Crucial Exams

AWS Certified AI Practitioner AIF-C01 Practice Question

Why can a transformer-based large language model usually perform inference more quickly on modern GPUs than a recurrent neural network (RNN) when both must analyze an equally long text sequence?

  • Transformers evaluate all tokens concurrently through self-attention, allowing the workload to be parallelized on the GPU.

  • Transformers cache the entire model vocabulary in GPU memory, so no additional computation is needed during inference.

  • Transformers rely mainly on convolutional layers, which require fewer floating-point operations than matrix multiplications.

  • Transformers omit positional encodings, reducing overhead compared with architectures that track token positions.

AWS Certified AI Practitioner AIF-C01
Fundamentals of Generative AI
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