Image Generation

4 milestones in AI history

Generative Adversarial Network architecture diagram
ResearchDeep Learning Breakthrough

Generative Adversarial Networks (GANs)

Ian Goodfellow introduced GANs — two neural networks (generator and discriminator) competing against each other, one creating fake data and the other trying to detect it. The concept allegedly came to him during a bar conversation. Yann LeCun called GANs 'the most interesting idea in the last 10 years in ML.'

Ian GoodfellowUniversité de Montréal
AI-generated image by DALL-E
ResearchThe Transformer Era

DALL-E: Text to Image Generation

OpenAI unveiled DALL-E, a model that could generate images from text descriptions — 'an armchair in the shape of an avocado' became iconic. Built on GPT-3's architecture adapted for images, it showed that language models could bridge the gap between text and visual creativity.

OpenAI
Astronaut riding a horse, iconic Stable Diffusion generated image
Open SourceGenerative AI Revolution

Stable Diffusion: Open-Source Image Generation

Stable Diffusion was released as a widely available text-to-image model that could run on consumer hardware, with model weights distributed under an open release rather than an API-only product. Unlike DALL-E, anyone could download it, run it locally, and build on top of it. An explosion of community modifications, fine-tunes, and applications followed.

Emad MostaqueStability AICompVis (LMU Munich)
Midjourney AI image generation logo
ProductGenerative AI Revolution

Midjourney V5: Photorealistic AI Art

Midjourney V5 produced images so photorealistic that AI-generated photos went viral and were mistaken for real photographs — including a fake image of the Pope in a puffer jacket and fake photos of Trump's arrest. The line between AI-generated and real imagery effectively dissolved.

David HolzMidjourney

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