Quotes from Andrew Ng

As leaders, it is incumbent on all of us to make sure we are building a world in which every individual has an opportunity to thrive. Understanding what AI can do and how it fits into your strategy is the beginning, not the end, of that process.

AI has been making tremendous progress in machine translation, self-driving cars, etc. Basically, all the progress I see is in specialised intelligence. It might be hundreds or thousands of years or, if there is an unexpected breakthrough, decades.

In my own life, I found that whenever I wasn't sure what to do next, I would go and learn a lot, read a lot, talk to experts. I don't know how the human brain works, but it's almost magical: when you read enough or talk to enough experts, when you have enough inputs, new ideas start appearing. This seems to happen for a lot of people that I know.

The big AI dreams of making machines that could someday evolve to do intelligent things like humans could - I was turned off by that. I didn't really think that was feasible when I first joined Stanford.

As the founding lead of the Google Brain team, former director of the Stanford Artificial Intelligence Laboratory, and now overall lead of Baidu's AI team of some 1,200 people, I've been privileged to nurture many of the world's leading AI groups and have built many AI products that are used by hundreds of millions of people.

I think the Indian AI ecosystem is growing rapidly. A lot of Indian entrepreneurs reach out to me seeking feedback about startups and products. And some of them have very interesting business ideas.

A lot of the progress in machine learning - and this is an unpopular opinion in academia - is driven by an increase in both computing power and data. An analogy is to building a space rocket: You need a huge rocket engine, and you need a lot of fuel.

Baidu's AI is incredibly strong, and the team is stacked up and down with talent; I am confident AI at Baidu will continue to flourish. After Baidu, I am excited to continue working toward the AI transformation of our society and the use of AI to make life better for everyone.

The success, or failure, of a CEO to implement AI throughout the organization will depend on them hiring a leader to build an organization to do this. In some companies, CIOs or chief data officers are playing this role.

When we automated away the elevator operator function, who knew that all the descendants of those operators would become social media marketers, machine learning engineers, and all these other jobs that we didn't even have a language to describe back then.

Text input is certainly useful, but images and speech are a much more natural way for humans to express their queries. Infants learn to see and speak well before they learn to type. The same is true of human evolution - we've had spoken language for a long time compared to written language, which is a relatively recent development.

Many researchers are exploring other forms of AI, some of which have proved useful in limited contexts; there may well be a breakthrough that makes higher levels of intelligence possible, but there is still no clear path yet to this goal.

Some of the most successful businesses succeed by exploiting their users.

In Silicon Valley, there are a lot of startups using computer vision for agriculture or shopping - there are a lot for clothes shopping. At Baidu, for example, if you find a picture of a movie star, we actually use facial recognition to identify that movie star and then tell you things like their age and hobbies.

Silicon Valley and Beijing are the leading hubs of AI, followed by the U.K. and Canada. I am seeing a lot of excitement in India, going by the number of people who are taking Coursera courses on AI.

Baidu Research has three labs - two in Beijing that are already largely built up, and the Silicon Valley one is being built from scratch. We're hiring pretty rapidly, about one person a week, but we are about a month in, so honestly, we haven't done that much work yet.

AI is creating tremendous economic value today.

The most trusted way to keep moving up that value chain is to keep investing in individuals - to help them grow in knowledge and skills. Education is hard. It takes individuals to do the hard work.

A lot of the game of AI today is finding the appropriate business context to fit it in. I love technology. It opens up lots of opportunities. But in the end, technology needs to be contextualized and fit into a business use case.

In terms of building consumer products, the U.S. and China are ahead of India. The interesting opportunity for India is whenever there is a disruption in technology, it gives every country a chance to leapfrog and take a lead. To take an example, China is leaping ahead in growing the China electric vehicle ecosystem.

One of my philosophies of building companies is the importance of velocity.

Education is not about thinning the herd. Education is about helping every student succeed.

If you have a lot of data and you want to create value from that data, one of the things you might consider is building up an AI team.

I just thought making machines intelligent was the coolest thing you could do. I had a summer internship in AI in high school, writing neural networks at National University of Singapore - early versions of deep learning algorithms. I thought it was amazing you could write software that would learn by itself and make predictions.