
🔥 Introduction:
The recent popularity of AI is undeniable, and names like Midjourney, Stable Diffusion, and DALL‑E 3 are now household words. Are you also curious about how these magical AI drawing tools turn text into stunning images? Today, we'll use plain language to reveal the secrets behind AI image generation and explore the past and present of AI drawing!
🤔 AI Image Generation, Where Did It Come From?
To talk about AI image generation, we have to mention several key milestones in its development history:
1. Early Exploration: GAN and Deep Dream
2014: GAN (Generative Adversarial Network)Remember GAN, which made AI drawing "show its first signs of brilliance" in 2014? It's like two "debaters," one responsible for drawing (the generator) and the other for criticizing (the discriminator). The drawing one tries desperately to make its drawings look more real, and the criticizing one tries desperately to find flaws in the drawings. The two "love and kill each other" in this way, and in the end, the level of the drawing one gets higher and higher, and the things it draws are enough to be fake!

Midjourney's early versions borrowed from the idea of GAN!
2015: Deep DreamGoogle's Deep Dream is more like an advanced filter. It throws the image into a "kaleidoscope" and then frantically "imagines" the image based on what it "sees". The result? Mmmm…you might see a lot of weird eyes and animal faces…

Although a bit "magical", Deep Dream is also a bold attempt at AI drawing!
2. Huge Breakthrough: DALL‑E Series
OpenAI's DALL‑E series is the "leader" in the AI image generation world! Its biggest breakthrough is the realization of the "text → image" leap!
- 2021: DALL‑E 1The core technologies of DALL‑E 1 are GPT‑3 and VAE.
- GPT‑3 (Transformer): Like a super "translator", it is responsible for translating your text instructions into "whispers" that AI can understand.
- VAE (Variational Autoencoder): Responsible for turning "whispers" into pictures. It first encodes and compresses the image, and then adds a normal function so that there are multiple results to refer to when the image is decoded and restored.
- GPT‑3 (Transformer): Like a super "translator", it is responsible for translating your text instructions into "whispers" that AI can understand.
- 2022: DALL‑E 2
DALL‑E 2 has switched to more powerful "weapons": CLIP and Diffusion!- CLIP (Contrastive Language-Image Pre-training): This time, the translator is directly upgraded to a "matchmaker", which can quickly match the common features of text and images.Diffusion (Diffusion Model): This is the "new favorite" of AI drawing! It first adds "noise" to the image, and then "denoises" it step by step to finally generate a clear image.
- CLIP (Contrastive Language-Image Pre-training): This time, the translator is directly upgraded to a "matchmaker", which can quickly match the common features of text and images.Diffusion (Diffusion Model): This is the "new favorite" of AI drawing! It first adds "noise" to the image, and then "denoises" it step by step to finally generate a clear image.
- 2023: DALL‑E 3DALL‑E 3 integrates CLIP, VAE and Diffusion, and its capabilities are even better!
3. A Hundred Flowers Bloom: Midjourney and Stable Diffusion
- MidjourneyMidjourney is known for its unique artistic style, and it draws on the ideas of GAN and CLIP. It is easy to operate and suitable for novice users.
- Stable Diffusion
Stable Diffusion is the "star" of the open source world. It is based on the Diffusion model and provides users with more control, but it also tests the "tuning" ability.

⚔️ Comparison of the Three Giants: Which is Better?
- Midjourney: Stunning visual effects, but coherence is sometimes lacking.
- DALL‑E 3: Better coherence, but the visual effects may be slightly inferior.
- Stable Diffusion: An all-rounder with the strongest controllability, but also the highest difficulty to get started.
🚀 Future Outlook
AI image generation technology is still developing rapidly. In the future, we can expect:
- Higher definition and more realistic images
- More personalized and controllable creation
- Wider application scenarios (games, design, education…)
AI image generation has a bright future!
I hope this "plain language" popular science can give you a clearer understanding of the underlying technology of AI image generation. If you find it useful, don't forget to like, share, and follow!
Must log in before commenting!
Sign Up