
Artificial Intelligence Lecture Videos - BucketSort
https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010/lecture-videos/
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jeyoor
On just a quick glance, the breadth of the topics covered here is stunning.

I also liked this quote from Lecture 23.

> A lot of times we ... confuse value with complexity.

> And many of the things that were the simplest in this subject are actually
> the most powerful.

> So be careful about confusing simplicity with triviality and thinking that
> something can't be important unless it's complicated and deeply
> mathematical.

~~~
BucketSort
Nice observations. The trade off is he doesn't go too deeply into anything,
but it's a great survey. Especially for people not acquainted with AI outside
of ML.

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kennethfriedman
Professor Winston (the lecture in these videos), also teaches a higher-level,
seminar based AI reading class called "The Human Intelligence Enterprise".

It too, is an incredible class. Here's the schedule & linked papers from last
semester:
[https://courses.csail.mit.edu/6.803/schedule.html](https://courses.csail.mit.edu/6.803/schedule.html)

(Disclaimer: Professor Winston is my current advisor)

~~~
BucketSort
Could you recommend any good books that would supplement this course? Also,
why does this course seem so weird. What's with the "communication"
assignments. Also, what's the deal with his project "genesis." Really
interesting stuff. I hope I get a chance to pick your brain.

~~~
kennethfriedman
Minsky's Society of Mind would be a good launching off point. Other than that
particularly famous example, I would just check out any of the authors of the
papers in that link.

This class fulfills a communication requirement at MIT, so there are a one-
page response/reflections due at each class. These reflections basically just
ensure that you have a decent grasp at the main points of the paper, so that
you would be ready for a seminar-style discussion in class.

Genesis is pretty interesting. Here's a link to the details:
[http://groups.csail.mit.edu/genesis/](http://groups.csail.mit.edu/genesis/)
But in short, it's an attempt to get computers to understand stories — and to
discover what is the fundamental difference between the human mind and all
other animals (spoiler alert: Winston's group believes it's the ability for
humans to take two concepts and merge them into a new concept, indefinitely.
AKA: creating "stories"). So the goal of Genesis is story-understanding.

~~~
BucketSort
Thanks for the link. I read through the three main papers. Very interesting.
The project seems to be dead though. Why hasn't there been any development in
the past few years? Did you guys reach a hurdle you couldn't overcome? Or have
people's interests shifted? Thanks for taking the time to answer Kenneth.

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todd8
I took this class given by Prof. Patrick Winston a while back, 43 or 44 years
ago. I liked it so much back then, it served me well in grad school and for
many years after. Next week I'm visiting with an AI company on behalf of
potential investors.

~~~
asimuvPR
You took the class 43-44 years ago? Is that a typo? If not, mind sharing more
about your experience?

~~~
finin
I took his AI class, 6.258, 45 years ago, in the Spring of 1971. It was
probably the first or second time he taught it. He's a great teacher and
inspired me to focus on AI. One aspect I remember was that our exams were all
take home exams that we had several days to work on. They were great learning
experiences.

~~~
asimuvPR
Amazing :)

Wish you listed a method of contact. I really enjoy having conversations with
more experienced hackers.

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icpmacdo
Lecture 15 is really really worth watching through, even if your not familiar
with the previous lectures

[https://ocw.mit.edu/courses/electrical-engineering-and-
compu...](https://ocw.mit.edu/courses/electrical-engineering-and-computer-
science/6-034-artificial-intelligence-fall-2010/lecture-
videos/lecture-15-learning-near-misses-felicity-conditions/)

~~~
byebyetech
Just wondering why do you recommend this particular lecture so highly ?

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kennethfriedman
I'm guessing, because the back half of the lecture has some great life lessons
in it.

~~~
icpmacdo
Yes exactly, I was not expecting a deeply useful life lesson at the end of a
random AI lecture I found on YouTube.

Really stands out as one of the best lectures I have had the pleasure of
watching.

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antirez
If you are interested in zooming into neural networks, at Coursera Hinton
himself will teach you a great deal of things:
[https://www.coursera.org/learn/neural-
networks](https://www.coursera.org/learn/neural-networks)

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zardo
This is a terrific class. I also recommend:
[https://ocw.mit.edu/courses/electrical-engineering-and-
compu...](https://ocw.mit.edu/courses/electrical-engineering-and-computer-
science/6-042j-mathematics-for-computer-science-fall-2010/)

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inovica
I have a side project to monitor the homepage of every domain and I want to
detect the type of site - ecommerce, blog, forum etc. I've just started on it
and ultimately I want to be able to automatically extract data, such as
product information from ecommerce sites. Would these videos help here or is
there anywhere else that someone would recommend. I know I sounds very naive
here... and I am, but there might be someone here who can give me a steer.
I've started looking at AI/ML... or whatever its now called and getting a bit
confused!

~~~
fnbr
You could absolutely do it. Here's a few things you could do to get started
(feel free to email me if you need more specific help, or have any additional
questions- my email's in my profile):

1\. Get as much data about each site as possible. Try to find data that you
think will separate the non-ecommerce sites from the ecommerce sites. This
data should be in a table form- think of an Excel spreadsheet, where each row
represents a different site.

