshit". AB. I of course mean "bullshit" in the highly technical sense defined by Frankfurt [1]. The defining feature that separates a bullshitter from a liar is that a liar knows and understands the truth and intentionally misrepresents the matters of fact to further their aims, whereas a bullshitter is wholly unconcerned with the truth of the matters they are discussing and is only interested in the social game aspect of the conversation. Bullshit is far more insidious than a lie, for bullshit can (and often does) turn out to be coincident with the truth. When that happens the bullshitter goes undetected and is free to infect our understanding with more bullshit made up on the spot. DallE generates the images it thinks you want to see. It is wholly unconcerned with the actual objects rendered that are the ostensible focus of the prompt. In other words, its bullshitting you. It was only trained on how to get your approval, not to understand the mechanics of the world it is drawing. In other words, we've trained a machine to have daddy issues. A profoundly interesting question (to me) is if there's a way to rig a system of "social game reasoning" into ordinary logical reasoning. Can we construct a Turing Tarpit out of a reasoning system with no true/false semantics, a system only designed to model people liking/disliking what you say? If the answer is yes, then maybe a system like Dalle will unexpectedly gain real understanding of what it is drawing. If not, systems like Dalle will always be Artificial Bullshit. [1] http://www2.csudh.edu/ccauthen/576f12/frankfurt__harry_-_on_bullshit.pdf http://www2.csudh.edu/ccauthen/576f12/frankfurt__harry_-_on_...
- deleted 4y ago
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- leereeves 4y ago
  > It is wholly unconcerned with the actual objects rendered that are the ostensible focus of the prompt. I disagree. To the extent that the training data are images of actual objects, recreating images of actual objects is the only thing DALL-E cares about. If we define "caring" about something as changing behavior to cause that to happen, then a neural network doesn't "care" about inference at all, because inference never changes the network's behavior. It also doesn't know or care about your approval. It only cares about minimizing the loss function. (But now that you bring this up, I think it would be really interesting to create a network that, after training initially on training data, began interacting with people and continued training to maximize approval.)
simion314 4y ago
There were so many articles about this project, but I can't find a demo page to test 3,4 outputs myself (unless it was some page I already tried when it was linked and I got nothing similar with what is shown on main page)
___rubidium___ 4y ago
Fascinating. I've noticed the same problem with Midjourney and Nightcafé as well.
can16358p 4y ago
Regardless of the content, the article has been "published 10 seconds ago" for the last few minutes, and has been submitted to HN 1 hour ago.
dukeofdoom 4y ago
Using midjourney, I'm fascinated with the geometric shapes it comes with. Just yesterday I was looking at a sort of a hexagon made with intersecting hearts. Not only was it aesthetically pleasing, it was such an unusual composition, that I think it would be extremely hard for an artist to come up with, maybe even a mathematician. So I think it's already capable of doing more sophisticated things than human artists.
- Cognitron 4y ago
  MidJourney is really good at creating abstract images. I’ve been playing with the multi-prompt syntax (::) a lot lately, just combining different words that evoke form or texture to see what it will come up with. I start by testing things one at a time and just take a guess at what might look cool together. I end up making strange images with prompts like “fractal :: stained glass :: feathers”, “antelope canyon :: tattered fabric :: cave”, “rubik’s cube :: Japanese woodblock”, you get the idea. I rarely try to make pictures of real things anymore. Definitely fun to play around with.
  - dukeofdoom 4y ago
    I'm pretty new to it. Any tips on making retro pixel art assets. I want a stone or brick wall I could tile into a game I'm making.
    - Cognitron 4y ago
      I think most of us are pretty new to it since they just opened the beta to a ton of people. I haven't tried to do anything like that with it though. All I can say is it tends to take a lot of experimentation to get what you want. And you'll probably have to do some work to the images to get them to tile seamlessly. If you can't get the pixelated look quite how you want it, you might try using it to generate a base image and then use a separate tool to pixelate it. Some people are using it as part of a larger pipeline. The discord is full of people sharing their experiments and approaches though. Maybe try asking in the prompt-craft channel to see if someone else has attempted something similar. Good luck!
KingOfCoders 4y ago
That's called creativity.
avalys 4y ago
I think DALL-E is clearly just gluing things together that it found in a massive dataset, and doesn't have any understanding of the underlying concepts. I thought it was easy to see the signs of this in examining its output. Same for GPT-3. However, what's amazing about DALL-E and these other statistical, generative models to me is that it's made me think about how much of my daily thought processes are actually just gluing things together from some kind of fuzzy statistical model in my head. When I see an acquaintance on the street, I don't carefully consider and "think" about what to say to them. I just blurt something out from some database of stock greetings in my head - which are probably based on and weighted by how people have reacted in the past, what my own friends have used similar greetings, and what "cool" people say in TV and other media in similar circumstances. "Hey man how's it going?" If I was asked to draw an airplane, I don't "think" about what an airplane looks like from first principles - I can just synthesize one in my head and start drawing. There are tons of daily activities like this that we do like this that don't involve anything I'd call "intelligent thought." I have several relatives that, in the realm of political thought, don't seem to have anything more in their head than a GPT-3 models trained on Fox News (that, just like GPT-3, can't detect any logical contradictions between sentences). DALL-E has convinced me that even current deep learning models are probably very close to replicating the performance of a significant part of my brain. Not the most important part or the most "human" part, perhaps. But I don't see any major conceptual roadblock between that part and what we call conscious, intelligent thought. Just many more layers of connectivity, abstraction, and training data. Before DALL-E I didn't believe that simply throwing more compute at the AGI problem would one day solve it. Now I do.
- dougmwne 4y ago
  I think our intelligence has 2 components, our conscious selves that are good at formal reasoning and meaning making, and a massive neural network that is good at statistical inference. I suspect the reason we need less training data for learning than dall-e is because our conscious selves can tease out the formal relationships and models, rather than relying purely on inference which requires enough datapoints.
- multibit 4y ago
  >I have several relatives that, in the realm of political thought, don't seem to have anything more in their head than a GPT-3 models trained on Fox News (that, just like GPT-3, can't detect any logical contradictions between sentences). If more people were to realize that we're all probably like this, trained on some particular dataset (like mainstream vs reactionary news/opinion), I wonder if that would lead to a kind of common peace and understanding, perhaps stemming only from a deep nihilism.
AbraKdabra 4y ago
I mean, if it is "gliung things together" is doing it pretty well...
boredumb 4y ago
GPT/DALL-E/etc... All of these models are of course gluing things together in some manner, but who cares? That's the point right? The AI pill i've taken is that you don't need AGI in order to make things that are useful for people and business. If you've ever ran a business and had to dive into creatives for blogs, SEO content, social media posts, etc then you spent an inordinate amount of time creating it or outsourced it and in both cases the final copy is NOT going to get you a literary prize any time soon but it is absolutely enough to inform potential customers, start ranking on google and start gaining social media clout. GPT will also not garner you a literary award but can absolutely get you quality copy that users, customers, google, facebook users will not be the wiser that you generated it with AI instead of paid a third party to hack it together for you. (https://neuralmates.com/ https://neuralmates.com/ I recently started putting together a web app to MVP this, and I hope to be able to integrate DALLE-2 soon to be able to start generating images for folks as well.)
- lancesells 4y ago
  This is the kind of response that turns me off on all of these amazing technologies. Blanketing the world with low-level content in the hopes to gain ranking and clout sounds awful. On the flip side I'm guessing we'll have some gpt-3/dall-e blocker extensions that help reduce some of it.
  - boredumb 4y ago
    Sure, but It's the reality of it. Also - you already live in this world but it's fueled by low cost copy writers and ghost accounts on fiver, I'd bet you are going to see the low water mark for content increase quite a bit in quality and volume over the next few years due to GPT3 being leagues better than the current state of content mills.
kemiller 4y ago
Anyone who has ever raised a small child will realize this is how kids learn too.
gizajob 4y ago
I recently used it to create a picture of "an analogue synthesizer made out of meat and gristle". I don't really know how you could glue these concepts together, because nothing in reality causes them to ever go together, but it did a great job anyway.
dezmou 4y ago
Another cool example is when you ask DALLE-E to make a "Jaguar XF", it does not really know if I talk about the car or the animal, yet it manage to blend the two together https://img-comment-fun.9cache.com/media/a6wG6Kq/aq04bGmR_700w_0.jpg https://img-comment-fun.9cache.com/media/a6wG6Kq/aq04bGmR_70...
thriftwy 4y ago
Maybe you could give DALL-E creativity lessons by finding such nonsense queries and adding creative interpretations of those into learning set.
aeturnum 4y ago
