Artificial Intelligence in Web3: Why Decentralization?

In 2024, decentralized AI has becomecryptocurrencyOne of the most dynamic and fastest growing sectors in the market. According to the Dune dashboard created by CryptoKoryo, AI stands out as a leading sector in terms of interest and investment in the crypto industry.

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By combining intelligent processing with the decentralized, user-centric approach of Web3, decentralization AI This convergence has brought significant benefits. This integration enhances the transparency, efficiency and adaptability of digital platforms. Enterprises can use the analytical power of artificial intelligence to optimize user experience and gain data-driven insights.

本指南探讨了 Web3 AI 的实际应用和更广泛的影响，强调了其变革潜力。 此外，我们还将了解 BNB Chain 如何为开发人员提供理想的平台和工具集，以创建真正强大的人工智能应用程序。

The rise of artificial intelligence

The artificial intelligence industry is experiencing a rapid and transformative rise, with significant impacts on various industries and the global economy. By 2022, the artificial intelligence market will be worth $136.55 billion.It is expected that the compound annual growth rate (CAGR) will reach 37.3% from 2023 to 2030, and is expected to reach $1.8 trillion by 2030.

This exponential growth is driven by continued research, innovation, and massive investments by tech giants, making AI a core technology in industries such as automotive, healthcare, retail, finance, and manufacturing.

Artificial intelligence has enormous transformative potential. It is expected that by 2030,Artificial Intelligence Could Contribute Up to $15.7 Trillion to the Global Economy, exceeding the current economic output of China and India combined. This growth will be driven by productivity gains and consumption side effects, with China and North America expected to see significant economic growth.

The integration of AI in various fields has begun to revolutionize operations, optimize processes and enhance user experience. From self-driving cars and life-saving medical devices to marketing automation and networkSafety, the impact of artificial intelligence is everywhere. As AI continues to advance, it is expected to reshape industries, drive economic growth, and create new opportunities.

In short, the market is huge and the potential is huge. However, are we really leveraging the full potential of the AI market? Is a centralized ecosystem really the best way to develop AI? Let's take a look.

The limitations of centralized AI

Centralized AI systems face significant limitations, primarily due to their susceptibility to single points of failure. When all operations rely on a central server, any failure or compromise can disrupt the entire system. This issue is particularly important in mission-critical applications, where uninterrupted functionality is non-negotiable. For example, if a centralized AI system used in healthcare or autonomous driving were to experience a server outage or cyberattack, it could result in severe consequences, including loss of life or significant financial losses. The reliance on a single point of control makes centralized AI systems inherently fragile and prone to systemic failures.

Scalability and efficiency are also major concerns with centralized AI. As the demand for AI applications grows, centralized systems may have difficulty handling the increased load. This often leads to performance bottlenecks, latency, and a degraded user experience. In a centralized AI architecture, the burden of processing large data sets and executing complex algorithms falls on a single core or a limited set of resources, which can lead to inefficiencies and slowdowns.

Data Privacy andSafetyThis is another key limitation of centralized AI. Centralized systems require data to be continuously transmitted to a central hub for processing, increasing the risk of unauthorized access during transmission and storage. This centralization makes them a prime target for cyberattacks, as compromising a central server could expose a ton of sensitive information.

AI monopolies could be dangerous and wrong

The rise of AI monopolies, exemplified by Microsoft’s strategic positioning in the OpenAI internal challenge, raises several significant questions. Such monopolies can stifle innovation, hinder collaboration, and lead to increased costs and inferior technology for end users.

The consolidation of AI capabilities within a few large companies could create silos that limit technological progress and economic growth. In addition, a monopolistic environment would restrict competition, making it difficult for emerging businesses to thrive, and could lead to biased decision-making and limited innovation.

In addition, the lack of diversity in data training sources may mean that AI modelsXiaobai NavigationModels are using a lot of data that is inherently biased and erroneous. Gemini, an AI tool released by Google that is designed to generate images of people, faced challenges due to insufficient testing. Soon after its launch, Gemini was found to have generated inaccurate historical images, such as multiracial and female U.S. senators in the 1800s, leading to rapid criticism on social media.

