Segmentation with OpenCV GPU
Posted: November 26, 2011 at 3:40 pm
In playing with code for deep learning (DBNs in particular) I’ve had to install CUDA to do matrix processing on the GPU. So I went ahead and recompiled openCV to use CUDA. Following is a similar segmentation image to the one in previous posts. This one was computed in 2.7s on the GPU, and on a different machine. The non GPU version did it in 6s, and the old machine did it in 9s. This machine is already a few years old, and has an older 8600GTS that barely supports CUDA. A faster machine, or perhaps just a faster GPU, may get these numbers down to something more real-time.
Global Workspace Theory, Free Will and The Location of Mental Images.
Posted: November 11, 2011 at 12:32 pm
I’m continuing to listen to some of Franklin’s lectures about LIDA and cognitive modelling in general. Yesterday I got through the one explaining Global Workspace Theory (GWT). Little did I know, but I had already come across this theory during my Masters research, and discounted it due to its causal disconnection between consciousness and cognitive processes. While I continue to find this problematic as a model of sentient creatures, the notion of “functional consciousness” is certainly interesting and useful in the case of machines and AI.
Can a LIDA imagine its own behaviour?
Posted: November 4, 2011 at 5:02 pm
In attempting to think through a possible integration of LIDA and the current conception of the dreaming system, I’ve stumbled upon the above question. In the previous sketch, the content of memory (the current state of the “conceptual system”) is used to generate visual sensory data that is the dream content. In LIDA, it becomes somewhat unclear from which module(s) the content of the dream would arise. Clearly, it would involve longer term memory structures, such as those in episodic memory, which are only explicitly manifest in the workspace and then “broadcast” into the global workspace. So where does the dream occur? In the workspace or in the global workspace? Since the agent is only conscious of what is in the global workspace, then that appears to be the logical location. (more…)
Sketch of conceptual system before diving deeper into LIDA.
Posted: November 1, 2011 at 4:39 pm
In this post I will describe the conceptual subsystem, as I have imagined it up to this point, before looking more closely into the LIDA architecture. The central feature of this conception is that each high level feature, for example location in space, or colour (or redness), is considered independent. This contrasts with many systems that concatenate all these features in order to create a cluster representation that encapsulates overall similarity. This is conceptualized as a highly shallow system where features are meant to be high level. In fact no clustering is needed at all, as only a distance function can be used to determine the distance between precepts in terms of each individual feature. (more…)