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Metadata enrichment – highly scalable data classification and data discovery

Metadata enrichment is about scaling the onboarding of new data into a governed data landscape by taking data and applying the appropriate business terms, data classes and quality assessments so it can be discovered, governed and utilized effectively. This feature significantly increases the productivity of the data stewards who provide business context to data by …

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AIOps reimagines hybrid multicloud platform operations

Today, most enterprises use services from more than one Cloud Service Provider (CSP). Getting operational visibility across all vendors is a common pain point for clients. Further, modern architecture such as a microservices architecture introduces additional operational complexity. Figure 1 Hybrid Multicloud and Complexity Evolution Traditionally this calls for more manpower. But this traditional approach …

Data fabric marketplace: The heart of data economy

In older civilizations, where transportation and communication were primitive, the marketplace was where people came to buy and sell products. This was the only way to know what was on offer and who needed it. Modern-day enterprises face a similar situation regarding data assets. On one side there is a need for data. Businesses ask: …

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Simplified Transfer Learning for Chest Radiography Model Development

Posted by Akib Uddin, Product Manager and Andrew Sellergren, Software Engineer, Google Health Every year, nearly a billion chest X-ray (CXR) images are taken globally to aid in the detection and management of health conditions ranging from collapsed lungs to infectious diseases. Generally, CXRs are cheaper and more accessible than other forms of medical imaging. …

Google at ICML 2022

Posted by Cat Armato, Program Manager, University Relations Google is a leader in machine learning (ML) research with groups innovating across virtually all aspects of the field, from theory to application. We build machine learning systems to solve deep scientific and engineering challenges in areas of language, music, visual processing, algorithm development, and more. Core …

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Towards Reliability in Deep Learning Systems

Posted by Dustin Tran and Balaji Lakshminarayanan, Research Scientists, Google Research Deep learning models have made impressive progress in vision, language, and other modalities, particularly with the rise of large-scale pre-training. Such models are most accurate when applied to test data drawn from the same distribution as their training set. However, in practice, the data …