Author Archives: Victor Dey - Page 2
When Karpenter is installed in a working cluster, it observes the aggregate resource requests of unscheduled pods and makes decisions to launch new nodes and terminate them to reduce scheduling latencies and infrastructure costs.
Google’s Open division submissions consist of a 480 billion parameter dense Transformer-based encoder-only benchmark using TensorFlow and a 200 billion-parameter JAX benchmark. These models are architecturally similar to MLPerf’s BERT model but with larger dimensions and number of layers.
Google’s Open division submissions consist of a 480 billion parameter dense Transformer-based encoder-only benchmark using TensorFlow and a 200 billion-parameter JAX benchmark. These models are architecturally similar to MLPerf’s BERT model but with larger dimensions and number of layers.
Google’s Open division submissions consist of a 480 billion parameter dense Transformer-based encoder-only benchmark using TensorFlow and a 200 billion-parameter JAX benchmark. These models are architecturally similar to MLPerf’s BERT model but with larger dimensions and number of layers.
With AWS Mainframe Modernization, customers can refactor their mainframe workloads to run on AWS by transforming legacy applications into modern Java-based cloud services.
The service helps automakers efficiently transfer data to the cloud in near-real-time using the service’s intelligent filtering capabilities that allow developers to reduce network traffic by selecting the data to transfer and defining rules for when to transfer it based on parameters like weather conditions, location, or vehicle type.
With AWS Private 5G, customers can specify a coverage area within a geographic location where they want to deploy a private 5G network, along with the amount of traffic they expect the network to handle.
SageMaker Canvas leverages the same technology as previous Amazon SageMaker to automatically clean and combine data, create hundreds of models under the hood, select the one performing best, and generate new individual or batch predictions.
Customers like DirecTV, Discovery, Epic Games, Formula 1, Honeycomb.io, Intuit, Lyft, MercardoLibre, NextRoll, Nielsen, SmugMug, Snap, Splunk, and Sprinklr have seen significant performance gains and reduced costs from running AWS Graviton2 based instances in production since they launched in 2020.
Julia 1.7 now uses a much smaller state of the Xoshiro256 family of RNGs to put a state in every task and fork it on each task creation.