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Silicon Photonics

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Entries in Luminous Computing (2)

Thursday
Mar242022

Building an AI supercomputer using silicon photonics 

  •  Luminous Computing is betting its future on silicon photonics as an enabler for an artificial intelligence (AI) supercomputer 

Silicon photonics is now mature enough to be used to design complete systems.

So says Michael Hochberg (pictured), who has been behind four start-ups including Luxtera and Elenion whose products used the technology. Hochberg has also co-authored a book along with Lukas Chrostowski on silicon photonics design.

In the first phase of silicon photonics, from 2000 to 2010, people wondered whether they could even do a design using the technology.

“Almost everything that was being done had to fit into an existing socket that could be served by some other material system,” says Hochberg.

A decade later it was more the case that sockets couldn’t be served without using silicon photonics. “Silicon photonics had dominated every one of the transceiver verticals that matter: intra data centre, data centre interconnect, metro and long haul,” he says.

Now people have started betting their systems using silicon photonics, says Hochberg, citing the examples as lidar, quantum optics, co-packaged optics and biosensing.

Several months ago Hochberg joined as president of Luminous Computing, a start-up that recently came out of stealth mode after raising $105 million in Series A funding.

Luminous is betting its future on silicon photonics as an enabler for an artificial intelligence (AI) supercomputer that it believes will significantly outperform existing platforms.

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Monday
Jun292020

CW-WDM MSA charts a parallel path for optics  

Artificial intelligence (AI) and machine learning have become an integral part of the businesses of the webscale players.

The mega data centre players apply machine learning to the treasure trove of data collected from users to improve services and target advertising.

They can also use their data centres to offer cloud-based AI services.

Training neural networks with data sets is so intensive that it is driving new processor and networking requirements.

It is also impacting optics. Optical interfaces will need to become faster to cope with the amount of data, and that means interfaces with more parallel channels.

Anticipating these trends, a group of companies has formed the Continuous-Wave Wavelength Division Multiplexing (CW-WDM) multi-source agreement (MSA).

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