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As emerging DevOps trends redefine software development, companies leverage advanced capabilities to speed up their AI adoption. That’s why, you need to embrace the dynamic duo of AI and DevOps to stay competitive and stay relevant. How does DevOps expedite AI? Poor data can distort AI responses.
DataQuality and Standardization The adage “garbage in, garbage out” holds true. Inconsistent data formats, missing values, and data bias can significantly impact the success of large-scale Data Science projects. This builds trust in model results and enables debugging or bias mitigation strategies.
Archana Joshi brings over 24 years of experience in the IT services industry, with expertise in AI (including generative AI), Agile and DevOps methodologies, and green software initiatives. As we continue to roll out new AI tools and platforms, we must ensure they meet our standards and regulations around the technology’s use.
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