【Blockchain EXE #10：ブロックチェーンによるモビリティの進化 - 世界トッププレイヤーが語る可能性】 Dimitri De Jonghe / Application Director at BigchainDB

1. Ocean Protocol:
Public Utility Network
For Data and AI
Dimitri De Jonghe
@DimitriDeJonghe
Head of Research - Ocean Protocol
BigchainDB, IPDB, ascribe, Interledger, Spherity

2. Centralized
Economies
from
Silo-ing
Resources
I’ll only open my
data set if I gain
insights and/or
profit from it!

3. The
tragedy of the commons
is an economic theory of a situation
within a shared-resource
system where individual users
acting independently according to
their own self-interest behave
contrary to the common
good of all users by
depleting or spoiling that
resource through their collective
action.

4. Users Applications B2C Service $$$ Services
Consumer goods
E-commerce
…
ConsequencesAppusage
Datagathering&serviceprovision
Datatrading&selling
▪ Lack of data control
and multiple versions
of “you” on different
databases
▪ No right to be
forgotten
▪ No user share in ad
revenue
Individual
How to farm Digital Me (d-Me)?

5. How online services “share” your data

6. Here’s
your
personal
data

7. Roses are red
violets are blue
with silo and moat
the service reads you
And shows you ads
for flower shops
and tracks your clicks
and never stops
It cares not that
privacy's harmed
money is green
so people are farmed
Twitter is cyan
facebook is blue
your friends are the product
and so are you.

8. Common Objectives
Incentives make people do stuff
Self-sustaining
Anti-fragile

9. Decentralized
Communities
from
Pooling
Resources

10. Blockchain Superpower:
Get people to do stuff
By rewarding with tokens

11. Bitcoin goal: maximize security of network
Token rewards if: run compute to secure network

12. Economic Incentive for Bitcoin
Objective: Maximize security of network
• Where “security” = compute power
• Therefore, super expensive to roll back changes to the transaction log
E(Ri
) α Hi
* T
E() = expected
value
# tokens (BTC)
dispensed each
block
block
rewards
hash power of actor
= contribution to
“security”

13. Bitcoin goal: maximize security of network
Token rewards if: run compute to secure network
TerraHashes / sec

14. Ethereum: The World Computer

15. “Be your own bank”
“Value store for e-gold”
“Tokenize Networks”
“An ICO launch platform”
& cryptokitties
ETH: Blockchain 2.0BTC: Blockchain 1.0

16. Public Utility Networks => Blockchain 3.0?
Public
Permissionless, rent-free
Token is the reward for good behavior > self-sustaining
Utility
The service delivered is useful work
Proof of X drives down margin cost to produce X
Network
Communities: Horizontal > vertical
Building blocks are co-owned, vision is shared

17. Decentralize the Reward Function (& Tokenize)
Proof
Stake
Reputation
Attention
...

18. Proof of ...
Resource /
Service /
Utility
Block/Client
Reward
(aka Token)
Proof / Stake
Token
Hashing Power
Transactions
Business Logic
Compute
Storage
Knowledge
Privacy
AI/ML training/testing
Existence
Identity
Burn
Roaming
Bandwidth
...
PROTOCOL

19. From Community to Utility Pooling
Prediction/Knowledge High Perf. Compute Data & IoT

20. From Community to Utility
Prediction Markets Dec. Compute Data & IoT MarketsKnowledge
Pools
Com
pute
Pools
DataPools

21. Decentralizing
Data?

22. Decentralized Me (de-Me): Personal & Private Data

23. ?DATA Blockchain
Self-sovereignty
Attribution
Commons
Data + Ownership[Blockchain] = self-sovereignty

24. But… Provenance & Attribution

25. Provenance of TITLE (IP) Provenance of COPIES

26. centralized application stack
FILE SYSTEM
e.g. S3, HDFS
APPLICATION
PROCESSING
e.g. EC2, Azure
DATABASE
e.g. MySQL, MongoDB
Bitcoin Blockchain?
PLATFORM
e.g. AWS, Google App Engine, Heroku
CONNECTNETWORKS
e.g.TCP/IP
HARDWARE

