Learn how Ocean Protocol can be used to further scientific research. A presentation by Ocean's Lead Data Scientist Marcus Jones at Blockchain for Science Conference in Berlin on November 3, 2019.
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Beyond Online PDFs
1. Ocean Protocol
Beyond online PDFs
Marcus Jones
Monday November 3rd, 2019
Blockchain for Science @ Beta Haus, Berlin
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2. Overview
- Motivation: The Data Economy => The AI Economy
- Ocean Protocol Overview
- Marketplace
- Data Science
- Static assets in Ocean
- Generalized assets = Services
- No Data Escape / Federated Learning / Compute to Data
- Beyond PDFs
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3. Motivation - What is the Data Economy?
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The Data Economy measures the overall impacts of the data market on the economy as a whole. It involves the following list
of data enabled by digital technologies. The data economy also includes the direct, indirect, and induced effects of the data
market on the economy.
* Source: A study commissioned by the EU
https://ec.europa.eu/newsroom/dae/document.cfm?doc_id=444
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The value of the data economy in 2016 was worth nearly 2% (330
Billion Euros) of the European GDP. BY 2020, this will rise to 729 Bn ->
Globally many Trillion EUR.
● Data Generation
● Data Collection
● Data Storage
● Data Processing
● Data Distribution
● Data Analysis
● Data Exploitation
4. Incentive to hoard and silo data
“It is not who has the best
algorithm that wins. It’s who
has the most data.”
- Banko, M., & Brill, E. (2001). Scaling to very very large corpora for
natural language disambiguation.
https://doi.org/10.3115/1073012.1073017
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5. Banko + Brill proven by Deep Learning
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Grace, K., Salvatier, J., Dafoe, A., Zhang, B., & Evans, O. (2018). Viewpoint:
When will ai exceed human performance? Evidence from ai experts.
Journal of Artificial Intelligence Research.
https://doi.org/10.1613/jair.1.11222
6. Unlocking the data economy: Data Orchestration
The end-to-end automation of data-driven processes, raw data -> value
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- data fragmentation
- confusing provenance
- organizational silos
- complicated technology integrations
______________________
loss of potential value
7. Unlocking the data economy: AI Orchestration
Challenges in AI-driven processes
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- data fragmentation
- even more confusing provenance
- organizational silos
- complicated technology integrations
- code authorship
- training history
- productionisation
- logging
______________________
loss of potential value!
26. The generalized AI asset (it’s a service)
SSH access to my GPU @ 2k
OCEAN / hr
27. The generalized AI asset (it’s a service)
SSH access to my GPU @ 2k
OCEAN / hr
Calculate the deforestedareas in uploaded image @10 OCEAN / image
28. The generalized AI asset (it’s a service)
SSH access to my GPU @ 2k
OCEAN / hr
Calculate the deforestedareas in uploaded image @10 OCEAN / image
Download the stream of IOT
data @ 50 OCEAN / hr
29. The generalized AI asset (it’s a service)
SSH access to my GPU @ 2k
OCEAN / hr
Calculate the deforestedareas in uploaded image @10 OCEAN / image
Download the stream of IOT
data @ 50 OCEAN / hr
Train a federated model on
our genetic data @ 500
OCEAN / 1%-increase
30. Research topics: Ownership of AI Assets
- Tied to identity
- Ownership loss through escape of
– Data
– AI Model
– ?
- Shared ownership?
- Delegated rights?
31. Research topics: Pricing of Digital Assets
- Fixed price
– Conditional
– Prorated over time, accuracy, etc.
- Negotiated
- Bonding-curve based
- Bounties/contests
(See “Data Pricing” blog series series)
https://blog.oceanprotocol.com/tagged/bonding-curves
https://blog.oceanprotocol.com/lets-talk-about-
data-pricing-part-i-bbc9cf781d9f
33. protocol with incentives
Bring model to the data
f(x)
private
data
modeling
pipeline
privately
train model
private
model
model
predictions
Data stays
behind
firewall
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35. Compute to data modes
- On premise compute
… third party premise compute
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36. Compute to data modes
- On premise compute
… third party premise compute
… federated learning
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37. Compute to data modes
- On premise compute
... third party premise compute
… federated learning
… homomorphic encryption
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38. Compute to data modes
- On premise compute
… third party premise compute
… federated learning
… homomorphic encryption
… production model as an AI Asset
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39. Federated / On-line / Incremental learning
Horizontal : Same feature
space
Vertical : Same ID space
Transfer : Different feature
and ID space
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43. Orchestration of Research Ecosystem
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100 OCEAN / Hour
594 Upvotes
Complete version
history
Delegated partial
payments
Dataset never leaves
premise,
compute-to-data
47. The road ahead (Ocean Protocol)
Unlock data
1) Allow and incentivize discovery and
access to data
2) Broaden the scope to allow composite
general assets
3) Build compute-to-data
Build a permissionless ecosystem
4) Expand incentivization mechanisms
5) Fully permissionless and ownerless
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Research and Experiment
Provenance
Curation
Bonding curves
Federated learning
Identity
Shared ownership
Delegated ownership
Non-fungible tokens