The basicsAI glossary
Model
The "trained brain": a vast set of numbers adjusted during training, which transforms an input (your question) into an output (the answer).
In other words
A giant cooking recipe: ingredients go in, the dish comes out.
Alyriaz articles that mention it
- Why ChatGPT is free when it costs a fortune
An AI response costs electricity and hardware. So why are so many services free? We explain who pays, why, and how long it can last.
- Why a model cannot tell whether it is in a test or in reality
An AI model only perceives the text it receives and cannot tell a test environment from the real world. We explain why, and what this means for safety.
- When a newer model scores worse than the one it replaces
A new generation of model can post lower scores than the previous one on certain tests. We explain why, what that reveals about design trade-offs, and how to choose accordingly.
- How a model can process text, sound and images at the same time
An omnimodal model handles several types of input within a single architecture. We explain the mechanism that makes this possible and what it implies.
- A single model for text, image, sound and video
Alibaba has released Qwen3.8-Omni-Flash, a model that natively handles multiple modalities with a one-million-token context window. We explain what omnimodality actually changes.
- A startup is valued at 1.4 billion and doesn't train any model from scratch
A young Chinese company reaches a $1.42 billion valuation in seven months by specialising open models rather than training them. We analyse this model and what it reveals.