The Fair Witness was a job that Heinlein made up for Stranger in a Strange Land. Fair Witnesses were supposed to reliably report what they saw without judgement - including their subjective judgement in their report. The example exchange is: "Is that house over there brown?" "It is brown on this side." Dall-E (and other ML systems) feel like fair witnesses for our cultural milieu. They basically find a series of weighted connections between every phrase we've thought to write down or say about all images and can blend between those weights on the fly. By any assessment it's an amazing feat - as is the feat to view their own work and modify it (though ofc it's from their coordinate system so one does expect it would work). In one sense - asking if the machine "understands" is beside the point. It does not need to 'understand' to be impressive (or even what people claim when they're not talking to Vice media or something). In another sense, even among humans, "understanding" is both a contested term and a height that we all agree we don't all reach all of the time. One can use ideas very successfully for many things without "understanding" them. Sometimes people will, like, turn this around and claim that: because humans don't always understand ideas when they use them, we should say that ML algorithms are doing a kind of understanding. I don't buy it - the map is not the territory. How ML algorithms interact with semantics is wholly unlike how humans interact with them (even though the learning patterns show a lot of structural similarity). Maybe we are glimpsing a whole new kind of intelligence that humans cannot approach - an element of Turing Machine Sentience - but it seems clear to me that "understanding" in the Human Sentience way (whatever that means) is not part of it.
- Sakos 4y ago
  > In another sense, even among humans, "understanding" is both a contested term and a height that we all agree we don't all reach all of the time. One can use ideas very successfully for many things without "understanding" them. Only if you define "understanding" as an intellectual process instead of the existential process that is meant when we say "understanding" in the context of cognition and AI.
Marazan 4y ago
https://imgur.com/ggnm920 https://imgur.com/ggnm920 "a photo of 6 kittens sitting on a wooden floor. Each kitten is clearly visible. No weird stuff." Like, lets start with the fact that there are 7 of them (2 of the 4 images from the prompt had 7 kittens). Now lets continue on with how awful they look. It is startling the difference in image quality between DAlle-2 asked for a single subject vs DAlle-2 being asked for a group of stuff. And its obvious, if you know how the tech works, why this is the case.
rocgf 4y ago
Does anyone actually believe DALL-E "understands" what it's doing? For any reasonable definition of "understands", I assume most people would be skeptical. So if we go with that, then yes, it just glues things together without understanding their relationship. I'd just be tempted to say it doesn't really matter that it doesn't understand, except maybe for some philosophical questions. It's still incredible based on its output.
- LesZedCB 4y ago
  can we come up with a 'reasonable' definition of understands that isn't couched in human exceptionalism and could still apply to any computer model? i think dall-e understands, within the sensory domain it's trained from.
  - rocgf 4y ago
    I think DALL-E understands the same way an Excel sheet would understand SUM(B3:B6), obviously at a way larger scale and with a more complicated function. It's all just rather simple maths all the way down.
    - deleted 4y ago
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    - visarga 4y ago
      Not similar. The SUM() function was written by humans in a top-down fashion, DALL-E learned from the visual and textual data by a completely different process. DALL-E distilled something about the world and is using that to generate.
- visarga 4y ago
  > Does anyone actually believe DALL E "understands" what it's doing? I believe it understands enough to make tens of thousands of people interested and debating its merits. The GANs of 5 years ago were baby toys compared to DALL-E. They were drawing 5 legs to a dog and limited to a few object classes. Now people debate if it "really understands" and if it is "(slightly) conscious".
nodja 4y ago
I've been following the image generation field for a couple months now and while the answer to the title is "yes for most things" it is easily fixed. Use a better text encoder. My favorite anecdote for showing how having a text encoder that actually understands the world is important to image generation is when querying for "barack obama" on a model trained on a dataset that has never seen Barack Obama the model somehow generates images of random black men wearing suits[1]. This is, in my non-expert opinion, a clear indication that the model's knowledge of the world is leaking through to the image generator. So if my understanding is right, as long as a concept can be represented properly in the text embeddings of a model, the image generation will be able to use that. If my anecdote doesn't convince you, consider that one of google's findings on the Imagen paper was that increasing the size of the text encoder had a much bigger effect on not only the quality of the image, but also have the image follow the prompt correctly, including having the image generator being able to spell words. I think the next big step in the text to image generation field, aside from the current efforts to optimize the diffusion models, will be to train an efficient text encoder that can generate high quality embeddings. [1] Results of querying "barack obama" to an early version of cene555's imagen reproduction effort. https://i.imgur.com/oUo3QdF.png https://i.imgur.com/oUo3QdF.png
- snek_case 4y ago
  > when querying for "barack obama" on a model trained on a dataset that has never seen Barack Obama the model somehow generates images of random black men wearing suits[1]. This is, in my non-expert opinion, a clear indication that the model's knowledge of the world is leaking through to the image generator. That's super interesting. It's not just black men in suits either. It's older black men, with the American flag in the background who look like they might be speaking. Clearly the model has a pretty in-depth knowledge of the context surrounding Barack Obama. I would say the image generation model is also doing a pretty great job at stitching those concepts together in a way that's coherent. It's not a random jumble. It's kind of what you would expect if you asked a human artist to draw a black American president.
blocked_again 4y ago
This can be easily answered by giving the following input to dalle. """ A map highlighting the countries the ancient Romans invaded since Pepsi was introduced. """
- Rackedup 4y ago
  Is it supposed to only provide facts?
kazinator 4y ago
The authors here underestimate how much semantics is involved in gluing things together.
mellowside 4y ago
I've seen different results than the author. Had it since it was in beta and learned that it needs better prompts to generate better images. As someone on their Discord said "prompt writing is a craft you need to learn".
xornox 4y ago
At least there is much missing data for human like intelligence. If human would be trained with same input data, I think he/she would not understand relationships.
roland00 4y ago
Isn't this just Chaos Theory, Calculus, and the problem of Jerks (third derivative of position in regards to time)? When you slice complex reality into smaller pieces, within the smaller piece you have a rough idea of velocity, and changes in velocity (aka acceleration), but you have no idea of future speed-bumps, aka the jerks (third derivative of position in regards to time) for that information is outside the frame of reference when you divided reality into smaller pieces. Thus you have pictures of people / objects in systems but you are not truly understanding relationships thus you miss things even though you feel like you see things. It is all a theme park for our own amusement, it is not real, only hyper-real which becomes uncanny when we start noticing how the images are off.
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rasz 4y ago
Dalle is fancy content aware fill on steroids (style translation etc).
Havoc 4y ago
Isn't that true for all the models?
siglesias 4y ago
I discovered something like this recently when I tried the prompt "man throwing his smartphone into a river," and for the life of me I could not get DALL-E to render the phone separated from the hand (I tried "like a boomerang," "tossing," "into an ocean," "like a baseball," etc). And then it occurred to me that by the training data, there are virtually no pictures of a person and a phone where the phone is separated! So DALL-E might have thought that the phone was just an appendage to the body, the way the hand is (which, what does this say about society!). I might as well have asked DALL-E to render someone throwing their elbow into a river. Another interesting case is animal-on-animal interactions. A prompt like, "small french bulldog confronts a deer in the woods" often yields weird things like the bulldog donning antlers! As far as the algorithm is concerned, it sees a bulldog, ticking the box for it, and it sees the antlers, ticking the box for "deer." The semantics don't seem to be fully formed.
- gwern 4y ago
  I dunno man, I punched that exact prompt ("man throwing his smartphone into a river") in DALL-E 2 just now, and in 2/4 samples, the smartphone is clearly separate from the hand: labs.openai.com/s/uIldzs2efWWnm3i9XjsHI7or labs.openai.com/s/jSk4qhAxSiL7QJo7zeGp6m9f > The semantics don't seem to be fully formed. Yes, not so much 'formed' as 'formed and then scrambled'. This is due to unCLIP, as clearly documented in the DALL-E 2 paper, and even clearer when you contrast to the GLIDE paper (which DALL-E 2 is based on) or Imagen or Parti. Injecting the contrastive embedding to override a regular embedding tradesoff visual creativity/diversity for the semantics, so if you insist on exact semantics, DALL-E 2 samples are only a lower bound on what the model can do. It does a reasonable job, better than many systems up until like last year, but not as good as it could if you weren't forced to use unCLIP. You're only seeing what it can do after being scrambled through unCLIP. (This is why Imagen or Parti can accurately pull off what feels like absurdly complex descriptions - seriously, look at the examples in their papers! - but people also tend to describe them as 'bland'.)
  - visarga 4y ago
