The rock ant is tiny, even for an ant. Individually each ant is the size of comma on this page. Their colonies are small too. Numbering about 100 workers, plus one queen, they normally nest between slivers of crumbling rock, hence their common name. Their entire society can fit into the glass case of a watch, or between the one-inch covers of a microscope slide, which is where they are usually bred in laboratories. The brain of a rock ant contains less than 100,000 neurons and is so small as to be invisible. Yet an rock ant mind can perform an amazing feat of calculation. To assess the potential of a new nesting site, rock ants will measure the dimensions of the room in total darkness and then calculate – and that is the proper word – the volume and desirability of it. For many millions of years, rock ants have used a mathematical trick that was only discovered by humans in 1733. Rock ants can estimate the volume of a space, even an irregular shaped one, by randomly laying a scent trail across the floor of the space, “recording” the length of that line, and then counting the number of times it encounters that scented line during additional diagonal runs across the floor. The calculated area is inversely proportional to the frequency of intersections times length. In other words, the ants discovered an approximate value for Π derived by intersecting diagonals. Headroom is measured by the ants with their bodies and then “multiplied” with the area to give an approximate volume of their hole. 

But these incredible tiny ant minds do more. They measure the width and number of entrances, the amount of light, the proximity of neighbors, and the degree of hygiene for the room. Then they tally these variables and calculate a desirability score for the potential nest by a process that resembles a “weighted additive” fuzzy logic formula in computer science. All in 100,000 neurons.

The minds of animals are legion, and even fairly dumb ones can yield amazement. Asian elephants will strip away branches to construct a fly-switch to keep pesky flies away from their hind parts. Beavers, mere rodents, have been known to stockpile construction materials before starting to build their dam, thus displaying the ability to anticipate a future intent. Beavers can even outwit humans trying to prevent their dams from flooding fields. Clever Homo sapiens will install ingenious “beaver baffler” drainage tubes upstream to siphon off water lower than the dam level, but the rodents can somehow figure this out and engineer ways to plug the intake – a modern need that would not ordinarily come about in nature.  Squirrels, another rodent, continually outwit very smart human suburbanites over control of their backyard birdfeeders. (I’ve been battling my own black squirrel Einstein.) Biologists have witnessed hawks submerging hard-to-kill prey underwater till they drown. The honeyguide bird in Kenya lures humans to wild bee nests so that the birds can feast on the remaining bee brood after the humans remove the honey; sometimes according to researchers the honeyguide will “deceive” the hunters of the actual distance to a deep forest nest if it is more than 2 kilometers away.

Asked what he could infer about nature’s Creator, biologist J. B. S. Haldane reputedly concluded that He must have “an inordinate fondness for beetles.”  But far more than beetles, nature displays an inordinate fondness for minds. Since every species of insect, and every animal, yields a mind, however limited, there are more minds, and more varieties of minds than beetles. Nature has a fundamental affinity, if not fondness, for intelligence.

Plants, too, posses a decentralized type of intelligence. As Anthony Trewavas argues in his remarkable paper, “Aspects of Plant Intelligence,” plants demonstrate a slow version of problem solving that fit most of our definitions of animal intelligence. They perceive their environment in great detail, they assess threats and competition, then they take action to either adapt or remedy the problems, and anticipate future states. Time-lapse motion pictures that speed up the action of vine tendrils probing their neighborhood make it clear that plants are closer to animals in their behavior than our fast lives permit us to see. Charles Darwin may have been the first to observe this. He wrote in 1822, “It is hardly an exaggeration to say that the tip of the root acts like the brain of one of the lower animals.” Like sensitive fingers, roots will caress the soil, seeking out moisture and nutrients much as a nose or trunk of a herbivore might dig in the earth.

Plants share with animals an almost mathematical ability to optimize their energy efficiency while gathering the most nutrients for the least effort. Plant and animal “foraging” models are almost identical.  Roots search for fertile areas while avoiding adversarial competitors. A distant rootlet can also recognize another rootlet as its own among many the underground tangle of roots, even when all the neighboring plants are genetic clones. Thus, says Trewavas, “Individual plants are able to distinguish self from non-self.”

