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Uber branches out into AI data labeling

CIO

Scaled Solutions grew out of the company’s own needs for data annotation, testing, and localization, and is now ready to offer those services to enterprises in retail, automotive and autonomous vehicles, social media, consumer apps, generative AI, manufacturing, and customer support.

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Using Data Annotations for Quality Control Purposes

Smart Data Collective

Data annotation helps the developers check each field after entering data into a database or creating a form. Data Annotation converts data from code to presentation format. Some companies specializing in services for data annotation can help you increase your productivity and efficiency. . Why is Data Annotation Important?

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How Aster DM Healthcare used federated learning to better secure AI analysis of sensitive data

CIO

To overcome these challenges, Aster Innovation and Research Centre, the innovation hub of Aster DM Healthcare, has deployed its Secure Federated Learning Platform (SFLP) that securely and rapidly enables access to anonymised and structured health data for research and collaboration. Addressing new data security challenges.

Learning 368
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Preparing the foundations for Generative AI

CIO

There may still be work to do in developing a cloud-first infrastructure, secure by design, where data that is unified, protected, and integrated with both existing business applications and AI systems, can be accessed through composable APIs. This requires skillsets that firms may not have in-house. This seems a formidable task.

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How guardrails allow enterprises to deploy safe, effective AI

CIO

The company’s IT team has been looking at gen AI to help with cybersecurity and other internal use cases, say, as a platform vendor releases a set of security updates. “It For security reasons, MyFitnessPal was very concerned about sending data to an external LLM. Tines ensures the security of MyFitnessPal’s data, Talaga says.

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3 things to get right with data management for gen AI projects

CIO

You have filtering, normalization, some sort of augmentation, and you have to annotate the data,” says Jelinkova. But then you also address security and privacy of the data, and you need to protect your own IP.” They need to make sure they’re not exposing themselves to risk. We’re very thoughtful about IP,” she says.

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Salesforce debuts gen AI benchmark for CRM

CIO

They want to make sure it’s the best model that’s compliant, fits their security standards, and doesn’t break the bank.” Trust and safety focuses on how the model handles sensitive customer data, adheres to data privacy regulations, and secures information. We want to expand with more metrics, use cases, data, and more annotations.”