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

Recent Posts

Intel announced new enterprise GPU with 32GB vram

If only it works well with work flow. Nvidia have CUDA, AMD have ROCM, I…

42 mins ago

5 Practical Techniques to Detect and Mitigate LLM Hallucinations Beyond Prompt Engineering

My friend who is a developer once asked an LLM to generate documentation for a…

42 mins ago

Exclusive Self Attention

We introduce exclusive self attention (XSA), a simple modification of self attention (SA) that improves…

42 mins ago

Unlocking video insights at scale with Amazon Bedrock multimodal models

Video content is now everywhere, from security surveillance and media production to social platforms and…

42 mins ago

DRA: A new era of Kubernetes device management with Dynamic Resource Allocation

The explosion of large language models (LLMs) has increased demand for high-performance accelerators like GPUs…

42 mins ago

Amazon Spring Sale Deal: The Typhur Dome 2 Air Fryer Is 30% Off

I tested more than 30 air fryers this past year. The Typhur Dome 2 is…

2 hours ago