Mind Matters Natural and Artificial Intelligence News and Analysis

Monthly Archive December 2020

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Colorful quantum world fractal

“Spooky Action at a Distance” Makes Sense—in the Quantum World

Einstein never liked quantum mechanics but each transistor in your cell phone is a quantum device

In last week’s podcast, “Enrique Blair on quantum computing,” Walter Bradley Center director Robert J. Marks talks with fellow computer engineer Enrique Blair about why quantum mechanics is so strange. The discussion turned to why Albert Einstein, a brilliant but orderly mathematical thinker, did not really like quantum mechanics at all and what we should learn from that: https://episodes.castos.com/mindmatters/Mind-Matters-110-Enrique-Blair.mp3 The discussion of Einstein and “spooky action at a distance” (his way of describing quantum particles’ behavior) starts at approximately 27:45. The Show Notes and transcript follow. Excerpts from the transcript: Robert J. Marks: Albert Einstein didn’t like quantum mechanics or certain aspects of quantum mechanics. Dd he die thinking that quantum mechanics was a fluke? Enrique Blair (pictured): That’s an…

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Human prion (3d model). Prion is an infectious agent that can fo

AlphaFold Scores Huge Breakthrough in Analyzing Causes of Disease

In a world so deeply designed and complexly organized, we need a quick and practical way of knowing what was going on in cells and viruses. AI can help

Alphabet’s DeepMind team has just scored a breakthrough in finding treatments for diseases. Their latest AlphaFold system won a grand challenge in analyzing the “folds” of proteins. Proteins—large and often very complex chains of amino acids—do the work in our cells. But, like all bodies, they are three-dimensional. We can’t understand them until we can analyze the folds (the third dimension) that are unique to each type among hundreds of thousands. Knowing what a given protein actually does (or doesn’t) is critical to developing many new medical treatments. How hard is the problem? In his acceptance speech for the 1972 Nobel Prize in Chemistry, Christian Anfinsen famously postulated that, in theory, a protein’s amino acid sequence should fully determine its…

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Laboratory mice in the experiment test. Blue filter.

Has Neuroscience “Proved” That the Mind Is Just the Brain?

This is hardly the first time that bizarre claims have been made for minimal findings. In neuroscience, materialism is the answer only if you don’t understand the questions.

Last month, materialist neurologist Steven Novella made a rather astonishing claim in a post at his Neurologica blog: A recent open-access study of learning and decision-making in mice shows that the human mind is merely what the human brain does. That’s a lot for mice to prove. In the study, the mice were trained to choose holes from which food is provided. Their brain activity was measured as they learned and decided which holes were best. The research looks specifically at quick and intuitive decision-making vs. decision-making that is slower and involves analysis of the situation. The investigators found that analysis-based decisions in the mice involve brain activity in the anterior cingulate cortex, which is a region of the brain…

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probability likelihood

How Bayes’ Math Rule Can Counter Unreasonable Skepticism

Mathematics is much more interesting if we know a bit about the players and their positions

Yesterday, we discussed the importance of Bayes’ rule in statistical reasoning. We used the example of a person who goes for a battery of screening tests and comes up positive for HIV. Let’s say she is surprised (and alarmed) because she is not at any known risk for HIV. But, it turns out, the risk of false positives for the test is several times greater than the incidence of HIV in the population. In that case, it is reasonable for her to suspect—on a statistics science basis, not just wishful thinking—that the test is a false positive. The formula we used is part of Bayesian reasoning, originally developed by an eighteen-century British clergyman and mathematician Thomas Bayes (1702–1761), but now…