I’ve been seeing this new genre of memes on Instagram recently. They go like “X: Died 1992 / Y: Born 1992 / Welcome back, X”. Since ChatGPT can make educated guesses about images, I’ve let it write an interpretation of such a meme. Results below.
An example of the kind of meme I’m talking about (source: knowyourmeme)
My prompt wasn’t really that much sophisticated, but sufficient, as I’m happy with the result.
Below is ChatGPT’s reply. I’m (somewhat) impressed by the fact that it has recognized that the humorous part of the meme revolves around the concept of reincarnation.
ChatGPT:
The meme juxtaposes two seemingly unrelated events: the Chernobyl disaster of 1986 and the birth of a popular figure in the same year, creating a humorous connection through the concept of reincarnation.
The left side shows a historical photo of the Chernobyl nuclear disaster site with the text “Died 1986,” while the right side shows a contemporary portrait of the individual with the text “Born 1986,” with a caption that humorously welcomes back the Chernobyl Reactor 4, personifying it.
The meme’s humor derives from the absurd idea of a nuclear reactor being reincarnated as a person. The use of a well-known individual intensifies the effect as it plays on their public image and the fame they have achieved. It’s a simple but effective piece of internet humor that relies on the viewer’s knowledge of both the historical event and the person’s identity to land the joke.
For my next trick, I’ll pick a more advanced meme to be interpreted. Stay tuned.
In other news: I’m working towards becoming a verified builder on OpenAI! So hopefully soon I’ll be able to publish FreudGPT (and my other GPTs).
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.
Go on ChatGPT. You need to have the subscription in order to use DALL-E 3, at least at the time of writing this.
Make sure to select ChatGPT 4 as a model in the upper left corner.
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
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.
Imgflip has an AI meme generator. I’ve tested it several times, and so far it has failed to impress me. Its extreme randomness, however, is sometimes entertaining. Let’s look at some memes I have generated.
Memes have become a cultural phenomenon, a form of digital communication that spreads virally and permeates social media. From Grumpy Cat to the Success Kid, memes have become a ubiquitous part of our online experience. With the rise of artificial intelligence (AI), it was only a matter of time before AI-generated memes entered the scene. However, while these memes may seem like a fun novelty at first glance, they lack the humor and originality of their human-generated counterparts.
One of the key appeals of memes is their relatability. They often draw on shared cultural references or experiences, and their humor often stems from a clever twist or subversion of expectations. While AI-generated memes may be able to mimic the structure and style of a traditional meme, they often lack the cultural awareness and contextual understanding needed to create truly relatable or humorous content.
Additionally, AI-generated memes often rely on the same set of pre-existing templates or templates generated from a specific dataset, leading to a lack of originality. This can make them feel repetitive or unoriginal, ultimately diminishing their impact and entertainment value.
Moreover, AI-generated memes can also perpetuate harmful stereotypes or offensive content, particularly when the algorithms are trained on biased or problematic data. Without the critical eye and moral judgment of a human creator, these memes can spread harmful or insensitive content that may be damaging to certain communities.
Of course, this is not to say that AI-generated memes can never be funny or entertaining. There have been some instances where AI-generated memes have garnered attention and humor, such as the popular “This Person Does Not Exist” meme. However, it is important to recognize the limitations and potential drawbacks of relying solely on AI to create memes.
In conclusion, while AI-generated memes may seem like a fun and novel way to explore the capabilities of artificial intelligence, they often lack the cultural awareness, originality, and humor of their human-generated counterparts. As we continue to integrate AI into our daily lives, it is important to remain critical of its limitations and potential biases, and to recognize the value of human creativity and humor in the digital landscape.
Here’s what imgflip says about their image generator:
Find a good one? Save it and submit it to the AI Memes stream!
These captions are generated by a deep artificial neural network. Nothing about the text generation is hardcoded, except that the maximum text length is limited for sanity. The model uses character-level prediction, so you can specify prefix text of one or more characters to influence the text generated. Using someone’s name or other short text as a prefix works best.
The network was trained using public images generated by users of the Imgflip Meme Generator for the top 48 most popular Meme Templates. Beware, no profanity filtering was done on the training data so you may encounter vulgarity.
Curious about the technical details of building the network? Check out the accompanying article Meme Text Generation with a Convolutional Network in Keras & Tensorflow.
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