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Posted by Carlos Esteves and Ameesh Makadia, Research Scientists, Google Research, Athena Team Typical deep learning models for computer vision, like convolutional neural networks (CNNs) and vision transformers (ViT), process signals assuming planar (flat) spaces. For example, digital images are represented as a grid of pixels on a plane. However, this type of data makes …
Read more “Scalable spherical CNNs for scientific applications”
Analyzing medical images plays a crucial role in diagnosing and treating diseases. The ability to automate this process using machine learning (ML) techniques allows healthcare professionals to more quickly diagnose certain cancers, coronary diseases, and ophthalmologic conditions. However, one of the key challenges faced by clinicians and researchers in this field is the time-consuming and …
Read more “Simplify medical image classification using Amazon SageMaker Canvas”
Generative AI marks a significant technological shift. Like the internet or the mobile phone, its potential impact on individual and business productivity is extraordinary. Indeed, 82% of organizations considering or currently using generative AI believe it will either significantly change or transform their industry (Google Cloud Gen AI Benchmarking Study, July 2023). In retail, the …
Read more “Generative AI for retail: how to keep pace and get ahead”
The countdown has officially begun! We’re just one month away from the highly anticipated Chatbot Conference, and the excitement is palpable. As we gear up for what promises to be an enlightening and engaging day, here’s a quick refresher on what to expect: LLMs Uncovered: Delve deep into Large Language Models and get a grasp of …
Read more “Only 1 Month To Go: The Chatbot Conference Awaits!”
We are launching a new set of resources for general-purpose robotics learning across different robot types, or embodiments. Together with partners from 34 academic labs we have pooled data from 22 different robot types to create the Open X-Embodiment dataset. We also release RT-1-X, a robotics transformer (RT) model derived from RT-1 and trained on …
Read more “Scaling up learning across many different robot types”
IT is under enormous pressure. The expectation is 24/7/365 performance while also delivering increasingly better customer experiences at the lowest possible cost. The reality is that it’s difficult to keep apps performing as designed, especially in modern, cloud-native environments with microservices and Kubernetes. Cloud costs are out of control, and teams spend too much time …
Read more “Operationalize automation for faster, more efficient incident resolution at a lower cost”
Today, we are thrilled to announce many improvements for forecasters on Vertex AI. We are launching TimeSeries Dense Encoder (TiDE), a new forecasting model architecture with massive performance improvements. The new model architecture is one of the many improvements enabled by a new forecasting backend that leverages Vertex AI Pipelines and provides more transparency, more …
Read more “10x performance improvement with the latest forecasting updates in Vertex AI”
Posted by Shaina Mehta, Program Manager, Google Google is proud to be a Platinum Sponsor of the International Conference on Computer Vision (ICCV 2023), a premier annual conference, which is being held this week in Paris, France. As a leader in computer vision research, Google has a strong presence at this year’s conference with 60 …
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