Categories: FAANG

An early warning system for novel AI risks

AI researchers already use a range of evaluation benchmarks to identify unwanted behaviours in AI systems, such as AI systems making misleading statements, biased decisions, or repeating copyrighted content. Now, as the AI community builds and deploys increasingly powerful AI, we must expand the evaluation portfolio to include the possibility of extreme risks from general-purpose AI models that have strong skills in manipulation, deception, cyber-offense, or other dangerous capabilities.
AI Generated Robotic Content

Share
Published by
AI Generated Robotic Content
Tags: ai/mlfaang
3 years ago

Recent Posts

3 Actionable AI Recommendations for Businesses in 2026

TL;DR In 2026, the businesses that win with AI will do three things differently: redesign…

7 hours ago

Improved Gemini audio models for powerful voice experiences

1 day ago

Revolutionizing Construction

How Cavanagh and Palantir Are Building Construction’s OS for the 21st CenturyEditor’s Note: This blog post…

1 day ago

Building a voice-driven AWS assistant with Amazon Nova Sonic

As cloud infrastructure becomes increasingly complex, the need for intuitive and efficient management interfaces has…

1 day ago

Cloud CISO Perspectives: Our 2026 Cybersecurity Forecast report

Welcome to the first Cloud CISO Perspectives for December 2025. Today, Francis deSouza, COO and…

1 day ago

As AI Grows More Complex, Model Builders Rely on NVIDIA

Unveiling what it describes as the most capable model series yet for professional knowledge work,…

1 day ago