    If you want multiple objects, each with individual attributes, the unCLIP model still has to make a single embedding vector representation. But the single vector is too small to contain an ever more detailed scene description. That's why it has failure modes like assigning the wrong colour to cubes and not being able to spell text. On the other hand the previous approach - autoregressive generation - allows full access through the attention mechanism to the prompt. For example Imagen encodes text to a sequence of embeddings. > Imagen comprises a frozen T5-XXL [52] encoder to map input text into a sequence of embeddings and a 64×64 image diffusion model, followed by two super-resolution diffusion models
upupandup 4y ago
Blake Lemon claimed that Google's chatbot was sentient which I disagreed with and its demonstrated through this article. AI can be optimized to respond in a way that can easily fool someone into thinking they are talking to a human but at the end of the day sentiency requires consciousness and that is not something that can be digitally produced. You can teach a parrot to respond to basic arithmetic but they are not aware of the concept of math rather they are acting in pathways set to induce the desired response. A truly conscious entity would simply have a mind of its own and will not do our bidding just like any other humans. They would be extremely selfish and apathetic, the idea that bunch of GPUs sitting in a datacenter is sentient is sheer lunacy. This Blake Lemon character will not be the last, there are always those that seek to be in the lime light with zero regards for authenticity. Such is sentient behavior.
JoshTko 4y ago
Do humans assume things without understanding their relationships?
aaroninsf 4y ago
Strong recommend for the book _The Alignment Problem_ which while only somewhat touching on systems which is an excellent lay overview of the state of ML which does a good effort to explain the principles involved, the challenges and blockers, and the ways in which progress has been made. The field is moving so quickly it will stop short of the current status quo, but, it's still remarkable. I have been myself playing with MidJourney, which like DALL-E 2 is a text prompt to image generation system; it has different goals and favors aestheticized output over photorealism. The premises of that project and its current execution (as an explicit exercise in collective- rather that siloed-and-contractual relations) are genuinely remarkable and I believe represent a watershed. The rate of evolution of what it is doing are something to behold. I have generated around 7500 images with MidJourney so far and am slowly developing what feels like an intuition for the way it "sees" images, which as the devs say in regular office hours, is unlike how humans see them. The limitations, and superpowers, of the system as it exists are already deeply provocative. When things scale again to the next level, the degree of uncanniness and challenge to our preconceptions about the nature and locus of intelligence in ourselves may be genuinely shaking. Or so I currently think. I highly recommend taking time to really feel out these systems, because the ways they do and do not succeed and fail serves as a very potent first-hand education in the opportunities, and perhaps much more important, perils, of their application in other more quotidian areas. It's one thing for them to reliable produce "nightmare fuel" because of their inability to retain very high level coherence down through low level details, when they are drawing limbs, hands, faces... ...it's another thing entirely when analogous failure modes quietly permeate their ability to recognize illness, or, approve a loan, or recommend an interest rate. Or—as the example which opens _The Alignment Problem_ spells out—recommend whether someone should or should not offered bail. (A real world example with life-changing consequences for people who interact with ML in this path, in something over 30 states today... at least, as of publication).
knighthack 4y ago
I don't see how the 'understanding of relationships' should be taken as the key intent of DALL-E 2. Consider procedural generation: it can create abstractions of both utter beauty or garbage without understanding context. You need to guide it towards something meaningful. Just the fact that DALL-E can 'glue things together' without need for human inspiration - yet where its output and intent can be understood by a human appraising it - that is not only a feat in itself, but I would say its key feature.
LesZedCB 4y ago
it does understand their relationships. the difference are the subjects of the domain it learns about exist purely as 2 dimensional images. once these models get larger and include wider ranges of sensory data beyond just imagery (as can be seen with models like GATO), they are clearly better able to "glue together" concepts across multiple domains. i would argue we absolutely do nothing different with regard to 'gluing things together'. we just have a wider range of sensory inputs.
kache_ 4y ago
define understand
- rexreed 4y ago
  exactly. or even ask these AI systems to define it. Just like a parrot, they'll repeat what other say without actually understanding what understanding is.
2OEH8eoCRo0 4y ago
What are we trying to accomplish with AI? What is "real" intelligence? What are we hoping that an AI does? What test does it need to pass?
otikik 4y ago
How does one define “understand their relationships”? To me it is a matter of degrees and has multiple axes. When my 6yo son draws a chair, it’s not the same as when Van Gogh draws one, which is different to when an expert furniture designer draws one. They all “understand” in different ways. A machine can also “understand”. It might do it in different degrees and across different axes that the ones humans usually have, that’s all. How we transform that understanding into action is what is important I think.
throwaway675309 4y ago
Yes, SHRDLU it most definitely is not.
xwdv 4y ago
For art generation, gluing things together without understanding relationships is basically creativity. Humans can assign meaning to the final output.
- visarga 4y ago
  There is some degree of understanding how to combine concepts, otherwise the avocado chair would not be possible.
arey_abhishek 4y ago
AI will never understand the actual context because not everything we feel/experience can be captured and communicated to a machine. For example, human language is incomplete and doesn’t encode every information because it doesn’t need to when used with other humans. I think it’s a romantic notion to imagine that AI will not be a Chinese room. Even human intelligence feels like a Chinese room. Especially noticeable when using complicated devices like flight controls. I’ve been playing the MSFT Flight simulator, and I don’t fully understand the relationship between the different instruments. But I can still fly planes(virtually). We’d be better off if we considered AI similar to an appliance like a microwave or a refrigerator. Does a fridge need to understand or taste what’s inside it to be helpful?
- Sakos 4y ago
  AI will never understand the actual context until we give it the same access to a physical and metaphysical environment that we have, as well as similar ways to navigate them. I still believe we're at most a few decades away from AGI, but it's going to take a step above what we're doing with ML. Though if we're lucky/unlucky, ML will pidgeon hole research so badly that we'll reach a local maxima that will prevent us from finding the right path to AGI.
rkwasny 4y ago
People are "gluing things together" for a very long time, that's what everyone does! All ideas as remixes of previous ideas
bawolff 4y ago
AI system is good at what it was trained to do and bad at what it was not trained to do! News at 11!
TheRealPomax 4y ago
"Yes". And that's why question headlines may not technically be click bait, but still qualify as something the world can do about.
anothernewdude 4y ago
Certainly seems that way, but I didn't get to use DALL-E 2 because its a Closed-AI.
prometheus76 4y ago
I want to see two DALL-E bots talk to each other. First bot: "Pete and Repeat were sitting on a fence. Pete fell off. Who was left?" Second bot: "Repeat" First bot: "Pete and Repeat were sitting on a fence. Pete fell off. Who was left?" What happens next?
- mkl 4y ago
  I think you're thinking of GPT-3. DALL-E and DALL-E 2 generate images, not text (and they're very bad at images of text).
  - prometheus76 4y ago
    Ah I'm sorry. Well, the curiosity remains!
RootKitBeerCat 4y ago
Having spent about 200$ on credits… yes, it glues together your words through transformers into images… of snippets of the identified corpus of images it has… with some specific prompt phrasings having cool weighting for making really nicely looking glued together results… it’s a model: classical computing - everything is turtles and duct tape and rivets and glue, all the way down…
- themodelplumber 4y ago
  Fixed relationship concepts are a deeply subjective model, too, and this isn't exactly taught in school. Imagining that one knows "the" relationship between even two really obvious things can be the sign of a closed mind, or a mind which locks out new perspectives. This can be even more true, the more obvious the relationships may seem due to shared sensory biases. IMO this is one reason why DALL-E 2 can be helpful for conceptualizing. If the user is open, DALL-E 2 can make mistakes and still teach you things through those same mistakes. Unfortunately the relationship between DALL-E 2 and the user, so to speak, is also perceived as relatively fixed by members of the tech community, so highly do they rate their own ability to tell how "good" such a model is, etc.
modeless 4y ago
I mean, that's what I do all day as a human, so why shouldn't an AI do it too? DALL-E 2 isn't as good at it as I am, but a decade or two from now?
rexreed 4y ago
Who said machine learning had anything to do with "understanding" or "reasoning"? There's no reasoning or understanding in these systems. Just probabilistic computations based on big data. And before you go saying "but that's how your brain works too", that's not the case. Because your brain can do a heck of a lot more than these big data magic tricks that we call machine learning can do.
bradgessler 4y ago
I make a living “gluing things together” and calling it software.
smusamashah 4y ago
I found that 'painting' or 'art' style does generate what you really asked for. Photos failed so often. e.g. "a monkey touching an iguana" https://imgur.com/a/5u0YNMe https://imgur.com/a/5u0YNMe These are the only 3 prompts I tried. First image in two of them painted exactly what I asked for when added painting/artwork. It did fail at 'a teacup under a cylinder' though https://imgur.com/a/owmnt5j https://imgur.com/a/owmnt5j
Sateeshm 4y ago
It definitely does not know what the image is. Generating variations of fireman with a hose resulted in a bunch of gardeners with hats that kinda look like fireman image but clearly gardeners

