Learn how an AI voice agent built with SAS Viya and LLMs can transform fraud detection into real-time, automated fraud resolution through customer interaction and governed decisioning.
Learn how an AI voice agent built with SAS Viya and LLMs can transform fraud detection into real-time, automated fraud resolution through customer interaction and governed decisioning.
Shahrzad Azizzadeh and team discuss optimizing inspector assignments using SAS Optimization in federal and state meat processing facilities.
Demonstrates how network analytics can transform a simple link list into actionable insights for public health decision-making.
As AI agents act autonomously in public spaces, recent incidents highlight the urgent need for strong guardrails, ethical alignment, and human judgment to ensure AI augments society rather than undermines trust, work, and human connection.
As AI agents optimize how they communicate, the shift away from human-readable language underscores why transparency and interpretability are essential for building trust in autonomous systems.
As AI agents gain autonomy and access to sensitive systems, emerging threats like prompt injection worms highlight how human-like security training and governance must evolve to prevent large-scale, opaque cybersecurity breaches driven by agent behavior.
Learn how integrating the Model Context Protocol (MCP) into SAS Retrieval Agent Manager transforms retrieval-augmented generation from a passive information system into a governed, scalable, and action-oriented enterprise AI platform capable of executing real business workflows.
This article was co-written with Sundaresh Sankaran. The Artificial Intelligence (AI) era is here. To prevent harm, ensure proper governance and secure data, we need to trust our AI output. We must demonstrate that it operates in a fair and responsible manner with a high level of efficiency. As builders of
When I first started as a data scientist, there was a gap. I met with dozens of organizations who would invest time and resources into building accurate and tuned models and then ask, “What now?” They had a fantastic model in hand but couldn’t get it into a place and
Small language models like GLiNER provide an efficient, deterministic, and flexible solution for named entity recognition, bridging the gap between traditional NLP and large language models for enterprise information extraction.