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Machine Learning and Fashion: The New Fashion of the Times

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We owe an overdue acknowledgment to a transformation in technology, as well as a revolution (more about below) in fashion, where the former makes the latter the new fashion of the times, so to speak. I refer, specifically, to the rise of machine learning and its ongoing influence—for the good of businesses and consumers alike—across a multitude of industries. It is this intuitive-like sense of wisdom, because we are beyond mere matters of intelligence (artificial or otherwise), which will create a more intimate relationship on behalf of users, shoppers and executives, among others.

According to Greg Corrado, a senior research scientist at Google:

"Before Internet technologies, if you worked in computer science, networking was some weird thing that weirdos did. And now everyone, regardless of whether they're an engineer or a software developer or a product designer or a CEO understands how Internet connectivity shapes their product, shapes the market, what they could possibly build."

It is that potential—it is this reality—that marks a major milestone in the personalization of technology because the subject itself is impersonal and abstract. Those scientists and entrepreneurs who manage to showcase the practical benefits of this shift, among those who convey this point to the public at large, will make all manner of software and customized search more accurate and exhaustive.

As Mike Yeomans, a post-doctoral fellow in the Department of Economics at Harvard University, explains in this article in the Harvard Business Review:

"Consider an online retailer's database of customers in a spreadsheet. Each customer gets a row, and if there are lots of customers then the dataset will be long. However, every variable in the data gets its own column, too, and we can now collect so much data on every customer—purchase history, browser history, mouse clicks, text from reviews—that the data are usually wide as well, to the point where there are even more columns than rows. Most of the tools in machine learning are designed to make better use of wide data."

Making better use of that data is the way companies can achieve greater connectivity—in every way—between themselves and the customers they seek to serve. In this regard, the impersonal nature of technology becomes the personal face of a collection of technologies that changes the binary language of so many ones and zeroes into the vernacular of the everyday consumer and the considerations of even the most discriminating buyers.

One pioneer at the forefront of these events is Jay Rao, Co-Founder of, a platform that helps shoppers discover, compare and review everything—or almost everything—under the category of fashion. Rao says:

"Machine learning is the next stage in a much larger advance toward enhancing the depth and breadth of individual searches for various goods and services. By continuously refining these results, and by presenting users with the most relevant selection of items, consumers get what they want—they get what they would not otherwise know they want—from the cataloging of millions of products on a daily basis.

"The subsequent experience for users is an immersive one: It curates products, highlights each consumer's favorite designers and even suggests styling looks. Call it data with its own designer, of proprietary algorithms and patented gowns and dresses."

We should champion machine learning as a symbol of progress, which offers greater convenience and more accurate search results than the status quo.

These accomplishments are not fads, far from it, as they represent—and as I reiterate once more that they are—the fashion of the times.

Welcome to the triumph of technology.