224 points by Hard_Space 4y ago

I'm a big Dall-E fan but this is no surprise to anyone who's used it for more than 5 minutes. It was one of the things highlighted by Google when they announced Imagen as a differentiator: https://imagen.research.google https://imagen.research.google The article touches on this but the headline is slightly deceptive.

causi 4y ago
Imagen would be amazing for an "Images Against Humanity" game where you score points by generating the funniest picture.
- Zircom 4y ago
  Absolutely stealing this idea, look forward to being credited for the idea in the future show hn post :P
andybak 4y ago
(Incidentally - I want to make it clear I don't mean "Dall-E has no understanding of the elements and it's just a fancy image search/compositor" - there are results that absolutely require some semantic "understanding". It's just there are limits and spatial understanding is one of the weak spots)

vannevar 4y ago

I'm sure it is, but "gluing things together" coherently in response to a text prompt is a stupendous achievement. It's not AGI, but it's miles ahead of where we were even a few years ago and opens the door to automating a class of jobs I don't think anyone back then believed could be automated, short of AGI.

danielmorozoff 4y ago
Where do you see DALLE automating away jobs?
- robertlagrant 4y ago
  There was a post on here recently on how someone designed their logo by asking DALL-E a load of questions. The rationale could be that it might not remove that job, but it would certainly be a powerful tool for a logo designer to take on way more clients, thus driving down the cost of logo design.
  - odessacubbage 4y ago
    i feel like this boils down to a client-side misunderstanding of where graphic designers actually spend the majority of their time. i'd actually argue that working from spec or even a crude doodle on the back of a napkin is a lot easier than dealing with a client who is married to a poor design that DALL-E puked out for them. one of the most important things about the sketch phase is to be able to iterate without too many assumptions while also being able to recognize and play upon the strengths of individual drawings. this is not a time consuming process but it also isn't something you want to rush anymore so than you'd want to rush the plastic surgeon performing your nose job. depersonalizing the design process in favor of volume does not particularly serve anyone and, moreover, it responds to a need that i don't really think exists. this is not to say that i don't think these kinds of image generators are without uses, but right now we are still in the phase where people are being impressed by graphical fidelity[which was already incredibly cheap] rather than usefulness. imo this stage of ai will primarily work well for tasks that benefit from randomness while also being relatively low stake in the overall production pipeline. training a network to generate typefaces or to randomize npc portraits for an open world game is precisely the sort of area where 'gluing things together' can potentially provide more benefits than headaches.
    - robertlagrant 4y ago
      I was saying a designer could use it for first draft ideas, not their client.

BiteCode_dev 4y ago

Amusingly, I get creative new ideas when I glue things together and ignore what I thought I understood about their relationships.

TremendousJudge 4y ago
Happens to me too -- it's a great way to make new things. However, the "creation" I'd argue happens when you look at the pile of random stuff and generate a new understanding, and decide that it is valuable. The difference between trash and art only exists in the head of the artist. Same thing happens with DALL-E output, really.

pera 4y ago

Interesting, DALL-E Mini / Craiyon actually generates a pretty accurate result for "a monkey touching an iguana" (at least semantically): https://i.imgur.com/Oq62gQI.png https://i.imgur.com/Oq62gQI.png

affgrff2 4y ago
Maybe it's in the training data? At least some special kind of monkey (human) touching some lizard is.
- johndough 4y ago
  https://rom1504.github.io/clip-retrieval/?index=laion5B&useMclip=false&query=monkey+touching+iguana&back=https%3A%2F%2Fknn5.laion.ai https://rom1504.github.io/clip-retrieval/?index=laion5B&useM... There seem to exist several pictures of marmoset monkeys touching iguanas, but DALL-E mini shows macaque monkeys. This makes me believe that DALL-E mini has at least some generalization capabilities.
walrus01 4y ago
imgur is providing a prompt before viewing this image "this image may contain erotic imagery, are you over 18, etc". i certainly hope not...

