Research

As organizations rush to implement artificial intelligence (AI), a new analysis of AI-related risks finds significant gaps in our understanding, highlighting an urgent need for a more comprehensive approach.

Ask a large language model (LLM) like GPT-4 to smell a rain-soaked campsite, and it’ll politely decline. Ask the same system to describe that scent to you, and it’ll wax poetic about “an air thick with anticipation" and “a scent that is both fresh and earthy," despite having neither prior experience with rain nor a nose to help it make such observations. 

The phrase “practice makes perfect” is usually reserved for humans, but it’s also a great maxim for robots newly deployed in unfamiliar environments.

At the top of many automation wish lists is a particularly time-consuming task: chores.