Goodbye Silicon, Hello DNA: The Future of Data Storage?

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One night a few years ago, two biologists sat in a bar in Hamburg, discussing DNA. Ewan Birney, the associate director of the European Bioinformatics Institute, and Nick Goldman, a research scientist there, were wondering how to handle the tsunami of data flooding the institute, whose job it is to maintain databases of DNA sequences, protein structures, and other biological information that scientists turn up in their research—databases that are growing exponentially, thanks mostly to dropping costs and increased automation. The maintenance of all this data on hard drives was pressing their budget to the breaking point.

Being genomicists, they joked that DNA, which is incredibly compact, sturdy, and of course has a rather lengthy history of storing data, would be a better way to go. Joking, however, gave way to fevered napkin-scribbling, and soon, recalls Goldman, “We had to order another beer, and call for more napkins to write on.”

Three years later, the results of that bar stool inspiration have been published in Nature, in a paper in which Birney, Goldman and their collaborators report using DNA to store a complete set of Shakespeare’s sonnets, a PDF of the first paper to describe DNA’s double helix structure, a 26-second mp3 clip from Martin Luther King, Jr.’s “I Have a Dream” speech, a text file of a compression algorithm, and a JPEG photograph of the institute. You may not be storing your personal data on DNA anytime soon—the process is time-consuming and expensive, and there’s the small matter of needing a DNA sequencer to open the files—but as the costs of making and sequencing DNA continue to plunge and as computer engineering approaches the limits of just how densely information can be encoded on silicon, such biological data storage be just what’s needed for institutes and other organizations with massive archival needs.

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To encode files in DNA, Birney and Goldman started by converting text, image, or audio data into binary code. Then, in several steps using software that Goldman wrote, they converted that into A, T, G, or C code, which stand for the four DNA bases. Working from that string of letters, they drew up the blueprints for thousands of pieces of DNA , each containing a snippet of a file, and sent their designs to Agilent Technologies, which manufactures custom DNA for biologists. Agilent sent back the completed DNA fragments—just a smidge of white dust in the bottom of a plastic tube, Goldman recalls. To open the files, the team used a standard DNA sequencer, a process that took about 2 weeks. They then used Goldman’s software to reassemble the sequenced DNA into coherent, readable files. With the exception of two small gaps in the DNA, the sonnets, photo, speech, PDF, and text file re-emerged from the white dust almost completely unscathed. After the scientists performed a little repair work, all of the information—about 739 KB worth—was retrieved with 100% accuracy.

The fidelity is impressive, and DNA, when kept in a cold, dry, dark place, can stay intact for thousands of years. But how long would you have to want to store something for this process to be cheaper than using archival magnetic tape, which needs to be replaced every 5 years but is still the current gold standard, thanks to its low power demands compared to hard drives or other storage technologies? Birney and Goldman calculate that if you wanted to put a file in storage today and have it last for at least 600 years, DNA would be cheaper than re-recording the data to fresh magnetic tape every half-decade or so, a process that would have to be repeated 120 times over the six-century span.

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Goldman speculates that if the price of making and sequencing DNA continues to fall at current rates, commercial services that store data in DNA might spring up around 50 years from now. “You would email documents and photographs and stuff that were valuable to you and your family [to the DNA storage company], and maybe a day later or a week later, they would ship you back a little bit of DNA,” says Goldman. “You could stick it in the fridge or bury it in the garden or they would store it. And they can guarantee it will be there a hundred thousand years later.”

Birney and Goldman are not the only genomicists who have realized the data-storage potential of DNA. In September 2012, genomicists George Church, Yuan Gao, and Sriram Kosuri published a short description of a similar system in Science. The Nature team stored slightly more data, and Goldman avoided one of the sources of error in the Science paper—strings of repeated bases that DNA sequencers have trouble handling—by adjusting the way his software converts the information into A, T, G, and C. But on the whole, the ideas are similar, and represent a big step forward from earlier, smaller studies.

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Still, Kosuri is quick to point out that this technology is in its infancy. “Both of our papers are pretty naive and simplistic, in the way we encode information,” he says. “We’re not bringing to bear the 30 years or so of electrical engineering that have gone into making CDs. We’re biologists, not electrical engineers.” And even if the technique gets faster and cheaper, DNA has two limitations: it’s not rewritable, so you couldn’t update information without redoing the whole process, and doesn’t allow random access, so you couldn’t read, for instance, a single Shakespeare sonnet from the 154 Birney and Goldman stored without decoding the entire file.

No matter what, the need for something new to replace our current data-storage technology is pressing. In 2011, according to the Digital Universe report, humanity had created 1.8 zetabytes of new data to store, around 1.8 trillion gigabytes. By 2020, the number is set to have grown 50 times over. And as of this year, Moore’s Law, the observation that the number of transistors on integrated circuits doubles every two years, is expected to apply no more. Doubling is projected to occur every three years from here on out as more and more circuits compete for a fixed amount of space. Silicon may have been the workhorse of the first, golden age of computers. But it may take something even better—the very stuff that makes up life—to get us to the second.

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Facebook’s Graph Search Is the Future of Facebook

Facebook

Facebook held a big press event this morning. The company only sent out invitations last week, and when it did, it didn’t disclose the topic. But in a sense, everyone who pays close attention to Facebook has been waiting for this event for most of the site’s history — because the subject was Graph Search, the social network’s first truly serious search feature.

Like other great big Facebook-altering features like Timeline, Graph Search isn’t being unleashed in one fell swoop. It’s a beta for now, and only a minuscule percentage of users will get it immediately. (Everyone else can get on the waitlist at facebook.com/graphsearch.) Still, its arrival in even limited form is an important moment.