IceMetalPunk 4y ago

Now, let's be critical of possible reasons for this. It's important to remember two things: 1) Any NN has zero experience with the world beyond its training data. Things that seem obvious to us from our experience are not obvious to a system that has never experienced those things. And 2) DALL-E 2 was trained on image-caption pairs scraped from the internet, basically. So it's quite possible the reason it doesn't understand things like "X under Y" very well is that its training set doesn't have a lot of captions describing positional information like that, as opposed to any failure in the architecture to even potentially understand these things.

burlesona 4y ago

Slight side tangent but reading this article it hit me how much this generation of work may be reinforcing English as the global language for generations to come. It seems like we are headed towards a phase of technology where learning how to feed well-crafted prompts into the AI system will be a highly valuable productivity skill. And since the major AI systems seem to be built around English, that would make English fluency even more valuable than it already is. I’m sure that’s obvious to non-native speakers who have worked hard to master English, I just hadn’t thought of it before. Less likely but still interesting, I wonder if the way we’re building these models will at some point begin to layer on top of each other such that English as it is used now becomes something deeply embedded in AI, and whether that will evolve with the spoken language or not. It’s funny to imagine a future where people would need to master an archaic flavor of English to get the best results working with their AI helpers.

affgrff2 4y ago
But the same work is also removing the language barriers at the same time with really good translation tools. I rather guess being fluent in English will be not as important as it is now. Edit: the same work = transformer based language models
mtlmtlmtlmtl 4y ago
Also worth noting that the internet has massively accelerated the importance of English already. As an ESL speaker who grew up on the internet, Norwegian was more or less useless to me outside school and family. Most of my time was spent on the internet, reading and writing lots of English. Norwegian wikipedia is pretty much useless unless you don't know English. That's still true today for the vast majority of articles, but back then was universally the case. There were Norwegian forums, but with a population of just 4 million and change at the time, they were never as interesting or active as international/American forums and IRC channels. In fact I'd say Norwegian is only my native language in spoken form, whereas English feels more natural to me to write and read. Doesn't help that Norwegian has two very divergent written forms, either. I even write my private notes in English, even though I will be the only one reading them.
Ajedi32 4y ago

QuadmasterXLII 4y ago

My intuition is that DALL-E is more a demonstration of how hard image synthesis is for humans, than how intelligent the algorithm is. The image generation models have orders of magnitude fewer parameters than the large language models.

adamsmith143 4y ago

Why is there this obsession with systems or algorithms having "understanding"? No one thinks these things have internal states equivalent to "understanding". "Understanding" or not you can't deny the capability of these systems.

chpatrick 4y ago

I think "understanding" is a super vague word.

i_am_toaster 4y ago
Bingo. This is also a fair comparison to how todays politics works in a nutshell. Overload a word with a vague context and people immediately attribute their own perspective to come to a conclusion that conflicts with an opposing argument. Relating back to this headline, using “understanding” creates lots of messages with differing views because everyone has their own take on the word. If instead you said something like, “DALLE fakes understanding of concepts to create new images,” I bet you’d get even closer to the “political message board” style of comments because you are now taking an objective position (yes/no,true/false,good/bad) on a subjective word (understanding).

IIAOPSW 4y ago

I have a phrase I'd like to coin in contrast to AI. "Artificial Bullshit". AB. I of course mean "bullshit" in the highly technical sense defined by Frankfurt [1]. The defining feature that separates a bullshitter from a liar is that a liar knows and understands the truth and intentionally misrepresents the matters of fact to further their aims, whereas a bullshitter is wholly unconcerned with the truth of the matters they are discussing and is only interested in the social game aspect of the conversation. Bullshit is far more insidious than a lie, for bullshit can (and often does) turn out to be coincident with the truth. When that happens the bullshitter goes undetected and is free to infect our understanding with more bullshit made up on the spot. DallE generates the images it thinks you want to see. It is wholly unconcerned with the actual objects rendered that are the ostensible focus of the prompt. In other words, its bullshitting you. It was only trained on how to get your approval, not to understand the mechanics of the world it is drawing. In other words, we've trained a machine to have daddy issues. A profoundly interesting question (to me) is if there's a way to rig a system of "social game reasoning" into ordinary logical reasoning. Can we construct a Turing Tarpit out of a reasoning system with no true/false semantics, a system only designed to model people liking/disliking what you say? If the answer is yes, then maybe a system like Dalle will unexpectedly gain real understanding of what it is drawing. If not, systems like Dalle will always be Artificial Bullshit. [1] http://www2.csudh.edu/ccauthen/576f12/frankfurt__harry_-_on_bullshit.pdf http://www2.csudh.edu/ccauthen/576f12/frankfurt__harry_-_on_...

deleted 4y ago
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leereeves 4y ago
> It is wholly unconcerned with the actual objects rendered that are the ostensible focus of the prompt. I disagree. To the extent that the training data are images of actual objects, recreating images of actual objects is the only thing DALL-E cares about. If we define "caring" about something as changing behavior to cause that to happen, then a neural network doesn't "care" about inference at all, because inference never changes the network's behavior. It also doesn't know or care about your approval. It only cares about minimizing the loss function. (But now that you bring this up, I think it would be really interesting to create a network that, after training initially on training data, began interacting with people and continued training to maximize approval.)

simion314 4y ago

There were so many articles about this project, but I can't find a demo page to test 3,4 outputs myself (unless it was some page I already tried when it was linked and I got nothing similar with what is shown on main page)

___rubidium___ 4y ago

Fascinating. I've noticed the same problem with Midjourney and Nightcafé as well.

can16358p 4y ago

Regardless of the content, the article has been "published 10 seconds ago" for the last few minutes, and has been submitted to HN 1 hour ago.

dukeofdoom 4y ago

Using midjourney, I'm fascinated with the geometric shapes it comes with. Just yesterday I was looking at a sort of a hexagon made with intersecting hearts. Not only was it aesthetically pleasing, it was such an unusual composition, that I think it would be extremely hard for an artist to come up with, maybe even a mathematician. So I think it's already capable of doing more sophisticated things than human artists.

Cognitron 4y ago
MidJourney is really good at creating abstract images. I’ve been playing with the multi-prompt syntax (::) a lot lately, just combining different words that evoke form or texture to see what it will come up with. I start by testing things one at a time and just take a guess at what might look cool together. I end up making strange images with prompts like “fractal :: stained glass :: feathers”, “antelope canyon :: tattered fabric :: cave”, “rubik’s cube :: Japanese woodblock”, you get the idea. I rarely try to make pictures of real things anymore. Definitely fun to play around with.
- dukeofdoom 4y ago
  I'm pretty new to it. Any tips on making retro pixel art assets. I want a stone or brick wall I could tile into a game I'm making.
  - Cognitron 4y ago
    I think most of us are pretty new to it since they just opened the beta to a ton of people. I haven't tried to do anything like that with it though. All I can say is it tends to take a lot of experimentation to get what you want. And you'll probably have to do some work to the images to get them to tile seamlessly. If you can't get the pixelated look quite how you want it, you might try using it to generate a base image and then use a separate tool to pixelate it. Some people are using it as part of a larger pipeline. The discord is full of people sharing their experiments and approaches though. Maybe try asking in the prompt-craft channel to see if someone else has attempted something similar. Good luck!

