Google no longer understands how its "deep learning" decision-making computer systems have made themselves so good at recognizing things in photos.
This means the internet giant may need fewer experts in future as it can instead rely on its semi-autonomous, semi-smart machines to solve problems all on their own.
The claims were made at the Machine Learning Conference in San Francisco on Friday by Google software engineer Quoc V. Le in a talk in which he outlined some of the ways the content-slurper is putting "deep learning" systems to work. (You find out more about machine learning, a computer science research topic, here [PDF].)
Google no longer understands how its "deep learning" decision-making computer systems have made themselves so good at recognizing things in photos.
This means the internet giant may need fewer experts in future as it can instead rely on its semi-autonomous, semi-smart machines to solve problems all on their own.
The claims were made at the Machine Learning Conference in San Francisco on Friday by Google software engineer Quoc V. Le in a talk in which he outlined some of the ways the content-slurper is putting "deep learning" systems to work. (You find out more about machine learning, a computer science research topic, here [PDF].)
"f you're an educator of any level, you know the importance of a great personal learning network. It's your professional lifeline in the digital age. It doesn't matter if you're a teacher, administrator, or any other form of educator. A personal learning network sustains and nurtures you in many ways."
"We [added] human mentors," says Thrun. "We have people almost 24-7 that help you when you get stuck. We also added a lot of projects that require human feedback and human grading. "And that human element, surprise, surprise, makes a huge difference in the student experience and the learning outcomes," he says.
So true! That's what independent schools have known for a long long time.