Education should learn from the positive side of gaming - reward, accomplishment, and fun.

If we study learning as a data science, we can reverse engineer the human brain and tailor learning techniques to maximize the chances of student success. This is the biggest revolution that could happen in education, turning it into a data-driven science, and not such a medieval set of rumors professors tend to carry on.

Corporate America is drowning in meetings. To make one thing clear, I am not against communication. Quick one-on-ones can be extremely effective. I am talking about those hour-long recurring meetings, devoid of a clear agenda, and attended by many. I dread them.

Machine learning is the science of getting computers to learn without being explicitly programmed.

In most parts of the world, starting a company that goes bust is dubbed a 'failure.' In Silicon Valley, we call this 'gaining experience.' We are willing to take the risks that are inherent for innovation.

It's important to celebrate your failures as much as your successes. If you celebrate your failures really well, and if you get to the motto and say, 'Wow, I failed, I tried, I was wrong, I learned something,' then you realize you have no fear, and when your fear goes away, you can move the world.

At the end of the day, the true value proposition of education is employment.

I'd really love to see a business model for higher education going forward that is actually affordable, that uses modern technology to reach scale and quality and that really reimburses the services rendered in a way that's meaningful to everybody.

When you program a robot to be intelligent, you learn a number of things. You become very humble and develop enormous respect for natural intelligence because, even if you work day and night for several years, your robot isn't that smart after all.

I believe e-courses will eventually change people's attitude toward learning. Education will play an increasingly dominant role in people's lives. For people of all ages and all geographies.

It's sad that we never get trained to leave assumptions behind.

To me, mathematics, computer science, and the arts are insanely related. They're all creative expressions.

I have been spending the better part of my professional life trying to create self-driving cars. At Google, I am working with a world-class team of engineers to turn science fiction into reality.

You could get an entire computer science education for free right now.

I ultimately got into robotics because for me, it was the best way to study intelligence.

Nobody phrases it this way, but I think that artificial intelligence is almost a humanities discipline. It's really an attempt to understand human intelligence and human cognition.

As a college student, what really interested me was the human brain and human intelligence.

You could claim that moving from pixelated perception, where the robot looks at sensor data, to understanding and predicting the environment is a Holy Grail of artificial intelligence.

In much of computer science, I can easily 'auto-grade' your work and give you an instant meaningful feedback. I can't do this when it comes to the subtlety of human thought, language, poetry, philosophy.

The individualization of learning fundamentally redefines the role of assessment.

Mercedes does beautiful work, absolutely.

Few ideas work on the first try. Iteration is key to innovation.