Understanding the Relationship: AI, Machine Learning, and MLOps
This paper provides a comparison of AI, Machine Learning and MLOps, defining their core focus, key activities, roles in development, and primary tools. It clarifies the distinction between AI as a broader concept and MLOps as a subset focused on operationalizing ML models.
Integri, LLC specializes in providing tailored, emerging technologies to high-stakes sectors like Aerospace and Defense, focusing on transforming technical challenges into mission successes. e utilize AI and MLOps to modernize systems and improve operational efficiency.
Key aspects of Integri's approach include:
Modernizing DoD MRO by adopting AI, MLOps, and cloud solutions.
Leveraging data for predictive maintenance and resource allocation.
Integrating systems for seamless operation.
Integri uses advanced integration and AI to drive innovation, deploying AI solutions to improve predictive maintenance and decision-making. Our expertise spans AI, cloud engineering, and cybersecurity. AI involves creating intelligent systems, while MLOps ensures these systems are effectively deployed and maintained. MLOps is crucial for scaling AI applications. Both require collaboration between data scientists, engineers, and operations teams.
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