Plants are in constant motion because their world is in motion. The microclimates around a plant vary by height above ground. The density of carbon dioxide and sunlight can vary by the minute as wind blows and shade shifts. Available nutrients vary by the day as other plants thrive nearby. Growth factors vary by the seasons and temperature, and they vary by the decade as the ecological progression changes. A plant’s entire shape, metabolism, and behavior will thus change by the minute as well, as if it is being governed by a nervous system. It can quickly fill its green leaves with toxins or anti-fungal pesticides to retaliate if animals or parasites munch on it. As competing plants invade its territory a plant can alter the orientation and the structure of its parts by deflating the stomata on one side of its leaves to bend them in certain directions. A plant can thus “see” its environment and move in response to this sight. Some plants walk across a landscape, branch bent to root raised to branch again, on the scale of decades. The ability of a leaf to follow the sun (heliotropism) to gain optimal light exposure can be replicated in a machine, but only by using a fairly sophisticated computer chip as a brain. A plant thinks without a brain. It uses a vast network of transducing molecular signals instead of electronic nerves to carry and process information.

Remarkably a plant mind also contains a memory. There are numerous examples of plants remembering signals for days, and even years. A memory is a way to move information from the past into the present. Plants can also move information from the present into future, or anticipate, which is a true mark of the most primitive intelligence. When a nearby competing plant dies, opening up previous shade to light, some plants send out “exploratory speculative growth” in order to test the new zone with small investments of chlorophyll before spending big time on expensive branches and leaves. Light reflected from nearby vegetation is richer in far-red wavelengths than unreflected light. Plants can use this information to not only see shade, but to anticipate the likelihood of shading by a competitor in the future. “When a change in the balance of red to far-red radiation is perceived,” says Trewavas, “an integrated adaptive response in phenotype structure [of the plant] results. New branches grow away from the putative competitor, stem growth is increased; the rate of branching diminishes, and such branches assume a more vertical direction: leaf area increases in anticipation of reduced incident flux; and the number of layers of leaf cells containing chlorophyll diminishes.”

Plants exhibit all the characteristics of intelligence, except they do it without a centralized brain, and in slow motion. Decentralized minds and slow minds are actually quite common in nature, and occur at many levels throughout the six kingdoms of life. A slime mold colony can solve the shortest distance to food in a maze, much like a rat. The animal immune system, whose primary purpose is to distinguish between self and non-self, retains a memory of outside antigens it has encountered in the past. It learns in a darwinian process, and in a sense also anticipates future variations of antigens. And throughout the animal kingdom collective intelligence is expressed in hundreds of ways, including the famous hive minds of social insects.

The manipulation, storage, and processing of information is a central theme of life. Learning erupts over and over again in the history of evolution, as if it were a force waiting to be released. A charismatic version of intelligence – the kind of anthropomorphic smartness we associate with apes – evolved not just in primates, but in at least two other unrelated taxon: in the whales, and birds.

Stories of dolphin intelligence are famous. Dolphins and whales not only demonstrate intelligence, they occasionally give hints they share a style of intelligence with us hairless apes. For instance, captive dolphins have been known to train each other. Yet the most recent common ancestor for apes, whales, dolphins was 250 million years ago. In between apes and dolphins are many families of animals without this variety of thought. We can only surmise that this style of intelligence evolved independently.

The same can be said for birds. Measured by their intelligence, crows, ravens and parrots are the “primates” of birds. The size of their forebrain is as relatively large as non-human apes, and the ratio of their brain weight to body weight is in the same line as apes. Like primates, crows live long and in complex social groups. New Caledonian crows, like chimpanzees, craft tiny spears to fish for grubs in crevices. Sometimes they save the manufactured spears and carry them around. In experiments with scrub-jays, researchers discovered that that jays would rehide their food later if another bird was watching them when they first hid it, but only if the jays had been robbed before. Naturalist David Quammen suggests that crow and raven behavior is so clever and peculiar that they should be evaluated “not by an ornithologist but by a psychiatrist.”  The famous African grey parrot Alex was taught to name colors, size, and shapes, and to put together simple spoken phrases. When questioned about novel objects he had not seen before, he could give correct answers about 80% of the time. He could also count to six.

