> People that count on willpower to do these things, it almost never works because willpower peters out. Instead I think people that are into creating habits -- you know, studying every week, working hard every week -- those are the most important. Those are the people most likely to succeed.<p>That is the one insight that I wished I truly understand years ago. After figured out that intelligence barely means anything, I thought that willpower would be the most important characteristics (because of endurance, perseverance yada yada you know).<p>Turned out that just like physical muscle, mental muscle get exhausted and you can run out of them. You really can't exert your willpower all the time, and have to preserve them for the really tough time. As human tends to do, we reverse to our habits for the majority of our lives. Well, I hope it's not a lesson learned too late.<p>That said, training for habits is damn hard.
>(On Tuesday, Baidu announced it had achieved the world's best results on a key artificial intelligence benchmark related to image identification, besting Google and Microsoft.)<p>And a week later was found to have cheated in said test, apologized, and withdrew its results[0].<p>[0] <a href="http://www.technologyreview.com/view/538111/why-and-how-baidu-cheated-an-artificial-intelligence-test" rel="nofollow">http://www.technologyreview.com/view/538111/why-and-how-baid...</a>
I loved his critique of the recent hyperventilation about AI taking over the world--<p>"I don't work on preventing AI from turning evil for the same reason that I don't work on combating overpopulation on the planet Mars."<p>As he points out later in the interview, much of the recent gains have been due to a great increase in data and computational power. The history of AI is replete with incredibly overoptimistic predictions of achieving Strong AI. Andrew's focus on the current, important problems of the field bodes well for the future of Baidu's AI work.
> As Ng explained, "The remarkable thing was that [the system] had discovered the concept of a cat itself. No one had ever told it what a cat is. That was a milestone in machine learning."
If you dont mind, let me call this bullshit out. No one in machine / deep learning thinks that this was anything more than PR fluff combined with a very very weak paper that people had to approximately cheat to find the actual cats. (You had to initialize your random vector very close to an actual cat image, and do gradient descent, before it "figured out" for itself about a cat).
I'm taking his machine learning course [1] and it's absolutely fantastic. It's one of the mondern wonders of the internet that you can have such a tutor for free. Plus it's fascinating to see what people go on to do after the course [2].<p>[1]: <a href="https://www.coursera.org/learn/machine-learning/" rel="nofollow">https://www.coursera.org/learn/machine-learning/</a><p>[2]: <a href="https://syrah.co/joshdickson40/5604e5e10fc1786b0152a51a" rel="nofollow">https://syrah.co/joshdickson40/5604e5e10fc1786b0152a51a</a>
At first sight I thought that the microphone was an spermatozoon mad with joy stirred up by Plutarch's quotation. Unfortunately that was only an illusion and life is not such exciting today.<p>To force to your mind to work creatively you must feed your mind with lots of examples and experiences. And the suggested way to accelerate the learning process is via showing off corner cases.<p>Innovation places us in a field in which the corner cases are unknown unknowns, his workshop is about an strategy to detect and anticipate corner cases in uncharted territories. That amounts to finding the fount of creativity, and that is not an easy feat.<p>Edited n+1 times for learning English.
> After figured out that intelligence barely means anything<p>I think that's probably an exaggeration. A better way to say it might be: intelligence only takes you so far, and true achievement requires something more.
Before you buy into the negativity of some comments on this thread, take a moment to pause. Andrew has achieved some truly remarkable feats. Why not accept what he has achieved is many standard deviations away from the average, and try and learn from what he thinks was useful?<p>To me, that the top comment right now is about how Baidu "cheated" on an AI benchmark says both that no one can have perfect oversight, but also that no matter your other achievements, someone will always point out a shortcoming.
I am learning the course of Machine Learning [1] at Coursera. I didn't know he co-founded Coursera. Can't believe this awesome course is free. Andrew Ng is really a good teacher. Thank you Andrew Ng and Coursera.<p>[1] <a href="https://www.coursera.org/learn/machine-learning/" rel="nofollow">https://www.coursera.org/learn/machine-learning/</a>
> But often, you first become good at something, and then you become passionate about it. And I think most people can become good at almost anything.<p>So many people don't get this. When parents send you to learn a profession, don't say "I'll do what I want". You can always do it later.<p>Instead, go get a proper, extensive education in anything - it will help you immensely, and you might find that you love doing what you learned.<p>Otherwise, you may waste years being stuck in a loop of finding yourself and your purpose, which sometimes really sucks...