Skip to Content

Will Big Data Get Too Big for the Metric System to Handle?

It’s dizzying to contemplate, but it might not be long before the volume of digital data surpasses the current limit of measures.
December 10, 2012

In 1991, the General Conference on Weights and Measures met to add a few prefixes to the metric system to deal with the very large and very small scales of measurement that scientific advances required. The largest they came up with is the “yotta,” a number that contains 24 zeroes. As in: the diameter of the observable universe is estimated to be 880 “yottameters.”

“Big data” sometimes feels like a buzzword, but it gets more concrete when you imagine that soon the volume of digital data processed could surpass this current upper bound, which only two decades ago was the limits of scientists’ imaginations.

That’s at least the prediction of Andrew McAfee, who is principal research scientist at MIT’s Center for Digital Business and a prominent thinker about business information technology trends (see “When Machines Do Your Job”). At a conference I attended, and on his blog, McAfee chronicles the “arms race” of organizations declaring first the era of the “terrabyte,” then the “petabyte,” and most recently, Cisco’s call for the “zettabyte” era, as measured by its forecast of annual global IP traffic in 2016.

“Yotta” comes next, and McAfee predicts the global measurement body will be contemplating its successor by the time the decade is up. His favorite contender for a new prefix? The “hella.” As a San Francisco resident, I support the idea.

Keep Reading

Most Popular

still from Embodied Intelligence video
still from Embodied Intelligence video

These weird virtual creatures evolve their bodies to solve problems

They show how intelligence and body plans are closely linked—and could unlock AI for robots.

conceptual illustration showing various women's faces being scanned
conceptual illustration showing various women's faces being scanned

A horrifying new AI app swaps women into porn videos with a click

Deepfake researchers have long feared the day this would arrive.

protein structures
protein structures

DeepMind says it will release the structure of every protein known to science

The company has already used its protein-folding AI, AlphaFold, to generate structures for the human proteome, as well as yeast, fruit flies, mice, and more.

Stay connected

Illustration by Rose WongIllustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.