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IS ARTIFICIAL INTELLIGENCE CONSIDERED "WEB3"?
The recent surge in web and mobile applications developed over the past year has ushered in a new era of technological integration. In particular, the convergence of Artificial Intelligence (AI) and Web3 presents a unique technological synergy that seems like a match made in heaven. This intersection has given rise to an array of opportunities, fostering innovation, and expanding the horizons of what can be achieved in the digital realm. The amalgamation of AI's ability to learn, predict, and automate with the decentralization, security, and user-centric ethos of Web3 is opening up exciting new possibilities. From decentralized finance and autonomous organizations to personalized, privacy-preserving services, the fusion of AI and Web3 is poised to redefine the future of technology.
📌So do the elements of AI fall under the WEB3 category of technology?
AI in itself isn’t intrinsically linked to the principles of web3, as its primary function lies in making machines and systems perform tasks that normally require some basic human intelligence. This includes tasks such as recognizing patterns, understanding languages, making decisions, and so forth.
Machine Learning (ML), a subset of AI, as a technology function also doesn’t inherently align with the vision of web3. ML involves algorithms that enable systems to learn from data, improve over time, and make predictions or decisions without being explicitly programmed to do so.
AI and ML are technologies that can function in any context, and can augment the functionalities of systems, be it centralized ones (like those of the tech giants) or decentralized ones (like envisioned in web3). Their function is not dependent on the structure of data ownership or the network they operate on. Instead, they work towards enhancing the capabilities of these systems.
One could definitely argue that AI and ML could have a big role to play in the context of web3. For instance, they could be used to enhance the functionality and efficiency of decentralized systems, provide personalization while maintaining data privacy, or facilitate complex decision-making processes in DAOs. By technical distinctions, they are not part of web3’s core infrastructure but rather auxiliary tools that can be applied in a web3 context to optimize processes and deliver value to users. Although, they are not inherently part of web3, but they can definitely play a significant role in shaping the future of a decentralized internet.
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AI and ML are not inherently part of web3, but they can be used to enhance the functionality and efficiency of decentralized systems, provide personalization while maintaining data privacy, and facilitate complex decision-making in DAOs. They are auxiliary tools that can optimize processes and deliver value to users in a web3 context.
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