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Manipulating information at the quantum level is profoundly different from manipulating it classically. This opens the door to some new and surprising applications such as quantum cryptography (in which the security of the encryption of a message is guaranteed by the laws of physics) or quantum computers (which could solve certain problems such as factoring exponentially faster than classical computers). The Laboratoire d’Information quantique is actively working on different aspects quantum information, both at the theoretical and experimental level.

Summary of Round Table

Dynamical Systems and Brain Inspired Computing

Brussels : 31 May – 2 June 2017

Summary of the Round Table on 1st June 2017

Around the Table: Raul Vicente, Ingo Fisher, Herbert Jaeger, Joni Dambre, David Wolpert.

Moderator: Serge Massar.

  • What is the key/most important cost measure (energy, speed, ..) of (analog) computing systems?
    • Depends on application, each platform will have specific applications. No general-purpose device
    • Find similarities between different systems -> use synergies
  • Is reservoir computing a niche or is there place to grow (esp. considering Deep Learning)
    • Try to find underlying (common) information processing requirements
  • Why does reservoir computing work so well (in different systems/platforms)?
    • It's a cheap trick, that works in limited fashion only
    • Disagreement on amount of non-linearity needed
    • Can use almost any non-linearity to get decent results
  • Description in terms of non-linear system:
    • Reservoir Computing needs negative conditional Lyapunov exponents (with respect to external drive)
  • How to define computation? What is computation?
  • Where can reservoir computing / analog computing beat state of the art technology?
    • Different platforms have different advantages
    • Hardware limits number of trainable parameters
    • Having a completely autonomous hardware for analog computation is tricky
  • Is there a niche where analog can beat digital?
    • Not obvious
    • How to implement error correction?
    • Not necessarily needed, digital too precise for many task requirements
  • Can we change the methodology/paradigms of computing?
  • How large is "large enough"? How large has the reservoir to be?
    • Can we go from 3 bit header recognition to 40 bit header recognition?
  • Can we use reservoir computing to explore thermodynamics? Improve energy efficiency for ExaScale computing
  • How can we extend the uses/impact of analog hardware platforms?
    • At the moment: Lack of communication, should reach out to more communities
  • Comparison to Quantum computing:
    • It is as far away from usable computing platform as reservoir computing
    • QC: Promise of exponential speed up, in contrast to polynomial speed up learning
    • D-Wave is/is not a quantum computer?
  • Reservoir Computing is too simple an idea to found a community
    • Reservoir Computing is a tool
  • Brains show the possibility of efficient/analog/flexible computing systems. But we are very far away from understanding
    • We need to accept that we can't understand the brain soon
    • start with smaller brains (insects)
    • The important questions are bigger than reservoir computing