Top 103 Quotes & Sayings by Andrew Ng

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.

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 see a minimum living wage as a long-term solution, but I'm not sure that's my favorite. I think society benefits if all the human race is empowered and aspiring to do great things. Giving people the skill sets to do great things will take work.

If a typical person can do a mental task with less than one second of thought, we can probably automate it using AI either now or in the near future.

We can build a much brighter future where humans are relieved of menial work using AI capabilities.

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.

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.

There are two companies that the AI Fund has invested in - Woebot and Landing AI - and the AI Fund has a number of internal teams working on new projects. We usually bring in people as employees, work with them to turn ideas into startups, then have the entrepreneurs go into the startup as founders.

Google Brain, which I led, was arguably the single biggest force for turning Google into a great A.I. company. I'm pretty sure I led the team that transformed Baidu as well. So one thing that really excites me is the potential for other companies to become great A.I. companies.

Baidu and Google are great companies, but there are a lot of things you can do outside them. Just as electricity and the Internet transformed the world, I think the rise of modern A.I. technology will create a lot of opportunities both for new startups and for incumbent companies to transform.

If we can make computers more intelligent - and I want to be careful of AI hype - and understand the world and the environment better, it can make life so much better for many of us. Just as the Industrial Revolution freed up a lot of humanity from physical drudgery I think AI has the potential to free up humanity from a lot of the mental drudgery.

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.

The Chinese market is very different. One of the things that I believe is that the biggest, hottest tech trend in China right now is O2O, or online-to-offline.

I think the rise of A.I. is bigger than the rise of mobile. Large companies are sometimes as worried about startups as startups are about large companies. Ultimately, it will be about who delivers the best service or product.

The biggest ethical challenge AI is facing is jobs. You have to reskill your workforce not just to create a wealthier society but a fairer one. A lot of call centre jobs will go away, and a radiologist's job will be transformed.

Our education system has succeeded so far in teaching generations to do different routine tasks. So when tractors displaced farming labor, we taught the next generation to work in factories. But what we've never really been good at is teaching a huge number of people to do non-routine creative work.

When you become sufficiently expert in the state of the art, you stop picking ideas at random. You are thoughtful in how to select ideas and how to combine ideas. You are thoughtful about when you should be generating many ideas versus pruning down ideas.

Job displacement is so huge, I'm tempted to not talk about anything other than that.

None of us today know how to get computers to learn with the speed and flexibility of a child.

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.

One of the things Baidu did well early on was to create an internal platform that made it possible for any engineer to apply deep learning to whatever application they wanted to, including applications that AI researchers like me would never have thought of.

Life is shockingly short; I don't want to waste that many days.

Despite all the hype and excitement about AI, it's still extremely limited today relative to what human intelligence is.

Every company has messy data, and even the best of AI companies are not fully satisfied with their data. If you have data, it is probably a good idea to get an AI team to have a look at it and give feedback. This can develop into a positive feedback loop for both the IT and AI teams in any company.

We're making this analogy that AI is the new electricity. Electricity transformed industries: agriculture, transportation, communication, manufacturing.

Most of the value of deep learning today is in narrow domains where you can get a lot of data. Here's one example of something it cannot do: have a meaningful conversation.

The thing that really excites me today is building a new AI-powered society.

The way AI complements people's work, it actually creates a lot of new jobs, a lot of demand. For example, if a automatic visual inspection technology helps spot flaws in manufacturing parts, I think that in some cases, this does create a lot more demand for people to come in to rework or to fix some of the parts that an AI has found to be flawed.

If you want to publish data, you should do it to share knowledge.

I am super optimistic about the near-term prospects of AI because every time there is a technological disruption, it gives us the opportunity of making the world a little different.

There's a very long tail of all sorts of creative products - beyond our core web search, image search and advertising businesses - that are powered by deep learning.

I believe that the ability to innovate and to be creative are teachable processes. There are ways by which people can systematically innovate or systematically become creative.

It seemed really amazing that you could write a few lines of code and have it learn to do interesting things.

India has a large base of tech talent, and I hope that a lot of AI machine learning education online will allow Indian software professionals to break into AI.

I thought the best place to advance the AI mission is at Baidu.

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.

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.

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.

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.

Our educational system globally has not been historically great in reskilling for newer job roles. We need a new social contract to do that. For India, lack of an incumbent structure might be an advantage, where it can use digital education to leapfrog.

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.

AI is witnessing an early innings in India. It has a thoughtful government, and India can race ahead if it chooses to.

Deep-learning will transform every single industry. Healthcare and transportation will be transformed by deep-learning. I want to live in an AI-powered society. When anyone goes to see a doctor, I want AI to help that doctor provide higher quality and lower cost medical service. I want every five-year-old to have a personalised tutor.

It is difficult to think of a major industry that AI will not transform. This includes healthcare, education, transportation, retail, communications, and agriculture. There are surprisingly clear paths for AI to make a big difference in all of these industries.

A single neuron in the brain is an incredibly complex machine that even today we don't understand. A single 'neuron' in a neural network is an incredibly simple mathematical function that captures a minuscule fraction of the complexity of a biological neuron.

I had a strong interest in free online education, and I was interested in what videos and formats would work for it. A lot of education workers were very sceptical about what computer scientists were doing. It was only after the first visible success of MOOCs that they started to take it seriously.

One thing I've been doing at Baidu is running a workshop on the strategy of innovation. The idea is that innovation is not these random unpredictable acts of genius but that, instead, one can be very systematic in creating things that have never been created before.

I think the world will just be better if AI is helping us. It will reduce the cost of goods, giving us good education, changing the way we run hospitals and the health-care system - there's just a long list of things.

Speech recognition today doesn't really work in noisy environments.

I want an AI-powered society because I see so many ways that AI can make human life better. We can make so many decisions more systematically or automate away repetitive tasks and save so much human time.

I am looking into quite a few ideas in parallel and exploring new AI businesses that I can build. One thing that excites me is finding ways to support the global AI community so that people everywhere can access the knowledge and tools that they need to make AI transformations.

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.

In English, there is one word for sister. In Chinese, there are two separate words, for elder and younger sister. This is actually a translation problem because if you see the word sister, you don't know how to translate it to Chinese because you don't know if it's an elder sister or younger.

Education is one of the industry categories with a big potential for AI. And Coursera is already doing some of this work.

Elon Musk is worried about AI apocalypse, but I am worried about people losing their jobs. The society will have to adapt to a situation where people learn throughout their lives depending on the skills needed in the marketplace.

I think that, hundreds of years from now, if people invent a technology that we haven't heard of yet, maybe a computer could turn evil. But the future is so uncertain. I don't know what's going to happen five years from now. The reason I say that I don't worry about AI turning evil is the same reason I don't worry about overpopulation on Mars.

One of the things that Baidu did well early on was to create an internal platform for deep learning. What that did was enable engineers all across the company, including people who were not AI researchers, to leverage deep learning in all sorts of creative ways - applications that an AI researcher like me never would have thought of.

In healthcare, we are beginning to see that AI can read the radiology images better than most radiologists. In education, we have a lot of data, and companies like Coursera are putting up a lot of content online.

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.