
Andrew Ng on Life, Creativity, and Failure - igonvalue
http://www.huffingtonpost.com.au/2015/05/13/andrew-ng_n_7267682.html
======
NhanH
> 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.

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).

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.

That said, training for habits is damn hard.

~~~
ronyeh
If you want to try out a new technique to train for habits, check out this
site by BJ Fogg @ Stanford University:

[http://tinyhabits.com/](http://tinyhabits.com/)

The method trains you to add a new habit to your life by doing a tiny habit
every day, anchored to an already existing habit. For example, "Before I visit
Hacker News, I will drop down and do TWO pushups." Eventually, you can grow
your new habit to make it a bigger part of your life.

~~~
lindseya
There is a lot of focus in the literature right now on developing habits. What
I'm interested in is the deeper motivations that drive a person to select
their habits in the first place. Why does Andrew read research papers and
books all day on a Saturday? Why did you decided to add two pushups to your
daily routine? I think that without understanding these deeper motivations, we
are left with habits that do not have enough fuel to drive them, leaving us to
resort to the habits with the least resistance (i.e. lazy habits).

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desdiv
>(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.)

And a week later was found to have cheated in said test, apologized, and
withdrew its results[0].

[0] [http://www.technologyreview.com/view/538111/why-and-how-
baid...](http://www.technologyreview.com/view/538111/why-and-how-baidu-
cheated-an-artificial-intelligence-test)

~~~
karpathy
I have no affiliation with Baidu but I'd like to defend them on this point a
bit because it seems to me that they are getting quite a lot more hate than
they deserve. Baidu had a without-a-doubt strong and at the very least a very
near state of the art visual recognition system. Then a group of people within
the company tried to squeeze out all the last few 0.01% they could with
questionable means. When people erase all context and say Baidu cheated, it
sounds as if there was a wide, organized top-down effort within Baidu to make
their bad system look good with blatant cheating. None of which, in my mind,
was the case. A slap on the wrist is more appropriate than burning at stake.
</endrant>

------
ryporter
I loved his critique of the recent hyperventilation about AI taking over the
world--

"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."

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.

~~~
Sven7
Chomsky has been saying this for a long time. He equates our current language
tech with stone age tools. Long way to go...

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strangeworld1
> 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).

~~~
asgard1024
I am not sure why you're saying they cheated. I am a layman, but my
understanding of that quote is that he refers to a rather large deep neural
network, which was trained unsupervised to encode general images (not just
cats), had a neuron representing the concept of "cat". You can run the network
in generative mode to see how the general concept of cat would look like.

So I am puzzled by your comment - you seem to be talking about supervised
learning, but I think the network was trained unsupervised.

~~~
conceit
> 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

and

> a rather large deep neural network, which was trained unsupervised to encode
> general images (not just cats)

seem to be in contradiction, afaict, or was general vector initialized rather
close _general images_?

~~~
pizza
The initial value of the vector determines what it will encode/converge to.

------
icc97
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].

[1]: [https://www.coursera.org/learn/machine-
learning/](https://www.coursera.org/learn/machine-learning/)

[2]:
[https://syrah.co/joshdickson40/5604e5e10fc1786b0152a51a](https://syrah.co/joshdickson40/5604e5e10fc1786b0152a51a)

~~~
copperx
I've heard that the course is diluted compared to the brick-and-mortar school
one, is this true?

------
notsurenot
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.

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.

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.

Edited n+1 times for learning English.

------
Pyxl101
> After figured out that intelligence barely means anything

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.

------
kulkarnic
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?

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.

------
vinceyuan
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.

[1] [https://www.coursera.org/learn/machine-
learning/](https://www.coursera.org/learn/machine-learning/)

------
prodmerc
> 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.

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.

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.

Otherwise, you may waste years being stuck in a loop of finding yourself and
your purpose, which sometimes really sucks...

~~~
temo4ka
I first heard the notion from someone here on HN: instead of doing what you
love, love what you do!

