Natalia emphasized that decentralization must not just be a concept but a lived reality, driving meaningful progress in the blockchain ecosystem. She underlined the importance of decentralization as a core value for future technologies, particularly in response to the growing influence of centralized AI systems. A commitment to this principle is essential if we aim to build a more inclusive and transparent digital future.
2. Addressing Centralization in AI
Natalia pointed out that the current landscape of AI is dominated by a few tech giants who control data and algorithms, leading to centralization that undermines the foundational ideals of Web 3. By advocating for a decentralized approach, she insisted that it is crucial to create an environment where AI can thrive independently, challenging the notion that AI development must be tied to centralized entities.
3. The Need for Scalable Solutions
Natalia highlighted that Ethereum, while historically significant to the Web 3 movement, is currently incapable of handling the demands introduced by AI. This presents an urgent need for scalable solutions, which is why Metis is stepping up to fill this gap. The ReGenesis initiative aims to provide the necessary infrastructure to ensure that decentralized systems can grow alongside evolving AI technologies without sacrificing performance.
4. Dual Chain Collaboration Mechanism
According to Natalia, the introduction of a dual chain collaboration mechanism through the Androma chain is integral to enabling real-time AI execution. This innovative approach promises to facilitate the interaction of AI models with smart contracts on-chain, fostering new use cases and expanding the possibilities for decentralized applications in the realm of artificial intelligence.
5. Instant Layer Two Capabilities
Natalia introduced Metis Hyperion, an instant Layer Two solution optimized for AI applications. With features like instant finality and parallel execution, it eliminates delays inherent in traditional blockchain systems. Such advancements are crucial for AI to process large datasets and perform computations effectively, signaling a transformative shift in how decentralized technologies can handle complex tasks.
6. AI Native Data Layer Development
As stated by Natalia, the creation of an AI-native decentralized data layer, referred to as Metis DB, will address significant challenges associated with data handling for AI models. With low latency and cryptographic security, this data layer aims to enhance real-time execution capabilities and support the robust training of AI applications, positioning Metis as a key player in the AI and blockchain intersection.
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