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TENESYS AI NEWS tracks the most important AI news and explains what changed, why it matters and whether a technology is worth testing.

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“Speech-to-Text” — 3 articles ✕

Voice AI· Important· 🧪 Worth Testing

Deepgram cuts batch transcription costs by porting Nova-3 to AWS Trainium2

AWS and Deepgram jointly rebuilt the Nova-3 speech-to-text model to run natively on Trainium2 chips instead of standard GPU-based PyTorch setups, targeting large offline transcription jobs. The work involved rewriting bottleneck layers as custom kernels and replacing Deepgram's Python serving layer with a Rust runtime calling Trainium directly. The result: a single trn2.3xlarge instance running eight parallel model copies delivers 11-70% more transcribed audio per dollar than Deepgram's prior infrastructure, with similar savings potentially available to customers self-hosting on SageMaker.

AWS Machine Learning
Models· Important· 🧪 Worth Testing

IBM combines transcription, decision-making and chat in a single Granite Switch model

IBM has released Granite Switch 4.1 in 8B and 30B sizes, a modular system that runs chat, decision-making and speech transcription from one hosted endpoint instead of separate models. The update adds a general-purpose Decision adapter, a specialized Guardian adapter for safety-related classifications, and an embedded ASR model, Granite-Speech-5.0-Turbo-CTC, which tops the OpenASR Leaderboard. Despite bundling three capabilities, the combined model uses roughly the same VRAM as the base model alone.

Hugging Face
Voice AI· Important· 🧪 Worth Testing

Deepgram's Flux STT cuts unwanted interruptions in Anam's avatar conversations by ~50%

Anam, which builds photorealistic interactive avatars, switched to Deepgram's Flux speech-to-text model to solve turn-taking problems in unscripted, real-time conversation. In A/B testing against a self-hosted open-source STT option, Flux cut unwanted avatar barge-ins by roughly 50% with no added latency penalty, and complaints about turn-taking on English sessions dropped to near zero. Anam deployed Flux self-hosted on its own Kubernetes/H100 infrastructure, rolling it out to 100% of turnkey users after a two-week self-hosted deployment (versus days for Deepgram's hosted option).

Deepgram