Top 50 Andrew Ng Quotes

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.

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

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.

Machine learning is the most popular course for people from India. There is a window of time when India can embrace and capture a large fraction of the AI opportunity. But it will not remain open for ever.

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.

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.

With the Google Brain project, we made the decision to build deep learning processes on top of Google’s existing infrastructure.

I am always mission driven, and I always ask myself what I want to be working on, what project excites me the most. I figure that out and then find the best place to do that work.

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.

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.

Imagine if we can just talk to our computers and have it understand, ‘Please schedule a meeting with Bob for next week.’ Or if each child could have a personalized tutor. Or if self-driving cars could save all of us hours of driving.

I think that solving the job impact of AI will require significant private and public efforts. And I think that many people actually underestimate the impact of AI on jobs. Having said that, I think that if we work on it and provide the skill training needed, then there will be many new jobs created.

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.

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.

People change jobs much more often, and therefore, companies, on average, invest less in employee development.

The true value proposition of education is employment.

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.

I think the next massive wave of value creation will be when you can get a manufacturing company or agriculture devices company or a health care company to develop dozens of AI solutions to help their businesses.

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

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

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.

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

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.

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

I joined Baidu in 2014 to work on AI. Since then, Baidu’s AI group has grown to roughly 1,300 people, which includes the 300-person Baidu Research. Our AI software is used every day by hundreds of millions of people.

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

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.

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.

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 two things I’m most excited about are self-driving cars and speech. Speech doesn’t sound like that much, but it’s one of those technologies with the potential to change everything. Steve Jobs didn’t invent the touch screen. He just made it work very well, and that’s changed everything.

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.

I think that AI will lead to a low cost and better quality life for millions of people. Like electricity, it’s a possibility to build a wonderful society. Also, right now, I don’t see a clear path for AI to surpass human-level intelligence.

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.

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.

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.

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’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.

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.

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.

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.

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

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’ve been to so many manufacturing plants. I’ve yet to walk into one where I did not think AI solutions wouldn’t help.

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.

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.

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

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

There are so many problems in the world worth working on and so many discoveries to make, you have to make a choice. My preference is to focus my efforts on solving problems that will help people.

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.

Deep learning is a very capital-intensive area, and it’s rare to find a company with both the necessary resources and a company structure where things can get done without having to pass through too many channels and committee meetings.