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Tag: learning

Query on interest in concept mapping

Query on interest in concept mapping

I like using concept maps to organize my thoughts and to plan articles and projects. I would like to share member-editable concept maps through this website. I’ve used the free Cmap Tools program for many years. Unfortunately, Cmap Tools is developed on the Java platform and I have been unable to get it to work on my Mac for about two years. (Apparently, it needs an older version of the Java Runtime Environment and several other tools I use need a…

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Book review – Life 3.0: Being Human in the Age of Artificial Intelligence, by Max Tegmark

Book review – Life 3.0: Being Human in the Age of Artificial Intelligence, by Max Tegmark

Max Tegmark’s book, Life 3.0: Being Human in the Age of Artificial Intelligence, introduces a framework for defining types of life based on the degree of design control that sensing, self-replicating entities have over their own ‘hardware’ (physical forms) and ‘software’ (“all the algorithms and knowledge that you use to process the information from your senses and decide what to do”). It’s a relatively non-academic read and well worth the effort for anyone interested in the potential to design the…

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Neuroplasticity at the neuron and synapse level – Neurons sort into functional networks

Neuroplasticity at the neuron and synapse level – Neurons sort into functional networks

“Individual neurons whose synapses are most likely to strengthen in response to a certain experience are more likely to connect to certain partner neurons, while those whose synapses weaken in response to a similar experience are more likely to connect to other partner neurons,” Friedlander said. “The neurons whose synapses do not change at all in response to that same experience are more likely to connect to yet other partner neurons, forming a more stable but non-plastic network.”

18 October meeting topic – General AI: Opportunities and Risks

18 October meeting topic – General AI: Opportunities and Risks

Artificial intelligence (AI) is being incorporated into an increasing range of engineered systems. Potential benefits are so desirable, there is no doubt that humans will pursue AI with increasing determination and resources. Potential risks to humans range from economic and labor disruptions to extinction, making AI risk analysis and mitigation critical. Specialized (narrow and shallow-to-deep) AI, such as Siri, OK Google, Watson, and vehicle-driving systems acquire pattern recognition accuracy by training on vast data sets containing the target patterns. Humans…

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