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New distributed Python capability accelerates large-scale AI operations while keeping data and compute within the Teradata platform SAN DIEGO, Oct. 14, 2026 /PRNewswire/ -- Teradata (NYSE: TDC ) today announced the general availability of Elastic Python Compute within AI Studio. The capability gives enterprise data science teams a managed, distributed Python environment for scaling AI compute and machine learning workloads through parallel Python execution for data engineering, machine learning, and model development. Elastic Python Compute is built on Ray, a distributed computing framework, and integrates natively with the Teradata Autonomous Knowledge Platform and AI Studio. Data scientists can parallelize model training, execute custom Python applications at scale, and serve high-scale ML and AI workloads without the overhead of manual cluster setup or managing Ray clusters. Elastic Python Compute supports both single-server and cluster deployments, giving organizations the flexibility to scale from individual workloads to enterprise-scale operations, with faster development cycles, stronger governance controls, and lower infrastructure costs. Keeping Data and AI Compute Within the Platform Elastic Python Compute supports local model hosting and governance, with no external API dependencies and no token -based inference costs. AI workloads run entirely within the...
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