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Securing your AI data pipeline with MLOps

Businesses increasingly implementing AI into their operations often encounter “spaghetti code,” a complex and convoluted coding mass carrying potential security risks. The rise of AI-written code, often created from publicly accessible snippets, can exacerbate these risks. One solution is to utilise standardised, traceable industrialised code, reducing the chances of human error and security vulnerabilities. Transferring to a system of implementing role-based access control and ‘guardrails’ that keep AI functions within specified parameters, alongside robust governance measures, can ensure AI system efficiency and security.

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