"Researchers Map AI Threat Landscape, Risks"

According to a new report from the Berryville Institute of Machine Learning (BIML) titled "An Architectural Risk Analysis of Large Language Models," many of the security issues associated with Large Language Models (LLMs) stem from the fact that they all have a black box at their core. LLMs' end users typically have little information about how providers collected and cleaned the data used to train their models, and model developers generally conduct only a surface-level evaluation of the data due to the volume of information available. The report emphasizes that a lack of visibility into how Artificial Intelligence (AI) makes decisions is the root cause of over a quarter of the risks posed by LLMs. This article continues to discuss researchers' key findings and points regarding the AI threat landscape and risks.

Dark Reading reports "Researchers Map AI Threat Landscape, Risks"

Submitted by grigby1