What is generative AI?
Generative AI, also known as generative artificial intelligence, is a type of artificial intelligence (AI) that can create new content, such as images, text, and music. Generative AI models are trained on large datasets of existing content, and they use this data to learn the patterns and rules that govern how that content is created. Once a generative AI model has been trained, it can be used to create new content that is similar to the content it was trained on.
Generative AI has a wide range of potential applications, including:
- Artificial art: Generative AI can be used to create realistic and creative images, paintings, and sculptures.
- Photo generation: Generative AI can learn from existing photos, like portraits or headshots, to create new versions of the original subject in unique styles and environments.
- Music generation: Generative AI can be used to create new music, such as songs, symphonies, and concertos.
- Text generation: Generative AI can be used to create new text, such as poems, stories, and articles.
- Video generation: Generative AI can be used to create new videos, such as movies, TV shows, and commercials.
- Game development: Generative AI can be used to create new games, such as role-playing games, strategy games, and puzzle games.
- Product design: Generative AI can be used to create new product designs, such as furniture, clothing, and toys.
- Medical research: Generative AI can be used to create new medical models and simulations, which can be used to study diseases and develop new treatments.
- Finance: Generative AI can be used to create new financial models and simulations, which can be used to predict market trends and make investment decisions.
Generative AI is a rapidly developing field, and new applications are being discovered all the time. As the technology continues to advance, generative AI is poised to have a major impact on our world.
Here are some examples of generative AI in action:
- DALL-E 2: DALL-E 2 is a generative AI model that can create realistic images from text descriptions. For example, you could type in "a cat sitting on a keyboard" and DALL-E 2 would generate an image of a cat sitting on a keyboard.
- ChatGPT: ChatGPT is a generative AI model that can generate realistic and engaging chat conversations. For example, you could start a conversation with ChatGPT and it would respond in a way that is both informative and entertaining.
- Midjourney: Midjourney is a generative AI tool that can create realistic and unique images from your text descriptions. It is currently in beta, but it is already being used by artists, designers, and filmmakers to create stunning new works of art.
- Snapshot AI: Our first of it’s kind AI Photo Booth that takes photo inputs of people, either via upload or capture, and outputs consistent but unique versions of the person in a unique style or environment, based on an engineered prompt.
What are AI generated photos?
AI-generated photos, often referred to as synthetic images or deepfakes for images, are pictures that are created by artificial intelligence algorithms rather than being taken with a camera. These photos can range from human faces to objects, animals, landscapes, or even complex scenes. There are various techniques and technologies used to generate such images, with some of the prominent ones being:
- Generative Adversarial Networks (GANs): GANs are a class of AI algorithms used in unsupervised machine learning, and they are widely used for generating synthetic images. They consist of two networks - a generator and a discriminator. The generator creates new data samples, while the discriminator evaluates them. The aim is to train the generator to produce data that is indistinguishable from real data, in this case, images. This is what we’re using for Snapshot AI - the first AI Photo Booth
- Variational Autoencoders (VAEs): VAEs are another type of generative model that can be used for creating images. They work by encoding the data into a lower-dimensional space and then decoding it back into the original space. During this process, variations can be introduced to generate new images.
- Neural Style Transfer: This is a technique where the style of one image is applied to the content of another image. For example, an image can be transformed to look like it was painted by a famous artist. This is done by using neural networks to separate and recombine the content and style of images.
- Deep Dream: Deep Dream is a computer vision program created by Google which uses a convolutional neural network to find and enhance patterns in images, thus creating a dream-like hallucinogenic appearance.
- Procedural Generation: This technique uses algorithms to automatically create data, in this case, images. It’s often used in video games for creating textures, terrains, and other assets.
AI-generated photos have a range of exciting applications, however, they also raise ethical concerns, especially when used to create realistic images of people that do not exist or to manipulate real photos in a deceptive way. The potential for misuse in spreading misinformation or engaging in identity theft, among other issues, is a significant concern broadly associated with AI-generated photos.
At Snapbar, we’re working directly with businesses to develop unique photo experiences with a carefully engineered prompt and thorough testing to ensure the outputs are consistent, high quality, and on-brand to the intended purpose. It’s also a new technology, so there’s plenty of room for unexpected results, so let’s break it down into the 2 core elements:
AI Photo Inputs (Training Data)
This is a collection of real, existing images that the AI uses to learn from. They serve as the "ground truth" from which the model identifies patterns, details, and nuances. The input photos could be of any kind, such as human faces, animals, buildings, or landscapes. The larger and more varied this dataset, the better the GAN can learn and the higher the quality of its outputs.
In the context of our AI Photo Booth, we are training the model on a user’s face by having them capture or upload 4+ selfies, ideally from different angles and moments to train the model on their unique likeness.
AI Photo Outputs (Generated Data)
These are the images that the GAN generates. They are not reproductions or alterations of the input data; instead, they are entirely new images that the GAN has created based on its learning from the input data.
Using our AI Photo Booth example, after training the GAN on several images of a person, we can then ask it to generate a new image of that person in a unique style, circumstance, or likeness. The output image would not be a specific image from the training data but a unique, AI-generated portrait that's the product of the patterns and characteristics the GAN has learned from all the various selfie images it was trained on.
