ITRMachines | OceanAI-py library implementation | Round 19

Project Name

ITRMachines


Project Category

Build & Integrate


Proposal Earmark

General


Proposal Description

Our software solution will allow AI developers to quickly access datasets from the Ocean marketplace and integrate them using Tensorflow (Python) to implement their custom AI models in a seamless way. Given the increasing demand for data and AI, our solution will increase the exposure of Ocean and will increase the network revenue by attracting multiple new users to the marketplace. For this particular integration we will use the Ocean.py library.


Grant Deliverables

  • Development of a wrapper library that will: integrate the current functionalities of the Ocean.py library (publishing datasets and selling data over the blockchain, token acquisition -value swap- , dataset downloading, etc…), provide several useful data transformation methods and provide a seamless funneling process for integrating that data with artificial intelligence computational models built using Tensorflow.
  • Development of the technical documentation of the library.
  • Inclusion of an Ocean Protocol section in our webpage that will promote Ocean protocol and Ocean AI toolkit (Oceanai.js, OceanAI.py)
  • 2 LinkedIn posts announcing the deployment of OceanAI.py and the status of Oceanai.js project. Linking the posts to the Ocean Marketplace.
  • One (1) virtual workshop via Zoom for developers introducing the toolkit ecosystem (Oceanai.js, OceanAI.py), the details of the workshop and the registration form will be shared in OceanProtocol discord server and ITRMachines LinkedIn.


Project Description

Development of a wrapper library that will allow a direct integration between the Ocean marketplace and the tensorflow.js library for artificial intelligence.


Final Product

not set


Value Add Criteria

How does the project and proposal add value to Ocean ecosystem?


This proposal will add a new integration channel between AI developers and Ocean protocol developers allowing a broader consumption of Ocean protocol resources and datasets.


A broader consumption also means that there will be more recognition of the Ocean protocol and its ecosystem as a platform for the development of data science, AI and DeFi projects.


Usage of Ocean — how well might the project drive usage of Ocean?


The Ocean ecosystem will benefit from this project by the raw amount of AI developers and data scientists from the Python ecosystem (17,579,395 for Tensorflow last month) that could be onboarded to the protocol. If only 0.1% of those users get interested in the Ocean platform that would mean an influx of 17000 (just using Tensorflow library as base line) new users each month.



Viability — what is the chance of success of the project?


ITRM is an established AI and big data company that has successfully provided FinTech solutions to multiple big institutional players in the past. Our AI driven algorithms have managed around 180 million USD through the prop trade desk of one of the major Colombian brokerage institutions. This goes in line with the deployment of multiple best execution and AI algos focused on capital markets for different international brokers, including crypto exchanges.


ITRM has been recognised and funded by the Colombian Government accelerator, Aldea-INNPULSA and was showcased as one of the most scalable and innovative ventures in the region. Regarding the DeFi space, the algorithms developed by ITRM together with the MetaGameHub DAO have generated over 25.000 API requests for NFT valuations showing the high demand for the solutions being developed.


ITRM also has succesfully created an initial version of this proposal in the round 13th with the deployment of OceanAI.js


Community Engagement — How active is the team in the community?



-Our data and AI team are closely following the weekly town halls and slide decks to keep updated with the progress of the tech working group.


-Our CTO (Discord Handle: Sat0#5947) is in contact with core developers and administrators regarding the fulfilment and the roadmap of past proposals: https://port.oceanprotocol.com/t/itrmachines-ocean-marketplace-tensorflow-js-integration/1274/13



Community Value — How does the project add value to the overall Ocean Community / Ecosystem?


As explained before; this proposal aims to the expansion of core tech capabilities of Ocean protocol such as the integration with AI and data science libraries with the added value of expanding the community in an overall sense, that means base users, datasets consumers and a renewed project pool for Ocean protocol.


Funding Requested
9000


Minimum Funding Requested
7000


Wallet Address
0xb74e2ad2a794caeeb32b4bfcae64088a591b1216


Hi,

Thank you for applying for R19!

Your proposal has been registered into the system and everything looks great!

Your previous Grant Deliverables have been reviewed and look to be in good condition. I have also looked at your Project Standing, it looks to be in good condition and ready to apply for another grant.

I would also recommend one (or all) of the following to increase support:

  1. Saying hi to the community in #ocean-dao and sharing your proposal.
  2. Saying hi to members of the #project-guiding WG and sharing your proposal.
  3. Meet with the Guides assigned to you by the #project-guiding WG.
  4. Attend a Town Hall or Project-Guiding WG meeting to talk about your project and proposal.

All the best!

-Your PGWG guide Christian Casazza

I applaud your efforts to help make Ocean more accessible to data scientists!

For reference, here are previous proposals and results.

oceanai-js looks good, congrats! And I see a few hundred downloads.

And, congrats on winning in R19!

This proposal also aims to onboard data scientists. References to key features in ocean:

  • all of ocean.py. As its name implies, it’s written in python. It’s tuned for AI/ML/data science folks. It can be used side-by-side with any AI/ML libraries, from TensorFlow to scikit-learn
  • ocean.py’s C2D README show how to build an AI model using C2D, via scikit-learn’s implementation of Gaussian Process Models.
  • Many examples by Algovera

A python library tuned for just TensorFlow with Ocean could be interesting, and I guess that’s the aim of this grant. Calling it “oceanai.py” feels like a stretch, since to live up to a more general AI setting it would have to support more AI libraries. At which point, why not just (a) do some PRs into ocean.py to make your target AI flows easier via ocean.py, and (b) add new README for C2D with TensorFlow?

Thanks again for your efforts to help make Ocean more accessible to data scientists:)

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