KingOfCoders 4y ago

That's called creativity.

avalys 4y ago

I think DALL-E is clearly just gluing things together that it found in a massive dataset, and doesn't have any understanding of the underlying concepts. I thought it was easy to see the signs of this in examining its output. Same for GPT-3. However, what's amazing about DALL-E and these other statistical, generative models to me is that it's made me think about how much of my daily thought processes are actually just gluing things together from some kind of fuzzy statistical model in my head. When I see an acquaintance on the street, I don't carefully consider and "think" about what to say to them. I just blurt something out from some database of stock greetings in my head - which are probably based on and weighted by how people have reacted in the past, what my own friends have used similar greetings, and what "cool" people say in TV and other media in similar circumstances. "Hey man how's it going?" If I was asked to draw an airplane, I don't "think" about what an airplane looks like from first principles - I can just synthesize one in my head and start drawing. There are tons of daily activities like this that we do like this that don't involve anything I'd call "intelligent thought." I have several relatives that, in the realm of political thought, don't seem to have anything more in their head than a GPT-3 models trained on Fox News (that, just like GPT-3, can't detect any logical contradictions between sentences). DALL-E has convinced me that even current deep learning models are probably very close to replicating the performance of a significant part of my brain. Not the most important part or the most "human" part, perhaps. But I don't see any major conceptual roadblock between that part and what we call conscious, intelligent thought. Just many more layers of connectivity, abstraction, and training data. Before DALL-E I didn't believe that simply throwing more compute at the AGI problem would one day solve it. Now I do.

dougmwne 4y ago
I think our intelligence has 2 components, our conscious selves that are good at formal reasoning and meaning making, and a massive neural network that is good at statistical inference. I suspect the reason we need less training data for learning than dall-e is because our conscious selves can tease out the formal relationships and models, rather than relying purely on inference which requires enough datapoints.
multibit 4y ago
>I have several relatives that, in the realm of political thought, don't seem to have anything more in their head than a GPT-3 models trained on Fox News (that, just like GPT-3, can't detect any logical contradictions between sentences). If more people were to realize that we're all probably like this, trained on some particular dataset (like mainstream vs reactionary news/opinion), I wonder if that would lead to a kind of common peace and understanding, perhaps stemming only from a deep nihilism.

AbraKdabra 4y ago

I mean, if it is "gliung things together" is doing it pretty well...

boredumb 4y ago

GPT/DALL-E/etc... All of these models are of course gluing things together in some manner, but who cares? That's the point right? The AI pill i've taken is that you don't need AGI in order to make things that are useful for people and business. If you've ever ran a business and had to dive into creatives for blogs, SEO content, social media posts, etc then you spent an inordinate amount of time creating it or outsourced it and in both cases the final copy is NOT going to get you a literary prize any time soon but it is absolutely enough to inform potential customers, start ranking on google and start gaining social media clout. GPT will also not garner you a literary award but can absolutely get you quality copy that users, customers, google, facebook users will not be the wiser that you generated it with AI instead of paid a third party to hack it together for you. (https://neuralmates.com/ https://neuralmates.com/ I recently started putting together a web app to MVP this, and I hope to be able to integrate DALLE-2 soon to be able to start generating images for folks as well.)

lancesells 4y ago
This is the kind of response that turns me off on all of these amazing technologies. Blanketing the world with low-level content in the hopes to gain ranking and clout sounds awful. On the flip side I'm guessing we'll have some gpt-3/dall-e blocker extensions that help reduce some of it.
- boredumb 4y ago
  Sure, but It's the reality of it. Also - you already live in this world but it's fueled by low cost copy writers and ghost accounts on fiver, I'd bet you are going to see the low water mark for content increase quite a bit in quality and volume over the next few years due to GPT3 being leagues better than the current state of content mills.

kemiller 4y ago

Anyone who has ever raised a small child will realize this is how kids learn too.

gizajob 4y ago

I recently used it to create a picture of "an analogue synthesizer made out of meat and gristle". I don't really know how you could glue these concepts together, because nothing in reality causes them to ever go together, but it did a great job anyway.

dezmou 4y ago

Another cool example is when you ask DALLE-E to make a "Jaguar XF", it does not really know if I talk about the car or the animal, yet it manage to blend the two together https://img-comment-fun.9cache.com/media/a6wG6Kq/aq04bGmR_700w_0.jpg https://img-comment-fun.9cache.com/media/a6wG6Kq/aq04bGmR_70...

thriftwy 4y ago

Maybe you could give DALL-E creativity lessons by finding such nonsense queries and adding creative interpretations of those into learning set.

aeturnum 4y ago

The Fair Witness was a job that Heinlein made up for Stranger in a Strange Land. Fair Witnesses were supposed to reliably report what they saw without judgement - including their subjective judgement in their report. The example exchange is: "Is that house over there brown?" "It is brown on this side." Dall-E (and other ML systems) feel like fair witnesses for our cultural milieu. They basically find a series of weighted connections between every phrase we've thought to write down or say about all images and can blend between those weights on the fly. By any assessment it's an amazing feat - as is the feat to view their own work and modify it (though ofc it's from their coordinate system so one does expect it would work). In one sense - asking if the machine "understands" is beside the point. It does not need to 'understand' to be impressive (or even what people claim when they're not talking to Vice media or something). In another sense, even among humans, "understanding" is both a contested term and a height that we all agree we don't all reach all of the time. One can use ideas very successfully for many things without "understanding" them. Sometimes people will, like, turn this around and claim that: because humans don't always understand ideas when they use them, we should say that ML algorithms are doing a kind of understanding. I don't buy it - the map is not the territory. How ML algorithms interact with semantics is wholly unlike how humans interact with them (even though the learning patterns show a lot of structural similarity). Maybe we are glimpsing a whole new kind of intelligence that humans cannot approach - an element of Turing Machine Sentience - but it seems clear to me that "understanding" in the Human Sentience way (whatever that means) is not part of it.

Sakos 4y ago
> In another sense, even among humans, "understanding" is both a contested term and a height that we all agree we don't all reach all of the time. One can use ideas very successfully for many things without "understanding" them. Only if you define "understanding" as an intellectual process instead of the existential process that is meant when we say "understanding" in the context of cognition and AI.

Marazan 4y ago

https://imgur.com/ggnm920 https://imgur.com/ggnm920 "a photo of 6 kittens sitting on a wooden floor. Each kitten is clearly visible. No weird stuff." Like, lets start with the fact that there are 7 of them (2 of the 4 images from the prompt had 7 kittens). Now lets continue on with how awful they look. It is startling the difference in image quality between DAlle-2 asked for a single subject vs DAlle-2 being asked for a group of stuff. And its obvious, if you know how the tech works, why this is the case.

rocgf 4y ago

Does anyone actually believe DALL-E "understands" what it's doing? For any reasonable definition of "understands", I assume most people would be skeptical. So if we go with that, then yes, it just glues things together without understanding their relationship. I'd just be tempted to say it doesn't really matter that it doesn't understand, except maybe for some philosophical questions. It's still incredible based on its output.