The common ancestor for birds, whales and apes was 280 million years ago. The vast majority of smart animals lie between these three very anthropomorphic taxon. Thus, charismatic intelligence evolved independently three times: in birds on wing, in mammals that returned to the sea, and in primates. It may have even evolved a fourth time. Birds are the only dinosaurs that survived the great dinosaur wipeout 65 million years ago. But it is very probable that before they disappeared large dinosaurs were way ahead of archaic mammals (typically no bigger than gophers) on the race to reach complex intelligence. Because birds today with their small brains can surprise us, dinosaurs with much larger brains may have been as smart as apes. Had dinos not vanished under the assault of the heavens, consciousness might have been birthed on earth in a highly evolved reptile, rather than a mammal. We can easily speculate about an alternative world where Saurians ran the place. A few years ago palaeontologist Dale Russell sketched out what Dinoman could have looked like. He would be warm-blooded, 1.33 meters tall, and weigh 32 kilograms.

Smartness is a competitive advantage everywhere. We see the widespread recurrence and reinvention of intelligence because the living universe is a place where learning makes a difference.

Organisms are so highly evolved to their respective ecological niches that in terms of variation almost every part of a creature is unique to that species. A good biologist, for instance, can identify an animal from its teeth alone. For the same reasons animal minds also vary by species to fit that animal’s livelihood. There are hundreds of types of learning in the animal kingdom.  Rats excel at the expert spatial intelligence they need to navigate a maze, while their cousins the guinea pigs fail in that department. Humming birds excel at timing, primates in social intelligence. If we knew enough about animal minds a good biologist could identify an animal solely from its species of intelligence.

What we call “intelligence” is in reality a suite of different specialty learning programs, and each species of intelligence is a different mix of those sub programs. One species of intelligence will dial up counting, while another dials up long-tem memory, or neglects social intelligence. Yet, a few animal behaviorists claim that to a rough order of magnitude, all animal intelligence shares a universal core. “There are no qualitative differences in cognition between animal species in the processes of learning and memory,” says Euan Macphail. “Pigeon, rat, monkey… doesn’t matter. Once you have allowed for differences in the ways in which they make contact with the environment…what remains of their behavior shows astonishingly similar properties,” says B.F. Skinner. “There are no consistent differences on such tasks between the performance of goldfish, pigeons, and chimpanzees,” says David McFarland. “…There’s an impressive similarity in basic associative learning among diverse species,” says Leslie Real. Edward Thorndike, one of the first animal behaviorists, was convinced the universal mind extended to invertebrates as well. He saw a common intelligence in honey bees and octopus. He believed that “octopus show precisely the type of progressive improvement in reversal problems [learn one pattern then reverse it] that the rat and monkey show.” In fact there is one report of octopuses learning a task while watching another octopus be trained (and rewarded). A fair number of scientists have tested lowly planarians with a full battery of IQ tests. Planarians are flat worms, tiny slugs. They turn out to be smarter than anyone would have guessed.

The problem in gauging the distribution of intelligence is that we can’t use the same test for every animal. You can’t measure a worm’s intelligence the same way you measure a walrus’s. Their niches, and input/output systems, are so different no uniform test is practical. When you devise a test that is suitable for a particular creature – say a maze for a rat, or levers for a pigeon — what you are really measuring is that animal’s specialty intelligence which has been evolved for its environment. Beneath this mix of specialty intelligences runs a more universal mind. All creatures seem to share a core mind based on elemental learning, memory, and decision-making routines, but with different operational characteristics for different inputs and environment.

Up and down the six kingdoms of life, minds have evolved many times. So many times, in fact, that minds seem inevitable. Yet, as inordinately fond as nature is of minds, the technium, or the seventh kingdom of life, is even more so. The technium is biased to birth minds. All the inventions we have constructed to assist our own minds – our many storage devices, signal processing, flows of information, and  distributed communication networks, – all these are also the essential ingredients for producing new minds. And  so new minds spawn in the technium in inordinate degrees.

