The next AI race exposes the limits of language
Our obsession with LLMs follows a long tradition of affiliating language with intelligence.
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Large language models – the technology underpinning the vast majority of today’s AI investment – have proven far more grounded than critics expected.
PHOTO: REUTERS
Catherine Thorbecke
More than 50 years after her death, Helen Keller still turns up in artificial intelligence debates. The communication breakthroughs of the American writer, who was deaf and blind, are often cited as evidence that language is the best path to creating machines that are as intelligent as humans.
Despite loud early doubters, large language models (LLMs) – the technology underpinning the vast majority of today’s AI investment – have proven far more grounded than critics expected. A computer can’t dip its toes in the ocean, but it can recognise enough patterns in the writings of the entire internet to mimic an understanding of what it means to get your feet wet. Our obsession with LLMs follows a long tradition of affiliating language with intelligence.