Skip to Content

100 Hot Zones

From the editor in chief
November 1, 1999

Although the readers of the 1899 Technology Review might not recognize the magazine you hold in your hands, this year marks our 100th year of continuous publication. This special issue was developed to commemorate a century of publishing history.

How to celebrate our centennial? When that question was raised last year, we quickly decided we weren’t going to publish an issue devoted to the past. Lots of magazines are doing that this year. The newsstands are filled with special issues on the “100 Best This” or the “100 Best That” of the century now wobbling to a close. Not us. The new Technology Review is focused on the future. We decided the best way to conclude a century of publishing was to talk about the next century.

That left us with a problem: The next century hasn’t happened. And most attempts to discuss the future, particularly the technological future, get very speculative very fast. This issue contains our solution to this problem: The TR100.

The TR100 are a group of young folk (under 35) who exemplify the spirit of innovation. They’re from universities and big companies, startups and government labs, and from every significant arena the new TR covers: biotechnology, information technology, materials science, business, entertainment, policy-even digital art. The editors of TR-with the help of a distinguished Panel of Judges-selected them because they have the potential to make big contributions in these fields in the decades to come.

Picking 100 young innovators is intriguing in itself. But it has an important collateral benefit: It’s a way to identify areas of research that will pay off in the near future. The young have an urgent need to identify growth areas-because they’re betting promising careers on their choices. As a result, reading the profiles we’ve written of the TR100 offers a guided tour of technology’s “hot zones”: the areas that the best and brightest believe will pay off during the next decade. That guided tour alone is worth the price of admission. But in addition, we’ve asked the TR100 to tell us what they think are the most significant trends emerging in hardware, software, biotech, materials and the World Wide Web.

The emphasis in this issue is on the young and on the future. Yet no generation invents itself; it must rely on the counsel and example of its predecessors. In that spirit, we asked Steve Hall, TR columnist and our nation’s best chronicler of biomedicine, to interview Nobel Prize winner Phil Sharp on key developments in biotech. We asked Bob Metcalfe, inventor of Ethernet and founder of 3Com, to tell young innovators what he has learned as a successful inventor and innovator (he thinks the two are very different).

In the end, in spite of our best intentions, we couldn’t resist a little summing up of the closing century: We picked the century’s 10 most notable human-machine interfaces. But even that exercise has a forward spin. We chose interfaces because we believe that in the next century humans will become increasingly intimate with their machines and interfaces will grow dramatically in importance.

We hope you enjoy this forward-looking celebration of our first century of publication. Over the course of TR’s next century, we promise to continue bringing you the future as it happens.

Keep Reading

Most Popular

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

OpenAI teases an amazing new generative video model called Sora

The firm is sharing Sora with a small group of safety testers but the rest of us will have to wait to learn more.

Google’s Gemini is now in everything. Here’s how you can try it out.

Gmail, Docs, and more will now come with Gemini baked in. But Europeans will have to wait before they can download the app.

This baby with a head camera helped teach an AI how kids learn language

A neural network trained on the experiences of a single young child managed to learn one of the core components of language: how to match words to the objects they represent.

Stay connected

Illustration 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.