Infrastructure
Quantization
Shrinking an AI model by reducing the precision of its numbers, making it faster and cheaper to run with minimal quality loss.
Definition
A technique for reducing model size and inference cost by representing weights with lower-precision numbers (e.g., 16-bit to 4-bit). Enables running large models on smaller hardware with minimal quality degradation.
Why it matters
Makes it possible to run powerful AI models on consumer hardware and dramatically reduces cloud inference costs.
Related terms in Infrastructure
API
A digital plug or messenger that lets two different software programs talk to each other.
API Gateway
The security guard at the front door of your software that checks IDs and directs traffic.
Cloud Computing
Renting powerful computers over the internet instead of buying and keeping them in your own office.
Edge AI
Running AI directly on the device (phone, camera, car) instead of sending data to the cloud, faster and more private.
From vocabulary to outcomes
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