Let us appreciate the state of AI imaging now by comparing with AI in 2022

A viral Reddit comparison has starkly illustrated the breakneck progress in AI image generation over the past two years. The post, by user danque, juxtaposes images created by 2022-era models like Midjourney v4 and DALL-E 2 with outputs from today's state-of-the-art systems, including Midjourney v6, DALL-E 3, and Stable Diffusion 3. The differences are not incremental but revolutionary. Prompts that once yielded distorted figures, nonsensical text, and muddy, impressionistic blobs now produce crisp, photorealistic scenes with accurate lighting, coherent anatomy, and intricate detail. This visual evidence underscores a fundamental shift from models that vaguely interpreted prompts to systems that understand and execute complex compositional requests with high fidelity.

The comparison highlights specific areas of monumental improvement. Text rendering within images, once a notorious weakness, is now largely solved, with models correctly spelling words on signs and products. Coherence in multi-subject scenes has dramatically increased, with models properly handling spatial relationships and interactions between characters. Furthermore, stylistic control has become far more precise, allowing users to reliably generate images in specific artistic genres or photographic styles. This leap is attributed to advances in model architecture, vastly larger and higher-quality training datasets, and more sophisticated training techniques like reinforcement learning from human feedback (RLHF). The progress suggests that the core challenge of generating high-quality static images from text is rapidly approaching a solved problem, shifting the industry's focus toward video generation, 3D asset creation, and real-time applications.