Trace Labs joins NVIDIA Inception program to collaborate on promoting Decentralization AI knowledge graph.

Psychologist Jung proposed the concept of the collective unconscious in psychology, and his theoretical foundation and school are based on this structure. Jung believes that there is a collective unconscious at the bottom of human society, which is shared by all humans. The collective unconscious does not come directly from individual experiences, but from human genetic inheritance and the common consciousness and prototypes created by the past collective. These collective consciousnesses can influence the future development of individuals and groups, but they can also be distorted and transmitted, allowing errors to be repeated, affecting knowledge transmission and hindering the development of civilized society.

This can explain the importance of decentralized knowledge graph (DKG for short) in verifying the source, copyright, and integrity value of data through blockchain.

The development of AI in various fields is booming, but there are still many flaws that seriously affect the future development of artificial intelligence in various fields. In order to prepare the generative AI to cope with large-scale social changes, it is necessary to limit the illusions, biases, and misjudgments of artificial intelligence, and eliminate infringement of intellectual property rights.

Decentralized AI knowledge graph provides information sources and ensures the verifiability of presented information, while respecting data ownership and sources, to address the deficiencies in AI.

OriginTrail's development team Trace Labs has joined the NVIDIA Inception program, hoping to achieve a decentralized knowledge graph (DKG) to create a verifiable Internet of artificial intelligence networks.

Trace Labs has implemented decentralized artificial intelligence knowledge graphs in supply chain, healthcare, construction, sports, aviation, and other fields. The collaboration with Nvidia can further perfect the combination of blockchain and artificial intelligence.

How Trace Labs and Nvidia build a decentralized AI knowledge graph

Origin Trail will collaborate with NVIDIA to build a decentralized AI knowledge graph by integrating its in-house developed Decentralized Knowledge Graph (DKG) with NVIDIA's AI generation.

Retrieval Augmented Generation (RAG) is an information retrieval generation mechanism that enhances and expands the generation of text, providing verifiable and reliable sources of knowledge information. RAG is a technology that allows machine learning models to extract relevant information from external databases before generating output, in order to improve the accuracy of answers and the relevance of context.

Decentralized RAG (dRAG) is an advanced version of RAG, allowing data to exist in the form of Knowledge Assets through OriginTrail's decentralized knowledge graph, with each asset having its specific identification and ownership, ensuring the traceability, integrity, and ownership of the data, significantly enhancing the accuracy and reliability of the GenAI model.

dRAG improves the RAG system by using a decentralized knowledge graph (DKG). Each knowledge asset includes graph data and vector embeddings, invariance proofs, decentralized identifiers (DID), and ownership NFTs. When connected to a permissionless DKG, the structure in the knowledge graph is enabled, allowing the combination of neural networks and symbols with artificial intelligence to enhance the model of AI generation through accurate inputs.

Knowledge asset owners can manage access to data in the knowledge asset pool, and each piece of knowledge information on DKG is accompanied by an encrypted certificate, ensuring that no tampering has occurred since publication with the verifiable and tamper-proof features brought by blockchain.

Development plan of NVIDIA Inception and Trace Labs

Nvidia and Trace Labs collaborate to develop a decentralized AI knowledge graph, providing VC investment opportunities. The Inception program also includes joining the NVIDIA Deep Learning Institute and NVIDIA Developer Forum, enabling Trace Labs to work with NVIDIA to promote the construction of a decentralized artificial intelligence ecosystem.

If human society has a collective unconscious, then artificial intelligence also has the collective unconscious of AI, which can redefine the changes that artificial intelligence can bring to human society.

The application scenario of decentralized artificial intelligence knowledge graph is AI agent, which uses the collective consciousness of the network on a large scale to obtain knowledge from a shared but sovereign knowledge base, meaning that artificial intelligence can provide coherent and accurate interactive integration with context without compromising the privacy and integrity of data, allowing each profession to establish a trustworthy AI agent ecosystem.

Decentralized AI knowledge graph utilizes Nvidia's supercomputers to process billions of knowledge assets, laying the foundation for decentralized science.

This article appeared first on Chain News ABMedia, which reports that Trace Labs has joined the NVIDIA Inception program to collaborate on promoting decentralized AI knowledge graphs.