Publication

Inference in artificial intelligence with deep optics and photonics

Demetri Psaltis
2020
Journal Articles

Abstract

Artificial intelligence tasks across numerous applications require accelerators for fast and low-power execution. Optical computing systems may be able to meet these domain-specific needs but, despite half a century of research, general-purpose optical computing systems have yet to mature into a practical technology. Artificial intelligence inference, however, especially for visual computing applications, may offer opportunities for inference based on optical and photonic systems. In this Perspective, we review recent work on optical computing for artificial intelligence applications and discuss its promise and challenges.

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https://infoscience.epfl.ch/entities/publication/7e504425-df73-4b77-8689-c8e1f4122c7b

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Demetri Psaltis
2020
Journal Articles

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/7e504425-df73-4b77-8689-c8e1f4122c7b

About this result

Related concepts (24)

Optical computing

Optical computing or photonic computing uses light waves produced by lasers or incoherent sources for data processing, data storage or data communication for computing. For decades, photons have shown promise to enable a higher bandwidth than the electrons used in conventional computers (see optical fibers). Most research projects focus on replacing current computer components with optical equivalents, resulting in an optical digital computer system processing binary data.

Inference

Inferences are steps in reasoning, moving from premises to logical consequences; etymologically, the word infer means to "carry forward". Inference is theoretically traditionally divided into deduction and induction, a distinction that in Europe dates at least to Aristotle (300s BCE). Deduction is inference deriving logical conclusions from premises known or assumed to be true, with the laws of valid inference being studied in logic. Induction is inference from particular evidence to a universal conclusion.

Computing

Computing is any goal-oriented activity requiring, benefiting from, or creating computing machinery. It includes the study and experimentation of algorithmic processes, and development of both hardware and software. Computing has scientific, engineering, mathematical, technological and social aspects. Major computing disciplines include computer engineering, computer science, cybersecurity, data science, information systems, information technology, digital art and software engineering.

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