To know what a user wants, before he or she does. That it the ultimate goal of Google Search. The company has come one step closer with the help from deep neural networks, a form of artificial intelligence rapidly remaking not just Google’s search engine but the entire company.
Deep neutral nets are pattern recognition systems that can learn to perform specific tasks by analyzing vast amounts of data. In this case, they’ve learned to take a long sentence or paragraph from a relevant page on the web and extract the upshot—the information you’re looking for.
Wired gives this example:
ASK THE GOOGLE search app “What is the fastest bird on Earth?,” and it will tell you.
“Peregrine falcon,” the phone says. “According to YouTube, the peregrine falcon has a maximum recorded airspeed of 389 kilometers per hour.”
That’s the right answer, but it doesn’t come from some master database inside Google. When you ask the question, Google’s search engine pinpoints a YouTube video describing the five fastest birds on the planet and then extracts just the information you’re looking for. Read More