Making AI operational in constrained public sector environments

TL;DR

Public sector organizations face pressure to adopt AI while managing unique constraints around security, governance, and operations. MIT Technology Review explores how purpose-built small language models can operationalize AI in government while maintaining control. SLMs emerge as a practical middle ground between full-scale LLM deployment and legacy constrained options in public sector agencies.

• •Public sector AI adoption faces distinct constraints: security, governance, operations
• •Purpose-built small language models designed for constrained government environments
• •SLMs balance AI capability with control requirements public sector agencies need

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