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Posted by Rajat Sen and Abhimanyu Das, Research Scientists, Google Research Time-series forecasting is an important research area that is critical to several scientific and industrial applications, like retail supply chain optimization, energy and traffic prediction, and weather forecasting. In retail use cases, for example, it has been observed that improving demand forecasting accuracy can …

Read more “Recent advances in deep long-horizon forecasting”

Each machine learning (ML) system has a unique service level agreement (SLA) requirement with respect to latency, throughput, and cost metrics. With advancements in hardware design, a wide range of CPU- and GPU-based infrastructures are available to help you speed up inference performance. Also, you can build these ML systems with a combination of ML …

Read more “Improved ML model deployment using Amazon SageMaker Inference Recommender”

Since our founding in 2003, Palantir has worked with governments — as well as commercial clients across some of the most secure and highly regulated industries — to deliver value from their most sensitive data holdings. In doing so, we have pioneered many of the security concepts and practices that have come to be known as Zero Trust. Today, security …

Read more “Building Software for a Zero Trust World”

Posted by Lauren Wilcox, Senior Staff Research Scientist, on behalf of the Technology, AI, Society, and Culture Team Google sees AI as a foundational and transformational technology, with recent advances in generative AI technologies, such as LaMDA, PaLM, Imagen, Parti, MusicLM, and similar machine learning (ML) models, some of which are now being incorporated into …

Read more “Responsible AI at Google Research: Technology, AI, Society and Culture”