71–80 of 82 posts
Ng's wife's company, Drive.ai, has made more progress in less time and with fewer resources than anybody in the autonomous driving space. So it's probably a billion dollar company. I wonder if that has anything to do with it. There's a lot of money in autonomous driving startups that can deliver results.
Just as electricity transformed many industries roughly 100 years ago, AI will also now change nearly every major industry This is an underrated point, and something I don't think most people outside of the high level Machine Learning/AI world take seriously. It's also one of the biggest challenges for the industry going forward because of natural monopolies. I say that because if AI is electricity then data is the c…
I can't think of other areas where it'll have such a big impact. Robotics (other than Automated driving) has decades more left to fulfill its promise.
Wow, I'm amazed at Andrew's list of accomplishments. I mean any one of these would be a career capstone for most people - Stanford Professor - Founding lead of the Google Brain project - Author of one of the most famous and loved MOOC's - Head of AI for Baidu, built up the AI team in both China and the US. - Founder of Coursera And I see from wikipedia that he and I are roughly the same age :( Engineers are often see…
I don't mean to put down Andrew's achievements, but once you have a dense enough (high-impact) network, these things appear to happen on their own. Also note: Andrew's wife is the founder of Drive.ai (and the other two founders are his students).
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I don't mean to put down Andrew's achievements, but once you have a dense enough (high-impact) network, these things appear to happen on their own. Also note: Andrew's wife is the founder of Drive.ai (and the other two founders are his students).
The smartest thing Andrew has done is to hire a PR agent right after he did the ml-class MOOC, and never breathed a day without consulting him/her ever since.
Wow, I'm amazed at Andrew's list of accomplishments. I mean any one of these would be a career capstone for most people - Stanford Professor - Founding lead of the Google Brain project - Author of one of the most famous and loved MOOC's - Head of AI for Baidu, built up the AI team in both China and the US. - Founder of Coursera And I see from wikipedia that he and I are roughly the same age :( Engineers are often see…
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The distinction should be made between training data and [actionable] data. In the former case we are taking data, labeling it, then using it to build our nets and models. You are correct to an extent that it's a usable model once trained and that data is less important. However, equally if not more important is the data that is being put into the net to come out as a result/action. Arguably this data comes through t…
If you don't have data to "put into the net" then you don't have a problem that you want to solve.
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> AI is electricity then data is the coal/oil that drives it. The big technology players have a massive advantage in their ability to build and deploy tools that collect the data, and then bring it back to be turned into "electricity." Data is important now, but when we have solved vision, speech, text and robotics to a decent degree, data won't matter as much. The great thing about AI is that we can cheaply copy alr…
Was about to say the same thing. The incumbents are probably even at a disadvantage because as a young upstart you can always get in on the action by building a more efficient and simpler model and then querying the incumbents to bootstrap yourself.
Except the big 5 have hoovered up a good portion of the ML talent from the universities and are themselves leading the pack in iterative improvement on ML capabilities.
If you are trying to bootstrap a ML company with the trickle of raw data that the big 5 puts out, you're not going to ever get to their size.
This is not about being able to create a 300k/yr company off the back of some table scraps. It's about major companies having too much influence over one market.
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Or, perhaps a little less cynically, that it takes a long time for your work to reach a critical mass, but past that point many factors come into play that allow you to ship stuff at a much increased pace: your work has a much higher visibility, more people are willing to collaborate with you, you have easier acccess to grants, etc
Become Stanford professor > Get prominent job > show you're cool > Get invited to do things! But I doubt his work rate and energy was any less before, just as you say, it's visibility. And very cool. Maybe we should all be on the lookout for at least one career move, that gains us a relative boost in visibility, even at the expense of other desiderata.
Just as electricity transformed many industries roughly 100 years ago, AI will also now change nearly every major industry This is an underrated point, and something I don't think most people outside of the high level Machine Learning/AI world take seriously. It's also one of the biggest challenges for the industry going forward because of natural monopolies. I say that because if AI is electricity then data is the c…
It's not clear that it will change every industry; it'll definitely lead to great job losses in certain fields with the oncoming ADAS boom. I can't think of other areas where it'll have such a big impact. Robotics (other than Automated driving) has decades more left to fulfill its promise.