The July 2022 issue of IEEE Spectrum is here!

Close bar

You in Your Internet of Things

Should privacy and security measures be built into devices before they reach the market?

2 min read
You in Your Internet of Things
Photo: Yagi Studio/Getty Images

My Fitbit sends me encouraging notes throughout the day. My iPhone does a remarkable job of telling me where I am, where I should be, and how to get from here to there. And then there’s my Honda, reminding me what music I last listened to. Would I like to hear something else?

For the most part, these devices work well, and I am pleased with the convenience that all this robust connectivity offers. On a more global scale, when my personal data is added to that of millions of others, I see the enormous value in all that aggregated information, culled and parsed by ever larger and more interconnected networks.

Keep Reading ↓Show less

This article is for IEEE members only. Join IEEE to access our full archive.

Join the world’s largest professional organization devoted to engineering and applied sciences and get access to all of Spectrum’s articles, podcasts, and special reports. Learn more →

If you're already an IEEE member, please sign in to continue reading.

Membership includes:

  • Get unlimited access to IEEE Spectrum content
  • Follow your favorite topics to create a personalized feed of IEEE Spectrum content
  • Save Spectrum articles to read later
  • Network with other technology professionals
  • Establish a professional profile
  • Create a group to share and collaborate on projects
  • Discover IEEE events and activities
  • Join and participate in discussions

The Future of Deep Learning Is Photonic

Computing with light could slash the energy needs of neural networks

10 min read
Image of a computer rendering.

This computer rendering depicts the pattern on a photonic chip that the author and his colleagues have devised for performing neural-network calculations using light.

Alexander Sludds

Think of the many tasks to which computers are being applied that in the not-so-distant past required human intuition. Computers routinely identify objects in images, transcribe speech, translate between languages, diagnose medical conditions, play complex games, and drive cars.

The technique that has empowered these stunning developments is called deep learning, a term that refers to mathematical models known as artificial neural networks. Deep learning is a subfield of machine learning, a branch of computer science based on fitting complex models to data.

Keep Reading ↓Show less