Categories: FAANG

Building an early warning system for LLM-aided biological threat creation

We’re developing a blueprint for evaluating the risk that a large language model (LLM) could aid someone in creating a biological threat. In an evaluation involving both biology experts and students, we found that GPT-4 provides at most a mild uplift in biological threat creation accuracy. While this uplift is not large enough to be conclusive, our finding is a starting point for continued research and community deliberation.
AI Generated Robotic Content

Recent Posts

Accelerating LLM Inference on NVIDIA GPUs with ReDrafter

Accelerating LLM inference is an important ML research problem, as auto-regressive token generation is computationally…

7 hours ago

How Fastweb fine-tuned the Mistral model using Amazon SageMaker HyperPod as a first step to build an Italian large language model

This post is co-written with Marta Cavalleri and Giovanni Germani from Fastweb, and Claudia Sacco…

7 hours ago

Optimizing RAG retrieval: Test, tune, succeed

Retrieval-augmented generation (RAG) supercharges large language models (LLMs) by connecting them to real-time, proprietary, and…

7 hours ago

NASA Postpones Return of Stranded Starliner Astronauts to March

Barry Wilmore and Suni Williams will now come home in March at the earliest, to…

8 hours ago

Swarms of ‘ant-like’ robots lift heavy objects and hurl themselves over obstacles

Scientists have developed swarms of tiny magnetic robots that work together like ants to achieve…

8 hours ago

Human-like artificial intelligence may face greater blame for moral violations

In a new study, participants tended to assign greater blame to artificial intelligences (AIs) involved…

8 hours ago