Skip to Content

Matters of Size

From The Editor In Chief
September 1, 1998

When we introduced the new technology review, we promised we would cover the entire “innovation system “of the United States and the rest of the industrial world. And we’ve begun to do that-giving you an inside view of university research labs, venture capital firms, high-tech startups and major technology companies. Within the overall innovation system, the glamor part is the startups. Magazines like Wired, Red Herring and Upside zero in on companies started by 20-year-olds working 18 hours a day so they can sell their startup to Microsoft by the time they’re 22. It’s understandable that these ventures get so much attention. They’re romantic, and unique: No other country has a climate so favorable to entrepreneurship.

But a look beneath the surface of our system shows that innovation is not confined to the double-latte set. In order to succeed, major technological corporations must also create internal environments as white-hot as anything you might find in a Seattle garage. To highlight the combined contributions of startups and industrial giants in our innovation system, we’ve chosen to pair two intriguing articles in our first Technology ReviewSpecial Report: Innovation Large and Small. Contributing Writer Robert Buderi takes you behind the scenes at the “new “Bell Labs. Bell Labs was for many years the crown jewel of American industrial R&D. Powered by a “research tax “on telephone service that was made possible by AT&T’s monopoly status, the labs allowed elite basic researchers to pursue fundamental investigations far removed from the goal of improving telephone service.

But times change. Following the breakup of AT&T in 1984, Bell Labs became a component of a new company called Lucent Technologies. Lucent shrank the lab and focused its work on the bottom line-provoking outrage from the research community and prompting the departure of some talented investigators, who found more congenial homes at universities. Buderi’s reporting shows that despite these protests basic research at Bell Labs may be healthier than ever.

The heart of Buderi’s tale is a large institution that has flourished because of the contributions of many individuals. In our companion piece, Simson Garfinkel tells the story of a scrappy company called Dragon Systems that was built by one married couple: Jim and Janet Baker. The Bakers are researcher-entrepreneurs who met at their computer screens. Their lives and professional interests are inextricably intertwined, and their company is a direct reflection of their personalities. In contrast to some of the flash-in-the-pan startups we see today, the Bakers worked for decades at the cutting edge of speech recognition, building a company and numerous products that today compete head-to-head with IBM in the marketplace.

Taken together, these penetrating articles offer a look at two dimensions of our innovation system: the very large and the very small. In future issues, we’ll be covering the rest of the innovation system. Because that’s our mandate. Innovation.

Keep Reading

Most Popular

open sourcing language models concept
open sourcing language models concept

Meta has built a massive new language AI—and it’s giving it away for free

Facebook’s parent company is inviting researchers to pore over and pick apart the flaws in its version of GPT-3

transplant surgery
transplant surgery

The gene-edited pig heart given to a dying patient was infected with a pig virus

The first transplant of a genetically-modified pig heart into a human may have ended prematurely because of a well-known—and avoidable—risk.

Muhammad bin Salman funds anti-aging research
Muhammad bin Salman funds anti-aging research

Saudi Arabia plans to spend $1 billion a year discovering treatments to slow aging

The oil kingdom fears that its population is aging at an accelerated rate and hopes to test drugs to reverse the problem. First up might be the diabetes drug metformin.

Yann LeCun
Yann LeCun

Yann LeCun has a bold new vision for the future of AI

One of the godfathers of deep learning pulls together old ideas to sketch out a fresh path for AI, but raises as many questions as he answers.

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.