Andrew Ng: How to be an innovator

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Andrew Ng: How to be an innovator
MIT Technology Review, September 12, 2023
Artificial Intelligence
by Andrew Ng

“Tips for aspiring innovators on trying, failing, and the future of AI.”

 

Innovation is a powerful engine for uplifting society and fueling economic growth. Antibiotics, electric lights, refrigerators, airplanes, smartphones—we have these things because innovators created something that didn’t exist before. MIT Technology Review’s Innovators Under 35 list celebrates individuals who have accomplished a lot early in their careers and are likely to accomplish much more still.

 

Having spent many years working on AI research and building AI products, I’m fortunate to have participated in a few innovations that made an impact, like using reinforcement learning to fly helicopter drones at Stanford, starting and leading Google Brain to drive large-scale deep learning, and creating online courses that led to the founding of Coursera. I’d like to share some thoughts about how to do it well, sidestep some of the pitfalls, and avoid building things that lead to serious harm along the way.

AI is a dominant driver of innovation today

As I have said before, I believe AI is the new electricity. Electricity revolutionized all industries and changed our way of life, and AI is doing the same. It’s reaching into every industry and discipline, and it’s yielding advances that help multitudes of people.

 

AI—like electricity—is a general-­purpose technology. Many innovations, such as a medical treatment, space rocket, or battery design, are fit for one purpose. In contrast, AI is useful for generating art, serving web pages that are relevant to a search query, optimizing shipping routes to save fuel, helping cars avoid collisions, and much more.

 

The advance of AI creates opportunities for everyone in all corners of the economy to explore whether or how it applies to their area. Thus, learning about AI creates disproportionately many opportunities to do something that no one else has ever done before.

 

For instance, at AI Fund, a venture studio that I lead, I’ve been privileged to participate in projects that apply AI to maritime shipping, relationship coaching, talent management, education, and other areas. Because many AI technologies are new, their application to most domains has not yet been explored. In this way, knowing how to take advantage of AI gives you numerous opportunities to collaborate with others.

 

Be optimistic, but dare to fail

That said, a lot of ideas that initially seem promising turn out to be duds. Duds are unavoidable if you take innovation seriously.

 

 

It was painful when these projects didn’t succeed, but the lessons I learned turned out to be instrumental for other projects that fared better. Through my failed attempt at V-shape flying, I learned to plan projects much better and front-load risks. The effort to unload dishwashers failed, but it led my team to build the Robot Operating System (ROS), which became a popular open-source framework that’s now in robots from self-driving cars to mechanical dogs. Even though my initial focus on unsupervised learning was a poor choice, the steps we took turned out to be critical in scaling up deep learning at Google Brain.

 

Innovation has never been easy. When you do something new, there will be skeptics. In my younger days, I faced a lot of skepticism when starting most of the projects that ultimately proved to be successful. But this is not to say the skeptics are always wrong. I faced skepticism for most of the unsuccessful projects as well.

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About the Author:

Andrew Ng is a renowned global AI innovator. He leads AI Fund, DeepLearning.AI, and Landing AI.

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