27. Towards a decentralized application stack
FILE SYSTEM
e.g. S3, HDFS
IPFS, SWARM
APPLICATION
PROCESSING
e.g. EC2, Azure, Ethereum, Hyperledger, Tendermint, Lisk, Corda
DATABASE
e.g. MySQL, MongoDB
BigchainDB, IPDB
PLATFORM
e.g. AWS, Google App Engine, Heroku, Eris/Monax, BlockApps
CONNECTNETWORKS
e.g.TCP/IP,InterledgerILP
e-Cash/e-Gold
Bitcoin, zCash, Ripple,
Blockstream, Multichain
HARDWARE
IoTA, Riddle & Code, Chronicled, Sawtooth Lake

28. Immutability
Decentralized Control
Native Assets
Scalable
Queryability
Operationalized
Traditional
Databases
Traditional
blockchains
BigchainDB
“Big Data” + “Blockchain”
- a blockchain database

29. Blockchain Consensus
Database Consensus
IMPLEMENT A 2 PHASE CONSENSUS
FEDERATION
Single Database
or
MongoDB RethinkDB
Database Options
Big Data Substrate + Federated Consensus / BFT

30. Users Applications 3th party services
Consumer goods
E-commerce
Automotive
Consequences
▪ Users and devices
control their data and
access can be
provided and revoked
▪ Only one single
version of your data
▪ Users get share of
revenue generated
from their data
Private Data
Access?
Data
…
Requestpermission
Share$$$
Bring YOUR DATA to the Service
Public Claims
Access?
Data /
Permission
@BigchainDB @GETJolocom

31. Digital Twin / Twin of Things

32. Blockchain: a trust network for supply chains
Powered by IoT
32
Recordkeeping
paper, sms, email, calls, …
Inefficiency
change records, own versions/formats, disagreements

33. 10
Tag unique
ID to asset
Info
added
to Digital
Twin
Data on Blockchain
Physical
path
of
asset
Path
of
Digital
Twin
Factory Logistics Retail Customer End of life
Info
added
to Digital
Twin
Info
added
to Digital
Twin
Set Digital
Twin
inactive
Traceability across the supply chain with Digital Twin

34. Innovation as a Luxury
34

35. DATABASE
IPDB
CLIENT SIDE APP
BROWSER/JS OR MOBILE APP
A digital twin for Cars

36. Provenance
+
Fraud detection

37. Data, AI & Tokens

38. 1 ZB1
16 ZB2
2010
2016
2025
160+ ZB2
1) Source: Apixel
2) Source: Storagenewsletter
Data is growing exponentially

39. 1 ZB1
16 ZB2
2010
2016
2025
160+ ZB2
1) Source: Apixel
2) Source: Storagenewsletter
3) McKinsey
% of data
analyzed3
But only a small amount is analyzed and shared

40. Market value of data in 2030 GDP of Germany in 2016
Up to 3.8 trn. USD1
3.5 trn. USD2
1) Source: Ocean Protocol analysis
2) Source: Worldbank
Unlocking data will open up Trillions in value

41. https://en.wikipedia.org/wiki/File:HTM_Hierarchy_example.png
Deep Learning: Neural Networks * Moore’s Law
≈1950s algorithms on 1000x+ more storage & compute

42. Deep learning
models with >> capacity
Error 5% .. 0.01%
Models with limited
capacity Error 25% .. 5%
Another 1000x more
data
Deep Learning Loves Data

43. ▪ AI needs data
▪ Without data, AI models are not
accurate
▪ 150 fundamental use cases across all
industry sectors identified
▪ AI advances 6x faster, if data is
available
AI is starving for data

44. AI Start-ups & researchers Multinationals & governments
▪ Have algorithms
▪ ...but no data
▪ Have data
▪ ...and want to monetize
Disconnection
AI and Data aren‘t connecting

45. Have lotsa data
(enterprises)
Have lotsa AI
(AI startups)$$

46. Have lotsa AI
(AI startups)
Have lotsa data
(enterprises)

47. Have lotsa AI
(AI startups)
Have lotsa data
(enterprises)
Market Market Market Market
Market Market Market Market
A new data economy

