GateLive AMA Recap-OriginTrail

Q1: What is OriginTrail?

OriginTrail is an eco building a Verifiable Internet for AI, providing an inclusive framework that tackles the world’s challenges in the AI era, such as hallucinations, bias, and model collapse, by ensuring the provenance and verifiability of data used by AI s. OriginTrail is used by global leaders like the British Standards Institution, Swiss Federal Railways, Supplier Compliance Audit Network (SCAN), representing over 40% of US imports and several consortia funded by the European Union among others. Advised by Turing award winner Dr. Bob Metcalfe, renowned for his law of network effects, the Trace Labs team (OriginTrail core developers) plays a crucial role in promoting a more inclusive, transparent, and decentralized AI.

Q2: What are real-world use cases of OriginTrail?

Initially adopted in global supply chains to provide a trusted data sharing hub, OriginTrail’s technology is increasingly vital across various sectors, including asset tokenization, construction, healthcare, the metaverse, and more due to its ability to authenticate and secure information.

(1)In the supply chain sector, BSI and SCAN are utilizing the OriginTraill to ensure the integrity of security audits for some of the largest US importers.

(2)BSI is also leveraging OriginTrail technology to facilitate the Flow of goods across UK borders.

(3)Swiss Federal Railways is utilizing OriginTrail to ensure the safety of train travel by tracking every piece of rail track material.

(4)In healthcare, OriginTrail is used to ensure that donated medicines reach the intended patients, even in complex environments.

(5)In construction OriginTrail technology is used to build a trusted knowledge base aiming to improve efficiency, reduce errors, and increase transparency and trust, ultimately leading to more sustainable construction projects.

(6)In metaverse, OriginTrail is integrated with Traverse, a story-telling project that uses Graph NFTs to offer an unparalleled, immersive storytelling experience.

Q3: Latest innovations in AI space?

The Trace Labs team (OriginTrail core developers) introduced ChatDKG, a truly open Artificial Intelligence, that drives synergies across the AI solution landscape to tackle hallucinations, bias, and model collapse as there should be no compromise in designing AI solutions when it comes to data ownership, information provenance, verifiability of information, or bias that would include any censorship-by-design approach. The risk of this revolution not unfolding in an inclusive way is a societal threat of establishing a monopoly on AI.

The team therefore introduced an effective way of establishing a new paradigm, using a Decentralized Retri-Augmented Generation (dRAG) framework. dRAG advances the RAG model by organizing external sources in a Decentralized Knowledge Graph (DKG) while introducing incentives to grow a global, crowdsourced network of knowledge made available for AI models to use. The dRAG framework enables a hybrid, decentralized AI that brings together neural (e.g. LLMs) and symbolic AI (e.g. Knowledge Graph) methodologies.

Contrary to using a solely probabilistic neural AI approach, the symbolic AI approach enhances it with the strength of Knowledge Graphs, introducing a more deterministic component. To harness a harmonious development between Web3 fundamentals and rapidly deployed AI s, the approach is to integrate the core Web3 technologies such as the OriginTrail Decentralized Knowledge Graph (DKG) and AI s (OpenAI, Gemini, Microsoft Co-pilot, xAI’s Grok, and others). We can realize the potential of trusted AI by creating a Verifiable Internet for AI that is founded on principles of neutrality, inclusiveness, and usability, while giving users freedom of choice with a multi-modal and a multi-model AI framework.

Q4: Possible integrations with ChatDKG?

The globally most adopted and centralized AI solutions like Google Gemini, OpenAI, xAI, Perplexity deliver an immense value for a spectrum of use cases. Leveraging Origin Trails dRAG — brand name ChatDKG.ai, they can improve their shortfalls by harnessing the synergy of neuro-symbolic AI, data ownership, and better cost performance. Therefore, ChatDKG.ai is not competing against any established AI solutions, but rather empowers users to enhance them with its dRAG, driving knowledge verifiability, cost effectiveness, users’ sovereignty in owning their data and freedom of AI model choice.

The open source and permissionless nature of the OriginTrail DKG, allows for inclusiveness and neutrality, giving users a tremendous level of freedom on all layers — to choose AI models enabled by DKG data portability, choose knowledge sources discoverable in DKG, as well as pick AI services, centralized or decentralized on different blockchains.

The same principles apply to AI agents, search engines, and a growing variety of AI services integrating into every tool in existence — leveraging dRAG, they will enable user freedom of choice, AI autonomy and trust, all while leveraging network effects through connectivity.

Q5: Roadmap - What’s next?

The upcoming Decentralized Knowledge Graph (DKG) V8 update represents a significant advancement in Decentralized AI, building on the achievements of previous innovations brought by V6. The DKG V6 materialized knowledge as a new asset class, with its core AI-ready Knowledge Assets setting the stage for advanced AI applications in the domains of real-world assets (RWAs), decentralized science (DeSci), industry 4.0, and more.

Moving forward, DKG V8 introduces autonomous DKG growth and also significantly increases scalability. With this, the Decentralized Retri Augmented Generation (dRAG) becomes a foundational framework instilled in the DKG V8, significantly advancing a spectrum of large language model (LLM) applications.

DKG V8 is tailored to drive the next generation of AI through multi-modal content, which is crucial for a diversified and robust AI eco. The integration of dRAG and other decentralized AI functionalities allows for a more verifiable and secure application of AI technologies, addressing challenges such as misinformation, data bias, and model collapse.

The DKG V8 roadmap update focuses on catalysts designed to bootstrap and accelerate these advancements, including enhanced knowledge mining processes, integration across multiple blockchain ecos, and scalability improvements aimed at supporting an expansive growth of knowledge assets. These initiatives ensure that DKG V8 not only extends its foundational network effects but also reinforces its position as a cornerstone of future AI developments.