The need for decentralized AI

Decentralized AI can promote transparency, privacy, and resilience. By eliminating the need for a central authority, decentralized AI ensures that power and control are not concentrated in one entity, thereby reducing the risk of monopoly control and systemic failure.

The model is enhanced by distributing data over the networkSafetyDecentralized AI promotes innovation and collaboration by allowing different nodes to contribute and work together, leveraging collective intelligence and achieving more adaptive and resilient AI systems.

The benefits of decentralized AI

• Safety和隐私：去中心化人工智能系统增强了数据隐私和Safety性。 数据在本地处理并分布在网络上，从而降低了违规和未经授权访问的风险。 BlockchainThe technology adds an immutable security layer, ensuring the integrity of data and models.

• Scalability and efficiency: Decentralized AI offers greater scalability. By leveraging a network of nodes, these systems can adapt and scale as needed, processing tasks in parallel to increase overall capacity and performance without overburdening any single component.

• Transparency and accountability: Decentralized AI systems governed by consensus mechanisms and distributed algorithms inherently promote transparency. Users and developers can scrutinize and verify AI processes, fostering trust and accountability.

• Reduced bias and fair outcomes: By leveraging diverse data inputs and distributed decision making, decentralized AI can reduce bias and produce more balanced and fair outcomes. Cryptographic verification and proofs ensure that AI model outputs are tamper-proof and reliable.

• Economic and social impact: Decentralized AI democratizes access to AI technology, reduces barriers to entry for smaller players and promotes fair access. This creates a competitive environment, drives innovation, and ensures that the benefits of AI are widely distributed across society. In addition, decentralized AI can check large-scale surveillance and manipulation by centralized entities, protecting individual interests.

• Decentralized Governance: Decentralized Autonomous Organizations (DAOs)DAO) can significantly benefit decentralized AI by providing a transparent and democratic governance structure. DAO In the project, governance is done throughTokenManaged, allowedTokenHolders propose, vote, and implement changes. This ensures that decision-making power is distributed among all stakeholders, promoting inclusivity and collaboration. An inclusive ecosystem promotes open source development, where developers and researchers from different backgrounds can contribute, making the system more complete and inclusive. Small companies and individuals can also participate, driving innovation and ensuring diverse perspectives.

The future of decentralized AI

useBlockchainTechnically, decentralized AI will eliminate the central points of control that currently dominate AI development. This shift will democratize access to AI resources, allowing a wider range of participants — including smaller entities and individual developers — to contribute to and benefit from AI advancements.

By breaking the monopoly of tech giants, decentralized AI will foster a more competitive and diverse ecosystem, spurring innovation and ensuring that AI technology develops to meet broader societal needs.

In addition, decentralized AI will revolutionize data privacy and security. By enabling local data processing and utilizing encrypted data for AI computations, these systems will significantly reduce the risks associated with data breaches and unauthorized access. This approach ensures that users retain control over their personal information, thereby enhancing trust in AI systems.

The integration of edge computing will further enhance decentralized AI by allowing data processing to take place closer to the data source. This can reduce latency, reduce bandwidth usage and support real-time AI applications, which are critical for scenarios such as autonomous driving and smart city infrastructure.

Finally, decentralized AI will promote collaborative intelligence by leveraging federated learning and other distributed learning techniques. AI models will be able to learn from globally diverse datasets, producing more robust and unbiased results. This collective approach to AI training will make AI systems more accurate and culturally aware. In addition,DAO The rise of blockchain will provide new governance frameworks for AI projects, enabling stakeholders to make decisions transparently and democratically.

As these trends continue to develop, the future of decentralized AI will be characterized by enhanced security, greater inclusion, and a more equitable distribution of the benefits of AI across society.

BNB Chain: The ideal platform for decentralized artificial intelligence

BNB Chain provides an ideal platform for decentralized AI with its powerful infrastructure and multi-chain architecture, including BNB Smart Chain (BSC), opBNB, and BNB Greenfield. BSC provides EVM compatibility, a proof-of-stake consensus model, and the ability to process up to 5,000 transactions per second at low transaction costs. This infrastructure supports high-volume and high-speed transactions that are critical to AI applications, while also being compatible with Ethereum-based DApp Compatibility accelerates deployment. Fast block finality and the potential for parallel EVM further enhance transaction execution, making BSC a secure, efficient, and scalable foundation for AI development.

opBNB is a layer 2 solution that uses optimistic rollup technology to significantly improve scalability and reduce gas costs. With transaction speeds of up to 10,000 TPS and extremely low fees, opBNB is ideal for high-performance AI applications that require fast data processing and low latency.

