@awsnews.bsky.socialAmazon SageMaker Unified Studio now supports ODBC connections for Microsoft Power BI and other analytics tools
Amazon SageMaker Unified Studio now supports ODBC connections, so data users can connect Microsoft Powe...
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@awsrecentnews.bsky.social🆕 Amazon SageMaker HyperPod now supports model caching to speed up inference autoscaling and reduce cold starts by pre-loading model weights and container images, cutting scale-out time by 60% and image-pull time by 97%. Available in all regions with HyperPod.
@awsnews.bsky.socialAmazon SageMaker HyperPod now supports model caching for faster inference autoscaling and reduced cold starts
Amazon SageMaker HyperPod now supports model caching, an inference optimization that pre-loads model weights and container images onto cluster nodes so pods start ...
@awsrecentnews.bsky.social🆕 Amazon SageMaker Feature Store now lets you update individual features, cutting write latency. Data scientists can modify specific features without rewriting records, reducing costs and latency. Available globally. For details, see Amazon Feature Store Runtime, Standard V2…
@awsnews.bsky.socialAmazon SageMaker Feature Store now supports individual feature updates to lower write latency
Amazon SageMaker Feature Store is a fully managed capability that makes it easy to compute, store, and retrieve features for training and deploying AI models. SageMaker Feature St...
@sergiocuellar.bsky.socialBusinesses in healthcare, retail, and life sciences can now harness the power of predictive data insights with Amazon SageMaker Canvas, a no-code ML workflow that connects seamlessly to Snowflake. #AmazonSageMaker #Snowflake #DataInsights #ML 📊🔍