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What is AI Engineering?
AI Engineering is a discipline for harnessing the people, systems and tools that it takes to deliver high-value, scalable, and trusted artificial intelligence (AI) for use in real-world contexts. Carnegie Mellon’s Software Engineering Institute considers the pillars of AI Engineering to be:
- Robust and Secure AI: AI application development, deployment, monitoring, maintenance, feedback, learning & value capture
- Scalable AI: Scaling AI applications across the enterprise for many use cases requires AI infrastructure, data, and models that can be reused across problem domains and deployments
- Human-centered AI: How AI systems are designed to align with humans, their behaviors, and their values – and built by teams across the enterprise (Data Science, ML Ops, Data Engineering, Subject Matter Experts, etc.)
By 2025, the 10% of enterprises who establish AI Engineering best practices will generate at least three times more value with their AI efforts than the 90% of enterprises who do not. ~ Gartner 2021
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