Google scientists working in the company's secretive X Labs have made great strides in using computers to simulate the human brain.
Best known for inventing self-driving cars
and augmented-reality eyewear, the lab created a neural network for
machine learning by connecting 16,000 computer processors and then
unleashed it on the Internet. Along the way, the network taught itself
to recognize cats.
While the act of finding cats on the Internet
doesn't sound all that challenging, the network's performance exceeded
researchers' expectations, doubling its accuracy rate in identifying
objects from a list of 20,000 items, according to a New York Times report.
To find the cats, the team fed the network thumbnail images chosen at
random from more than 10 billion YouTube videos. The results appeared to
support biologists' theories that suggest that neurons in the brain are
trained to identify specific objects.
"We never told it during the training, 'This is a cat,'" Google fellow
Jeff Dean told the newspaper. "It basically invented the concept of a
Falling computing costs has led to significant advancements in areas of
computer science such as machine vision, speech recognition, and
language translation, The Times noted.
Machine learning is useful for improving translation algorithms and
semantic understanding and a favorite topic of Google co-founders Sergey
Brin and Larry Page, according to Google.