January 2020 AI Reality Chart Tracks the Analog and Photonic AI Hardware Accelerator Race

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Pages: 8
Tables, Charts,
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Publication Date: 1Q 2020
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In producing the AI Reality (AIR) chart on AI hardware accelerators in January 2019, Ovum focused on conventional (classical) computer hardware and did not cover the esoteric parts of the spectrum: hardware exploiting optical or photonic physics, analog physics (light also falls into this category), and photonic quantum effects. In this edition of the AIR chart Ovum takes a closer look at these types of AI acceleration chips.

The market in photonics was stimulated by a pivotal paper published in 2017, which reported applying optical technology to training deep learning neural networks. The current state of this segment of the AI hardware acceleration market has startups in various modes of incubation, as well as large high-tech players involved in research projects. This Ovum report identifies eight startups and two incumbents working in photonics as well as two other groups working on other analog technology.

Key Questions Addressed:

  • How do AI hardware accelerators support deep learning?
  • What benefits do optics bring to deep learning?
  • What are some startups in the photonic AI accelerator segment?
  • How do analog and photonic AI hardware accelerators compare in terms of state of development?

Who Needs This Report?

  • AI technology and platform companies
  • AI hardware companies
  • Professional services firms
  • Government agencies
  • Investor community

Table of Contents

  1. Ovum View
    1. Summary
    2. Introduction
    3. The analog and photonic hardware acceleration vendors
      1. Fathom Computing
      2. IBM
      3. Intel
      4. Lightelligence
      5. Lightmatter
      6. LightOn
      7. Luminous Computing
      8. Mythic
      9. Optalysys
      10. PsiQ
      11. Xanadu
  2. AIR Chart
  3. Methodology
  4. Appendix

List of Charts, Figures, and Tables

  • January 2020 AIR check for analog and photonic AI hardware acceleration