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Gnawing on his left index finger with his chipped old British teeth, temporal veins bulging and brow pensively squinched beneath the day-before-yesterday’s hair, the mathematician John Horton Conway unapologetically whiles away his hours tinkering and thinkering — which is to say he’s ruminating, although he will insist he’s doing nothing, being lazy, playing games.

Based at Princeton University, though he found fame at Cambridge (as a student and professor from 1957 to 1987), Conway, 77, claims never to have worked a day in his life. Instead, he purports to have frittered away reams and reams of time playing. Yet he is Princeton’s John von Neumann Professor in Applied and Computational Mathematics (now emeritus). He’s a fellow of the Royal Society. And he is roundly praised as a genius. “The word ‘genius’ gets misused an awful lot,” said Persi Diaconis, a mathematician at Stanford University. “John Conway is a genius. And the thing about John is he’ll think about anything.… He has a real sense of whimsy. You can’t put him in a mathematical box.”

The experiments demonstrated that the blood cells can sense when the environment outside the capillaries is low in oxygen – which occurs when neurons take up more oxygen to generate energy – and respond by rushing to deliver more. They also observed that this response if very rapid, occurring less than a second after oxygen is pulled out of the surrounding tissue.

This phenomenon is unique to the capillaries because of their size. The thin walls of the microvessels mean that the oxygen levels in adjacent brain tissue are mirrored within the capillaries, which can signal to red blood cells to spring into action.

The findings could have implications for a number of neurological disorders, including Alzheimer’s disease. It has been observed that blood flow in the brains of people with the disorder is impaired when compared to healthy brains. The difficulty in delivering the oxygen necessary for neuronal activity may help explain the cognitive difficulties that are one of the hallmarks of the disease.

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Where does the mind end and the world begin? Is the mind locked inside its skull, sealed in with skin, or does it expand outward, merging with things and places and other minds that it thinks with? What if there are objects outside—a pen and paper, a phone—that serve the same function as parts of the brain, enabling it to calculate or remember?

In their famous 1998 paper “The Extended Mind,” philosophers Andy Clark and David J. Chalmers posed those questions and answered them provocatively: cognitive processes “ain’t all in the head.” The environment has an active role in driving cognition; cognition is sometimes made up of neural, bodily, and environmental processes.

From where he started in cognitive science in the early nineteen-eighties, taking an interest in A.I., professor Clark has moved quite far. “I was very much on the machine-functionalism side back in those days,” he says. “I thought that mind and intelligence were quite high-level abstract achievements where having the right low-level structures in place didn’t really matter.”

Each step he took, from symbolic A.I. to connectionism, from connectionism to embodied cognition, and now to predictive processing, took Clark farther away from the idea of cognition as a disembodied language and toward thinking of it as fundamentally shaped by the particular structure of its animal body, with its arms and its legs and its neuronal brain. He had come far enough that he had now to confront a question: If cognition was a deeply animal business, then how far could artificial intelligence go?

What is extended mind? How does the mind work? It’s not obvious. Where does the mind stop and the rest of the world begin? What is extended mind? What is embodied mind? Featuring interviews with David Chalmers, Andy Clark, and Raymond Tallis.

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Closer To Truth host Robert Lawrence Kuhn takes viewers on an intriguing global journey into cutting-edge labs, magnificent libraries, hidden gardens, and revered sanctuaries in order to discover state-of-the-art ideas and make them real and relevant.

Microbial life may have resided within the first four kilometers of Mars’s porous crust.

Four billion years ago, the solar system was still young. Almost fully formed, its planets were starting to experience asteroid strikes a little less frequently. Our own planet could have become habitable as long as 3.9 billion years ago, but its primitive biosphere was much different than it is today. Life had not yet invented photosynthesis, which some 500 million years later would become its main source of energy. The primordial microbes — the common ancestors to all current life forms on Earth — in our planet’s oceans, therefore, had to survive on another source of energy. They consumed chemicals released from inside the planet through its hydrothermal systems and volcanoes, which built up as gas in the atmosphere.

Some of the oldest life forms in our biosphere were microorganisms known as “hydrogenotrophic methanogens” that particularly benefited from the atmospheric composition of the time. Feeding on the CO2 (carbon dioxide) and H2 (dihydrogen) that abounded in the atmosphere (with H2 representing between 0.01 and 0.1% of the atmospheric composition, compared to the current approximate of 0.00005%), they harnessed enough energy to colonize the surface of our planet’s oceans. we explore Mars, it is becoming clearer that similar environmental conditions were developing on its surface at the same time as those that enabled methanogens to flourish in the oceans back on Earth.

Could energy efficiency be quantum computers’ greatest strength yet?

Quantum computers have attracted considerable interest of late for their potential to crack problems in a few hours where they might take the age of the universe (i.e., tens of billions of years) on the best supercomputers. Their real-life applications range from drug and materials design to solving complex optimization problems. They are, therefore, primarily intended for scientific and industrial research.

Traditionally, “quantum supremacy” is sought from the point of view of raw computing power: we want to calculate (much) faster.

However, the question of its energy consumption could also now warrant research, with current supercomputers sometimes consuming as much electricity as a small town (which could in fact limit the increase in their computing power). Information technologies, at their end, accounted for 11% of global electricity consumption in 2020.