The democratization of AI mirrors the historical rise of literacy, moving from a specialized skill held by "high priests" in big tech to a universal tool for all. While AI currently thrives on massive, one-size-fits-all datasets for web search and advertising, a "long tail" of high-value, small-scale projects remains untapped in sectors like local retail and manufacturing. These unique applications, such as a pizzeria predicting demand or a textile inspector identifying fabric defects, are often too small to justify expensive engineering teams. Emerging low-code platforms shift the development focus from complex programming to data labeling, allowing non-technical workers to train custom models. By empowering individuals like accountants and farmers to build their own AI systems, society can ensure that the wealth and productivity gains generated by artificial intelligence are distributed far beyond the internet sector.
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