What is Quantisation?
Reducing the precision of numbers in an AI model to make it smaller and faster without losing much accuracy.
Why It Matters
Quantisation allows large AI models to run on consumer hardware and mobile devices.
Real-World Example
Converting a model from 32-bit to 8-bit precision to run it on a laptop instead of a data centre.
“Understanding terms like Quantisation matters because it helps you have better conversations with developers and make smarter decisions about your software. You do not need to be technical. You just need to know enough to ask the right questions.”
Related Terms
Model Distillation
Creating a smaller, faster AI model that mimics the behaviour of a larger, more capable one.
Inference
The process of using a trained AI model to generate predictions or outputs from new input data.
Edge AI
Running AI models directly on local devices like phones or sensors rather than in the cloud.
Large Language Model (LLM)
An AI system trained on massive amounts of text that can understand and generate human language.
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Related Terms
Large Language Model (LLM)
An AI system trained on massive amounts of text that can understand and generate human language.
Model Distillation
Creating a smaller, faster AI model that mimics the behaviour of a larger, more capable one.
Inference
The process of using a trained AI model to generate predictions or outputs from new input data.
Edge AI
Running AI models directly on local devices like phones or sensors rather than in the cloud.
Transformer
A type of AI architecture that processes text by paying attention to relationships between all words at once, rather...
Attention Mechanism
A technique that lets AI models focus on the most relevant parts of the input when generating output.