Tag Archives: Neuromorphic Computing
04 Jul Cognitive Multi-Processing
Joe Roushar – July 2017 Divide and Conquer Swarm computing applications, with large numbers of autonomous agents are beginning to appear and deliver stunning results. The combination of autonomy, simple tasks and parallelism has great power. Today I’ll address parallel computing and models for breaking down computational problems. I will not address the question of autonomy today, […]
09 Jan 2017 – The Year of AI
Joe Roushar – January 2017 Intelligent but Artificial Recently, January 5th, 2017, on my ride into work I was listening to BBC World Update with Dan Damon, as I often do, and heard him interviewing someone about the new artificial intelligence (AI) app for the British National Health Service from Babylon Health (similar story on […]
11 May Thinking in Parallel
A Parallel Expert I once rode the Trans-Siberian Railway from Moscow to Ulan-Batar, Mongolia (not the picture at right – the engines were diesel). Several times along the journey we passed slower trains, and we were passed by faster ones. When people and freight are confined to a single lane, the speed of the slowest defines the speed of […]
23 Feb Inference in Knowledge Apps
In Section 5 we discussed different kinds of knowledge, including existential or hierarchical knowledge and causal knowledge. In Section 7 we discussed modeling approaches and search techniques that could be applied to any kind of knowledge. We saw that causal knowledge can be modeled as chains of causes and effects, and that existential knowledge can be […]
08 Feb Just In Time Knowledge
One of the beautiful things about the human brain is it’s adaptability: people can “change” their minds at the last minute based on the changing situation (context). This is not trivial, but I believe that it is one of the characteristics of human cognition that is relatively straightforward to mimic in computer programs and apps. In […]
14 Jan Segregating Layers of Intelligence
Layered Architectures Layers appear regularly in my blog, whether it’s layers of the brain, layers of processing nodes in artificial neural networks or layers in systems architectures. Layering embodies important patterns in the inexorable move toward a knowledge economy with knowledge systems. In today’s post, I’m going to talk about what layering brings to enterprise […]
29 Dec Unhuman Expertise
Artificial Intelligence has suffered from a persistent scale problem: up to now, many techniques have been shown to work well and reliably in narrowly defined domains, but outside the domains of their expertise, they fall apart very quickly. No techniques of which I am aware, have exhibited common sense in the way we expect humans […]
23 Dec Visual Knowledge Dimensions
Visualizing knowledge in graphs and charts empowers decision makers by giving them actionable knowledge in understandable format. To make this most effective, the labels on the graph must provide clearly defined context cues that make it easy to interpret. Converging data strategies using Big Data (Hadoop, NoSQL, Cassandra, MapReduce…) can change the way we access content […]
17 Dec Visualizing Knowledge
Visualizing Knowledge – Automatic Generation Words are so symbolic that even symbolic thinkers, like me, understand more when there’s a picture to go along with the words. is partly explains my crazy use of images in this blog. The various forms of graphical representations are superb inventions that enable us to view and understand mathematical data […]
10 Dec Measuring Knowledge
Sometimes you need to know about your knowledge. When you’re in the middle of trying to build a system that knows stuff, you may ask, how much does the system know after this training or learning cycle as a percent of the total knowable amount? When we test students in their learning cycles, we use a […]