Hello, I'm new here, and I'd like to learn.
TLDR: I would love your opinion and to discuss about the possibility of implementing an intelligent tutor bot. What are the problems? What are the obstacles? Is the state of the art enough? What subjects need to be tackled before achieving this? Can you please help me on this? Longer version: I'm working with a group of people to create an intelligent TutorBot that helps people during learning and guides them thought different materials, examples and . I've been looking for technologies that could allow to do this, and last Thursday I've found a presentation from Jeff Hawkins about CLA and Sparse coding, and also found about cortical.io After what I was amazed and completely exited about the technologies. I've spent all my non-working time last days reading, studying and watching every single thing that I could find about it. Trying to understand the concepts behind and trying to figure out if the goal I'm targeting is achievable in a reasonable time (at least a first technology demo). After reading the papers at: http://arxiv.org/abs/1411.4702 http://numenta.com/learn/properties-of-sparse-distributed-representations.html http://www.eecs.harvard.edu/~michaelm/NEWWORK/postscripts/BloomFilterSurvey.pdf I've focused mainly on the NLP videos and resources as: https://www.youtube.com/watch?v=X4XjYXFRIAQ&start=7084 https://www.youtube.com/watch?v=hjMjhhmYKhI https://github.com/subutai/nupic_nlp and also the examples and tutorials from the hackathons. I haven't finished with all the material yet. I've also started with NuPic installation (I have managed to install it correctly). Note on installing the software, the bug on numpy version (conflict 7 and 9) is painful. I wrote a script that solves the issue for me (I should clean it up and upload it to github). To go into more depth if I imagine a TutorBot I can see different macro tasks needed: - Guidance to student, for example asking targeted (and necessary) questions to the student - Remembering what was discussed about, and using those facts in the future (continuous learning) - training the TutorBot itself One of the problems is context. I thought about the possibility of clustering to be able to retrieve subjects that are similar, using cortical.io API will be even possible to create a signature for phrases and sentences that are meaningful for the topic in discussion. Later a CLA trained algorithm can predict the best option for discussion. There is a difficulty here, that if it learns continuously, how to evaluate the success of the task? There are technologies like AIML (it is not intelligent and it is too much work to be able to create and maintain a rule based bot) we want to build something at which I can give knowledge in huge chunks and that it will be smart enough to use that knowledge when it has to. One of the thoughts is training the tutorbot with many discussions, and use the prediction from the CLA directly, for what an action will be required (motor response maybe?) About the possibility to train the system, about CLAs I haven't found (or understood) a way to direct the training of the algorithm with feedback (positive, and negative feedback), Is this possible to achieve with current state of the art? If not, what is needed? Well, I thing is a nice subject to discuss, besides the practical application I'm looking for, because it implies many other areas where learning can be used. Best -- Ing. Leonardo Manuel Rocha
