Skip to Content
Uncategorized

10 Emerging Technologies

They promise to change the world. But how will their development be funded?
April 25, 2012

Every year, the editors of Technology Review pick the 10 emerging technologies we think are most likely to change the world: the TR10. Other lists we publish, such as the TR35, our annual list of 35 young innovators under the age of 35, are less subjective: innovators nominate their most admirable young peers and colleagues, and a panel of distinguished judges grades the nominees. The TR10, by contrast, reflect our judgments. We consider the major technological domains and award recognition to the breakthroughs “that we believe will have the greatest impact on the shape of innovation in years to come” (to quote the editor of the TR10, Technology Review’s special projects editor, Stephen Cass).

The technologies are always various. This year’s TR10, include a fertility technology developed by Jonathan Tilly of Boston-based OvaScience, in which stem cells in ovarian tissue could be coaxed into forming new eggs or rejuvenating a woman’s existing eggs; the light-field photography of Lytro, a startup in Mountain View, California, which has reinvented the camera by capturing three-dimensional patterns of light that software can manipulate to stunning effect; solar microgrids, cheap solar panels and LEDs combined by Mera Gao Power of New Delhi, India, to provide clean light and charge phones in the rural subcontinent; and an alternative to traditional venture capital funding called “crowdfunding,” created by the New York–based website Kickstarter, which encourages communities of enthusiasts to fund new projects with small sums.

Amid all this celebration of emerging technologies, a few words of mild caution are appropriate. How will these technologies be funded and commercialized? Kickstarter, for 
all the interest it has attracted, is an experiment that (so far, at least) has funded mostly experiments that don’t require much money. Traditional venture capital, as it evolved in Silicon Valley during the 1970s and ’80s and flowered in the ’90s, was supremely well suited to funding new information and Web technologies during an era when the public markets were exuberantly receptive to the stock offerings of new IT and Web companies.

With great difficulty and mixed success, ­Silicon Valley–
style venture capital was applied to funding biotechnology: large pharmaceutical companies, hungry for blockbuster drugs, would pay licensing fees that justified initial public offerings and acquisitions of biotech startups. But venture capital struggles to help commercialize other emerging technologies. As David Rotman writes in “Can Energy Startups Be Saved?” Venture capital is “ill suited to creating energy companies on its own.” And taken as a whole over the decade since the dot-com bubble burst, venture capital hasn’t even been very effective at funding new information and Web technologies (see “What’s Wrong with Venture Capital?” March/April 2010).

A successful public offering of Facebook’s stock will make it easier for other Web and IT startups to repay their investors and may repair venture capital’s mode of business in limited domains; but if emerging technologies are to provide solutions for the big, civilizational problems in energy, health, education, and resource management, we’ll need new mechanisms for commercialization.

But write to me at jason.pontin@
technologyreview.com and tell me what you think.

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.