How Deepgram optimized voice AI at scale with AWS Trainium
Deepgram worked with the AWS Forward Deployed Engineering team to port its Nova-3 speech-to-text model to AWS Trainium2 for offline batch inference. This post covers porting to the AWS Neuron stack, kernel-level tuning, a data-parallel Rust runtime, and the throughput and cost results on batch transcription.
What happened
Deepgram worked with the AWS Forward Deployed Engineering team to port its Nova-3 speech-to-text model to AWS Trainium2 for offline batch inference. This post covers porting to the AWS Neuron stack, kernel-level tuning, a data-parallel Rust runtime, and the throughput and cost results on batch transcription.
Why it matters
The financing changes available capital and competitive capacity around Amazon; terms and investor participation remain key.
Affected entities
View evidence
2 reports · 1 original report · 2 independent
- AWS Machine Learning BlogPrimary source · Supports · EN · 100%How Deepgram optimized voice AI at scale with AWS Trainium ↗
- Hugging FaceIndependent · Supports · EN · 49%TorchNeuron: running HF models on AWS Trainium is easier than ever ↗
Claims
- How Deepgram optimized voice AI at scale with AWS Trainium Observed
Conflicts
No material conflict detected in the available evidence.
Timeline
- First reported
- Primary source · 74/76%
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