“Foundation models” represent a breakthrough in artificial intelligence or AI. They are a new form of creative, non-human intelligence and promise to bring great benefits
. Loosely based on the networked structure of neurons in the human brain,systems are “trained” using millions or billions of examples of texts, images or sound clips. In recent years the ballooning cost, in time and money, of training ever-largeraidoes indeed continue to unlock ever more impressive new capabilities. Nobody knows where the limit lies.
Foundation models have some surprising and useful properties. The eeriest of these is their “emergent” behaviour—that is, skills which arise from the size and depth of the models, rather than being the result of deliberate design. Just as a rapid succession of still photographs gives the sensation of movement, so trillions of binary computational decisions fuse into a simulacrum of fluid human comprehension and creativity that, whatever the philosophers may say, looks a lot like the real thing.
A more penetrating worry is over who controls foundation models. Training a really large system such as Google’scosts more than $10m a go and requires access to huge amounts of data—the more computing power and the more data the better. This raises the spectre of a technology concentrated in the hands of a small number of tech companies or governments.
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