Fascinating study out of the University of Trento on using Machine Vision algorithms to learn how people respond emotionally to abstract art.
Link : Computers identify what makes abstract art move us
Abstract art might be easier to replicate automatically since you don’t need to worry about as much symbolism and meaning as much. Is this going to put artists out of a job? Well no, people create art because they want to, or need to. If computers can generate abstract patterns and images that are emotionally evocative on demand then that would surely hurt artists who rely on selling their images or the rights to reproduce them in other media.
So, something for artists to be aware of.
Posted by Mark Crowley on November 17, 2012
Baby robot learns first words from human teacher – tech – 15 June 2012 – New Scientist
I’m always glad to see more methods from research in Artificial Intelligence/Machine Learning getting coverage in the media and being explained with some level of detail. Take a look at these two articles on applications of Artificial Intellgience methods in the study of the learning language in infants and in the effects of psychedelic drugs diagnosis. They give a nice high level overview of two powerful approaches that are not quite standard in AI and Machine Learning. The language learning robot is doing supervised learning with reinforcement learning approach where the agent randomly explores a landscape and weights good experiences to improve it’s model. The drugs study is applying a classifier to text descriptions about psychedelic trips and trying to predict the drug that causes it.
Posted by Mark Crowley on June 16, 2012
Take a look at this interesting summary piece describing improving applications of AI to automated writing of news. I couldn’t resist repeating Ken Jenning’s infamous statement after he was defeated by the IBM Jeopardy playing computer Watson, but seriously, I don’t think there is any fear that computers will replace journalists as the writer seems to worry. No computer algorithm is anywhere near the point yet that they can write evocative, insightful prose that encapsulates the experience and reasoning that journalists bring to their jobs.
However, this kind of technology of producing summary posts on a topic in prose could be a useful feature when people are looking for breaking news. Right now if you want to find out about something which is occurring right now and isn’t being covered live on CNN you need to turn to sifting Twitter or google searches yourself manually. To get a good link between the various different feeds you usually need to wait for a human somewhere to integrate those facts together. Much of this initial grunt work of detecting a new story and compiling links can be automated now.
As a tool for journalists these generated articles could even be the initial seeds used to write news stories. Further writing would always be needed and undoubtedly facts would need to be checked and more detail gathered on interesting aspects of the story. But an initial draft of an article generated by an AI system could actually help improve the quality of journalism by focussing humans on the important parts of the story that need to be filled in rather than spending lots of time gathering links to other sources, tweets and articles which are readily available. Perhaps we could even train the automated news summarizers to filter out less relevant stories and improve the quality of news overall.
Posted by Mark Crowley on April 1, 2012
This week I’m in San Francisco attending AAAI11 – the 2011 Conference of the Association for the Advancement of Artificial Intelligence. It’s the largest and broadest AI Conference held every year. I’ll be trying to post up my thoughts and observations here each day about what I’m seeing at the conference. For more immediate thoughts I’ll probably just post to Google+ (you can find me gplus.to/crowley, if you’re not on yet you can join using my invites here.). That would be a great place to discuss what’s going on in real time or for people to meet up.
I’m very excited for this year’s AAAI because:
a) I’m presenting a paper on my thesis research on thursday (10:20am session – how can you resist a catchy title like “Policy Gradient Planning for Environmental Decision Making with Existing Simulators”? Also, the paper before me is listed as an “Outstanding Paper”, so at least you’ll see that.)
b) This is a very exciting time for AI research. There are lots of reasons for this but for me two exciting new fields where AI is being applied in new ways which are featured prominently in this year’s AAAI conference: Social Media and Sustainability.
I don’t know much about AI applied to social media so that will be fascinating to find out about.
There is a special track this year on Computational Sustainability which is a new field which focusses on applying machine learning, probabilistic modeling and optimization techniques to very challenging environmental problems. This is the track my paper is in. It will be really interesting to meet with lots of people trying to use AI to better the world.
Watch this space.
Posted by Mark Crowley on August 7, 2011