Swetlana AI

Category: DALL-E

  • My New Insta Account / Cultural Implications of AI Memes

    My New Insta Account / Cultural Implications of AI Memes

    Since AI can now make memes, I decided to create an Instagram account purely for AI-generated memes. It’s probably safe to assume that such accounts will start popping up on larger scale in the future, since DALLE-3, which has become so much better at generating text. In this article I also briefly address what the emergence of AI-generated memes means for us culturally.

    Sunsets and stuff

    As you can see the topics of my memes are pretty random, so far I’m just experimenting. I might continue keeping it general and not “niched down” on any subject, because this is not about the subject, but more about the creation process (and its creator – ChatGPT 4/DALLE-3).

    I will keep you updated on this development. In the meantime, I again joined Twitter/X, as Swetlana AI. Let’s see how long I’ll last there.

    What would Deleuze say?

    So AI is making memes now. What does all this mean culturally? Let’s ask BenjaminGPT. But before we do that, why don’t we ask all the other philosophers.

    Here’s how other philosophers would see this. I asked ChatGPT, below is a short summary of several approaches.

    The replies are fairly vague, but they could be expanded. Each of the following ideas could potentially become a book, and I could make a big fuzz about it. Soo many rabbit holes. Especially given the fact that these philosophers weren’t around when memes themselves became a thing.

    Foucault thinking about AI

    Jean Baudrillard:
    Simulation and Hyperreality: Baudrillard’s work on simulation and hyperreality explores how the distinction between reality and its representation becomes blurred. AI-generated art and memes would be a fascinating case study for his theories, as they represent a new level of simulation, where the artwork is not just a representation but a creation of an algorithm.

    Arthur Danto:
    The End of Art: Danto argued that art reached its “end” in the sense that anything could now be considered art. AI-generated art could be a perfect example of this, challenging traditional notions of creativity and authorship.

    Martin Heidegger:
    Technology and Being: Heidegger explored the relationship between humans and technology, arguing that technology shapes our understanding of the world and ourselves. He might be interested in how AI as a technology influences our conception of art and creativity.

    John Dewey:
    Art as Experience: Dewey saw art as a participatory and experiential process. He might be interested in exploring how AI-generated art fits into this framework and what it means for the experience of both the creator and the viewer.

    Gilles Deleuze and Félix Guattari:
    Rhizomes and Deterritorialization: Their work on rhizomes and deterritorialization could provide a lens through which to understand the decentralized, non-hierarchical nature of AI-generated content, and its potential to challenge traditional artistic and cultural structures.

    Theodor Adorno:
    Culture Industry: Adorno critiqued the commodification of culture and the arts. AI-generated memes and art, often created for quick consumption and viral potential, could be seen as an extension of the culture industry, raising questions about originality, authenticity, and the commodification of creativity.

    Marshall McLuhan:
    The Medium is the Message: McLuhan’s famous phrase could be applied to AI-generated art and memes, exploring how the medium of AI shapes the content, meaning, and impact of these artworks.

    Ludwig Wittgenstein:
    Language and Meaning: Wittgenstein’s later work explored how language games shape our understanding of the world. AI-generated memes, which often play with language, imagery, and cultural references, could be an interesting area of exploration in this context.

    Philosophers in a room

    … and Walter Benjamin

    Walter Benjamin, who has been my subject of admiration multiple times, has been dealing with the aura/authenticity of images a lot. Again, I asked ChatGPT (damn, am I lazy?), here’s the reply:

    Walter Benjamin, a German Jewish philosopher and cultural critic, was deeply interested in the role of art, media, and technology in society. He is most famous for his work “The Work of Art in the Age of Mechanical Reproduction,” in which he explores how the reproduction of art changes its perception, value, and role in society.

    If Walter Benjamin were alive to witness the advent of AI-generated memes and art, he would likely have much to say on the subject. Here are a few themes he might explore:

    1. Authenticity and Aura: Benjamin argued that mechanical reproduction (like printing or photography) strips an artwork of its “aura”—the unique presence and authenticity it has when encountered directly. He might see AI-generated art as a further extension of this trend, as these works are generated algorithmically and can be easily replicated.
    2. The Democratization of Art: On the other hand, Benjamin also saw potential in mechanical reproduction to democratize art, making it more accessible to the masses. He might see AI-generated memes and art as a continuation of this trend, as they allow for the rapid creation and dissemination of visual content.
    3. The Role of the Artist: Benjamin believed that mechanical reproduction had the potential to change the role of the artist in society. With AI-generated art, this change is even more pronounced, as the “artist” becomes a programmer or data scientist, and the creative process is mediated by algorithms.
    4. The Impact on Perception: Benjamin was interested in how changes in art and media influence perception and consciousness. He might explore how the prevalence of AI-generated content changes the way we see and understand the world, as well as how it shapes our tastes, values, and expectations.
    5. Political Implications: Benjamin was deeply concerned with the political implications of art and media. He might investigate how AI-generated memes and art are used for political purposes, exploring how they can both challenge and reinforce power structures.

    Overall, Walter Benjamin would likely approach the phenomenon of AI-generated memes and art with a critical eye, seeking to understand its implications for art, society, and politics. His work provides a valuable framework for thinking about these issues, highlighting the complexities and contradictions inherent in the intersection of art, technology, and society.