48. Have lotsa AI
(AI startups)
Have lotsa data
(enterprises)
Market Market Market Market
Market Market Market Market
Ocean Protocol
A new data economy

49. Ocean goal: maximize supply of relevant data
Token rewards if: supply data, and curate it

50. Economic Incentive for Ocean
Objective: Maximize supply of relevant data
• This means: reward curating data + making it available
• Where “curating” = betting on data. Reward taste-making.
E(Rij
) α log10(Sij
) * log10(Dj
) * T *Ri
Expected
reward for
user i on
dataset j
Dj
= proofed
popularity
= # times made
dataset available
Sij
= predicted
popularity = user’s
curation market stake
in dataset j
# tokens
during
interval

51. From AI data to AI services
Motivations:
•Privacy, so compute on-premise or decentralized
•Data is heavy, so compute on-premise
•Link in emerging decentralized AI compute
Objective function: Maximize supply of relevant services
=reward curating services + proving that it was delivered
E(Rij
) α log10(Sij
) * log10(Dj
) * T *Ri
proofed popularity
of service
predicted popularity
of service

52. Ocean Protocol
Public Service Network
Ingestion
Service
Processing
Service
Storage
Service
Enterprise
Service
Discovery
Service
Ecosystem
Service
Privacy
Service
Compute
Service

53. Ocean is a network of curated services. An AI services hub.
Availability Consumption Privacy GovernanceProduction
commons
Inter-
OperabilityDiscovery
*Note: logos shown are examples and do not imply partnerships or integrations

54. Client
contracts
metadata
block N-3
proofs
accounts
Client Service
API
Keepers
Node
N2
N4
VerifierService
API
Service
API
Proof
ask
bid
access
authorize
verify
access
challenge
1. Contract setup 2. Access Control 3. Verification
verify
proof
CONTRACT 0x12345...
Lock: Consumer.fee
Execute: Proof.valid
Abort: Timeout
response
contracts
metadata
block N-2
proofs
accounts
contracts
metadata
block N-1
proofs
accounts
contracts
metadata
block N
proofs
accounts

55. Service Integrity: Crypto-Proofs of Service

56. CONTRACT 0x12345...
Lock: Consumer.fee
Execute: Proof.valid
Abort: Timeout
Data Source:
● Tokenized access control
● Curated
Decentralized Model
● Community owned
● Benefits for the commons
Service
(Data + Proof)
Reward
(Token)

57. CONTRACT
Lock
Execute
Abort
CONTRACT
Lock
Execute
Abort
Data Service:
● Royalty Attribution
● Contract-driven supply chain
● Algorithms, labels,
visualizations, ...
% Royalty Reward
(Token)
Reward
(Token)

58. CONTRACT
Lock
Execute
Abort
CONTRACT
Lock
Execute
Abort
CONTRACT
Lock
Execute
Abort
CONTRACT
Lock
Execute
Abort
CONTRACT
Lock
Execute
Abort
CONTRACT
Lock
Execute
Abort
CONTRACT
Lock
Execute
Abort
CONTRACT
Lock
Execute
Abort
CONTRACT
Lock
Execute
Abort
CONTRACT
Lock
Execute
Abort
Autonomous Driving
Smart Logistics
Industry 4.0
Personalized Health
Environmental Monitor

59. Prototypes

61. Sandbox with Singapore Data Authority

62. What unlocking AI
data & services
unlocks

63. Self-driving cars: fewer accidents, more mobility

64. >100x more data for health
care research

65. Erode the data silos

66. Erode the data silos

67. Erode the data silos

68. Conclusion

69. AI data is siloed.
AI services are siloed.
Let’s change the rules of the game with
incentives.
Let’s democratize access to AI data & services!
Dimitri De Jonghe
@DimitriDeJonghe

70. Dimitri De Jonghe
dimi@oceanprotocol.com
@DimitriDeJonghe
Project contributions:
oceanprotocol.com
bigchaindb.com
ipdb.foundation
interledger.org
ascribe.io
Thanks for listening
interledger