Undersea Observatory Survives Setback

Neptune Canada recovers from an outage and its U.S. counterpart finally gets started

3 min read
Photo: CSSF/IFREMER/NEPTUNE Canada
Undersea instruments: The Tempo-Mini platform, part of Neptune Canada, houses temperature and chemical sensors.
Photo: CSSF/IFREMER/NEPTUNE Canada

Few things make engineers as proud as seeing their creations shrug off a failure and keep delivering. That's exactly how the designers and operators of Neptune Canadathe world's largest remotely operated undersea observatory—must feel. Since going live in December 2009, Neptune has weathered several insults, including a dangerous encounter with a trawler, but it has still produced a near-continuous stream of live data from over 125 instruments at depths of nearly 2400 meters, including deep-sea video cameras, sonars, seismometers, and robotic crawlers.

At the end of last year, Neptune Canada had managed to bounce back from its biggest technical troubles yet, but now it faces a budget crunch that could put it on life support as early as next month. And that's happening just as the observatory's colleagues in the U.S. Pacific Northwest seem to finally be overcoming budget constraints that held up a sister observatory.

Keep Reading ↓ Show less

Stay ahead of the latest trends in technology. Become an IEEE member.

This article is for IEEE members only. 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 →

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

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