Optical processor startup claims to outperform GPUs for AI workloads

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Optical processor startup claims to outperform GPUs for AI workloads

Fathom Computing, a startup founded by brothers William and Michael
Andregg, is aiming to design an optical computer for neural networks. As
performance increases in traditional transistor-based CPUs have
relatively stagnated over the last few years, alternative computing
paradigms such as quantum computers have been gaining traction. While
optical computers are not a new concept—Coherent Optical Computers was
published in 1972—they have been relegated to university research
laboratories for decades.

The design of the Fathom prototype performs mathematical operations by
encoding numbers into light, according to this profile in Wired. The
light is then passed through a series of lenses and other optical
components. The measured result of this process is the calculated result
of the operation.

The Fathom prototype is not a general-purpose processor, it is designed
to compute specific types of linear algebra operations. Specifically,
Fathom is targeting the long short-term memory type of recurrent neural
networks, as well as the non-recurrent feedforward neural network. This
mirrors trends in quantum computers, as systems produced by D-Wave are
similarly targeted toward quantum annealing, rather than general processing.

In a recent blog post, Fathom indicated that they are still two years
away from launching, but that they expect their platform to
"significantly outperform state-of-the-art GPUs." The first systems will
be available as a cloud service for researchers working in artificial
intelligence.

Read more here:

https://www.techrepublic.com/article/optical-processor-startup-claims-to-outperform-gpus-for-ai-workloads/


Thank you,
Amine Moulay Ramdane.