Information

Steve Meyer, author of Darwin’s Doubt, offers a handy illustration of the sort of specified complexity that life forms show, which indicates design, in an April 2018 essay: Cryptographers distinguish between random signals and those carrying encoded messages, the latter indicating an intelligent source. Recognizing the activity of intelligent agents constitutes a common and fully rational mode of inference. More importantly, [design theorist William] Dembski explicates criteria by which rational agents recognize or detect the effects of other rational agents, and distinguish them from the effects of natural causes. He demonstrates that systems or sequences with the joint properties of “high complexity” (or small probability) and “specification” invariably result from intelligent causes, not chance or physical-chemical laws. Dembski noted that Read More ›

Neither randomness nor order alone create meaning. So how can we identify communications in a scientifically meaningful way? Dropping a handful of toothpicks on the table seems to produce a different sort of pattern than spelling out a word with toothpicks. Surprisingly, this intuitive distinction is harder to make in math and the sciences. Algorithmic specified complexity (ASC) enables us to distinguish them. Neither Shannon information nor Kolmogorov complexity work well for this purpose. This leads us to a third concept, algorithmic specified complexity (ASC). ASC solves the problem by combining the two measures. ASC states that an event has a high amount of information if it has both low probability and a concise description. This matches our intuition much Read More ›

Quantum theory specifies that information is never lost but what happens to the information when a black hole vanishes? In the latest paper, Hawking (1942-2018) and his colleagues show how some information at least may be preserved. Toss an object into a black hole and the black hole’s temperature ought to change. So too will a property called entropy, a measure of an object’s internal disorder, which rises the hotter it gets. The physicists, including Sasha Haco at Cambridge and Andrew Strominger at Harvard, show that a black hole’s entropy may be recorded by photons that surround the black hole’s event horizon, the point at which light cannot escape the intense gravitational pull. They call this sheen of photons “soft hair”. Read More ›

That’s tech philosopher George Gilder’s view: Last month, World News Daily did a three-part interview with George Gilder on the publication of Life after Google: The Fall of Big Data and the Rise of the Blockchain Economy, which unpacks some of the book’s main ideas: Part One: “Reagan guru, predictor of iPhone foresees new web revolution” In 1981, his bestselling “Wealth and Poverty” provided a blueprint for the economic revolution led by Ronald Reagan, who cited him more than any other living author. In the 1994 version of his book “Life After Television,” he predicted the digital world in which we now live and the invention of the smartphone that now dominates daily life. And long before the iPhone was introduced Read More ›

Holloway distinguishes between meaningful information and artificial intelligence: What is meaningful information, and how does it relate to the artificial intelligence question? First, let’s start with Claude Shannon’s definition of information. Shannon (1916–2001), a mathematician and computer scientist, stated that an event’s information content is the negative logarithm* of its probability. So, if I flip a coin, I generate 1 bit of information, according to his theory. The coin came down heads or tails. That’s all the information it provides. However, Shannon’s definition of information does not capture our intuition of information. Suppose I paid money to learn a lot of information at a lecture and the lecturer spent the whole session flipping a coin and calling out the result. Read More ›

We’ve been talking about intelligence in termite mounds. Not “of” termite mounds but “in” them. From a review of The Revolutionary Genius of Plants: A New Understanding of Plant Intelligence and Behavior, by plant biologist Stefan Mancuso, To overcome the human bias toward brain-centered intelligence, Mancuso writes, one must consider that, unlike animals, plants can’t move. Being anchored in one spot required that plants evolve entirely different solutions to short- and long-term threats like predators, fire and drought. (Animals do not solve problems, notes Mancuso, they avoid them.) The plant solution is decentralization: Rather than having a brain, kidneys or other organs that would be points of vulnerability, plants are modular. Functions that would be carried out by organs in an Read More ›

Programmer Winston Ewert has developed a dependency graph, as an alternative to the Darwinian “tree of life,” to understand relationships among life forms. Here he discusses it with Jonathan McLatchie: Dr. Winston Ewert … proposes an alternative model to common descent to explain the hierarchical classification of life. Based on his paper published in Bio-Complexity, available here. Note: Winston Ewert, who works at the Evolutionary Informatics Lab, is an author of Introduction to Evolutionary Informatics See also: Evolutionary informatics: A simplified explanation of Winston Ewert’s dependency graph and New “fixed” bacterial Tree of Life looks like a cityscape seen from below

At Mind Matters Today: “Machine learning” is a hot field, and tremendous strides are being made in programming machines to improve as they work. Such machines work toward a goal, in a way that appears autonomous and seems eerily like human learning. But can machines really learn? What happens during machine learning, and is it the same thing as human learning? Because the algorithms that generate machine learning are complex, what is really happening during the “learning” process is obscured both by the inherent complexity of the subject and the technical jargon of computer science. Thus it is useful to consider the principles that underlie machine learning in a simplified way to see what we really mean by such “learning.” Read More ›

The old Gaia asserts that living organisms and their inorganic surroundings have evolved together as a single living system that greatly affects the chemistry and conditions of Earth’s surface. Some scientists believe that this “Gaian system” self-regulates global temperature, atmospheric content, ocean salinity, and other factors in an “automatic” manner. Earth’s living system appears to keep conditions on our planet just right for life to persist! The Gaia Theory has already inspired ideas and practical applications for economic systems, policy, scientific inquiry, and other valuable work. The future holds more of the same. More. The new Gaia is leaner, greener, and meaner. She has discovered the “selfish gene”: Doolittle has recently proposed that Gaia could have arisen through ‘selection by Read More ›

From ScienceDaily: A University of Montana researcher has discovered that mountain pine beetles may avoid certain trees within a population they normally would kill due to genetics in the trees. UM Professor Diana Six made the discovery after studying mature whitebark and lodgepole trees that were the age and size that mountain pine beetle prefer, but had somehow escaped attack during the recent outbreak. After DNA screening, survivor trees all contained a similar genetic makeup that was distinctly different from the general population that were mostly susceptible to the beetle. “Our findings suggest that survivorship is genetically based and, thus, heritable,” Six said, “which is what gives us hope.” In western North America, whitebark pine, a high elevation keystone species Read More ›