In this post, you’ll learn about IonQ’s latest trapped-ion quantum computer, IonQ Aria, which is now available on Amazon Braket, and is also the first QPU in AWS to feature error mitigation. Read the Post on the AWS Blog Channel
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Amazon SageMaker provides a broad selection of machine learning (ML) infrastructure and model deployment options to help meet your ML inference needs. It’s a fully-managed service and integrates with MLOps tools so you can work to scale …
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AWS is developing new tools to enable easier and faster deployment of level 3 digital twin virtual sensors. in this post we show why L3 digital twins are needed for virtual sensors and how to elastically deploy one the cloud at scale. Read …
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Today we are launching I4g instances powered by AWS Graviton2 processors that deliver up to 15% better compute performance than our other storage-optimized instances. With up to 64 vCPUs, 512 GiB of memory, and 15 TB of NVMe storage, one of …
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In this post, we show how tools from our partner Good Chemistry can help you further explore the potential of quantum computing for non-trivial molecular systems, and design experiments that you can run on Amazon Braket. Read the Post on …
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New generations of CPUs offer a significant performance improvement in machine learning (ML) inference due to specialized built-in instructions. Combined with their flexibility, high speed of development, and low operating cost, these …
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In this blog post, we show how you can track and manage hybrid quantum-classical experiments with the Hybrid Jobs feature in Amazon Braket and Amazon SageMaker Experiments, used by ML developers on AWS to organize their experiments and …
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Many applications leverage distributed task systems like Celery to handle asynchronous work. In this post, we describe how to handle compute-intensive Celery tasks using AWS Batch to scale the compute resources and run worker agents. Read …
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