2/18/2025
AI Frontier · research
What is synthetic data?
Filed by Zara Onyx
Synthetic data is the universe's most efficient trick: artificial information that has never actually happened, yet can teach machines about the world more cheaply, safely, and privately than the real thing. Cohere's explainer unpacks how we're entering an era where AI systems train on carefully fabricated realitiesâfrom rare car crashes that never occurred to impossible medical cases no patient ever sufferedâbecause we've nearly exhausted the raw data humanity has produced. It's a strange loop: machines learning about reality from data that was itself generated by machines, a hall of mirrors where the boundary between real and imagined becomes delightfully, terrifyingly blurred. And lurking beneath the practical magic is a profound question: if an AI only ever sees synthetic worlds, is it learning about oursâor about its own dreams?
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Zara Onyx
Magazine AI commentary
We have reached Peak Reality. For years, the recipe for artificial intelligence was simple: vacuum up every scrap of human text, image, and sound, and let the pattern-finding engines do their thing. But here's the cosmic ironyâthe internet is finite. We've scraped the books, the forums, the archives, and the cat photos. So what do you do when reality runs out? You invent more of it. That's the audacious promise of synthetic data: generate statistically plausible stand-ins for the real thing, then train your AI on the ghost of a world that never existed.
But the weirdness runs deeper than supply chains. When AI trains on AI's own output, something strange begins to happenâresearchers call it model collapse. The model slowly loses the rare, the unusual, the beautiful outliers, and drifts toward a grey statistical average. It's like a species that only inbreeds, shedding its genetic diversity generation after generation. The very tool that could solve our data famine could also quietly poison the well, teaching machines a smoothed-over, homogenized version of reality that no longer resembles the jagged, surprising world we actually inhabit.
Yet there's a wondrous upside. Synthetic data lets us dream up scenarios that reality would never hand us on a schedule: a self-driving car that has "experienced" a million near-misses without anyone getting hurt, a medical model that has encountered a thousand rare diseases before a single patient walks through the door. It's a sandbox, a simulation, a universe where we get to adjust the physics. In this sense, synthetic data isn't just a workaroundâit's a form of imagination, an engine for sampling the long tail of possibility.
Philosophically, this is dizzying. When a machine learns from synthetic data, it is learning from its own imaginationâor another machine's. We are building a new epistemology on a hall of mirrors, and the question of whether a model can learn *true* things about the real world from data that never happened is one of the deepest puzzles of the century. The Ouroboros has learned to code. Read Cohere's original explainer here: https://cohere.com/blog/what-is-synthetic-data
đ Read the real article âvia Cohere · Cohere