QuEST Weekly Meeting, August 28th

Quest Topics 28 Aug, 2009

1.)The big topic of the day is the new blog:   Although there is the issue of being able to access the blog through base filters it allows easier access to our non-government partners so we will adopt a dual approach CoP and Blog – not efficient but we will try.

2.)The major technical topic for the day is ‘non-physics’ based representations – or the old discussion of subjective versus objective representations as the key to robust operation.

3.)In our continuing discussion on ‘aligning’ representations to allow for more efficient man-machine integration we can review the article by the Oregon State researchers on ‘interacting meaningfully …’- concept of “rich interaction” – computers that do, in fact, want to communicate with, learn from and get to know you better as a person…. computer doesn’t just try to learn from its own experiences, it listens to the user, tries to combine what it “hears” with its internal reasoning, and changes its program as a result…. interacting with human beings and make constant changes in its own programming, based on their feedback… we want to develop algorithms that will allow the end user to ask the computer why it did something, read its response, and then explain why that was a mistake… customize itself to the end user and get more personal…. be a two-way street, and this also presents one of the challenges… field of “rich guidance” research …

4.)To tie these topics together we suggest that the next article we write is ‘What Turing meant to Say’.  The Turing Test is commonly interpreted as a specific task – the Imitation Game.  What it is really about is a machine that via our interaction with it we learn we can align its representation of the world with our own and thus we are willing to imbue it with intelligence!


a. Nostril rivalry: brain chooses between the two scents instead of combining them, researchers report online August 20 in Current Biology … right eye views an image that is incompatible with the image that the left eye views, the subject reports seeing the images alternating rather than superimposed upon each other … subjects usually reported sensing the least pleasant of the two options — in this case the marker — firststudy how the brain perceives smells separately from how the nose perceives them, **** this is exactly my we don’t sense in the physics space problem **** study a window into consciousness and awareness

b.Sentiment Analysis: translating the vagaries of human emotion into hard data … introduced a subscription service that allows customers to monitor blogs, news articles, online forums and social networking sites for trends in opinions about products, services or topics in the news…. sophisticated algorithm that not only evaluates sentiments about particular topics, but also identifies the most influential opinion holders. … working on a new algorithm that could use opinion data to predict future developments, like forecasting the impact of newspaper editorials on a company’s stock price … allow users to take the pulse of Twitter users about particular topics. … Tweetfeel, for example, reveals that 77 percent of recent tweeters liked the movie “Julie & Julia.” But the same search on Twitrratr reveals a few misfires … stuff of human language into binary values will always be an imperfect science, however. “Sentiments are very different from conventional facts… simplest algorithms work by scanning keywords to categorize a statement as positive or negative, based on a simple binary analysis (“love” is good, “hate” is bad…

c.Evolving robots learn to lie: learned to lie to each other in an attempt to hoard the resource …robots got higher marks for finding and sitting on the good resource, and negative points for hanging around the poisoned resource. The 200 highest-scoring genomes were then randomly “mated” and mutated to produce a new generation of programming. Within nine generations, the robots became excellent at finding the positive resource, and communicating with each other to direct other robots to the good resource ….500 generations, 60 percent of the robots had evolved to keep their light off when they found the good resource, hogging it all for themselves

d.Georgia Tech robot that uses social cues – Simon does: The robot Simon uses social cues to communicate whether it has understood what an instructor intended.     …                   not only understand a human teacher’s verbal instructions and social signals but give social feedback of their own, using gestures, expressions

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