TechnicalAI glossary
Seed
The number that sets the random starting point for an image generation: it determines the initial noise that the diffusion model will then sculpt. The same prompt and the same seed give the same image again; that is why the same request, rerun with a different seed, produces a different result.
In other words
The initial shuffle of a deck of cards: same shuffle, same game; new shuffle, different game.
Alyriaz articles that mention it
- How does an AI create an image? The answer is stranger than you think.
AI image generators don't draw in the way we understand it. They start from a chaos of random pixels and progressively denoise it until an image emerges. We explain how diffusion models work, without jargon, and what this process implies about the nature of these creations.
- What are we passing on to our children when AI already knows everything?
For the first time in human history, parents are passing on to their children skills that a machine already performs better than they do. Reading, writing, arithmetic, memorising: the machine wins. So what? Few people dare to ask this question directly. And yet it is probably the most important one of our age.
- SubQ: the startup that may have killed the transformer
Since 2017 and the publication of the paper "Attention is All You Need", every major AI model has been based on the transformer architecture. SubQ, launched on 5 May 2026, is the first commercial model to break with this paradigm. Here is what changes technically, and why the AI community is deeply divided over the implications.