Graph Search lets you enter plain-English concepts that tie together multiple things the social network knows about the people who use it: where they live, where they work, where they’ve taken photos and what things they’ve liked. Among the searches Facebook provides as examples are “people who like tennis and live nearby,” “tourist attractions in Italy visited by my friends,” “movies liked by people who are film directors” and “friends of friends who have been to Yosemite National Park.”

The results aren’t Google-style links to external sites — they’re Facebook pages for the people, places and other things that match the query. In theory, at least, this new way to find information is both faster and far more personal than a conventional search engine. The notion that we might end up doing most of our interacting with Facebook by searching rather than browsing seems entirely plausible.

At the press event, Facebook did try to keep everyone’s expectations in check. CEO Mark Zuckerberg spent much of his presentation emphasizing what Graph Search isn’t. He kept saying that it’s not the same thing as “Web search” (or, as most of us tend to call it, Google).

More important, it isn’t a fully fleshed-out idea. This first version helps you find people, photos, interests and places, but there’s lots of stuff on Facebook it doesn’t know about yet. It doesn’t search status updates, for instance, and it’s not hooked into Facebook’s Open Graph, which ties the site together with third-party services like Spotify. It also doesn’t work on Facebook’s mobile apps yet. (Zuckerberg says Facebook’s to-do list for Graph Search should keep the company busy for the next several years.)

It’s not even clear yet just how useful Graph Search’s limited initial features will be. As I scanned the results for the example searches performed by Zuck and his co-presenters, Graph Search honchos Tom Stocky and Lars Rasmussen, many of them seemed painfully obvious, like a list of friends’ favorite TV shows that contained “well, duh” items such as The Office and Game of Thrones.

The most instantly appealing aspect of Graph Search may be photo search, which looks slick and fun. Without it, I have trouble finding my own snapshots I’ve uploaded, let alone ones from friends or public ones I might like.

If Graph Search fails to come up with any results at all — an outcome that sounds like it might be common — it’ll give you a standard page of Web search results. Those will be powered by Facebook partner and part owner Microsoft, and will be largely the same as the results you’d get if you just conducted the same search on Bing.

When Facebook launches something major, it’s easy to get irrationally exuberant about its potential: the e-mail-like messaging features it introduced in November 2010, which looked like they might be a landmark, didn’t usher in a new era for either Facebook or e-mail after all. But it’s been clear all along that a sophisticated search feature was the biggest missing piece of the Facebook puzzle — the one to let the site tap into everything it knows about a billion people in ways that might be both highly useful and enormously profitable. Now we know that Facebook is at work on that challenge.

Other than allowing for “Sponsored Search” promotional links, Facebook isn’t trying to make money off Graph Search yet. But if it takes off, and people start using Facebook to find restaurants, doctors, travel destinations and much more, it’s tough to imagine a scenario in which the site doesn’t make enormous amounts of money from precisely targeted advertising. It could rival Google as a money machine on a level it hasn’t done to date.

We’re talking Facebook here, so it’s a given that Graph Search is going to be controversial, at least at first. It doesn’t let you see anything you couldn’t have seen otherwise: all privacy settings are respected, and people won’t even show up in results if they haven’t given you access to the relevant facts that would otherwise put them there, such as their employer or location.

But Graph Search will make it a whole lot easier to find out stuff on Facebook. Facts that would otherwise have been buried in a profile or that might have scrolled off into the Timeline’s distant past will be only a search query away. It’ll be fascinating to see how that changes the way people use the service, and whether it rankles a meaningful number of users.

Facebook isn’t introducing any new privacy features related to Graph Search; at today’s event, Zuckerberg simply recapped recent privacy upgrades like the ability to review all your recent activity and adjust settings on the fly. He also said before Graph Search is made widely available, Facebook members will get a prominent message encouraging them to review their privacy choices. I expect that this won’t be enough to pacify privacy advocates and Facebook skeptics — though truth to tell, I think that much of the angst over Facebook privacy issues is overblown. (I’m never clear on why people who dislike Facebook use it at all.)

Me, I’m guardedly optimistic about Graph Search. I use Facebook for things I want to share, not for things I want to hide, so I’m not worried about the privacy implications. And my single biggest beef with the site is that it’s impenetrable: too much of the worthwhile stuff it contains is too hard to uncover. Graph Search could change that.

But it won’t change anything until millions of people get their hands on it. More thoughts to come once I do. For now, I’m reading what Wired’s Steven Levy and Search Engine Land’s Danny Sullivan have to say about all this.

Fork from the Future Senses When You’re Eating Too Fast, Vibrates to Slow You Down

Jared Newman / TIME.com

And lo, on the eighth day of the calendar month of January in the year 2013, a fork from the future appeared before the bewildered eyes of weary pressfolk attending a technology event in the city of Las Vegas.

They called the fork HAPIfork. But this was no common fork, and he who beholds such a fork may find no HAPI-ness in having to use it – for this fork’s purpose is to goad its owner into sensible eating patterns.

The common fork cares not how often it shovels food into its owners mouth; the HAPIfork’s magical motion sensor knows how often food is shoveled into its owners mouth and vibrates if it deems such mouthfuls too frequent. The HAPIfork demands its owner eat slowly! Perhaps by eating slowly, the owner will feel full without overeating.

The common fork is an inexpensive investment; the HAPIfork will cost $99 when it ships in the springtime. The HAPIfork connects to a computer with a USB cable, transfers information to the Internet and makes the information available via the web and smartphone apps so its owner can experience ultimate levels of self-loathing and/or pride; the common fork, of course, does no such thing.

Product Page: HAPIfork [HAPILABS.com]

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