BNB Greenfield complements this by providing decentralized and secure data storage, which is essential for managing large amounts of data with enhanced privacy and security. Its user-centric model allows for granular data access control, ensuring that AI development is ethical and compliant with data protection regulations. Together, these components of the BNB chain create a comprehensive, scalable, and secure environment for decentralized AI innovation and deployment.

The BNB Chain ecosystem is a hub for innovative AI projects across a variety of sectors, enhancing user interaction, content creation, data management, and developer resources.

Here is a quick overview:

• Artificial Intelligence Agent:

  • MyShell: Enhances the discovery, creation, and staking of AI-native applications through an open development environment that supports a variety of models and APIs. It meets the needs of both advanced and novice developers, provides an application store for publishing and managing AI applications, and provides a transparent reward distribution system for all ecosystem contributors.

  • ChainGPT: Provides smartcontractTools for blockchain generation, NFT creation, crypto trading models, and on-chain data analysis. The platform provides real-time updates, SDK and API services, and $CGPT for accessing advanced tools, staking pools, and DAO voting. Token.

• Content Generation:

  • NFPrompt: A UGC (User Generated Content) platform that enables users to create, own, socialize and monetize their imaginative works. Leveraging Web3 technology, it transforms everyday users into content creators, ensuring verifiable ownership of AI-generated art.

  • StoryChain: An innovative platform that uses artificial intelligence to create immersive, interactive stories that push the boundaries of digital storytelling.

• smart robot:

  • Web3go: A data intelligence network that builds a data preprocessing layer for decentralized artificial intelligence.BlockchainTechnology enhances data flow and AI agent development. Web3Go aims to create accessible infrastructure for data collection and dissemination, encouraging user participation and network improvement.

• Data management and processing:

• Glacier Network: Providing scalable and modular solutions for AI applicationsBlockchainInfrastructure, focusing on data storage, indexing, and processing. In addition, Glacier Network provides tools for GameFi and SocialFi developers to manage game metadata and social connections in blockchain applications.

• Web3go xData: Data labeling service on opBNB uses artificial intelligence to simplify and automate data processing, making data management more efficient and reliable

• Infrastructure Services:

  • NetMind: NetMind uses idle GPUs to create a global computing network for AI models, providing a large-scale distributed computing platform. It combines diverse resources with grid and voluntary computing scheduling and load balancing technology to make the development of artificial intelligence models more economical and efficient.

  • Aggregata: aims to revolutionize AI by expanding the definition of AI data to include models, vector databases, pipelines, environments, and weights. This approach enhances data flow with speed, efficiency, simplicity, and decentralization. Aggregata supports AI innovation by providing a comprehensive data infrastructure.

• Developer Tools:

  • Aspecta: Currently in the incubation stage, Aspecta will revolutionize developer tools and resources, enabling developers to create more advanced and efficient AI applications.

  • CodexField: Provides developers with the tools they need to build and deploy innovative AI solutions, fostering a vibrant ecosystem of technological advancements.

• ZKML:

  • zkPass: A breakthrough project on BSC, usingZero knowledge proofTo enhance the privacy and security of AI models.

  • BAS: Generates proofs for verifying information within the BNB ecosystem, supporting both on-chain and off-chain verification. Users can store proofs in Greenfield to ensure data privacy and control. BAS solves the need to verify off-chain data, thereby enabling ownership claims, data privacy, access management, and data assetization within the Web3 ecosystem.

Click here to learn more about the BNB Chain AI ecosystem and what makes it different.

Conclusion

Decentralized AI powered by blockchain technology enhances security, privacy, and scalability while democratizing access and promoting innovation. It reduces centralization risk, increases transparency, and ensures a strong, unbiased AI system. By enabling diverse contributions and fair AI benefits, decentralized AI drives industry growth and economic development. Platforms such as BNB Chain provide an ideal ecosystem and tools for developers to create groundbreaking decentralized AI applications.

The article comes from the Internet:Artificial Intelligence in Web3: Why Decentralization?

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