AI-Generated Images have been all over social the last 6 months, no wonder why we see how many AI image generators have been launched: Dall-E, Midjourney, Stable Diffusion, and Argil.
While some are super skeptical in regard to this hype, we focused our AI Images positioning on practical and actionable features to solve concrete image-related challenges in various industries.
In today's article, we’ll get through that and explain how important it is for you to grasp the applicability areas of AI-generated images.
Let's dive right in.
Want a concrete example? Let’s get straight to that:
Imagine you're a designer working on a project. The client wants a unique background, something that's never been seen before.
You could spend hours, days even, creating that perfect image. But what if an AI could do it for you?
And that is based on a single text description shared by your potential clients. You now can send him drafts on the same day he contacted you, thus increasing the probability of making a deal.
How does it work?
AI image generation is all about training machines to create unique, visually appealing images. A subfield of AI called Generative Adversarial Networks (GANs) is behind this wizardry.
Two neural networks, the generator, and the discriminator, work together. The generator creates images, the discriminator critiques them, and the cycle continues until the AI produces a satisfactory image.
Let's consider a few industries where AI-generated images are making a significant impact:
Customers love personalization. Imagine an online clothing store that can generate images of a customer wearing the clothes they're interested in. AI can do that.
You can already do that on Argil, with our fine-tuning features it’s possible for you to train an AI model on yourself and your products, streamline that creation to a notion folder for example and directly upload them to your product page.
Real estate agents often struggle to sell properties under construction. AI can generate images of the finished property, helping potential buyers visualize the end result.
This works even better for interior designs brands:
You need to rent an apartment/close a client but fail to provide enough projection in the future apartment.
Using Image to Image features will give you the hand on that:
You input the image of an empty apartment and give a specific description about how you want it to be equipped, the AI will do it for you and you can now share it with your client.
Game designers spend countless hours creating intricate, detailed environments. AI can generate realistic, high-resolution images to aid in world creation, speeding up the design process significantly.
Big players like Nvidia have already begun using AI for image generation in their game design processes.
And we’re just months before it’s possible to create super high-quality 3D scenes based on a single text input.
Here's a quick rundown of how AI-generated images can benefit you and your business:
Benefits of AI-Generated ImagesWho Stands to GainEfficiency: AI can generate images faster than any human designer, saving time and resources.
Designers looking to streamline their workflow. Personalization: AI can generate images tailored to individual customers, enhancing the user experience.
Marketers aiming to improve customer engagement through personalized content.Potential: AI can visualize things that don't yet exist, opening up new possibilities for business.Entrepreneurs searching for innovative ways to enhance their business processes.
That's the question on everyone's mind, isn't it?
Well, the answer is both simpler and more complex than you might think.
AI is a tool, not a replacement. Yes, it can generate images, but it can't replicate the creativity and intuition of a human designer (yet).
Think of it as a paintbrush. A paintbrush doesn't replace the painter; it merely aids them in their work.
What will happen however once the tool became better than the user?
This a good question only time will answer.
At Argil, we’re not just providing efficient Ai workflows but also targeting the AI-generated images market.
While there are plenty of competitors, none of them in industry agnostic, and they’re still relying too much on prompting (the process of giving a specific description to the AI model to create an image).
We aim to provide you with the AI Image studio on steroids, with unique features such as:
We’re just at the tip of the iceberg in regard to all the potential use cases for Image generation on Argil, but to push this further, we need your feedback and propositions.
Jump on the platform: here.