GateLive AMA Recap-Apu Apustaja

Q1: What is OriginTrail?

OriginTrail is an ecosstem 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, b ensuring the provenance and verifiabilit of data used b AI sstems. OriginTrail is used b global leaders like the British Standards Institution, Swiss Federal Railwas, Supplier Compliance Audit Network (SCAN), representing over 40% of US imports and several consortia funded b the European Union among others. Advised b Turing award winner Dr. Bob Metcalfe, renowned for his law of network effects, the Trace Labs team (OriginTrail core developers) plas a crucial role in promoting a more inclusive, transparent, and decentralied AI.

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

Initiall adopted in global suppl chains to provide a trusted data sharing hub, OriginTrail's technolog is increasingl vital across various sectors, including asset tokeniation, construction, healthcare, the metaverse, and more due to its abilit to authenticate and secure information.

(1)In the suppl chain sector, BSI and SCAN are utiliing the OriginTraill to ensure the integrit of securit audits for some of the largest US importers.

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

(3)Swiss Federal Railwas is utiliing OriginTrail to ensure the safet of train travel b tracking ever 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 technolog is used to build a trusted knowledge base aiming to improve efficienc, reduce errors, and increase transparenc and trust, ultimatel leading to more sustainable construction projects.

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

Q3: Latest innovations in AI space?

The Trace Labs team (OriginTrail core developers) introduced ChatDKG, a trul open Artificial Intelligence, that drives snergies 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, verifiabilit of information, or bias that would include an censorship-b-design approach. The risk of this revolution not unfolding in an inclusive wa is a societal threat of establishing a monopol on AI.

The team therefore introduced an effective wa of establishing a new paradigm, using a Decentralied Retrieval-Augmented Generation (dRAG) framework. dRAG advances the RAG model b organiing external sources in a Decentralied 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 hbrid, decentralied AI sstem that brings together neural (e.g. LLMs) and smbolic AI (e.g. Knowledge Graph) methodologies.

Contrar to using a solel probabilistic neural AI approach, the smbolic AI approach enhances it with the strength of Knowledge Graphs, introducing a more deterministic component. To harness a harmonious development between Web3 fundamentals and rapidl deploed AI sstems, the approach is to integrate the core Web3 technologies such as the OriginTrail Decentralied Knowledge Graph (DKG) and AI sstems (OpenAI, Gemini, Microsoft Co-pilot, xAIs Grok, and others). We can realie the potential of trusted AI b creating a Verifiable Internet for AI that is founded on principles of neutralit, inclusiveness, and usabilit, while giving users freedom of choice with a multi-modal and a multi-model AI framework.

Q4: Possible integrations with ChatDKG?

The globall most adopted and centralied AI solutions like Google Gemini, OpenAI, xAI, Perplexit deliver an immense value for a spectrum of use cases. Leveraging Origin Trails dRAG brand name ChatDKG.ai, the can improve their shortfalls b harnessing the snerg of neuro-smbolic AI, data ownership, and better cost performance. Therefore, ChatDKG.ai is not competing against an established AI solutions, but rather empowers users to enhance them with its dRAG, driving knowledge verifiabilit, cost effectiveness, users sovereignt in owning their data and freedom of AI model choice.

The open source and permissionless nature of the OriginTrail DKG, allows for inclusiveness and neutralit, giving users a tremendous level of freedom on all laers to choose AI models enabled b DKG data portabilit, choose knowledge sources discoverable in DKG, as well as pick AI services, centralied or decentralied on different blockchains.

The same principles appl to AI agents, search engines, and a growing variet of AI services integrating into ever tool in existence leveraging dRAG, the will enable user freedom of choice, AI autonom and trust, all while leveraging network effects through connectivit.

Q5: Roadmap - Whats next?

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

Moving forward, DKG V8 introduces autonomous DKG growth and also significantl increases scalabilit. With this, the Decentralied Retrieval Augmented Generation (dRAG) becomes a foundational framework instilled in the DKG V8, significantl 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 ecosstem. The integration of dRAG and other decentralied 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 catalsts designed to bootstrap and accelerate these advancements, including enhanced knowledge mining processes, integration across multiple blockchain ecosstems, and scalabilit improvements aimed at supporting an expansive growth of knowledge assets. These initiatives ensure that DKG V8 not onl extends its foundational network effects but also reinforces its position as a cornerstone of future AI developments.