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Summary: Documentation, content and meta files about GUT-AI Initiative in general. This repository is common point of reference for everyone looking to learn about our worldwide, permissionless, decentralized Initiative.
| For Developers | For Reserchers | For Investors |
|---|---|---|
| DAO Foundation | The Problem | Pitch |
| Components | Research Proposal | Whitepaper |
| Software tools | Datasets | FAQ |
Table of Contents
GUT-AI Initiative is a totally decentralized initiative, which aims to eliminate the multiple single points of failure when using AI for practical applications in the real world in order to achieve the ultimate purpose of both ‘narrow AI’ and ‘strong AI’, which is to actually "open" the "black box" of an ML system in order to eventually unlock the mysteries of nature and the universe (from Brain Consciousness and Abiogenesis to Quantum Gravity and Genesis Cosmology ). For instance, does evolution or the universe have a conscious or intelligent “geist” (spirit), as Max Planck once claimed?
We believe that there should be no organization or person in our world who wants to use AI, but not be able to do so. We also believe in a world where AI hand-in-hand with human interaction are in an ever-improving situation.
We are on a mission to create the most user-friendly Open-Data, Open-Source, Decentralized ecosystem for AI using cutting-edge technology, either of the 21st century or that we might invent by ourselves.
Read a brief Summary of the Whitepaper.
- Kourouklides, I. (2022). Bayesian Deep Multi-Agent Multimodal Reinforcement Learning for Embedded Systems in Games, Natural Language Processing and Robotics. OSF Preprints. https://doi.org/10.31219/osf.io/sjrkh
- Kourouklides, I., & Alexandrou, K. (2023). An Overview of GUT-AI Foundation: Vision for an Ecosystem of Concepts and Implementations. OSF Preprints. https://doi.org/10.31219/osf.io/bxw4h
A picture is worth a thousand words. You can see the picture below and draw your own conclusions.
- Can AI understand humour? No.
- Should AI understand humour? Yes.
- How do we get there?
(Image credits: Anonymous online user)
The purpose of GUT-AI Foundation is to have a supportive role, while acting as a catalyst in order to accelerate GUT-AI Initiative, but without interfering with the decentralized nature of the whole initiative. In other words, GUT-AI Foundation is merely a pure subset of GUT-AI Initiative. The Foundation is currently in the process of becoming a Decentralized Autonomous Organization (DAO).
See FAQ for more details about the relationship of the Initiative and the Foundation.
GUT-AI has the potential to affect and transform the vast majorities of industries, including the following:
- Aerospace & Geospatial Technologies
- Agriculture and Aeroponics
- Aquaponics and Hydroponics
- Augmented and Mixed Reality
- Automotive and Self-Driving Cars
- Biotech, Pharma and Medical Devices
- Blockchain
- Cloud Infrastructure and Networking
- Cybersecurity
- E-Commerce (Wholesale and Retail)
- Education and E-Learning
- Energy
- Financial Services
- Food and Beverage
- Gaming
- Healthcare and Telemedicine
- Hospitality
- Insurance
- Logistics
- Manufacturing and Construction
- Marketing and Advertising
- Media and Entertainment
- Medical Imaging
- Real Estate
- Retail
- Security and Surveillance
- Smart Cities
- Sports
- Telecoms
- Water Supply and Sanitation
See Use Cases.
Depending on the modality (or modalities) of the data used, GUT-AI has applications in countless domains, including the following:
- Bioinformatics
- Compressed Sensing
- Computational Finance
- Computer Vision
- Control
- Energy
- Environmetrics
- Geospatial Data (including LiDAR, Hyperspectral images and GIS)
- Information Retrieval
- Medical Imaging
- Multimodal Learning
- Natural Language Processing
- Physics (including Astrophysics, Nuclear, Particle and Quantum Physics)
- Robotics
- Recommender Engines
- Sequential Data (including Time Series)
- Speech Processing
- Transportation
The following is the official landing page of GUT-AI Foundation:
Thanks to OSF (by the Center for Open Science), the Initiative is temporarily hosted at:
Initiative identifier: https://doi.org/10.17605/OSF.IO/RN2S4
Please note that the above is the DOI for the whole initiative, not for this GitHub repository. For the identifiers of each specific component, check identifiers. See also how to cite this.
Currently, there are countless centralized “solutions” in the cyberspace, but with the following problems and challenges:
- no interoperability
- limited communication
- inefficient processes
- multiple single points of failure
- bureaucratic hegemony
- censorship
- no privacy
- no transparency
- no customization
- security vulnerabilities
See Components for a list of subprojects.
See Roadmap.
See Simulators.
See Datasets.
See Model Zoo.
See Software tools.
See FAQ.
EVERY contributor is welcome!
- Join our Community Discord for collaboration and discussion.
- Join our governance wiki to share your knowledge.
- Check other ways to contribute.
- If you have any suggestions or feedback, please feel free to open an issue or submit a pull request.
If you want to do so, feel free to cite GUT-AI in your publications:
@article{kourouklides2022gut_ai,
author = {Ioannis Kourouklides},
journal = {OSF Preprints},
title = {Bayesian Deep Multi-Agent Multimodal Reinforcement Learning for Embedded Systems in Games, Natural Language Processing and Robotics},
year = {2022},
doi = {10.17605/osf.io/sjrkh},
license = {Creative Commons Zero CC0 1.0 Universal}
}
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