By imbuing enormous vectors with semantic meaning, we can get machines to reason more abstractly — and efficiently — than before

Anil Ananthaswamy in Quanta:

The key is that each piece of information, such as the notion of a car, or its make, model or color, or all of it together, is represented as a single entity: a hyperdimensional vector.

A vector is simply an ordered array of numbers. A 3D vector, for example, comprises three numbers: the xy and z coordinates of a point in 3D space. A hyperdimensional vector, or hypervector, could be an array of 10,000 numbers, say, representing a point in 10,000-dimensional space. These mathematical objects and the algebra to manipulate them are flexible and powerful enough to take modern computing beyond some of its current limitations and foster a new approach to artificial intelligence.

“This is the thing that I’ve been most excited about, practically in my entire career,” Olshausen said. To him and many others, hyperdimensional computing promises a new world in which computing is efficient and robust, and machine-made decisions are entirely transparent.

More here.