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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
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
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
DECENTRALIZED AI
Federated Learning
Blockchain
Homomorphic Encryption
Data Exchanges
Marketplaces
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
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
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 ?
OPENMINED
DATA EXCHANGE
• Blockchain for Data Provenance
• User Owned Data
• Time expiry for data
• Ethically Sourced Data
– Transparency
– Fairness
– Privacy
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
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
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
DEEPCLOUD AI PLATFORM
VISIT
US @
EXPO
280
www.deepcloudai.com
https://t.me/deepcloud_ai
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/
QUESTIONS?
http://bit.ly/geeta4c
geeta@deepcloudai.com
@geeta4c
https://t.me/deepcloud_ai

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Decentralized AI: Convergence of AI + Blockchain

  • 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. 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. 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. DECENTRALIZED AI Federated Learning Blockchain Homomorphic Encryption Data Exchanges Marketplaces
  • 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. 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. 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 ?
  • 9. DATA EXCHANGE • Blockchain for Data Provenance • User Owned Data • Time expiry for data • Ethically Sourced Data – Transparency – Fairness – Privacy
  • 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. 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. 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
  • 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/