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Traders deciding on the next big market bet. A navigation app quickly mapping out a less-explored area. Fashion brands choosing the hottest color of the season. An airport managing flight delays.
What do these scenarios have in common? In each one, swarm intelligence blends global and local insight to improve how businesses make decisions.
Swarm intelligence is a form of artificial intelligence (AI) inspired by the insect kingdom. In nature, it describes how honeybees migrate, how ants form perfect trails, and how birds flock. In the world of AI, swarm systems draw input from individual people or machine sensors and then use algorithms to optimize the overall performance of the group or system in real time.
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Consider Waze, the popular road navigation app that uses swarm intelligence to create and modify maps. Starting with limited digital maps, it began making tweaks based on its users’ GPS data along with manual map modifications by registered users. Entire cities have been mapped using this method, as was the case in Costa Rica’s capital, San José. And just as ants signal danger to their counterparts, so too do Waze users contribute live information from accident locations and traffic jams.
Swarm intelligence is now being used to predict everything from the outcome of the Super Bowl to fashion trends to major political events. Using swarm intelligence, investors can better predict market movements, and retailers can more accurately forecast sales.
While the swarm intelligence concept isn’t new, the advent of edge computing has renewed its impetus. This technology enables greater processing and data storage on local devices instead of big data centers or the cloud. Advances in internet of things (IoT) technologies, machine learning, and 5G also make swarm systems faster and more efficient.
In a world of increasing flux, scale, and complexity, swarm intelligence will help businesses in two main ways: finding new sources of growth, and anticipating and managing disruption.
Following the Ant Trail to Growth
Ants have a very particular approach to finding a trail to food: Constantly releasing pheromones, they signal their progress to the rest of the collective. Each ant learns from all the other ants’ experiences, and as a result, each gets closer to a food source. Eventually, the colony identifies the best trail based on the feedback of individual ants.
This approach presents a valuable lesson for businesses looking to identify new growth opportunities.