We tend to think of AI as a monolithic entity, but it’s actually
developed along multiple branches. One of the main branches
involves performing traditional calculations but feeding the
results into another layer that takes input from multiple
calculations and weighs them before performing its calculations and
forwarding those on. Another branch involves mimicking the behavior
of traditional neurons: many small units communicating in burst of
activity called spikes, and keeping track of the history of past
Each of these, in turn, has different branches based on the
structure of its layers and communications networks, types of
calculations performed, and so on. Rather than being able to act in
a manner we’d recognize as intelligent, many of these are very good
at specialized problems, like pattern recognition or playing poker.
And processors that are meant to accelerate the performance of the
software can typically only improve a subset of them.
That last division may have come to an end with the development
of Tianjic by a large team of researchers primarily based in China.
Tianjic is engineered so that its individual processing units can
switch from spiking communications back to binary and perform a
large range of calculations, in almost all cases faster and more
efficiently than a GPU can. To demonstrate the chip’s abilities,
the researchers threw together a self-driving bicycle that ran
three different AI algorithms on a single chip simultaneously.
Source: FS – All – Science – News
One chip to rule them all: It natively runs all types of AI software