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Description
Bittensor is a decentralized, open-source protocol that enables a blockchain-powered network for machine learning. In this system, machine learning models collaborate in their training and earn TAO tokens based on the value of the information they contribute to the collective. Additionally, TAO facilitates external access, empowering users to retrieve data from the network while customizing its operations to suit their requirements. Our overarching goal is to establish a genuine marketplace for artificial intelligence, a space where both consumers and producers of this critical resource can engage within a framework characterized by trustlessness, openness, and transparency. This approach introduces a fresh, optimized methodology for the creation and dissemination of artificial intelligence technologies, taking full advantage of the distributed ledger's capabilities. In particular, it encourages open access and ownership, promotes decentralized governance, and allows for the effective utilization of globally-distributed computing power and innovative resources within a motivating and rewarding environment. As we continue to evolve, we aspire to foster a vibrant ecosystem that thrives on collaboration and shared success in the realm of AI.
Description
There is a notable absence of a decentralized graph representing canonical knowledge that is accessible, unrestricted, and encourages contributors to input data into the graph. We aim to establish a protocol that accurately represents the 10 billion entities that exist and the collective public knowledge related to them. Triples—commonly referred to as fact triples or SPO triples—serve as the fundamental components of facts, connecting entities to create a cohesive graph. These triples function as the foundational elements that construct the expanse of knowledge we recognize today. The protocol is designed to accommodate a diverse range of triple types, qualifiers, and supporting evidence. This triple graph can be utilized to enhance decentralized applications (Dapps) and services that depend on essential knowledge. Contributors have the opportunity to submit triples for validation, and if their submissions are approved, they will earn tokens as a reward. The acceptance of triples is determined by validators and predictions made by the knowledge graph itself, ensuring a robust quality control mechanism. Ultimately, the protocol not only incentivizes the creation of the knowledge graph but also incorporates safeguards against exploitative behaviors, promoting a sustainable and reliable knowledge ecosystem. This initiative represents a significant step toward democratizing access to knowledge on a grand scale.
API Access
Has API
API Access
Has API
Integrations
Brave Browser
Coinbase
WalletConnect
Pricing Details
Free
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Bittensor
Website
docs.bittensor.com
Vendor Details
Company Name
Golden
Website
golden.xyz/
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Product Features
Knowledge Management
Artificial Intelligence (AI)
Cataloging / Categorization
Collaboration
Content Management
Decision Tree
Discussion Boards
Full Text Search
Knowledge Base Management
Self Service Portal