Catching Up - Cortical Networks & Generalized Artificial Intelligence

Been away for awhile.  Lots of work, uncertainty and stress during past 9 months on the personal and career fronts.  Currently in the midst of a mad blast of catch up reading, re-ramping up on artificial intelligence, robotics and software fronts.

Here's what I'm currently reading...

BRAIN CORTICAL NETWORKS / MAPS

Catching up on some neuroscience news / articles and caught a dandy little blog from Ben Goertzel named The Multiverse According to Ben . 

Ben has been a leading figure in the generalized AI community for quite some time now.  He's become a seasoned leader in a variety of AI and futurism based conferences and gatherings and his popularity outide this community is starting to build due to all the Singularity buzz.  He seems like a good dude, knows his shit and seems to have just enough pragmatism (probably from years of trying to build a real generalized AI system in his Novamente architecture) that whatever he's currently reading and looking into is probably a worthwhile subject to follow up on. 

Ben's most recent blog titled Unraveling Modha and Singhs Map of Macaque is an interesting dive into the robust functional cortical maps created by IBM researchers Dharmendra Modha and Raghavendra Singh.  These maps illustrate a distinct cortical network architecture between major functional areas and subnetworks of the brain.  Check out their paper, datasets, an audio moderated powerpoint slide presentation and a short blog post directly from the researchers regarding their superlative work. 

Ben provides an interesting restructuring of the results into a textual hierarchical format to further clarify inbound, outbound connectivity of the cortical networks.

Hierarchical Temporal Memory

Catching up on progress from Jeff Hawkins HTM venture Numenta.  Looks like a couple of papers and videos I need to start with .. I better go and start this list (copy and pasted from Numenta)

Hierarchical Temporal Memory including HTM Cortical Learning Algorithms (PDF)
This document describes in detail HTM technology and the new algorithms for learning and prediction. This document will be updated periodically with additional material. Questions and comments regarding the new algorithms may be posted on the HTM Theory forum. Last Updated: December 10, 2010.

Brains, Minds and Machines (video)
MIT recently held a symposium on Brain, Minds and Machines as part of their 150th anniversary celebration. Jeff Hawkins was invited to participate on a panel that addressed the question: Is it time to try again to understand the brain and engineer the mind? Jeff presents his answer to this question in this 10-minute video. This talk was given on May 4, 2011.

Advances in modeling neocortex and its impact on machine intelligence (video)
Jeff Hawkins presents the new HTM algorithms at the Beckman Institute, University of Illinois at Urbana-Champaign. This talk was given on November 12, 2010.

Advances in modeling neocortex and its impact on machine intelligence (video)
Jeff Hawkins presents the new HTM algorithms for a graduate class on neural computation at the University of California at Berkeley. This talk is very similar to the Beckman Institute talk above, but might be useful for those viewers who want to hear the talk given again with some shades of difference. In addition, this talk includes a question & answer section. Note that the video is not high quality. This talk was given on December 2, 2010.