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

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 ?

8. OPENMINED

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

13. DEEPCLOUD AI PLATFORM

14. VISIT
US @
EXPO
280
www.deepcloudai.com
https://t.me/deepcloud_ai

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. QUESTIONS?
http://bit.ly/geeta4c
geeta@deepcloudai.com
@geeta4c
https://t.me/deepcloud_ai