This document discusses the convergence of blockchain and AI through decentralized AI approaches. It outlines challenges with centralized AI models regarding privacy, influence, economics and transparency. Decentralized solutions proposed include federated learning, blockchain, homomorphic encryption, and data marketplaces. Blockchain provides an open, trustless network to replace centralized authorities and enable applications like data exchanges, AI marketplaces and distributed machine learning across devices. Overall the goal is to democratize AI and data through user ownership and control.

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 D E E P C L O U DA I

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?

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

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
Source: Economist.com

7. FULLY DEMOCRATIZE INTERNET
Source: Tribune.com, Design: Sunara Nizami
Information Age ➔ Internet of Value
Commerce
Assets
Data
Organizations

8. 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. OPENMINED

10. DATA EXCHANGE
• Blockchain for Data Provenance
• User Owned Data
• Time expiry for data
• Ethically Sourced Data
– Transparency
– Fairness
– Privacy

11. 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

12. 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

13. Democratizing cloud computing
for cloud resource providers
and application developers

14. DEEPCLOUD AI PLATFORM

15. REFERENCES
• Google Research: Federated Learning:
https://research.googleblog.com/2017/04/federated-
learning-collaborative.html
• 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