What are some effective techniques for reducing AI latency?
There are several techniques to reduce AI latency, including model optimization, hardware acceleration, and data preprocessing.
Can you explain model optimization?
Model optimization involves simplifying the model architecture, pruning unnecessary parameters, and quantizing weights to speed up inference.
What about hardware acceleration?
Hardware acceleration uses specialized hardware like GPUs or TPUs to perform computations faster than traditional CPUs.
How does data preprocessing help?
Data preprocessing reduces the amount of data that needs to be processed by the model, which can significantly lower latency.
Are there any tools to help with these techniques?
Yes, tools like TensorRT, ONNX Runtime, and TensorFlow Lite can assist in optimizing models and improving performance.
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