Published: 24 June 2024
DSML platforms provide capabilities that span the life cycle of AI models, including generative AI, helping to bridge the gap from development to production. Data and analytics leaders should utilize these platforms to strengthen organizational MLOps practices.
Data science and machine learning (DSML) platform vendors have made significant investments in capabilities for working with generative artificial intelligence (AI) models, providing model libraries, prompt handling, hosting, evaluation and integration with vector databases.
DSML platform capabilities for pipeline creation and optimization, model management, and monitoring and observability are reducing the complexity of deploying and monitoring models in production.
The most differentiated capabilities among DSML platform vendors are for machine learning (ML) feature management. The least differentiated set of capabilities are for performance and scalability.
Combine generative AI development with DSML development in a single platform or single vendor stack
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Analysts:
Afraz Jaffri, Aura Popa, Peter Krensky, Jim Hare, Tong Zhang, Maryam Hassanlou, Raghvender Bhati
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For more information, see the FAQ on How Products and Services Are Evaluated in Gartner Critical Capabilities or visit the Gartner Critical Capabilities methodology page.
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