Pixel partner designer Phillip Lim shares how the camera and technology helps his team source https://blog.google/products/pixel/phillip-lim-google-pixel/
Introducing queryable object metadata for Amazon S3 buckets (preview)
AWS customers make use of Amazon Simple Storage Service (Amazon S3) at an incredible scale, regularly creating individual buckets that contain billions or trillions of objects! At that scale, finding the objects which meet particular criteria — objects with keys that match a pattern, objects of a particular size, or objects with a specific tag — becomes challenging. Our customers have had to build systems that capture, store, and query for this information. These systems can become complex and hard to scale, and can fall out of sync with the actual state of the bucket and the objects within. Rich Metadata Today we are enabling in preview automatic generation of metadata that is captured when S3 objects are added or…
New Amazon S3 Tables: Storage optimized for analytics workloads
Amazon S3 Tables give you storage that is optimized for tabular data such as daily purchase transactions, streaming sensor data, and ad impressions in Apache Iceberg format, for easy queries using popular query engines like Amazon Athena, Amazon EMR, and Apache Spark. When compared to self-managed table storage, you can expect up to 3x faster query performance and up to 10x more transactions per second, along with the operational efficiency that is part-and-parcel when you use a fully managed service. Iceberg has become the most popular way to manage Parquet files, with thousands of AWS customers using Iceberg to query across often billions of files containing petabytes or even exabytes of data. Table Buckets, Tables, and Namespaces Table buckets are…
Amazon EC2 Trn2 Instances and Trn2 UltraServers for AI/ML training and inference are now available
The new Amazon Elastic Compute Cloud (Amazon EC2) Trn2 instances and Trn2 UltraServers are the most powerful EC2 compute options for ML training and inference. Powered by the second generation of AWS Trainium chips (AWS Trainium2), the Trn2 instances are 4x faster, offer 4x more memory bandwidth, and 3x more memory capacity than the first-generation Trn1 instances. Trn2 instances offer 30-40% better price performance than the current generation of GPU-based EC2 P5e and P5en instances. In addition to the 16 Trainium2 chips, each Trn2 instance features 192 vCPUs, 2 TiB of memory, and 3.2 Tbps of Elastic Fabric Adapter (EFA) v3 network bandwidth, which offers up to 50% lower latency than the previous generation. The Trn2 UltraServers, which are a…