Technology is anything a mind makes. Built by minds, the technium is primed to make more minds. These mind children will be small, dim, and dumb at first, but tiny minds keep getting better. And more abundant. Last year there were 1 billion electronic brains etched into silicon. Many contained a billion transistors each but the smallest had a minimum of 100,000 transistors, about as many neurons as the brain of the rock ant. They, too, can do surprising feats. Tiny synthetic ant-minds know where on earth they are (GPS), and how to get back to your home, and remember the names of your friends, and translate foreign languages. These dim minds are finding their way into everything: shoes, door knobs, books, lamps, pets, beds, clothes, cars, light switches, kitchen appliances and toys.

We are blind to this massive eruption of minds in the technium because humans have a chauvinistic bias towards any kind of intelligence that does not precisely mirror a human’s. Unless an artificial mind behaves exactly like a human, we don’t count it as intelligent. Sometimes we dismiss it by calling it “machine learning.” So while we aren’t looking, billions of tiny minds, on the scale of biology, have blossomed in the technium.

One of the smartest artificial minds going is a website that plays the classic game of twenty questions. Nobody, including the inventors, calls it an artificial mind. In this game you think of something and the software mind in the website’s servers, called 20Q, will guess what you are thinking of after 20 yes-no questions.  20Q will guess right 80% of the time, and if you let it go on to ask 25 questions, it will nail what you are thinking 98% of the time.  With 10 million synaptic connections, 20Q is about as smart as a house fly – if a fly spent its brain power on answering questions instead of flying. 20Q has been trained to think by people playing the game. It has been played, or trained, over 70 million times so far. It has been learning since 1988. No other AI has lived so long. 20Q’s bottom-up training produces answers that reflect what people in general think. If most people believe a book has a spine, it does too. If most people believe “blue” is something you can wear, it is. What 20Q believes can change day to day. Creator Robin Burgener says, “It has a personality. Some days it does well, and some days, it’s just off.” There are a dozen different language-specific 20Qs, so the questions play out differently in different languages.  A smaller version of the American/English mind has been extracted and squeezed into a tiny chip inside a plastic toy orb about the size of a snow globe. Some 35 million of these handheld micro-minds have been sold. This autonomous 20Q knows only 2,000 objects, but its still a marvel. Most children can’t stump it. Because it is so small, so self-contained (it sits in your hand like a sea urchin), its intelligence is shocking to the unprepared. For about ten dollars you can get a tiny insect mind which, in one narrow specialty, is smarter than you are.

The cramped, autistic mind of a $10 digital calculator is another species of intelligence, currently produced in the hundreds of millions. It also is an alien intelligence smarter than you — in mathematics.  Billions of insect-like artificial minds have spawned deep into the technium doing invisible, low-profile chores like reliably detecting credit-card fraud, or filtering email spam, or reading text from documents. These proliferating micro-minds run speech recognition on the phone, assist in crucial medical diagnosis, and aid stock market analysis, power fuzzy logic appliances, and guide automatic gearshifts and brakes in cars. A few experimental minds can even drive a car autonomously for a hundred miles.

Two arenas where artificial minds are flourishing without disguise is in multi-player online games, and in web search. In game’s artificial intelligences (AI) can inhabit non-human players in order to make the game more exciting or challenging. Other types of game AIs (such as those in Left 4 Dead) work behind the scenes creating dynamic narratives for human players. The artificial tiny minds generate new monsters, sounds, or actions based on a player’s previous game. Or they place enemies based on each player’s location, status, and skill. Some game AIs (as in Spore) will complete your actions in a smart way.

The artificial intelligence behind internet search does not pretend – at the moment – to be human. In fact, web AI’s main attraction is its ability to find material in a way no human could –- by remembering everything.  However, in the near future services which can understand queries asked in ordinary language will make the web’s non-human intelligence seem more human. Then the AI will feel less alien, and more familiar.

Unlike the billions of minds in the wild, the minds of the technium are  getting smarter by the year. There seems to be no place a mind can’t be born, or inserted. Technology wants to produce minds.

The daily grinding of evolution, as accelerated by technology, churns out more and more complex organisms, with higher rates of energy use, and with increasing specialization. Minds are the ideal way to express complexity, energy density, increasing specialization, expanding diversity — all in one system. Mindedness is what evolution produces. Mindedness is what technology wants, too.