Scale is one of the biggest challenges currently facing the AI and robotics “revolution,” which is to say: How are we going to set up all the infrastructure needed for all these autonomous tools? One answer that you’re about to hear a lot more often: swarms. While OpenAI and other major artificial intelligence firms continue to build multi-billion-dollar centralized data centers, a more decentralized approach is starting to take hold.

The Register recently highlighted one company taking the “swarm” approach to AI, and apparently producing some impressive results. Startup company Fortytwo published benchmarks that showed its approach of running small AI models on personal computers has managed to outperform some of the latest models in reasoning tests, claiming better outcomes than OpenAI’s GPT-5, Google’s Gemini 2.5 Pro, Anthropic’s Claude Opus 4.1, and DeepSeek’s R1.

The company’s theory, which appears to be borne out in the results, is pretty simple: large AI models can get stuck in reasoning loops when given complex tasks. Smaller models, meanwhile, not only limit those reasoning death spirals but also provide multiple answers that can be ranked to find the best available answer. That can, in theory, be done by distributing the computing tasks across many devices rather than having it done in a single, central data center—not unlike how cryptocurrencies farm out the computing tasks for logging transactions to many different machines. Fittingly, the company is offering a crypto-based reward to folks who create specialized models and run them as part of the swarm.

Something similar is developing in the robotics realm, per the Wall Street Journal, which recently highlighted research that shows how robots could operate with a sort of colony-like communication that would allow them to work as a collective intelligence. The researchers suggested such a model could be used in settings like wildfire monitoring, where swarms of drones are tasked with identifying potential fires. If one drone were to fail, the others would identify that it went down and pick up the slack. Another example the researchers floated was developing microscopic robots that could work together to do things like deliver medication inside the human body or clear a blockage without requiring surgery. That latter example was apparently not theoretical: researchers used tiny magnetic robots to form a chain push as a unit to clear blockages in artificial blood vessels.

The basic idea behind the research is that these machines can be extremely simple but perform more complex tasks when operating together. Researchers completed an experiment in which a swarm of robots that was only able to perform three abilities—move forward, make sound, and listen to neighbors—was able to link together and navigate around obstacles in a way they couldn’t do on their own. Apparently, the old idiom, “two heads are better than one,” applies to AI and robots, as well.