In other words, the GAN uses the patterns it recognized in the input data to generate output data that mimics the input as closely as possible. While the outputs are usually impressive, they aren't perfect and sometimes can have flaws or errors that a human observer can identify as "not quite right", which is an area of ongoing research in improving GANs.
What are AI prompts?
AI prompts are instructions or guidelines that are given to a generative AI model to help it generate text, images, or other creative content. They can be as simple as a single word or phrase, or as detailed as a paragraph or even an entire essay. The goal of a good AI prompt is to provide the model with enough information to generate the desired output, while also being specific enough to prevent the model from generating something that is irrelevant or nonsensical.
Here are some guidelines we follow for writing effective AI prompts:
- Be specific. The more specific you can be in your prompt, the more likely the model is to generate something that is relevant and on-topic.
- Use keywords. When possible, use keywords that are related to the desired output. This will help the model focus its attention on the relevant information.
- Provide examples. If possible, provide examples of the desired output, like a particular artistic style or photography effect. This will help the model understand what you are looking for.
- Be creative. Don't be afraid to experiment with different prompts and see what works best. There is no one right way to write an AI prompt, so the best way to find out what works is to try different things.
What is a negative prompt in AI?
A negative prompt in AI is a type of prompt that tells a generative AI model what not to include in the generated output. This can be used to fine-tune the output of the model and to ensure that it does not generate images that contain certain elements or features.
Negative prompts are typically written in natural language and can be as simple as a single word or phrase, or as detailed as a paragraph or even an entire essay. When writing a negative prompt, it is important to be as specific as possible. The more specific the prompt, the more likely the model is to avoid generating the unwanted content.
Negative prompts are important for fine tuning, but they can also have unexpected effects on the quality and output consistency. This is why we do extensive testing before going live with any AI Photo Booth activation - as with any new technology, you can’t control for or predict everything that might happen.
What can go wrong with AI photo generation
In the use case of business and our AI Photo Booth, there are some very standard negative prompts we use to ensure all outputs are PG and ‘safe for work’, but we still get some surprising variation at times, and inconsistencies. Here are some of the common things we’ve seen that we’ll continue to refine out of our models:
- Inconsistent faces - this one is somewhat common and largely dependent on the quality of the training data. If people upload poor quality photos, or photos with a lot of other elements that confuse the training model, it will improvise and sometimes the final result is a bit odd
- Unexpected artifacts - depending on the style of the output and how much background, landscape, or other elements there are in the image, sometimes you get unexpected things added to the photos
For these reasons, we always provide 8 unique outputs for each user, making it highly likely that at least a couple will be truly amazing, one-of-a-kind AI creations they’ll be super excited about.
What is an AI photo generator?
An AI photo generator is a tool that uses artificial intelligence to generate realistic images from text. These generators are trained on a dataset of images and their corresponding descriptions. When you then give the generator a text prompt, it will generate an image or set of images that match the description as closely as possible.
AI photo generators can be used for a variety of purposes, such as:
- An AI Photo Booth. Our newest product and the first of it’s kind, offering businesses, events, and marketers a completely novel and fun way to generate amazing photo outputs of people based on selfies they upload or capture, and a unique prompt we work with each client to develop.
- Generating inspiration for your creative projects. If you're a writer, artist, or designer, AI photo generators can help you come up with new ideas. For example, you could use an AI photo generator to generate images of different landscapes, characters, or objects. These images could then inspire you to write a story, create a painting, or design a new product.
- Visualizing ideas. If you have an idea for a product, service, or marketing campaign, but you're having trouble visualizing it, an AI photo generator can help. Simply describe your idea to the generator, and it will generate an image that shows you what your idea could look like.
- Exploring different scenarios or concepts. AI photo generators can be used to explore different scenarios or concepts. For example, you could use an AI photo generator to generate images of different historical events, scientific discoveries, or fictional worlds. These images can help you better understand these events, discoveries, or worlds.
- Simply for fun. AI photo generators can also be used for fun. For example, you could use an AI photo generator to generate images of your favorite characters, places, or things. You could also use an AI photo generator to generate silly or funny images.
How Snapshot AI, our AI photo booth works
Snapbar’s innovative photo booth platform uses custom-prompts we develop with each client along with cutting-edge AI to dynamically transform photos into captivating, themed visuals. You can now use our AI Photo Booth to bring excitement and engagement to any events, campaign, or any other use-case we haven’t thought of yet.
The AI Photo Booth User Experience
- Someone reaches the AI photo booth via QR code, link, or even with an in-person setup and will see your custom-branded landing page
- After accepting a customizable disclaimer and entering their email for delivery, they will upload or capture 4+ selfies or images of themselves based on some standard guidelines we provide
- The AI magic works in the background, training the AI model on the provided images, and then generates 8 one-of-a-kind AI images based on that person and the prompt we developed for that specific photo booth
- If included in the experience, any additional photo manipulations will occur automatically, like applying overlaid filters, logos, or branding
- Users receive an email 10-20 minutes later with their amazing photo creations for them to download and share
If you’d like to learn more or get a quote for your own Snapshot AI activation, get in touch with us today!