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IMAGINE a future in which humanity’s accumulated wisdom about Earth — our vast experience with weather trends, fish spawning and migration patterns, plant pollination and much more — turns increasingly obsolete. As each decade passes, knowledge of Earth’s past becomes progressively less effective as a guide to the future. Civilization enters a dark age in its practical understanding of our planet.

as Earth warms, our historical understanding will turn obsolete faster than we can replace it with new knowledge. Some patterns will change significantly; others will be largely unaffected, though it will be difficult to say what will change, by how much, and when.

Until then, farmers will struggle to reliably predict new seasonal patterns and regularly plant the wrong crops. Early signs of major drought will go unrecognized, so costly irrigation will be built in the wrong places. Disruptive societal impacts will be widespread.

Not only are machines rapidly catching up to — and exceeding — humans in terms of raw computing power, they are also starting to do things that we used to consider inherently human

Quite simply, humans are amazing pattern-recognition machines. They have the ability to recognize many different types of patterns - and then transform these "recursive probabalistic fractals" into concrete, actionable steps.

Intelligence, then, is really just a matter of being able to store more patterns than anyone else

picture yourself in our grandchildren’s time, a century hence. Significant global warming has occurred, as scientists predicted. Nature’s longstanding, repeatable patterns — relied on for millenniums by humanity to plan everything from infrastructure to agriculture — are no longer so reliable. Cycles that have been largely unwavering during modern human history are disrupted by substantial changes in temperature and precipitation.

As Earth’s warming stabilizes, new patterns begin to appear. At first, they are confusing and hard to identify. Scientists note similarities to Earth’s emergence from the last ice age. These new patterns need many years — sometimes decades or more — to reveal themselves fully, even when monitored with our sophisticated observing systems

Disruptive societal impacts will be widespread.

When you walk or drive in the UK, you’re being nudged by dozens of hidden messages embedded in the roads and pavements.

He suffers from a rare inherited condition that leaves him only able to make out vague colour contrasts around him. Yet he is able to safely pick his way through the hectic city streets, thanks to dozens of hidden messages embedded in our roads and pavements that few of us even notice are there.

This subtle form of communication is not just confined to the pavement, either: increasingly, motorists and cyclists are also unknowingly being told what to do.

Although pattern recognition is commonly associated with computer science and engineering, it also applies to nature, people and social systems. In fact, even animals and babies are born with the ability to recognize patterns. Sharpening our pattern recognition ability helps us cultivate vision, which is crucial for gaining an edge in a rapidly changing world.

(Unfortunately, technology also allows powerful interests to recognize patterns in big data to manipulate voters and consumers, but that's another story.)

We can become slaves to patterns. Extrapolate this tendency broadly and you can see how a society becomes fixed in its ways.

The Feynman trap—ransacking data for patterns without any preconceived idea of what one is looking for—is the Achilles heel of studies based on data mining. Finding something unusual or surprising after it has already occurred is neither unusual nor surprising. Patterns are sure to be found, and are likely to be misleading, absurd, or worse.

A standard neuroscience experiment involves showing a volunteer in an MRI machine various images and asking questions about the images. The measurements are noisy, picking up magnetic signals from the environment and from variations in the density of fatty tissue in different parts of the brain. Sometimes they miss brain activity; sometimes they suggest activity where there is none.A Dartmouth graduate student used an MRI machine to study the brain activity of a salmon as it was shown photographs and asked questions. The most interesting thing about the study was not that a salmon was studied, but that the salmon was dead. Yep, a dead salmon purchased at a local market was put into the MRI machine, and some patterns were discovered. There were inevitably patterns—and they were invariably meaningless.

after a decade of failed attempts, David Smith, a self-described shape hobbyist of Bridlington in East Yorkshire, England, suspected that he might have finally solved an open problem in the mathematics of tiling: That is, he thought he might have discovered an “einstein.”

In less poetic terms, an einstein is an “aperiodic monotile,” a shape that tiles a plane, or an infinite two-dimensional flat surface, but only in a nonrepeating pattern. (The term “einstein” comes from the German “ein stein,” or “one stone” — more loosely, “one tile” or “one shape.”)

Your typical wallpaper or tiled floor is part of an infinite pattern that repeats periodically; when shifted, or “translated,” the pattern can be exactly superimposed on itself

Since 2006, Michael Puett has taught an undergraduate survey course at Harvard University on Chinese philosophy, examining how classic Chinese texts are relevant today. The course is now one of Harvard’s most popular, third only to “Introduction to Computer Science” and “Principles of Economics.”

So-called Confucianism, for example, is read as simply being about forcing people to accept their social roles, while so-called Taoism is about harmonizing with the larger natural world. So Confucianism is often presented as bad and Taoism as good. But in neither case are we really learning from them.

we shouldn’t domesticate them to our own way of thinking. When we read them as self-help, we are assuming our own definition of the self and then simply picking up pieces of these ideas that fit into such a vision

The science of pattern recognition has been explored for hundreds of years, with the primary goal of optimally extracting patterns from data or situations, and effectively separating one pattern from another. Applications of pattern recognition are found everywhere, whether it’s categorizing disease, predicting outbreaks of disease, identifying individuals (through face or speech recognition), or classifying data. In fact, pattern recognition is so ingrained in many things we do, we often forget that it’s a unique discipline which must be treated as such if we want to really benefit from it.

