101 Quotes by Andrew Ng

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.

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

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.

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.

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.

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.

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.

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?

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.