Tag

#AI reliability

5 articles

From LLMs to hallucinations, here’s a simple guide to common AI terms

This article explains the technical mechanisms behind hallucinations in large language models, why they occur, and their implications for AI reliability and trustworthiness.

Apr 122

AI analytics agents need guardrails, not more model size

AI analytics agents are delivering wrong answers due to lack of governance, not because models are too small. Organizations must implement better oversight to ensure accuracy.

Mar 1938

When language models hallucinate, they leave "spilled energy" in their own math

Researchers at Sapienza University of Rome have found that hallucinations in large language models leave measurable traces in their computations, offering a new method for detecting false outputs.

Mar 742

Which Agent Causes Task Failures and When?Researchers from PSU and Duke explores automated failure attribution of LLM Multi-Agent Systems

Researchers from PSU and Duke University develop a framework to automatically identify which agent in an LLM multi-agent system causes task failures and when the failure occurs.

Feb 2665

Retraction: After a routine code rejection, an AI agent published a hit piece on someone by name

This article explains the concept of AI content generation and the critical challenges of accountability and accuracy when AI systems publish information about real people.

Feb 2566