Figure 1: The Region-Layer component. The upper surface in the figure is the Region-Layer, which consists of Cells (small rectangles) grouped into Columns. Within each Column, only a few cells are active at any time. The output of the Region-Layer is the activity of the Cells. Columns in the Region-Layer… Read More »The Region-Layer: A building block for AGI
What’s AlphaGo? AlphaGo is a system that can play Go at least as well as the best humans. Go was widely cited as the hardest (and only remaining) game at which humans could beat machines, so this is a big deal. AlphaGo has just defeated a top-ranked human expert. AlphaGo… Read More »What’s after AlphaGo?
The artificial neuron model used by Jeff Hawkins and Subutai Ahmad in their new paper (image reproduced from their paper, and cropped). Their neuron model is inspired by the pyramidal cells found in neocortex layers 2/3 and 5. It has been several years since Jeff Hawkins and Numenta published the… Read More »New HTM paper – “Why Neurons Have Thousands of Synapses, A Theory of Sequence Memory in Neocortex”
Authors: D Rawlinson and G Kowadlo This is the first of three articles detailing our latest thinking on general intelligence: A one-size-fits-all algorithm that, like people, is able to learn how to function effectively in almost any environment. This differs from most Artificial Intelligence (AI), which is designed by people… Read More »How to build a General Intelligence: What we think we already know
An interesting article by Gerard Rinkus comparing the qualities of sparse distributed representation and quantum computing. In effect, he argues that because distributed representations can simultaneously represent multiple states, you get the same effect as a quantum superposition. The article was originally titled “sparse distributed coding via quantum computing” but… Read More »“Quantum computing” via Sparse distributed coding?
By David Rawlinson and Gideon Kowadlo The aim of this post is to take a short departure from more technical issues and deal with some of the philosophical questions about Artificial General Intelligence (AGI). The Elephant in the room This metaphor implies willful ignorance of something blindingly obvious. Something that’s difficult… Read More »Consciousness & “Free Will”: The Elephants in the Room
by David Rawlinson and Gideon Kowadlo Why the retina is worth a deeper look Recently, we have been looking at the retina – light sensitive cell layers inside the eyeball, that detect wavelength and intensity, and compute some initial encoding of this data that is transmitted to the brain proper… Read More »Another look at the retina
This might be our new test suite for the algorithms! http://www.arcadelearningenvironment.org/ “The Arcade Learning Environment (ALE) is a simple object-oriented framework that allows researchers and hobbyists to develop AI agents for Atari 2600 games. It is built on top of the Atari 2600 emulator Stella and separates the details of… Read More »The Arcade Learning Environment – a test suite for AGI
If you’re looking for a formal and precise description of the current HTM/CLA algorithm, then this blog [1, 2] by Fergal Byrne may be of interest. Our experience is that while pseudocode is a good way of describing an algorithm, equations can often be more succinct and specific. The CLA… Read More »Mathematics of HTM by Fergal Byrne
This post asks some questions about the agency of hierarchical action selection. We assume various pieces of HTM / MPF canon, such as a cortical hierarchy. Agency The concept of agency has various meanings in psychology, neuroscience, artificial intelligence and philosophy. The common element is having control over a system, with… Read More »Agency and Hierarchical Action Selection