Here’s where it starts to get more interesting:

“But much of what we do with machine learning happens beneath the surface. Machine learning drives our algorithms for demand forecasting, product search ranking, product and deals recommendations, merchandising placements, fraud detection, translations, and much more.”

And then, when Bezos gets into what all this means for Amazon Web Services, Amazon’s cloud services platform, is where it gets really interesting:

“Inside AWS, we’re excited to lower the costs and barriers to machine learning and AI so organizations of all sizes can take advantage of these advanced techniques,” Bezos writes.

He goes on to describe how Amazon’s cloud-services clients can use the company’s pre-packaged deep-learning frameworks—including the systems that power the Amazon Echo; Amazon Polly, the company’s text-to-speech program; and Amazon Rekognition, its facial recognition software.

Clients have access to these technologies through a simple API, Bezos says, meaning developers for a range of companies can tap into Amazon’s suite of A.I. programs without having any machine learning expertise themselves.

This is a big deal for a few reasons. Mainly, because it means Amazon is enabling countless organizations to track its users more precisely than ever.

Amazon Web Services is huge. It is, for starters, the backbone of the commercial web. (That’s why, when AWS has a server problem, it seems like the entire internet is coming apart at the seams.) It reported a stunning $12.2 billion in sales last year, and more than $3 billion in profit. Giving all AWS clients easy access to advanced data-tracking tools means Amazon is making the baseline for corporate surveillance online much more sophisticated.

This may be exciting news for businesses that want to follow and analyze their customers and potential customers more closely. But for people concerned about individual privacy, this is not so great. (Amazon did not respond to my request for an interview.)

Of course, many of the biggest companies that use Amazon Web Services already run in their own high-level data-tracking operations. (Remember, AWS clients include McDonald’s, Netflix, Airbnb, Adobe, Capital One, GE, and Pinterest, to name a few.) It was in Bezos’s shareholder letter last year that he boasted of AWS’s stunning client base: “more than a million customers from organizations of every size across nearly every industry,” he wrote.

Amazon Web Services helps power a massive swath of the global economy—across markets and industries that are all deeply vested in collecting and sharing detailed data about individuals and their behaviors. Yet there’s clear incentive for companies to leverage machine-learning technology beyond tracking individual behaviors. There are all sorts of applications for a computer that can be trained to recognize patterns. Bezos included this lucid explanation in his letter: “Over the past decades computers have broadly automated tasks that programmers could describe with clear rules and algorithms. Modern machine learning techniques now allow us to do the same for tasks where describing the precise rules is much harder.”