Wednesday, October 14, 2009

Gmail Machine Learning

I just quickly tried the new Gmail Labs feature "Got the wrong Bob"? and it actually works quite nicely! I put some email addresses of family members, followed by the address of an old professor, who has the same first name of one of my cousins, and... Gmail found it! :) It suggested right way to change to the correct person, based on context!
The other new feature, called "Don't forget Bob", is probably simpler, but quite useful as well. As I typed names of some close friends, I got more suggestions of friends I often email jointly with the previous ones.
I wonder if the models to run this feature are very complicated. Probably they are not. I guess one just has to estimate the probability of each email address in our contacts to appear in the "To:" field, given the addresses we have already typed. To estimate these, you just have to use a frequentist approach and count how many times this happened in the past. With this in hands, "Got the wrong Bob?" will notice unlikely email addresses and "Don't forget Bob" will suggest likely ones that are missing.


I think it's a really cool idea, in the same spirit of "Forgotten Attachement Detector". A bit of machine learning helping daily life!

Monday, October 5, 2009

Schools kill creativity


My good friend Miguel called my attention to a TED talk that you might also find interesting:




Ken Robinson argues that "schools kill creativity", because kids are not given the chance to discover their interests and talents. Since very soon, students get a negative reward for making mistakes, which makes them too risk averse. He goes further, saying that the educational system is built to create university professors, leaving the majority of the students behing along the way. More space should be given to other forms of expressing intelligence, such as the arts or sports.

I strongly recommend this video. Besides the interest of the subject, the presentation is actually quite funny, it somehow resembles a British-style stand-up comedy!


Sunday, August 2, 2009

(My) ideal society

Each individual is respected as such and has the freedom and the means to pursue its own interests without having to harm the others.

Don't know how it looks like. It's a pretty simple (non-constructive) definition, however.
I'm sure mathematicians like it!

Read more at my webpage:
http://hpenedones.googlepages.com/thoughtsonlife

Note: This essay will be in beta version, longer than any Google product.

Wednesday, July 22, 2009

Personal productivity, happiness and optimization algorithms

I spend lots of time wondering about the best ways to be both more productive and happy. Curiously, I'm coming to the conclusion that this is exactly what I should not do.

Being productive, like being happy, requires living the present moment, not thinking about it.

If you want to complete a task, the best strategy is just doing it! You might start by setting up a plan, a sequence of smaller actions that lead you to your goal, but once you have this, just do it. Spending too much energy re-planning and judging yourself along the way is just counter-productive.

Curiously, this is not easy! Our brain seems to have some bad habits hard-wired. Want it or not, we start thinking about the past or making predictions about the future. Worse, we start multi-tasking (as you read this blog, you might also be listening to music, doing some work, or chatting with your friends in facebook)
Perhaps the only solution is to re-train our neuron connections. One way to do it would be meditating or repeatedly performing a task that requires one to be focused on the present. Feeling, not thinking. After enough practicing, the brain should start rewiring.

I recently came across this famous Hemingway sentence:


“Happiness in intelligent people is the rarest thing I know.”


Perhaps intelligent people have the tendency to plan too much? Planning involves predicting the reward associated with a set of possible actions and choosing the best ones. What if the reward function is not easily predictable? Perhaps the best optimization algorithm in this case is a greedy one. Don't plan to be happy only next year or next month or even tomorrow. You are dealing with a real-time multi-agent system, you have only partial and noisy data about the world, the system is recursive, and finding the optimal reward is probably NP-hard-as-it-can-be!

Increasing the scope

In the past it happened that I didn't publish some potentially interesting thoughts in this blog, just because they didn't exactly fit the "about intelligence" topic.
I'm fed up of this self-imposed censorship. In the future the scope will be broader.

Wednesday, May 6, 2009

Machine Learning to AI

John Langford wrote a very interesting post on the failures of Artificial Intelligence research and why Machine Learning has been a safer bet. Read it here.

Wednesday, April 1, 2009

Google CADIE vs Wolfram Alpha

Google already has a tradition of April fool's jokes: this year they are introducing an Artificial Intelligence brain!

They describe the development process of their so called CADIE : Cognitive Autoheuristic Distributed-Intelligence Entity like this:

"For several years now a small research group has been working on some challenging problems in the areas of neural networking, natural language and autonomous problem-solving. Last fall this group achieved a significant breakthrough: a powerful new technique for solving reinforcement learning problems, resulting in the first functional global-scale neuro-evolutionary learning cluster."

Remember, this is an April fool's hoax. But now compare it with Wolfram's announcement of the new Wolfram Alpha:

"I wasn’t at all sure it was going to work. But I’m happy to say that with a mixture of many clever algorithms and heuristics, lots of linguistic discovery and linguistic curation, and what probably amount to some serious theoretical breakthroughs, we’re actually managing to make it work."

I find them quite similar! ;)

Now more seriously: I don't doubt Wolfram Alpha will have interesting features, but please don't try to sell it like the ultimate AI search engine. By the way, Daniel Tunkelang has a recent and well informed post on this topic.

Update: Indeed this sneak preview of Wolfram Alpha shows some cool features! In the meanwhile Google also gave some steps in the direction of better public data/statistics visualization.

Saturday, March 28, 2009

Machine Learning artwork

Today I tried out a great site to generate tag clouds, it is called wordle.net. I rendered some images just by copy-pasting the text from wikipedia about machine learning.

The results were pretty cool and I guess one could print awesome t-shirts with them. What do you say?




This one became officially my computer wallpaper:














Wednesday, March 18, 2009

ACM Paris Kanellakis Theory and Practice Award 2008

The 2008 ACM Paris Kanellakis Theory and Practice Award was awarded to Corinna Cortes and Vladimir Vapnik "for the development of Support Vector Machines, a highly effective algorithm for classification and related machine learning problems".

It's not the first time this award is given to Machine Learning people. In 2004 it was awarded to Yoav Freund and Robert Schapire "for the development of the theory and practice of boosting and its applications to machine learning."

I found a bit weird that they left Bernhard Boser and Isabelle Guyon out of the prize, because they were Vapnik's co-authors in the 1992 paper "A training algorithm for optimal margin classifiers", which I guess is considered to be the first paper on Support Vector Machines...

Anyway, congratulation to the winners. These are indeed elegant algorithms with sound theoretical foundations and numerous sucessful applications to vision, speech, natural language and robotics, to name just a few.

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Remarks:

Thanks to my cousin Rui for the link to this news.

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Related post:

Vapnik's picture explained.

Friday, February 6, 2009

Social features on this blog

The readers of this blog can now:

1. Easily subscribe to the RSS feed with their reader of choice [left panel].
2. Decide to become a visible "follower" of this blog [left panel].
3. Rate each blog entry from 1 to 5 stars [end of each post].

I would be particularly happy to see people rating the posts. It's less informative than writing comments but still it's very good feedback for me.

Thanks!