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Category: learning

Seeing my blindfold

Seeing my blindfold

I’ve found some thought-provoking answers on the Q&A social media site, Quora. Follow the link to a perceptive and helpful answer to, “Can a person be able to objectively identify exactly when and how their thinking processes are being affected by cognitive biases?” The author provides some practical (if exhausting) recommendations that, if even partly followed by a third-to-half of people (my guestimate), would possibly collapse the adversarial culture in our country.

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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Wild systems theory (WST) – context and relationships make reality meaningful

Wild systems theory (WST) – context and relationships make reality meaningful

Edward has posted some great thoughts and resources on embodied cognition (EC). I stumbled on some interesting information on a line of thinking within the EC literature. I find contextualist, connectivist approaches compelling in their ability to address complex-systems such as life and (possibly) consciousness. Wild systems theory (WST) “conceptualizes organisms as multi-scale self-sustaining embodiments of the phylogenetic, cultural, social, and developmental contexts in which they emerged and in which they sustain themselves. Such self-sustaining embodiments of context are naturally and necessarily…

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State of AI progress

State of AI progress

An MIT Technology Review article introduces the man responsible for the 30-year-old deep learning approach, explains what deep machine learning is, and questions whether deep learning may be the last significant innovation in the AI field. The article also touches on a potential way forward for developing AIs with qualities more analogous to the human brain’s functioning.

Should AI agents’ voice interactions be more like our own? What effects should we anticipate?

Should AI agents’ voice interactions be more like our own? What effects should we anticipate?

An article at Wired.com considers the pros and cons of making the voice interactions of AI assistants more humanlike. The assumption that more human-like speech from AIs is naturally better may prove as incorrect as the belief that the desktop metaphor was the best way to make humans more proficient in using computers. When designing the interfaces between humans and machines, should we minimize the demands placed on users to learn more about the system they’re interacting with? That seems…

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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.”

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