One of the main goals of Neurdon, since its very beginnings, was to educate readers to tell apart fiction from reality. Nowadays, big companies are diving (or dive-bombing) in the field of neural computing with hyperbolic claims of being able to simulate biological brains, from feline to humans. One of such a claim comes, again, from IBM. This is the truth behind what IBM calls "cognitive computer". Read the rest of this entry »
August 25, 2011|
February 2, 2010|
One of the major themes in the SyNAPSE project is developing chips that can learn meaningful information, and preserve it over time. In other words: memristors can learn, but we need to ensure that they are stably learning something useful for the system they are embedded in.
Some help to solve this technological problem comes from neuroscience. The question of how can the cerebral cortex develop stable memories while at the same time incorporating new information through an organism lifetime has been a central theme in many research groups. The talk posted on Neurdon describes one of these approaches. Read the rest of this entry »
June 28, 2009|
I'm a 4th-year PhD student in the Institute of Cognitive Science at The University of Louisiana at Lafayette. When I entered the program, I was mostly interested in AI and evolutionary algorithms. I wanted to evolve a Go-playing program. But my interests shifted, especially in my first year when I read Jeff Hawkins' On Intelligence. I thought it was great stuff, and I liked two things central to his framework: 1) The temporal aspect of cognition, and 2) The crucial role of feedback. He made a convincing case that every modality and skill is essentially a matter of learning and processing sequences. So that's where I started focusing my attention. Read the rest of this entry »