LesZedCB 4y ago
can we come up with a 'reasonable' definition of understands that isn't couched in human exceptionalism and could still apply to any computer model? i think dall-e understands, within the sensory domain it's trained from.
- rocgf 4y ago
  I think DALL-E understands the same way an Excel sheet would understand SUM(B3:B6), obviously at a way larger scale and with a more complicated function. It's all just rather simple maths all the way down.
  - deleted 4y ago
    [deleted]
  - visarga 4y ago
    Not similar. The SUM() function was written by humans in a top-down fashion, DALL-E learned from the visual and textual data by a completely different process. DALL-E distilled something about the world and is using that to generate.
visarga 4y ago
> Does anyone actually believe DALL E "understands" what it's doing? I believe it understands enough to make tens of thousands of people interested and debating its merits. The GANs of 5 years ago were baby toys compared to DALL-E. They were drawing 5 legs to a dog and limited to a few object classes. Now people debate if it "really understands" and if it is "(slightly) conscious".

nodja 4y ago

I've been following the image generation field for a couple months now and while the answer to the title is "yes for most things" it is easily fixed. Use a better text encoder. My favorite anecdote for showing how having a text encoder that actually understands the world is important to image generation is when querying for "barack obama" on a model trained on a dataset that has never seen Barack Obama the model somehow generates images of random black men wearing suits[1]. This is, in my non-expert opinion, a clear indication that the model's knowledge of the world is leaking through to the image generator. So if my understanding is right, as long as a concept can be represented properly in the text embeddings of a model, the image generation will be able to use that. If my anecdote doesn't convince you, consider that one of google's findings on the Imagen paper was that increasing the size of the text encoder had a much bigger effect on not only the quality of the image, but also have the image follow the prompt correctly, including having the image generator being able to spell words. I think the next big step in the text to image generation field, aside from the current efforts to optimize the diffusion models, will be to train an efficient text encoder that can generate high quality embeddings. [1] Results of querying "barack obama" to an early version of cene555's imagen reproduction effort. https://i.imgur.com/oUo3QdF.png https://i.imgur.com/oUo3QdF.png

snek_case 4y ago
> when querying for "barack obama" on a model trained on a dataset that has never seen Barack Obama the model somehow generates images of random black men wearing suits[1]. This is, in my non-expert opinion, a clear indication that the model's knowledge of the world is leaking through to the image generator. That's super interesting. It's not just black men in suits either. It's older black men, with the American flag in the background who look like they might be speaking. Clearly the model has a pretty in-depth knowledge of the context surrounding Barack Obama. I would say the image generation model is also doing a pretty great job at stitching those concepts together in a way that's coherent. It's not a random jumble. It's kind of what you would expect if you asked a human artist to draw a black American president.

blocked_again 4y ago

This can be easily answered by giving the following input to dalle. """ A map highlighting the countries the ancient Romans invaded since Pepsi was introduced. """

Rackedup 4y ago
Is it supposed to only provide facts?

kazinator 4y ago

The authors here underestimate how much semantics is involved in gluing things together.

mellowside 4y ago

I've seen different results than the author. Had it since it was in beta and learned that it needs better prompts to generate better images. As someone on their Discord said "prompt writing is a craft you need to learn".

xornox 4y ago

At least there is much missing data for human like intelligence. If human would be trained with same input data, I think he/she would not understand relationships.

roland00 4y ago

Isn't this just Chaos Theory, Calculus, and the problem of Jerks (third derivative of position in regards to time)? When you slice complex reality into smaller pieces, within the smaller piece you have a rough idea of velocity, and changes in velocity (aka acceleration), but you have no idea of future speed-bumps, aka the jerks (third derivative of position in regards to time) for that information is outside the frame of reference when you divided reality into smaller pieces. Thus you have pictures of people / objects in systems but you are not truly understanding relationships thus you miss things even though you feel like you see things. It is all a theme park for our own amusement, it is not real, only hyper-real which becomes uncanny when we start noticing how the images are off.

deleted 4y ago

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rasz 4y ago

Dalle is fancy content aware fill on steroids (style translation etc).

Havoc 4y ago

Isn't that true for all the models?

siglesias 4y ago

I discovered something like this recently when I tried the prompt "man throwing his smartphone into a river," and for the life of me I could not get DALL-E to render the phone separated from the hand (I tried "like a boomerang," "tossing," "into an ocean," "like a baseball," etc). And then it occurred to me that by the training data, there are virtually no pictures of a person and a phone where the phone is separated! So DALL-E might have thought that the phone was just an appendage to the body, the way the hand is (which, what does this say about society!). I might as well have asked DALL-E to render someone throwing their elbow into a river. Another interesting case is animal-on-animal interactions. A prompt like, "small french bulldog confronts a deer in the woods" often yields weird things like the bulldog donning antlers! As far as the algorithm is concerned, it sees a bulldog, ticking the box for it, and it sees the antlers, ticking the box for "deer." The semantics don't seem to be fully formed.

gwern 4y ago
I dunno man, I punched that exact prompt ("man throwing his smartphone into a river") in DALL-E 2 just now, and in 2/4 samples, the smartphone is clearly separate from the hand: labs.openai.com/s/uIldzs2efWWnm3i9XjsHI7or labs.openai.com/s/jSk4qhAxSiL7QJo7zeGp6m9f > The semantics don't seem to be fully formed. Yes, not so much 'formed' as 'formed and then scrambled'. This is due to unCLIP, as clearly documented in the DALL-E 2 paper, and even clearer when you contrast to the GLIDE paper (which DALL-E 2 is based on) or Imagen or Parti. Injecting the contrastive embedding to override a regular embedding tradesoff visual creativity/diversity for the semantics, so if you insist on exact semantics, DALL-E 2 samples are only a lower bound on what the model can do. It does a reasonable job, better than many systems up until like last year, but not as good as it could if you weren't forced to use unCLIP. You're only seeing what it can do after being scrambled through unCLIP. (This is why Imagen or Parti can accurately pull off what feels like absurdly complex descriptions - seriously, look at the examples in their papers! - but people also tend to describe them as 'bland'.)
- visarga 4y ago
  If you want multiple objects, each with individual attributes, the unCLIP model still has to make a single embedding vector representation. But the single vector is too small to contain an ever more detailed scene description. That's why it has failure modes like assigning the wrong colour to cubes and not being able to spell text. On the other hand the previous approach - autoregressive generation - allows full access through the attention mechanism to the prompt. For example Imagen encodes text to a sequence of embeddings. > Imagen comprises a frozen T5-XXL [52] encoder to map input text into a sequence of embeddings and a 64×64 image diffusion model, followed by two super-resolution diffusion models

upupandup 4y ago

Blake Lemon claimed that Google's chatbot was sentient which I disagreed with and its demonstrated through this article. AI can be optimized to respond in a way that can easily fool someone into thinking they are talking to a human but at the end of the day sentiency requires consciousness and that is not something that can be digitally produced. You can teach a parrot to respond to basic arithmetic but they are not aware of the concept of math rather they are acting in pathways set to induce the desired response. A truly conscious entity would simply have a mind of its own and will not do our bidding just like any other humans. They would be extremely selfish and apathetic, the idea that bunch of GPUs sitting in a datacenter is sentient is sheer lunacy. This Blake Lemon character will not be the last, there are always those that seek to be in the lime light with zero regards for authenticity. Such is sentient behavior.

