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Scale AI, the data infrastructure for AI, has been named a Cool Vendor in the 2022 Gartner Cool Vendors™ in Data-Centric AI by Svetlana Sicular, Arun Chandrasekaran, Sumit Agarwal, Oleksandr Matvitskyy and Anthony Mullen.
The biggest barriers for organizations looking to implement data-centric AI strategies are having the necessary resources, talent, experience and high-quality data needed to feed algorithms and leverage the power of AI. Scale provides AI solutions tailored to business use cases and machine learning tools to unlock breakthroughs like Generative AI and operationalize AI for all organizations spanning the U.S. government, researchers, startups and Fortune 500 companies across e-commerce, logistics, technology, fintech, and more industries. Organizations such as Microsoft, Open AI, SAP, Flexport and the U.S. Army partner with Scale to solve problems with data labeling and annotation, scenario-based model testing and validation, content understanding and contextualization, AI catalog for asset reusability and more.
According to Gartner, “Data challenges plague AI implementations. They are often unexpected because AI teams focus on algorithms, and data concerns come as an afterthought.” It recommends that when evaluating data-centric AI solutions, organizations should “work with stakeholders to determine what data characteristics are high value for AI,” and “add AI capabilities such as AI-specific data management, synthetic data and data labeling – to your data management toolbox.”
“It’s an honor to be named a Data-Centric AI Cool Vendor by Gartner. We believe that it is a testament to Scale’s mission to accelerate the development of AI applications and showcases the market impact of our vision,” said Alexandr Wang, CEO and Founder of Scale AI. “The solutions that we provide enable organizations to reap the benefits of AI, whether they are building or applying AI. This means better business outcomes, a real return on investment, and a faster time to production.”
According to the Gartner report, “By 2025, 90% of new data and analytics deployments will be through an established data ecosystem, causing consolidation across the data and analytics market.” Therefore, introducing a data management approach, such as data quality, data diversity, data and analytics governance, and data literacy to AI teams now, is imperative to any organization’s AI strategy.
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