The Other Exponentials
Any stable system can become unstable when even one component experiences exponential growth. In information technology, this translates into opportunities for new research and new business models.
Moore’s Law – Gordon Moore’s 1965 prediction that the number of transistors on a chip will roughly double every 18 months come rain or shine – describes infotech’s most famous exponential growth factor. But there are many other infotech exponentials, and it’s a good idea to think through their consequences.
Storage leaps to mind. In 2003, a $400 iPod had 10 gigabytes of memory. By early this year, a $400 iPod had 20 gigabytes of memory. If this annual doubling holds up, then 20 years from now we’ll have portable devices with 20 petabytes of storage – that’s 20 million gigabytes – sitting in our pockets. What might we want to do with all that storage, and what new services might it enable?
The iPod is now big enough to contain the entire personal music collection of today’s average listener. But the immediate consequence of storage growth is that our personal music collections will grow as well. CDs will no longer be a practical way to distribute content; they will go the way of wax cylinders and vinyl platters. That’s why so many companies are rushing in to follow Apple in the music content download and management business.
Before too long, CD readers and writers will disappear from personal computers, just as floppy disks have already become obsolete. Flash memory cards are one possible successor, but today’s versions are too slow and aren’t cheap enough to be disposable. Some new technology awaits invention or adoption.
Today’s iPod could store 20,000 books. That’s more than most people would read in a lifetime. But just 10 years from now, an iPod might be able to hold 20 million books – more than are in Harvard University’s collection. (If you insist on having the pictures and diagrams in those books, too, perhaps you have to wait until 2017. By then you’ll be able to carry around the complete text for all the volumes in the Library of Congress.) To complete this vision, of course, we’ll need a lightweight, easy-to-read screen to display text. And we’ll need technologies that allow for rapidly digitizing millions of books and other documents, and for extracting text without errors, so the books are searchable.
If we go out a few more years, iPods and similar devices will be able to store massive numbers of movies, rather than the paltry one or two you can carry around today. In fact, 20 years from now, a teenager will probably be able to shuffle down the street with every movie ever made in a $400 iPod. There will be tremendous business opportunities in digitizing old television shows and films, and for developing technologies that will let users browse and search them all. And of course we’ll witness epic battles over content ownership and compensation.
But personal storage is only one exponential technology: plenty of others exist. Intel has just announced that it is going to add a second processor to its previously one-processor consumer chips. And chips with even more processors are coming: I know of lab prototype chips with 16 processors. Multiple processors allow many threads of computation to proceed at once, and this changes the paradigm of how to do computing. It requires new approaches in some aspects of programming and other areas of computer science – but it will enable new applications, such as fast, cheap processing of stereo vision.
Meanwhile, wireless bandwidth and range are surging. Wireless connections to laptops and desktops have speeded up nearly fivefold in recent years. Over the next five years, we’ll see another 20-fold gain. New high-bandwidth networks will have ranges of tens of kilometers, versus today’s tens of meters. These trends will let us live always-connected broadband lives and enjoy a range of new services.
Finally, the cost of sequencing DNA is diminishing exponentially. By next year, the cost of sequencing a person’s genome is expected to be a mere penny per base pair. Compare that to the $10 it cost in 1990. At that rate, sequencing a person’s 3.2 billion base pairs should cost only $32,000 by 2020. As a practical matter, it’s only necessary to look at 10 million base pairs to cover all the variations in the human genome. Sequencing this number – in order to determine a person’s genetic fingerprint and disease susceptibility – would cost only about one dollar by sometime in the 2020s.
One can find plenty more exponentials out there, from the volume of scientific literature (increasing exponentially for hundreds of years already!), to the number of networked sensors that surround us, to the amount of spam we all receive. They, and others, are all going to have an impact on research and development opportunities, and on our lives. Bring them on!
The inside story of how ChatGPT was built from the people who made it
Exclusive conversations that take us behind the scenes of a cultural phenomenon.
How Rust went from a side project to the world’s most-loved programming language
For decades, coders wrote critical systems in C and C++. Now they turn to Rust.
Design thinking was supposed to fix the world. Where did it go wrong?
An approach that promised to democratize design may have done the opposite.
Sam Altman invested $180 million into a company trying to delay death
Can anti-aging breakthroughs add 10 healthy years to the human life span? The CEO of OpenAI is paying to find out.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.