JoshTko 4y ago

Do humans assume things without understanding their relationships?

aaroninsf 4y ago

Strong recommend for the book _The Alignment Problem_ which while only somewhat touching on systems which is an excellent lay overview of the state of ML which does a good effort to explain the principles involved, the challenges and blockers, and the ways in which progress has been made. The field is moving so quickly it will stop short of the current status quo, but, it's still remarkable. I have been myself playing with MidJourney, which like DALL-E 2 is a text prompt to image generation system; it has different goals and favors aestheticized output over photorealism. The premises of that project and its current execution (as an explicit exercise in collective- rather that siloed-and-contractual relations) are genuinely remarkable and I believe represent a watershed. The rate of evolution of what it is doing are something to behold. I have generated around 7500 images with MidJourney so far and am slowly developing what feels like an intuition for the way it "sees" images, which as the devs say in regular office hours, is unlike how humans see them. The limitations, and superpowers, of the system as it exists are already deeply provocative. When things scale again to the next level, the degree of uncanniness and challenge to our preconceptions about the nature and locus of intelligence in ourselves may be genuinely shaking. Or so I currently think. I highly recommend taking time to really feel out these systems, because the ways they do and do not succeed and fail serves as a very potent first-hand education in the opportunities, and perhaps much more important, perils, of their application in other more quotidian areas. It's one thing for them to reliable produce "nightmare fuel" because of their inability to retain very high level coherence down through low level details, when they are drawing limbs, hands, faces... ...it's another thing entirely when analogous failure modes quietly permeate their ability to recognize illness, or, approve a loan, or recommend an interest rate. Or—as the example which opens _The Alignment Problem_ spells out—recommend whether someone should or should not offered bail. (A real world example with life-changing consequences for people who interact with ML in this path, in something over 30 states today... at least, as of publication).

knighthack 4y ago

I don't see how the 'understanding of relationships' should be taken as the key intent of DALL-E 2. Consider procedural generation: it can create abstractions of both utter beauty or garbage without understanding context. You need to guide it towards something meaningful. Just the fact that DALL-E can 'glue things together' without need for human inspiration - yet where its output and intent can be understood by a human appraising it - that is not only a feat in itself, but I would say its key feature.

LesZedCB 4y ago

it does understand their relationships. the difference are the subjects of the domain it learns about exist purely as 2 dimensional images. once these models get larger and include wider ranges of sensory data beyond just imagery (as can be seen with models like GATO), they are clearly better able to "glue together" concepts across multiple domains. i would argue we absolutely do nothing different with regard to 'gluing things together'. we just have a wider range of sensory inputs.

kache_ 4y ago

define understand

rexreed 4y ago
exactly. or even ask these AI systems to define it. Just like a parrot, they'll repeat what other say without actually understanding what understanding is.

2OEH8eoCRo0 4y ago

What are we trying to accomplish with AI? What is "real" intelligence? What are we hoping that an AI does? What test does it need to pass?

otikik 4y ago

How does one define “understand their relationships”? To me it is a matter of degrees and has multiple axes. When my 6yo son draws a chair, it’s not the same as when Van Gogh draws one, which is different to when an expert furniture designer draws one. They all “understand” in different ways. A machine can also “understand”. It might do it in different degrees and across different axes that the ones humans usually have, that’s all. How we transform that understanding into action is what is important I think.

throwaway675309 4y ago

Yes, SHRDLU it most definitely is not.

xwdv 4y ago

For art generation, gluing things together without understanding relationships is basically creativity. Humans can assign meaning to the final output.

visarga 4y ago
There is some degree of understanding how to combine concepts, otherwise the avocado chair would not be possible.

arey_abhishek 4y ago

AI will never understand the actual context because not everything we feel/experience can be captured and communicated to a machine. For example, human language is incomplete and doesn’t encode every information because it doesn’t need to when used with other humans. I think it’s a romantic notion to imagine that AI will not be a Chinese room. Even human intelligence feels like a Chinese room. Especially noticeable when using complicated devices like flight controls. I’ve been playing the MSFT Flight simulator, and I don’t fully understand the relationship between the different instruments. But I can still fly planes(virtually). We’d be better off if we considered AI similar to an appliance like a microwave or a refrigerator. Does a fridge need to understand or taste what’s inside it to be helpful?

Sakos 4y ago
AI will never understand the actual context until we give it the same access to a physical and metaphysical environment that we have, as well as similar ways to navigate them. I still believe we're at most a few decades away from AGI, but it's going to take a step above what we're doing with ML. Though if we're lucky/unlucky, ML will pidgeon hole research so badly that we'll reach a local maxima that will prevent us from finding the right path to AGI.

rkwasny 4y ago

People are "gluing things together" for a very long time, that's what everyone does! All ideas as remixes of previous ideas

bawolff 4y ago

AI system is good at what it was trained to do and bad at what it was not trained to do! News at 11!

TheRealPomax 4y ago

"Yes". And that's why question headlines may not technically be click bait, but still qualify as something the world can do about.

anothernewdude 4y ago

Certainly seems that way, but I didn't get to use DALL-E 2 because its a Closed-AI.

prometheus76 4y ago

I want to see two DALL-E bots talk to each other. First bot: "Pete and Repeat were sitting on a fence. Pete fell off. Who was left?" Second bot: "Repeat" First bot: "Pete and Repeat were sitting on a fence. Pete fell off. Who was left?" What happens next?

mkl 4y ago
I think you're thinking of GPT-3. DALL-E and DALL-E 2 generate images, not text (and they're very bad at images of text).
- prometheus76 4y ago
  Ah I'm sorry. Well, the curiosity remains!

RootKitBeerCat 4y ago

Having spent about 200$ on credits… yes, it glues together your words through transformers into images… of snippets of the identified corpus of images it has… with some specific prompt phrasings having cool weighting for making really nicely looking glued together results… it’s a model: classical computing - everything is turtles and duct tape and rivets and glue, all the way down…

themodelplumber 4y ago
Fixed relationship concepts are a deeply subjective model, too, and this isn't exactly taught in school. Imagining that one knows "the" relationship between even two really obvious things can be the sign of a closed mind, or a mind which locks out new perspectives. This can be even more true, the more obvious the relationships may seem due to shared sensory biases. IMO this is one reason why DALL-E 2 can be helpful for conceptualizing. If the user is open, DALL-E 2 can make mistakes and still teach you things through those same mistakes. Unfortunately the relationship between DALL-E 2 and the user, so to speak, is also perceived as relatively fixed by members of the tech community, so highly do they rate their own ability to tell how "good" such a model is, etc.

modeless 4y ago

I mean, that's what I do all day as a human, so why shouldn't an AI do it too? DALL-E 2 isn't as good at it as I am, but a decade or two from now?

rexreed 4y ago

Who said machine learning had anything to do with "understanding" or "reasoning"? There's no reasoning or understanding in these systems. Just probabilistic computations based on big data. And before you go saying "but that's how your brain works too", that's not the case. Because your brain can do a heck of a lot more than these big data magic tricks that we call machine learning can do.

bradgessler 4y ago

I make a living “gluing things together” and calling it software.

smusamashah 4y ago

I found that 'painting' or 'art' style does generate what you really asked for. Photos failed so often. e.g. "a monkey touching an iguana" https://imgur.com/a/5u0YNMe https://imgur.com/a/5u0YNMe These are the only 3 prompts I tried. First image in two of them painted exactly what I asked for when added painting/artwork. It did fail at 'a teacup under a cylinder' though https://imgur.com/a/owmnt5j https://imgur.com/a/owmnt5j

Sateeshm 4y ago

It definitely does not know what the image is. Generating variations of fireman with a hose resulted in a bunch of gardeners with hats that kinda look like fireman image but clearly gardeners