Cost-optimizing AssemblyAI speech-to-text inference on AWS with Amazon EC2 Spot

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Speech-to-text inference is computationally intensive. Each audio file triggers a pipeline of deep learning models (acoustic models, language models, and post-processing stages) running on NVIDIA GPUs to meet latency requirements. At scale, this means thousands of GPU instances running continuously. AssemblyAI needed a way to run GPU-intensive inference workloads cost-effectively at scale, without sacrificing the availability and latency guarantees their customers depend on. Running entirely on…