Model quantization is reducing the numeric precision of a model's weights, for example from 16-bit to 8-bit or 4-bit values. The model then needs less memory and runs faster.
FinOps is an operating practice that brings engineering, finance and business teams together to manage cloud spending. Teams share visibility of costs and make trade-offs between speed, quality and spend.
A small language model is a language model with relatively few parameters, built to run cheaply and quickly on a single server, device or private environment.
Edge AI is running machine learning models directly on devices or local hardware instead of a cloud server. Phones, cameras, vehicles and factory gateways are typical hosts.
Inference is running a trained model to produce an output, as opposed to training it. In production this is where most of the cost, latency and scaling work of an AI feature sits.
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