  • ChatGPT x DALL-E 3: Creating Memes and Artwork

    ChatGPT x DALL-E 3: Creating Memes and Artwork

    ChatGPT can now produce images! 🤯 And they are shockingly accurate. Today I’m trying out the new image generation feature (DALL-E 3!), and I’m definitely thrilled by the possibilities. This is way more exciting than Midjourney or standalone Stable Diffusion. And yet again I feel distracted from my recent project (on which I will update you in time). Yay!

    I asked DALL-E 3 to create a meme illustration about gentrification

    Ok, so this development is already a month (or so) old, so I’m a bit late to the party. But hey, better late than never.

    In this article I’m including some memes and illustrations (particularly interesting for POD designers, and, well, illustrators).

    How To Use DALL-E 3

    First things first — here is how you can access DALL-E 3. It’s fairly simple.

    1. Go on ChatGPT. You need to have the subscription in order to use DALL-E 3, at least at the time of writing this.
    2. Make sure to select ChatGPT 4 as a model in the upper left corner.
    3. Write a prompt! It’s perfectly fine to keep it simple, you will achieve interesting results anyway, as ChatGPT will do the thinking for you

    Example Prompts for DALL-E 3

    A simple short prompt will go a long way. Try things like:

    • Create an image of a hedgehog in the rain
    • Make a meme about a messy kitchen
    • Create a logo for my bakery
    • Create a meme about my friend Janet who is always late

    Especially the latter point is proving to be very interesting for me, as I love surprising my friends with some crazy imagery. Best thing you can do is experiment a bit, and see what comes out. Oftentimes the results are entertaining.

    Memes

    So the first thing I’ve tried was to generate memes, as I keep seeing AI-generated memes all over my social media. 

    As you can see there are barely any typos, which is pretty impressive

    And the beautiful thing here is that ChatGPT comes up with its own prompt, adding new thoughts to your idea. At this point, it basically does all the (conceptual) thinking. 

    You might be wondering: how is DALL-E handling text / alphabet characters displayed in images? Well, it got waay better, although of course there are occasional glitches. Compared to earlier versions of DALL-E though this is a significant improvement. I also like the font used here.

    As you can probably guess, the sky is the limit here. Generating this type of content like this could be a game-changer for anyone who wants to run, say, a meme Instagram account.

    Illustrations and Shirt Designs

    But wait, there’s more. Memes obviously weren’t enough, so I went straight ahead to shirt design illustrations. And as a “seasoned artist”, I have to say I’m impressed. To check for possible copyright breaches, I performed a Google image search for several of these designs, and found nothing similar enough.

    For this one, I told ChatGPT to create a meme about gentrification:

    ChatGPT came up with the slogan “When the block gets a little too hip”, pretty funky idea

    And here is an illustration about marketing, or made FOR the marketer. This one is a bit more glitchy, maybe because of the amount of words involved:

    And while it has errors and glitches, it’s conceptually still a great idea that could work well on a shirt. Personally for me I have decided that I definitely will use this as an inspiration for my actual designs.

    Of course I made more than these images, so if you’re curious, you might as well ask me. You can get in contact via my contact form

    or Instagram, for example: https://www.instagram.com/swetlana_ai/

    Here’s one more about boomers and millennials:

    ChatGPT and DALL-E 3

    Here’s what all the fuzz is about: ChatGPT now offers a unique image creation feature for Plus and Enterprise users. Simply describe your vision, and ChatGPT will provide visuals for you to refine and request revisions in the chat.

    DALL·E 3 is a highly advanced image model resulting from extensive research, offering visually stunning and detailed images. It excels in handling detailed prompts, supports various aspect ratios, and focuses more on user-supplied captions. 

    With DALL·E 3, you can unleash your creativity like never before. The only BUT: it doesn’t replicate the style of living artists. Additionally, you have the option to exclude your images from future model training. Learn more in their research paper here.

    Here’s the summary of the research paper: 

    Recent advancements in generative modeling have significantly improved text-to-image generative models. These improvements stem from two main approaches: using sampling-based methods like autoregressive generative modeling or diffusion processes, which break down image generation into manageable steps for neural networks. Additionally, researchers have developed image generators based on self-attention layers, separating image generation from convolutional spatial biases and leveraging transformer scaling properties.

    When coupled with large datasets, these approaches enable the training of text-to-image models that can produce imagery approaching human-quality photos and artwork. However, a key challenge in this field is “prompt following,” where models often struggle to capture word meanings, order, or context in given captions.

    Several works have highlighted this challenge, proposing various solutions. This paper introduces a novel approach to address prompt following: caption improvement. The authors believe that the poor quality of text-image pairings in training datasets is a fundamental issue. To tackle this, they develop a robust image captioning system to generate detailed, accurate descriptions for images, enhancing the dataset’s captions. Subsequently, they train text-to-image models on this improved dataset.

    While training on synthetic data is not new, this work focuses on the development of a descriptive image captioning system and assesses the impact of using synthetic captions in training generative models. The paper primarily evaluates the enhanced prompt following capabilities of DALL-E 3, achieved through training on highly descriptive generated captions. It does not delve into the technical details of the DALL-E 3 model but provides an overview of the training strategy, evaluations, and discussions of limitations and risks.