Deepgram added Enhanced Metrics to its Deepgram speech-to-text and text-to-speech deployments on Amazon SageMaker AI to close gaps in billing and performance observability. The billing transparency stream reports ConsumedUnits, using the same metered inference-unit values that drive AWS Marketplace metered billing. The result is CloudWatch metrics for per-request billing/feature usage plus engine and per-GPU visibility via Prometheus and OpenTelemetry within SageMaker’s detailed observability, without deploying an agent, sidecar, or collector.
Nvidia reportedly agreed to buy Hugging Face for $12.9 billion, which would place an open-model hub and deployment platform used by developers under Nvidia control. The deal centers on Hugging Face’s “defaults” and hosting/integration paths, including how models are run on hardware choices like Nvidia, AMD, Intel, and AWS. If it goes through, Nvidia could make its inference stack more prominent while other chipmakers may face shifting incentives to keep or move integration work.
Anthropic moved its Files API and computer-use tools out of beta and tested using Files API uploads versus repeatedly pasting reference text and using prompt caching for the same support-bot workload. Prompt caching cut billed input to about a third of pasting across 5 requests, while Files API added about 125 more input tokens than pasting. Files API primarily saves setup time, whereas prompt caching is what reduces cost (and the best option is using both when both needs apply).
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