The first AWS service I used, more than ten years ago, was Amazon Elastic Compute Cloud (Amazon EC2). Over time, EC2 has added a wide selection of instance types optimized to fit different use cases, with a varying combination of CPU/GPU, memory, storage, and networking capacity to give you the flexibility to choose the appropriate mix of resources for your applications. One of the key advantages of the cloud is elasticity. With EC2 Fleet, you can synchronously request capacity across multiple instance types and purchase options, launching your instances across multiple Availability Zones, using the On-Demand, Reserved, and Spot Instances together. With EC2 Auto Scaling, you can automatically add or remove EC2 instances according to conditions you define and add…
Month: October 2021
Pixel 6’s camera combines hardware, software and ML
Last week, we announced Pixel 6 and Pixel 6 Pro, and we spent some time introducing the new Pixel Camera, which gets a big boost from Google Tensor, Google’s first System on a Chip (SoC) designed specifically for Pixel. But there’s so much more to talk about — so we wanted to take some time to show you how the new camera uses the latest technology from the Pixel hardware and research teams as well as our Pixel software team. From HDR+ to Night Sight, Pixel has a history of building state-of-the-art cameras using computational photography, and Pixel 6 and Pixel 6 Pro are no exception. Google Tensor allows us to combine new camera hardware with thoughtful software, as well…
New – EC2 Instances Powered by Gaudi Accelerators for Training Deep Learning Models
There are more applications today for deep learning than ever before. Natural language processing, recommendation systems, image recognition, video recognition, and more can all benefit from high-quality, well-trained models. The process of building such a model is iterative: construct an initial model, train it on the ground truth data, do some test inferences, refine the model and repeat. Deep learning models contain many layers (hence the name), each of which transforms outputs of the previous layer. The training process is math and processor intensive, and places demands on just about every part of the systems used for training including the GPU or other training accelerator, the network, and local or network storage. This sophistication and complexity increases training time and…
AWS Local Zones Are Now Open in Las Vegas, New York City, and Portland
Today, we are opening three new AWS Local Zones in Las Vegas, New York City (located in New Jersey), and Portland metro areas. We are now at a total of 14 Local Zones in 13 cities since Jeff Barr announced the first Local Zone in Los Angeles in December 2019. These three new Local Zones join the ones in full operation in Boston, Chicago, Dallas, Denver, Houston, Kansas City, Los Angeles, Miami, Minneapolis, and Philadelphia. Local Zones are one of the ways we bring select AWS services much closer to large populations and geographic areas where major industries come together. By having this proximity, you can deploy latency-sensitive workloads such as real-time gaming platforms, financial transaction processing, media and entertainment…