Posts in category

DevOps

Artificial IntelligenceDevOpsMachine Learning

The drive for progress in Information Technology (IT) for the year 2022 will emerge from the anxieties churned up by 2020 and 2021. No matter what plans and vision accompanied us as we entered this decade, things have uniformly aligned themselves to a single human goal – Sustainability. This is the umbrella under which our …

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Artificial IntelligenceDevOps

  ​What’s New: Since OpenVINO™ launched in 2018, Intel has enabled hundreds of thousands of developers to dramatically accelerate AI inferencing performance, starting at the edge and extending to the enterprise and the client. Today, ahead of MWC Barcelona 2022, the company launched a new version of the Intel® Distribution of OpenVINO Toolkit. New features are built upon …

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Artificial IntelligenceDevOpsMachine Learning

AI-driven organizations are using data and machine learning to solve their hardest problems and are reaping the rewards. “Companies that fully absorb AI in their value-producing workflows by 2025 will dominate the 2030 world economy with +120% cash flow growth,”1 according to McKinsey Global Institute. But it’s not easy right now. Machine learning (ML) systems have …

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Artificial IntelligenceDevOpsPlatforms

“In the era of big data, insights collected from cloud services running at the scale of Azure quickly exceed the attention span of humans. It’s critical to identify the right steps to maintain the highest possible quality of service based on the large volume of data collected. In applying this to Azure, we envision infusing …

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DataDevOpsMachine LearningPlatforms

Microsoft Build 2019 | Breaking the Wall between Data Scientists and App Developers with MLOps Session ID: BRK2004   MLOps is DevOps for machine learning and brings continuous integration, delivery and learning to the machine learning lifecycle. This session will show you how to get to market faster with better models, and operationalize more reliably …

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DataDevOpsMachine Learning

Microsoft Build 2019 | MLOps: How to Bring Your Data Science to Production Session ID: BDL2026   While many enterprises have already adopted DevOps and GitOps strategies to improve their developers’ efficiency, most have yet to employ the same techniques for their machine learning pipelines. In this panel, we will discuss the practice of MLOps, …

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DevOpsPlatformsTechnology

Google Cloud Next 2019 | Game Sessions Google Cloud Next 2019 | Networking On Cloud: Unity’s Networking Journey On GCP Unity has a global team across five continents with over six business units that have more than 50 aggregated services managed by different teams. Now what makes this migration journey interesting is that the entire …

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DataDevOpsPlatformsTechnology

Google Cloud Next 2019 | Retail Sessions Google Cloud Next 2019 | BigQuery Tips: Nested and Repeated Fields And How GOJEK Builds Data Warehouses Gain expert advice on BigQuery to take advantage of data warehousing. In this session, GOJEK, a global company with multiple products and services and lots of data, will share how they …

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DevOpsPlatformsTechnology

Google Cloud Next 2019 | Retail Sessions Google Cloud Next 2019 | Things I Wish I Knew Before Building Serverless ML Solutions Building ML models for a proof-of-concept app is easy. To deploy them in a production system is hard. It becomes even more challenging when you have to keep your models fresh by retraining …

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DevelopmentDevOpsHybrid CloudPlatformsTechnology

 Google Cloud Next 2019 | Financial Services Sessions Google Cloud Next 2019 | Maintain Control Over Hybrid Workloads With DevOps Best Practices From Google Cloud Maintaining visibility, control, and compliance of hybrid workloads is increasingly complex. Administrators need to navigate and upkeep multiple tools, configs, policy systems and languages to ensure that their security …

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