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.
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.
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.
Speech recognition today doesn't really work in noisy environments.
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?
There are some outcomes in finance we don't want, and government should regulate that.
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.
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.
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.
One of my philosophies of building companies is the importance of velocity.
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.
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.
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.
If you want to publish data, you should do it to share knowledge.
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.
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 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 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.
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.