“Because of its analogies with the rise, fall and alterations of a society of living organisms, it belongs to a growing class of what are called ‘simulation games,’” Mr. Gardner wrote when he introduced Life to the world 50 years ago with his October 1970 column.

The Game of Life motivated the use of cellular automata in the rich field of complexity science, with simulations modeling everything from ants to traffic, clouds to galaxies. More trivially, the game attracted a cult of “Lifenthusiasts,” programmers who spent a lot of time hacking Life — that is, constructing patterns in hopes of spotting new Life-forms.

The tree of Life also includes oscillators, such as the blinker, and spaceships of various sizes (the glider being the smallest).

the pace of improvement in technology would become a runaway phenomenon that would transform all aspects of human civilization.

the structure and functioning of the human brain is actually quite simple, a basic unit of cognition repeated millions of times. Therefore, creating an artificial brain will not require simulating the human brain at every level of detail. It will only require reverse engineering this basic repeating unit.

From an evolutionary perspective, it makes no sense whatsoever that music makes us feel emotions. Why would our ancestors have cared about music?

Why does something as abstract as music provoke such consistent emotions?

Studies have shown that when we listen to music, our brains release dopamine, which in turn makes us happy

Every culture ever studied has been found to make music, and among the oldest artistic objects known are slender flutes carved from mammoth bone some 43,000 years ago — 24,000 years before the cave paintings of Lascaux.

, many researchers had long assumed that the human brain must be equipped with some sort of music room, a distinctive piece of cortical architecture dedicated to detecting and interpreting the dulcet signals of song. Yet for years, scientists failed to find any clear evidence of a music-specific domain through conventional brain-scanning technology

devised a radical new approach to brain imaging that reveals what past studies had missed. By mathematically analyzing scans of the auditory cortex and grouping clusters of brain cells with similar activation patterns, the scientists have identified neural pathways that react almost exclusively to the sound of music — any music. It may be Bach, bluegrass, hip-hop, big band, sitar or Julie Andrews. A listener may relish the sampled genre or revile it. No matter. When a musical passage is played, a distinct set of neurons tucked inside a furrow of a listener’s auditory cortex will fire in response.Other sounds, by contrast — a dog barking, a car skidding, a toilet flushing — leave the musical circuits unmoved.

I leave the Y grinning from ear to ear, uplifted not just by my own workout but even more so by my interaction with these darling representatives of the next generation.

I lived for half a century with a man who suffered from periodic bouts of depression, so I understand how challenging negativism can be.

“micro-moments of positivity,”

I think most people’s ideas of science fiction are formed by Hollywood movies, so they think most science fiction is a special effects-driven story revolving around a battle between good and evil

I don’t think of that as a science fiction story. You can tell a good-versus-evil story in any time period and in any setting. Setting it in the future and adding robots to it doesn’t make it a science fiction story.

I think science fiction is fundamentally a post-industrial revolution form of storytelling. Some literary critics have noted that the good-versus-evil story follows a pattern where the world starts out as a good place, evil intrudes, the heroes fight and eventually defeat evil, and the world goes back to being a good place. Those critics have said that this is fundamentally a conservative storyline because it’s about maintaining the status quo. This is a common story pattern in crime fiction, too—there’s some disruption to the order, but eventually order is restored. Science fiction offers a different kind of story, a story where the world starts out as recognizable and familiar but is disrupted or changed by some new discovery or technology. At the end of the story, the world is changed permanently. The original condition is never restored. And so in this sense, this story pattern is progressive because its underlying message is not that you should maintain the status quo, but that change is inevitable. The consequences of this new discovery or technology—whether they’re positive or negative—are here to stay and we’ll have to deal with them.

Predictive statistical analysis, harnessed to big data, appears poised to alter the way millions of people are hired and assessed.

By one estimate, more than 98 percent of the world’s information is now stored digitally, and the volume of that data has quadrupled since 2007.

The application of predictive analytics to people’s careers—an emerging field sometimes called “people analytics”—is enormously challenging, not to mention ethically fraught

A study published this week that looked at brain scans of people on psychedelics suggested that one effect is “a mixing of the senses” – an accurate description.

“fountains of colour”

Can I see the colours begin to glow brighter, or are they humming loudly into new levels of vividness?

There are many different kinds of intelligence, each reliant on its own set of skills and abilities. One such ability is pattern recognition, without which we’d have trouble recognizing faces, learning languages, or reading other people’s emotions. Because it’s so central to our cognitive and social functioning, pattern recognition is sometimes used by researchers as a shorthand for overall intelligence.

Finding that higher pattern detection ability puts people at greater risk to detect and apply stereotypes, but also to reverse them, implicates this ability as a cognitive mechanism underlying stereotyping,” co-author Jonathan Freeman said in the statement.