Top 103 Quotes & Sayings by Andrew Ng - Page 2

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.

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.

There are some outcomes in finance we don't want, and government should regulate that.

We think that many companies view Coursera as a quality, convenient, inexpensive way to continue employee development. Is there a contract with a company that might make sense? I don't have an answer to that yet.

I'm super excited about health care; I'm super excited about education - major industries where AI can play a big role.

No university is the best place to execute every mission and no one company the best place to execute every mission.

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.

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.

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.

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.

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.

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.

We're doing a lot of work on self-driving cars. We do not currently have cars in the U.S., but we plan to, for development and testing. I think we are within striking distance of making self-driving cars a reality, and these would be powered by deep learning.

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.

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.

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

One of my relatives had been asking me on how he could break into AI. For him to learn AI - deep-learning, technically - a lot of facts exist on the Internet, but it is difficult for someone to go and read the right combination of research papers and find blog posts and YouTube videos and figure out themselves on how to learn deep-learning.

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

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.

With human inspectors, it's difficult to get even the same person to make consistent judgments.

I find it a very encouraging sign for a society if employers are bringing online education to their companies, helping employees gain more knowledge.

Animals see a video of the world. If an animal were only to see still images, how would its vision develop? Neuroscientists have run experiments in cats in a dark environment with a strobe so it can only see still images - and those cats' visual systems actually underdevelop. So motion is important, but what is the algorithm?

When you go to Japan, there is such a talent shortage that the debate about AI taking jobs is almost non-existent. The debate is, how can we automate this so we can get all the work done?

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.

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.

Beyond helping other people build AI systems with Deeplearning.ai, I also hope to build some AI systems myself!

I think the first wave of deep learning progress was mainly big companies with a ton of data training very large neural networks, right? So if you want to build a speech recognition system, train it on 100,000 hours of data.

The true value proposition of education is employment.

AI is creating tremendous economic value today.

Want to train a machine translation system? Train it on a gazillion pairs of sentences of parallel corpora, and that creates a lot of breakthrough results. Increasingly, I'm seeing results on small data where you want to try to take in results even if you have 1,000 images.

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 will continue my work to shepherd in this important societal change... In addition to working on AI myself, I will also explore new ways to support all of you in the global AI community so that we can all work together to bring this AI-powered society to fruition.

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.

It takes a government to set up public-private partnerships and develop university programmes. I think this is the best path for India, given the rapid progress the country has already made and given the rapid progress we all hope India will continue to make.

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

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.

Even companies like Baidu and Google, which have amazing AI teams, cannot do all the work needed to get us to an AI-powered society. I thought the best way to get us there would be creating courses to welcome more people to deep learning.

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

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.

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.

If you show a poetry professor your shiny new multiple choice teaching technology, he will invite you to exit his office.

No one knows what the right algorithm is, but it gives us hope that if we can discover some crude approximation of whatever this algorithm is and implement it on a computer, that can help us make a lot of progress.

Imagine if your success in life is determined only by your guts, your hard work, and your willpower, and not by the wealth of your parents. I think it'll be a much more interesting world. I think this could change the way the planet is run.