Artificial Intelligence – Debunking Myths

Exploring around the interwebs, I came across this article by Rupert Goodwins in ArsTechnica about debunking myths about Artificial Intelligence. 

HAL 9000 in the film 2001.

It is a good read and it you have a few minutes to spare, do give it a go.

Rupert addresses the following myths:

  1. AI’s makes machines that can think.
  2. AI will not be bound by human ethics.
  3. AI will get out of control
  4. Breakthroughs in AI will all happen in sudden jumps.

It is true that there are a number of effort to try to replicate (and therefore understand) human thought. Some examples include the Blue Brain project in the École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland. However, this does not imply that they will get immediately a machine such as HAL or C3-PO.

This is because the brain is fat more complex than the current efforts are able to simulate. As a matter of fact, even simpler brains are significantly more complex for simulation. This does not mean that we should not try to understand and learn how brains work.

Part of the problem is that it is difficult to even define what we mean by “thought”— the so called hard problem. So finding a solution to the strong AI problem is not going to be here soon, but we should definitely try.

So, once that myth is out of the way, the idea that a Terminator-like robot is around the corner is put into perspective. Sure, there are attempts at getting some self-driving cars and such but we are not quite there yet. All in all, it is true that a number of technological advances can be used for good or bad causes, and that is surely something that we all should bear in mind.

Data Science and Machine Learning Podcasts

I have been having a break from creating the Quantum Tunnel Podcast. Partly this was because I did not have a suitable replacement to host the material after Apple got rid of MobileMe and sites… Then I just didn’t have that much time. I will pick it up one of these days… Do remind me please.

Nonetheless, my podcast listening has continued and I get my fix from the likes of the excellent RadioLab podcast, Freakonomics and even More or Less. Recently I have started collecting podcasts that talk about data science and machine learning and here are some examples of what has hit my podcast list:

DataStoriesPodcastData Stories

Data Stories is a great chat forum between Enrico Bertini and Moritz Stefaner plus guests; really interesting guests! The main focus is data visualisation but they chat about all sorts of related topics.

iTunes

Data SkepticThe Data Skeptic

The Data Skeptic ranges from 10 minute conversations between Kyle Polich and his wife Linda, trying to elucidate concepts and areas of interest in statistics, machine learning, probability and others, through to interviews/chats with guests. Worth checking out!

iTunes

Linear DigressionsLinear Digressions

Covering information about machine learning and data science, this podcast is brought to us by Udacity’s Ben Jaffe and Katie Malone. Weekly episodes will keep you well informed.

iTunes

Talking MachinesTalking Machines

I really enjoy the conversations that Katherine Gorman and Ryan Adams have regarding topics around machine learning. I like the question and answer session where listeners can send their queries. Interesting guests and always fun to listen to

iTunes

Data ShowThe O’Reilly Data Show

I recently heard about this podcast and just downloaded the latest episode but have not had a chance to hear it. I assume that the information will be as interesting as other O’Reilly’s outlets. Looking forward to hearing what Ben Lorica has to say!

iTunes

Partially DerivativePartially Derivative

Why would you not listen to a podcast with such a cool name? Besides, Jonathon Morgan and Chris Albon chat over a beer is a good fun way to hear about the latest and greatest in the data science and technology arena.

iTunes

Learning MachinesLearning Machines 101

In the best style of a 101 course, this podcast addresses questions such as how do devices that use machine learning work? How can they get in smarter? What does it take to make them more human-like? Listen to it to find out some answers!

iTunes

This is not an exhaustive list, let me know of your favourite podcasts and why you like them!

Help me! I’m a Tweenbot…

tweenbot
Image by xbettyx via Flickr

I am sure that most people have found themselves in a situation where they need a bit of help from people around. Are you trying to find an address, but can’t figure out where it is? Do you need directions to the closest cashpoint? Or perhaps you simply need to know where you are? Well, asking people around you might be the best solution.

Now, you might be at the other end of these situations, and I am sure that you have provided someone else with the key information to ge to the closest petrol station. But, how would you react if the request did not come from a human being, but from a robot? Would you help it find its way? Well, if you happen to be in New York City, this question might actually be possible. Kacie Kinzer has tried to answer this question by launching the Tweenbots project.

So, what are Tweenbots? According to Kacie:

Tweenbots are human-dependent robots that navigate the city with the help of pedestrians they encounter. Rolling at a constant speed, in a straight line, Tweenbots have a destination displayed on a flag, and rely on people they meet to read this flag and to aim them in the right direction to reach their goal.

the directions
Image by noneck via Flickr

Kacie shot a video of the first mission in Washington Park in NYC and to her surprise most people actually stopped to help the robot to reach its destination. It seems that people treat the smiley robot as a live being. In the video you can see how people stop and help the robot when it gets stuck, or change the direction in case it is going in the wrong way.

What would you do if you came across a wandering robot in need of a nudge to the right direction? Would you help it?