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Authors: Daniel Suarez
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McKinney had originally been drawn to myrmecology because of social insects’ unique evolutionary strategy; where most organisms had a single body, Hymenoptera—the order of social insects that included wasps, bees, and ants—were in effect a single organism consisting of millions of separate bodies. The physician Lewis Thomas once described ants as “a brain with a million legs.” It was like being able to send your hand to go get things while you were off doing something else. The great myrmecologist E. O. Wilson proposed that ants were a “superorganism”—an organism that transcended the limitations of a single body to enact a collective will. And that will had an intelligence superior to that of the individual ants themselves. Precisely how this occurred was still unknown, and it was a mystery that McKinney had dedicated her career to unraveling.
Studying the screen, she keyed observations into her laptop and spoke via speakerphone to a graduate student several miles away. “Mike, check the lens on camera nine. There’s an occlusion that’s confusing the tracking software.”
“Got it. Rich, can you move the lift closer?”
Another voice came in over the line. “There in a sec.”
“Thanks.”
McKinney zoomed the image out, displaying dozens of thumbnail video insets on the panoramic HD monitor that, when tiled together, outlined an entire mango tree as a three-dimensional model. She rotated the model as though it were a video game—the difference being that the tree was real and the images real-time. The tree stood on the verdant hillsides near the Marikitanda Research Station, where McKinney ran her field lab. The mango tree’s entire surface was being recorded in real time from dozens of separate digital video cameras placed on scaffolding around it. Software was stitching the imagery together into a single live 3-D image wrapped around the tree. Just one nest out of this colony’s domain of a dozen trees, covering nearly eight hundred square meters of ground with nearly a half million ants in all. It had taken years of research and grant applications for her to get this system up and running—and to obtain such up-close and complete imagery of an entire weaver nest in real time. Of the superorganism in motion. And all to test whether her software model of weaver society was accurate. And, in turn, whether it could form the basis of a general model of Hymenoptera intelligence. That, in turn, might reveal secrets as to the very nature of intelligence itself.
McKinney turned on the tracking overlay and now saw glowing red dots hovering above individual weaver ants. She wanted to confirm that the computer vision software was accurately identifying individual weavers, and correctly distinguishing them from their much larger and darker siafu enemies. The enemy ants were denoted with blue dots by the tracking software. It seemed to be doing a fair job of telling the ants apart. McKinney would use the red dots from the data set to analyze weaver swarming attack. The idea was to capture the geometry of weaver movements, recording their collective action for analysis against her Myrmidon computer model. It would be interesting to see how her behavioral algorithms held up.
She smiled. Either way, this kicked ass. She was finally getting the raw data she needed to refine her model. To understand the processing power of insect societies. How intelligence could emerge from relatively unintelligent agents and amass into a collective mind.
With only a quarter million neurons in an individual weaver ant’s brain, a single ant “knew” very little—especially compared to the one hundred billion neurons in an average human brain. And yet, multiplied by a half million ants, the number of neurons in a colony began to approximate the raw, collective processing power of the human brain.
An ant colony exhibited nothing like a human’s sophistication, of course, but there definitely was a specialized
McKinney had originally been drawn to myrmecology because of social insects’ unique evolutionary strategy; where most organisms had a single body, Hymenoptera—the order of social insects that included wasps, bees, and ants—were in effect a single organism consisting of millions of separate bodies. The physician Lewis Thomas once described ants as “a brain with a million legs.” It was like being able to send your hand to go get things while you were off doing something else. The great myrmecologist E. O. Wilson proposed that ants were a “superorganism”—an organism that transcended the limitations of a single body to enact a collective will. And that will had an intelligence superior to that of the individual ants themselves. Precisely how this occurred was still unknown, and it was a mystery that McKinney had dedicated her career to unraveling.
Studying the screen, she keyed observations into her laptop and spoke via speakerphone to a graduate student several miles away. “Mike, check the lens on camera nine. There’s an occlusion that’s confusing the tracking software.”
“Got it. Rich, can you move the lift closer?”
Another voice came in over the line. “There in a sec.”
“Thanks.”
McKinney zoomed the image out, displaying dozens of thumbnail video insets on the panoramic HD monitor that, when tiled together, outlined an entire mango tree as a three-dimensional model. She rotated the model as though it were a video game—the difference being that the tree was real and the images real-time. The tree stood on the verdant hillsides near the Marikitanda Research Station, where McKinney ran her field lab. The mango tree’s entire surface was being recorded in real time from dozens of separate digital video cameras placed on scaffolding around it. Software was stitching the imagery together into a single live 3-D image wrapped around the tree. Just one nest out of this colony’s domain of a dozen trees, covering nearly eight hundred square meters of ground with nearly a half million ants in all. It had taken years of research and grant applications for her to get this system up and running—and to obtain such up-close and complete imagery of an entire weaver nest in real time. Of the superorganism in motion. And all to test whether her software model of weaver society was accurate. And, in turn, whether it could form the basis of a general model of Hymenoptera intelligence. That, in turn, might reveal secrets as to the very nature of intelligence itself.
McKinney turned on the tracking overlay and now saw glowing red dots hovering above individual weaver ants. She wanted to confirm that the computer vision software was accurately identifying individual weavers, and correctly distinguishing them from their much larger and darker siafu enemies. The enemy ants were denoted with blue dots by the tracking software. It seemed to be doing a fair job of telling the ants apart. McKinney would use the red dots from the data set to analyze weaver swarming attack. The idea was to capture the geometry of weaver movements, recording their collective action for analysis against her Myrmidon computer model. It would be interesting to see how her behavioral algorithms held up.
She smiled. Either way, this kicked ass. She was finally getting the raw data she needed to refine her model. To understand the processing power of insect societies. How intelligence could emerge from relatively unintelligent agents and amass into a collective mind.
With only a quarter million neurons in an individual weaver ant’s brain, a single ant “knew” very little—especially compared to the one hundred billion neurons in an average human brain. And yet, multiplied by a half million ants, the number of neurons in a colony began to approximate the raw, collective processing power of the human brain.
An ant colony exhibited nothing like a human’s sophistication, of course, but there definitely was a specialized
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