How AI (Artificial Intelligence) develop more AI (Artificial Intelligence) with the help of GOOGLE !
Whether you're fascinated by
thoughts of a future where robots make our lives better or your dystopian
visions of a world overrun by mechanical beings keep you up at night, there's
no question that artificial intelligence is here to stay. At the recent annual
Google I/O conference the company introduced what may be its most jaw-dropping
AI innovation yet, AutoML—a technology that can utilize neural networks to
teach itself.
The Rise of Neural
Networks -
Inspired by the human brain
and nervous system, neural networks are mathematical systems designed to
analyze enormous amounts of data. Like a brain, neural networks rely on large
numbers of interconnected "neurons" work at the same time to solve
problems. But instead of following instructions like a traditional computer,
they follow examples and "learn" to improve the rules and methods
they use. That's where cutting edge fields like artificial intelligence,
machine learning, and deep learning come in. Many companies are already using
this technology to recognize images, recommend things you might like to watch
or buy, or even predict the results of legal proceedings.
Machine learning (ML) is
becoming so popular, in fact, that there's a shortage of experts who
can make the software. It's an intensive process for scientists and engineers,
and that has limited the use of neural networks and machine learning to small
pools of computer experts and academics. That's where AutoML comes in. Its
machine-learning software that can help create machine-learning software. With
it, Google aims to address a shortage of machine-learning experts and further
"democratize" AI technology across the development community and
beyond.
Google's early testing of AutoML
shows that the technology may be faster and more efficient at writing the
layers of code necessary to create machine-learning neural networks that beat
humans. For example, when researchers Quoc Le and Barrett Zoph
tasked a machine-learning system to pinpoint which architecture to use to have
software solve tasks such as recognizing images and languages, the system came
up with a solution comparable to the best human-created solutions we have—and
totally surpassed them on language recognition.
Google's AutoML is
still in its early stages. But if the successes seen in the tests by Le
and Zoph can be replicated, it has the potential to accelerate
the entire field of AI faster than what was ever imaginable. And the more
that people that have the ability to create customized neural networks, the
greater ability the technology has to improve human lives.
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