2\. Label the data as belonging to each type of site. This is going to be
tedious and take some time. You can also try hiring people via Mechanical Turk
to do this.

3\. Use
[Weka]([http://www.cs.waikato.ac.nz/ml/weka/](http://www.cs.waikato.ac.nz/ml/weka/))
or [Vowpal
Wabbit]([https://github.com/JohnLangford/vowpal_wabbit/wiki](https://github.com/JohnLangford/vowpal_wabbit/wiki))
to run some preliminary estimations on the model. Weka and VW are great tools
as they come with a lot of the configuration done out of the box, so you won't
have to write any code to get started.

Check your results and see how happy you are with them. Weka has a lot of
visualization capacities, so you can see how the data that you've collected
aligns with the different types of sites.

Now, you can start iterating, which is the key part of any ML project.
Consider which aspects of the model you think you can improve on- adding more
data, adding more kinds of sites, using a different machine learner.

~~~
afro88
> 1\. Get as much data about each site as possible. Try to find data that you
> think will separate the non-ecommerce sites from the ecommerce sites. This
> data should be in a table form- think of an Excel spreadsheet, where each
> row represents a different site.

This will be the hardest step. Feature extraction from html for identifying
specific things like products, for any given site, is very hard (in my
experience, which I will admit is pretty limited). Would love to be proven
wrong though.

~~~
fnbr
I was thinking you could approach it as a document classification problem,
where you extract the text from the HTML and work with that.

I had a lot of success finding duplicate bug reports by comparing the text
from the bug reports with reference documents in a variety of topics (e.g.
security, networking, C++), and getting a sense of how similar the text is to
the reference text. That gives you a score of how relevant each subject is to
the document.

You could do something similar here- download the text from 10 ecommerce
sites, run some sort of topic extraction algorithm (like LDA) on it and then
compare the text from the sites you're trying to classify with the text from
the reference sites.

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carlosgg
_MEGA-Recitation_ Videos :-)

[https://ocw.mit.edu/courses/electrical-engineering-and-
compu...](https://ocw.mit.edu/courses/electrical-engineering-and-computer-
science/6-034-artificial-intelligence-fall-2010/mega-recitation-videos/)

~~~
cagmz
Wow, are you my doppelgänger? We share the same name and I was about to post
the same link.

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monfrere
I took this class a couple of years ago. It's outdated and overrated imho,
with nowhere enough mathematical rigor to be useful. For example, the
discussion of support vector machines (and classification in general if I
recall correctly) was limited to two dimensions so that you didn't need linear
algebra. The class also spends a lot of time on problems like path finding
that you should be able to solve with your standard CS algorithms toolkit or
just "logic" rather than needing to reach for anything that deserves the name
"artificial intelligence" (at least today). Prof. Winston furthermore spends
way too much time on vague truisms that may sum up or organize what's in his
brain but aren't helpful to students. ("What if the answer doesn't depend on
the data at all? Then you've got the trying to build a cake without flour.")

I hate to dismiss something as ambitious as this course and just tell people
to blindly follow trends, but my honest advice would be to just skim these
notes if you're interested and go take a normal machine learning course
instead.

~~~
joelg
It depends on what you want out of it! If you're looking for immediately
practical skills, of course you're better off taking 6.036 (machine learning).
That's not the point of 6.034, which is something more vague that emphasizes
intuition over rigor. Personally I think that offering both - a skills-
oriented class and an idea-oriented class - is super cool and unique and I
wish that pattern was more common.

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matmatmttam
Anyone has lecture 20? - "Lecture 20, which focuses on the AI business, is not
available."

~~~
BucketSort
Good catch. I can't seem to find it either on YouTube.

~~~
zardo
According to a YouTube comment... Prof. Winston did not allow OCW to share
that lecture, no reason was given.

~~~
akhilcacharya
He's keeping a competitive advantage for MIT students probably :)

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o2l
Does anyone think these lectures would be a good place to start for someone
with web development experience (LAMP + JS) and zero AI & ML knowledge ?

If yes, what is missing from these lectures ( related to AI or ML or Deep
Learning ) which has been discovered or developed recently and should be
learned during the start ?

~~~
zardo
It's a great introduction to the broader world of AI, but you will barely skim
the surface of ML.

~~~
o2l
What would you recommend then ?

~~~
zardo
Andrew Ng's ML course and Chris Olah, Andrej Karpathy, and Jeremy Kun's blogs
were great resources that contributed to my understanding of ML.

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msie
Wow! Taught by Patrick Winston, he was the author of my AI textbook many moons
ago! You can still meet many of the legends of Computing Science...

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zelon88
Amazing! I hope you don't mind but I cross-posted to /r/artifical. Thanks for
the videos! This will make sure I get nothing done tonight but I should be
smarter in the morning!

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sotojuan
One day I hope to have enough time to go through a majority of OCW!

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sudhirkhanger
What are requirements for this course?

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sagivo
you can find all of the videos in this youtube playlist -
[https://www.youtube.com/watch?v=TjZBTDzGeGg&list=PLUl4u3cNGP...](https://www.youtube.com/watch?v=TjZBTDzGeGg&list=PLUl4u3cNGP63gFHB6xb-
kVBiQHYe_4hSi)

