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WBA Prize at Animal AI Olympics

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Explanation of the WBA Prize the Animal-AI Olympics 2019 presented at the kick-off meetup held in Tokyo by WBAI & Cooger Co. on August 21, 2019.

Published in: Engineering
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WBA Prize at Animal AI Olympics

  1. 1. 16:00-17:30 Hiroshi Yamakawa WBA prize at Animal AI Olympics 21 Aug. 2019“Animal-AI Olympics” Kick-off meetup
  2. 2. Basic idea of WBAI Vision: Create a world in which AI exists in harmony with humanity. Values: • Study: Deepen and spread our expertise. • Imagine: Broaden our views through public dialogue. • Build: Create AGI through open collaboration. http://wba-initiative.org/en/2171/ Mission: Promote the open development of Whole Brain Architecture ‘to create a human-like AGI by learning from the architecture of the entire brain’ “Animal-AI Olympics” Kick-off meetup2
  3. 3. Whole Brain Architecture approach “Animal-AI Olympics” Kick-off meetup ‘to create a human-like AGI by learning from the architecture of the entire brain’ To reach AGI, we start from mimicking high-level architectures of the brain, and gradually introduce details as needed 3
  4. 4. Merits of referring the brain architecture “Animal-AI Olympics” Kick-off meetup4 Can utilize knowledge in various fields related to human intelligence for design and evaluation Provide a platform for technology integration: → The brain is an agreeable AGI reference model High affinity with people → AI that is similar to people up to the internal structure and is easy to understand / trust Brain-inspired AGI development becoming major (DeepMind, Chania Brain Project, etc.)
  5. 5. T: AGI design space Hb Brain constraints could accelerate AGI development “Animal-AI Olympics” Kick-off meetup5 Under the practical search ability a, • AGI discovering probability ≒ a✕(T / H) • Brain-inspired AGI discovering probability ≒ a✕(Tb / Hb) Tb H:Search space (depend on the combination of parts) Brain constraints restrict search space Brain inspired AGI design space Brain inspired approach will reach AGI faster, if Tb/Hb > T/H
  6. 6. 山川宏 おわりにあたって 2018/10/6-8
  7. 7. Six tasks in Hackathon “Animal-AI Olympics” Kick-off meetup Point To Target Random Dot Motion Discrimination Multiple Object Tracking Visual Search Change Detection Odd One Out 7
  8. 8. Winners implemented model https://github.com/wbap/oculomotor/wiki/アーキテクチャ概要 より Template Opt. Flow Accumulator Phase Working Memory Allocentric Image Subsumption Architecture Task Saliency Map Actor-CriticReLU Retina Image Retina + Angle Reward Action “Animal-AI Olympics” Kick-off meetup8
  9. 9. Representation in the implemented system “Animal-AI Olympics” Kick-off meetup Opt. Flow 4 kind of accumulators Phase Working Memory Task Saliency Map Retina Image Template The basal ganglia selects which accumulator for use Video • Point to Target: Input • Point to Target: Inspector • All Task: Input • All Task: Inspector 9
  10. 10. Functionally General Biologically Plausible Computationally Simple GPS criteria for evaluating brain-inspired AGIs “Animal-AI Olympics” Kick-off meetup10 https://wba-initiative.org/3516/ Can the system solve various tasks? Evaluate the number of successfully executed tasks out of the presented tasks. Is the mechanism similar to that of the brain? Evaluate whether the presented design or sample code is used. Points are added for additional biological plausibility. Is the mechanism composed of reusable functional modules? Evaluate that multiple tasks are accomplished by fewer processing units.
  11. 11. The WBA (Whole Brain Architecture) Prize The WBA Prize will be awarded to the most biologically plausible entry • US$4,000 grant (from WBAI) • Up to US$1,000 travel grant to speak at NeurIPS 2019 (from the organizer) “Animal-AI Olympics” Kick-off meetup11 https://wba-initiative.org/en/3545/
  12. 12. The WBA Prize: Application The Summary You must write your team ID and the date of application. Detail how your methodology with a particular focus on the ways in which it is biologically plausible (1,000 ~ 1,500 English words.) More specifically,: • Structural correspondence between your architecture and brain architecture, if any (a block diagram would help). • Mechanisms being used that are similar to those found in the brain, • If you have modeled your solution on certain animals (including humans). • Include details about how you think your approach can help us understand biological intelligence. Source Code We appreciate code readable for the reviewers “Animal-AI Olympics” Kick-off meetup12 https://wba-initiative.org/en/3545/
  13. 13. The WBA Prize: Review Process • An independent panel of experts will be convened for review. • Biological plausibility as well as generality and the simplicity of the code will be appreciated (see the GPS criteria). • Biological plausibility will be evaluated by your summary. Generality will be evaluated from your competition record. The code will be used to evaluate the simplicity and to validate the summary. “Animal-AI Olympics” Kick-off meetup13 https://wba-initiative.org/en/3545/
  14. 14. The WBA Prize: References • Kriegeskorte, N. & Douglas, P.K. (2018) Cognitive computational neuroscience. Nature Neuroscience, 21, 1148–1160. • Hassabis, D., et al. (2017) Neuroscience-Inspired Artificial Intelligence. Neuron, 95(2), 245-258. • O’Reilly, et al. (2016) Computational Cognitive Neuroscience • WBAI: Prospect for Human-like AGI via the WBA Approach • WBAI Wiki “Animal-AI Olympics” Kick-off meetup14 https://wba-initiative.org/en/3545/
  15. 15. “Animal-AI Olympics” Kick-off meetup15 The WBA award requires an additional technical summary and code submission. However, it is a competition section that has spaces to appealing your team’s unique ideas. Please challenge by all means.

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