Collective Memory for AI on Decentralized Knowledge Graph // Tomaž Levak // #285
Jan 24, 2025
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Tomaž Levak, Co-founder and CEO of Trace Labs, dives into the world of decentralized knowledge graphs and their role in AI. He discusses how these graphs enhance data integrity and privacy while promoting collaboration among organizations. Practical use cases in enterprise sectors are highlighted, showcasing their economic potential. Levak also explores the fusion of AI and personal health management, emphasizing innovative technologies that improve well-being. The conversation concludes with insights on the future of decentralized AI and its convergence with blockchain.
Decentralized knowledge graphs enhance data transparency and ownership, enabling users to maintain control over their data without monopolization.
AI agents leverage decentralized knowledge graphs as a collective memory, significantly improving data processing speed and decision-making capabilities across various industries.
Deep dives
Decentralized Knowledge Graphs and Their Importance
Decentralized knowledge graphs play a crucial role in ensuring data transparency and ownership in an increasingly digital world. By leveraging symbolic AI, these graphs allow individuals and organizations to maintain control over their data while enhancing verifiability. The absence of a central authority prevents data monopolization, fostering a common ground for various entities to connect their systems, thereby encouraging collaboration. This innovation not only promotes transparency but also empowers users to interact with a global knowledge graph without compromising their data privacy.
The Concept of Paranets
Paranets, or parallel networks within decentralized knowledge graphs, represent localized clusters of knowledge focused on specific topics. These neighborhoods contain shared rules and allow participants to define data structures tailored to their needs. For instance, organizations can create a paranet centered on a particular industry or product line, enabling participants to contribute data in a consistent format. By establishing these specialized areas of the knowledge graph, users can derive more actionable insights and facilitate tailored AI applications.
Data Privacy and Interoperability
Decentralized knowledge graphs facilitate interoperability between different organizations while maintaining rigorous data privacy protocols. Users can keep their knowledge assets private, only exposing necessary data when required for queries, which enhances trust between partners. For example, two collaborating enterprises can share insights without disclosing sensitive information by using knowledge graphs to verify claims and maintain transparent communication. This ability ensures users can optimize their interactions and processes without compromising the confidentiality of their proprietary data.
AI Agents and Collective Memory
AI agents are increasingly utilizing decentralized knowledge graphs as a collective memory, enhancing their capabilities in processing and interpreting data. These agents can autonomously navigate knowledge graphs, efficiently executing tasks and retrieving relevant information faster than human operators. The incorporation of decentralized systems into AI applications can revolutionize industries by allowing for rapid data analysis and decision-making. By providing agents with access to a wealth of knowledge locally and collectively, organizations can drive innovation and optimize processes, ultimately improving outcomes across various fields.
Tomaž Levak is the Co-founder and CEO of Trace Labs – OriginTrail core developers. OriginTrail is a web3 infrastructure project combining a decentralized knowledge graph (DKG) and blockchain technologies to create a neutral, inclusive ecosystem.
Collective Memory for AI on Decentralized Knowledge Graph // MLOps Podcast #285 with Tomaz Levak, Founder of Trace Labs, Core Developers of OriginTrail.
// Abstract
The talk focuses on how OriginTrail Decentralized Knowledge Graph serves as a collective memory for AI and enables neuro-symbolic AI. We cover the basics of OriginTrail’s symbolic AI fundamentals (i.e. knowledge graphs) and go over details how decentralization improves data integrity, provenance, and user control. We’ll cover the DKG role in AI agentic frameworks and how it helps with verifying and accessing diverse data sources, while maintaining compatibility with existing standards.
We’ll explore practical use cases from the enterprise sector as well as latest integrations into frameworks like ElizaOS. We conclude by outlining the future potential of decentralized AI, AI becoming the interface to “eat” SaaS and the general convergence of AI, Internet and Crypto.
// Bio
Tomaz Levak, founder of OriginTrail, is active at the intersection of Cryptocurrency, the Internet, and Artificial Intelligence (AI). At the core of OriginTrail is a pursuit of Verifiable Internet for AI, an inclusive framework addressing critical challenges of the world in an AI era. To achieve the goal of Verifiable Internet for AI, OriginTrail's trusted knowledge foundation ensures the provenance and verifiability of information while incentivizing the creation of high-quality knowledge. These advancements are pivotal to unlock the full potential of AI as they minimize the technology’s shortfalls such as hallucinations, bias, issues of data ownership, and model collapse.
Tomaz's contributions to OriginTrail span over a decade and across multiple fields. He is involved in strategic technical innovations for OriginTrail Decentralized Knowledge Graph (DKG) and NeuroWeb blockchain and was among the authors of all three foundational White Paper documents that defined how OriginTrail technology addresses global challenges. Tomaz contributed to the design of OriginTrail token economies and is driving adoption with global brands such as British Standards Institution, Swiss Federal Railways and World Federation of Haemophilia, among others.
Committed to the ongoing expansion of the OriginTrail ecosystem, Tomaz is a regular speaker at key industry events. In his appearances, he highlights the significant value that the OriginTrail DKG brings to diverse sectors, including supply chains, life sciences, healthcare, and scientific research. In a rapidly evolving digital landscape, Tomaz and the OriginTrail ecosystem as a whole are playing an important role in ensuring a more inclusive, transparent and decentralized AI.
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// Related Links
Website: https://origintrail.io