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For starters, AWS played the "I can develop my own GPU too" as it launched Inferentia, a dedicated machine learning chip that will compete with Nvidia as well as Google's TPU efforts.
followed by XLNX (4%), AMD (2%), INTC (2%), and two new entrants Amazon Inferentia (2%) and Google TPU (1%). We think the power of the x86 and NVidia ecosystems are underestimated, and start-up risk overestimated by the Street. Is CPU/GPU Use Driven by the Processor, or the Ecosystem? If someone were to offer
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We cover all of AWS’ most important ML and AI announcements, including SageMaker Ground Truth, Reinforcement Learning and New, DeepRacer, Inferentia and Elastic Inference, ML Marketplace, Personalize, Forecast and Textract, and more.
Qualcomm's Cloud AI 100 is a power-efficient edge and cloud computing chip purpose-built for machine learning and big data workloads.
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Choosing an AWS region is not a trivial decision. There are many variables that affect the price, performance and availability of your application as well as the AWS services you can use. If you choose the wrong region you could end up paying more than double and waiting several months before you can take advantage of new products and features.