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Venture capital for the decentralised future
We invest and partner with tokenised
communities that are creating the
new decentralised economy.
H₂O bridges Haja Networks and Ocean Protocol.
The P2P distributed database
● Created by Haja Networks.
● Runs on IPFS (already live).
● Highly user-friendly JavaScript
implementation.
● Core functions: create, load,
put/get, listen for event.
Ocean components used by H₂O
Squid-Py
Python client
library for
interacting with
the Ocean stack.
Keeper
Smart contracts
implementing
TCRs, CPMs and
the Ocean
token.
Aquarius
Metadata store
for published
assets.
Docker Images
Docker images
for quickly
spinning up
Ocean
components and
getting used to
the Ocean stack.
Use case: optimal car deployment for a
decentralised ride sharing fleet
Unprocessed data
Uber pickup location
data for New York.
Data stored and
managed using
OrbitDB.
Machine learning
Specify the number of
cars owned in the app.
H₂O performs k-means
clustering to optimise
distance to pickups.
Processed data
Optimal deployment
locations for the fleet.
The data can be
published, available to
buy on the Ocean
Protocol data market.
Source: Andrey A. Shabalin
H₂O’s utility to the AI community
● H₂O seeds Ocean Protocol’s global
marketplace with datasets.
● Organisations without access to
powerful hardware can find the
datasets they need clustered
available for purchase instead.
● The app allows organisations with
powerful hardware to monetise it
by clustering popular datasets.
● H₂O also serves as a framework for
decentralised ML apps.
h2o.outlierventures.io
More info
Documentation
Getting the code
Live version
theo@outlierventures.io

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H2O Machine Learning with OrbitBD and Ocean Protocol

  • 1.
  • 2. Venture capital for the decentralised future We invest and partner with tokenised communities that are creating the new decentralised economy.
  • 3.
  • 4. H₂O bridges Haja Networks and Ocean Protocol.
  • 5. The P2P distributed database ● Created by Haja Networks. ● Runs on IPFS (already live). ● Highly user-friendly JavaScript implementation. ● Core functions: create, load, put/get, listen for event.
  • 6.
  • 7. Ocean components used by H₂O Squid-Py Python client library for interacting with the Ocean stack. Keeper Smart contracts implementing TCRs, CPMs and the Ocean token. Aquarius Metadata store for published assets. Docker Images Docker images for quickly spinning up Ocean components and getting used to the Ocean stack.
  • 8. Use case: optimal car deployment for a decentralised ride sharing fleet Unprocessed data Uber pickup location data for New York. Data stored and managed using OrbitDB. Machine learning Specify the number of cars owned in the app. H₂O performs k-means clustering to optimise distance to pickups. Processed data Optimal deployment locations for the fleet. The data can be published, available to buy on the Ocean Protocol data market.
  • 9.
  • 10. Source: Andrey A. Shabalin
  • 11. H₂O’s utility to the AI community ● H₂O seeds Ocean Protocol’s global marketplace with datasets. ● Organisations without access to powerful hardware can find the datasets they need clustered available for purchase instead. ● The app allows organisations with powerful hardware to monetise it by clustering popular datasets. ● H₂O also serves as a framework for decentralised ML apps.
  • 12. h2o.outlierventures.io More info Documentation Getting the code Live version theo@outlierventures.io