How Zencastr transcribed hundreds of years worth of audio in just a few days

This post details Zencastr's migration from managing their own Kubernetes GPU nodes to Modal for AI workloads, specifically speech transcription. Key contributions include: 1. Demonstrating cost savings through Modal's true scale-to-zero capability for spiky transcription workloads. 2. Highlighting seamless management of remote environments and dependency management via Modal Images and pre-installed CUDA drivers. 3. Showcasing flexibility in experimenting with different GPU models and concurrency settings for performance trade-offs. 4. Illustrating a large-scale batch audio processing architecture using Modal Functions, S3 Gateway endpoints, and Modal Volumes, culminating in a successful scale-up to 1,500 concurrent GPUs.