To run an AI model, you do not need a general-purpose computer, you don't need a powerful CPU capable of executing a wide variety of code. You mostly need massive amounts of matrix multiplication, and some simpler operations.
You also don't need very high precision: many models perform well even using 8-bit floats. This allows to ditch the whole digital approach and implement analog circuits, which, while sometimes less precise, are massively simpler and more energy-efficient.
So they built a mostly-analog device specialized for running ML models, and used optics instead of electronics, which allows to make certain things much faster, on top of the simplification.
There are known attempts to use electronic approaches, such as using flash-like structures that store charge as an analog value to store model weighs, and to do addition and multiplication right inside the cells.
You also don't need very high precision: many models perform well even using 8-bit floats. This allows to ditch the whole digital approach and implement analog circuits, which, while sometimes less precise, are massively simpler and more energy-efficient.
So they built a mostly-analog device specialized for running ML models, and used optics instead of electronics, which allows to make certain things much faster, on top of the simplification.
There are known attempts to use electronic approaches, such as using flash-like structures that store charge as an analog value to store model weighs, and to do addition and multiplication right inside the cells.