Search for AI Revolution in Web3: Distributed AI, Data Ownership and Future Road
Alisa Davidson
Publication: May 9, 2025 11: 4 update: May 9, 2025 11:4 am
Edit and fact confirmation: May 9, 2025 11:4 am
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One of the discussions held at Dubai’s Hack Seasons Conference focused on developing blockchain development and user interactions by focusing on the development of autonomous agents, AI driving DApps, and security and data analysis.
On May 2, Dubai held the Hack Seasons Conference to gather major experts to explore how AI WAVE reconstructs blockchain development and user interactions. Led by Tomer Sharoni, TEMER SHORONI co -founder and CEO, this panel is the Evgeny Pony of Fluence Network, Aethir’s Mark Rydon, OpenLEDGER Ramkumar and 0g Labs We introduced industry leaders including Michael Heinrich. This discussion deals with the development of autonomous agents, the development of AI driving distribution applications (DApps) and security and data analysis, and emphasizes how AI changes Web3 infrastructure and governance and investigates the future border of this convergence.
One of the central questions was the current dominant of the centralized AI model that depends on closed data, closed computing resources and limited incentives. The speaker identified the decentralization as a means to overcome these limitations.
Today, while identifying the major problems of AI, we have emphasized that we can contribute to the development of AI by enabling more comprehensive data collection and labeling processes. The ability to collect a lot of resources and use what people need is another problem of paying attention. The possibility of verification of AI components is also not compensated for the challenge and the data they offer. In this case, password stimuli incentives serve as potential opportunities to be transparent to contributors. On the other hand, the main infrastructure problem is limited to access to the GPU, an important engine of AI, which emphasizes the urgency of democratizing computing access to ensure a wide range of participation.
Infrastructure distributed as a path to transparent, verifiable and reliable AI system
Restoration of trust in the AI system is another essential problem. Especially in an environment where decisions become more and more opaque. Therefore, decentralization of decentralization brings visibility to both data and model movements.
For example, the distributed storage layer can set the data source from the moment the information enters the system, so that the user can track the origin and modifications. In terms of operation, real -time model alignment through blockchain -based incentives and penalty mechanisms (slashes) creates a system that can be verified and adapted using a path to dynamic governance of AI operation.
AI’s Daum Frontier Lock: ownership of distributed AI models
Another major point in the discussion was data properties and quality assurance. Today, most large language models (LLM) have been educated on public scratches, but the panelist emphasizes that the most valuable data set is owned by individuals and companies with domain -specific knowledge.
For example, OpenLEDGER aims to allow individuals and organizations to use these special data sets to build customized models in sectors such as medical and electronic commerce. Through their framework, the contributor can maintain ownership of data while contributing and being rewarded. In particular, OpenLEDGER provides a mechanism that tracks data that contributes to certain AI outputs, which are not available in most current LLMs.
From all -chain trading automation to reinforced cryptographic stimulus economy: What is the future?
When asked about the most interesting ideas in the AI space, which is expected to be realized in the near future, the speaker emphasized the possibility of performing a wide range of human work using an AI agent. One example discussed was the AI sorting node, which can act as a natural police by detecting data addiction and backdoor attacks. The panelists also emphasized the role of AI in abstracting humans and improving efficiency in everyday work.
Speakers predicted that self -autonomous AI agents could carry out a large amount of warmth in the next three to five years.
Another notable idea is that AI can be used to optimize everything from software development to the defi strategy distributed. As the AI continues to develop, the potential for the completely new encryption organization and financial model, which is driven by the AI itself and optimized, is increasing. In this new paradigm, cryptocurrency can be used not only as a tool for guessing but also as a capital of AI -centered economy.
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About the author
Alisa, a dedicated reporter for MPOST, specializes in the vast areas of Cryptocurrency, Zero-ehnowedge Proofs, Investments and Web3. She provides a comprehensive coverage that captures a new trend and a keen eye on technology, providing and involving readers in a digital financial environment that constantly evolves.
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Alisa Davidson
Alisa, a dedicated reporter for MPOST, specializes in the vast areas of Cryptocurrency, Zero-ehnowedge Proofs, Investments and Web3. She provides a comprehensive coverage that captures a new trend and a keen eye on technology, providing and involving readers in a digital financial environment that constantly evolves.
More