Decision Intelligence (DI) is a data-driven approach to decision-making that leverages advanced analytics, machine learning, and artificial intelligence (AI) to empower organizations with actionable insights.
Structured outputs in large language models (LLMs) refer to the ability of these models to generate responses in specific, predefined formats rather than just free-form text.
Causal AI is a branch of artificial intelligence focused on understanding and determining cause-and-effect relationships rather than merely identifying patterns or correlations.
ReACT and function calling agents represent two distinct but powerful approaches to extending the capabilities of LLMs, each with its own strengths and weaknesses.
Composite AI refers to an advanced AI approach that integrates multiple artificial intelligence (AI) technologies to create a more sophisticated, flexible, and intelligent system.
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