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Decentralized AI: Convergence of AI + Blockchain

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Santa Clara IoT Expo talk slides - convering convergence of of AI and Blockchain and how it solves challenges for IoT, Ai@Edge and Data Ethics and User Data Monetization

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Decentralized AI: Convergence of AI + Blockchain

  1. 1. D E C E N T R A L I Z E D A I : C O N V E R G E N C E O F B L O C K C H A I N + A I G E E TA C H A U H A N , C TO
  2. 2. C E N T R A L I Z E D A I I S L I K E T H E C L O S E D S O U R C E O F T H E 1 9 9 0 S
  3. 3. CHALLENGES? Privacy Problem Can entities train model without disclosing data? Influence problem Can 3rd parties contribute towards behavior of AI model in a way that is quantifiably influential? Economic Problem Can 3rd parties be correctly incentivized to contribute to knowledge & quality of AI models? Transparency Problem Can the activity of behaviour of AI model be transparently available to all parties without a trusting middleman? Latency Problem Centralized AI is inappropriate for use-cases where AI needs to interact in real time with the real world
  4. 4. DECENTRALIZED AI Federated Learning Blockchain Homomorphic Encryption Data Exchanges Marketplaces
  5. 5. FEDERATED AI • Subset of devices selected, each downloads the model • Train model with local data • Model updates – gradients – sent back to server • Server aggregates • Cancer treatment centers training models
  6. 6. WHAT IS BLOCKCHAIN? • An Immutable record of digital events shared peer to peer between different parties • Distributed Ledger • Open +Trust + Secure • Replaces MIDDLEMAN • Smart Contracts → DApps, DAOs • Fully Democratize Internet Information Age → Internet ofValue Source: Economist.com
  7. 7. W H A T I S H O M O M O R P H I C E N C R Y P T I O N ?
  8. 8. OPENMINED
  9. 9. DATA EXCHANGE • Blockchain for Data Provenance • User Owned Data • Time expiry for data • Ethically Sourced Data – Transparency – Fairness – Privacy
  10. 10. AI MARKETPLACE • Data Competition each week • Encrypted data released • Crowdsource Data Science Model • Data Scientists retain IP – encrypted models • Participants paid in Bitcoin based on accuracy of their guesses, payouts to top 60 • Originality paid extra
  11. 11. OTHER PLAYERS SingularityNET Smart Contracts for Decentralized AI Microservices Ocean Protocol Ecosystem for Sharing Data and Services Effect.AI Decentralized Mturk, Human in the loop AI Distributed ML Blockchain agnostic Runtime to run ML models across devices
  12. 12. LATENCY CHALLENGE • Slow Inference problem • Real-time scenarios • AI needs to interact in real-time with real-world • Need compute on / close to edge devices Democratizing cloud computing for cloud resource providers and application developers
  13. 13. DEEPCLOUD AI PLATFORM
  14. 14. VISIT US @ EXPO 280 www.deepcloudai.com https://t.me/deepcloud_ai
  15. 15. REFERENCES • Google Research: Federated Learning: https://arxiv.org/abs/1610.05492 • Homomorphic Encryption: https://en.wikipedia.org/wiki/Homomorphic_encryption • Openmined https://www.openmined.org/ • Numer.ai https://numer.ai/ • SingularityNET https://singularitynet.io/ • Ocean Protocol https://oceanprotocol.com/ • Effect.AI http://effect.ai/ • DML https://decentralizedml.com/ • DeepCloud AI https://www.deepcloudai.com/
  16. 16. QUESTIONS? http://bit.ly/geeta4c geeta@deepcloudai.com @geeta4c https://t.me/deepcloud_ai

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