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GUT-AI

Summary: Documents and meta files about the GUT-AI Initiative in general.

Table of Contents (click to open)

About

Pitch

The GUT-AI initiative is an initiative which aims to eliminate the multiple, single-points-of-failure when using AI for real-life applications in the real world in order to achive 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).

Vision

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.

Mission

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 ourselves.

Main papers

Research Proposal

Coming soon!

Whitepaper

Coming soon!

DAO Foundation

The GUT-AI Foundation has a supportive role, while acting as a catalyst in order to accelerate the GUT-AI Initiative, but without interfering with the decentralized nature of the whole initiative. In other words, the GUT-AI Foundation is merely a pure subset of the initiative.

Selected publications

Coming soon!

Real-life impact

Industries

GUT-AI has the potential to affect and transform the vast majorities of industries, including the following:

  • Aerospace
  • Agriculture and Aeroponics
  • Aquaponics and Hydroponics
  • Automotive and Self-Driving Cars
  • Biotech, Pharma and Medical Devices
  • Cloud Infrastructure and Networking
  • Cyber Security
  • E-Commerce (Wholesale and Retail)
  • Education and E-Learning
  • Energy
  • Finance
  • Food and Beverage
  • Gaming
  • Healthcare and Telemedicine
  • Hospitality
  • Insurance
  • Logistics
  • Manufacturing and Construction
  • Media and Entertainment
  • Medical Imaging
  • Real Estate
  • Retail
  • Sports
  • Security and Surveillance
  • Telecoms

Use Cases

See Use Cases.

Areas of application

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)
  • Medical Imaging
  • Multimodal Learning
  • Natural Language Processing
  • Physics (including Astrophysics, Nuclear, Particle and Quantum Physics)
  • Robotics
  • Recommender Systems
  • Sequential Data (including Time Series)
  • Speech Processing
  • Transportation

Project files

Landing page

The following is the official landing page for the whole initiative of GUT-AI:

Project page

Thanks to OSF (by the Center for Open Science), the project is temporarily hosted at:

Project DOI

Project identifier: DOI 10.17605/OSF.IO/RN2S4

Please note that the above is the DOI for the whole project, not for this GitHub repository.

List of components

See Components.

Environment simulators

See Simulators.

Datasets

See Datasets.

Model Zoos

See Model Zoos.

License

Creative Commons Zero CC0 1.0 (Public Domain)

About

Documents and meta files about GUT-AI.

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