The July 2022 issue of IEEE Spectrum is here!

Close bar

Networking Know-How

Using online networking sites could land you your next job

5 min read

Looking for a job? Even if you aren't, it's important to remember that the era of lifetime employment at a single company is over. Sooner or later, most of us are going to find ourselves looking for a new employer. Bearing that in mind, you need to make sure that your next job is a step up, not a stopgap, and one of the best ways to do this is by networking with others in your industry and related fields, even while you're happily employed.

Career-related professional organizations, such as the IEEE, are an ideal way to build networks. Attending local chapter events, or better still, getting involved with running a society, will make it more likely that when you send your job application to a business, you won't be a complete unknown.

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
DarkBlue1

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