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Informative neuroscience presentations at NYU Center for Mind, Brain & Consciousness

Informative neuroscience presentations at NYU Center for Mind, Brain & Consciousness

The NYU Center for Mind, Brain & Consciousness hosts presentations, including topical debates among leading neuroscience researchers. Many of the sessions are recorded for later viewing. The upcoming debate among Joseph LeDoux (Center for Neural Science, NYU), Yaïr Pinto (Psychology, University of Amsterdam), and Elizabeth Schechter (Philosophy, Washington University in St. Louis), will tackle the question, “Do Split-brain patients have two minds?” Previous topics addressed animal consciousness, hierarchical predictive coding and perception, AI ‘machinery,’ AI ethics, unconscious perception, research replication issues,…

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Can we understand other minds? Novels and stories say: no

Can we understand other minds? Novels and stories say: no

by Kanta Dihal This article was originally published at Aeon and has been republished under Creative Commons. Cassandra woke up to the rays of the sun streaming through the slats on her blinds, cascading over her naked chest. She stretched, her breasts lifting with her arms as she greeted the sun. She rolled out of bed and put on a shirt, her nipples prominently showing through the thin fabric. She breasted boobily to the stairs, and titted downwards. This particular…

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Deep clustering machine learning enables AI to distinguish individual voices in a crowd

Deep clustering machine learning enables AI to distinguish individual voices in a crowd

AI system can isolate individuals’ voices from other environmental noise, including other voices. Such a system has many potential uses, both benign and nefarious. The ability is rapidly improving to untangle signals from noise and identify which signals are from which sources. The approach should be able to apply to other kinds of signals too, not only sounds. https://www.newscientist.com/article/2151268-an-ai-has-learned-how-to-pick-a-single-voice-out-of-a-crowd/

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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Will self-improving AI inevitably lead to catastrophe?

Will self-improving AI inevitably lead to catastrophe?

Paul W sent the following TED Talk link and said If AI is by definition a program designed to improve its ability to access and process information, I suspect we cannot come up with serious AI that is not dangerous. It will evolve so fast and down such unpredictable pathways that it will leave us in the dust. The mandate to improve information-processing capabilities implicitly includes a mandate to compete for resources (need’s better hardware, better programmers, technicians, etc.) It…

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Deep learning AI approach trains autonomous vehicle

Deep learning AI approach trains autonomous vehicle

“Once the trained CNN [convolutional neural network] showed solid performance in the simulator, we loaded it onto DRIVE PX [vehicle control computer] and took it out for a road test in the car. The vehicle drove along paved and unpaved roads with and without lane markings, and handled a wide range of weather conditions. As more training data was gathered, performance continually improved. The car even flawlessly cruised the Garden State Parkway.”

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