Emerging Technologies / Blockchain and Web3

The primary objectives include enhancing the value of digital assets through blockchain, improving efficiency across sectors like healthcare and finance, and establishing Beijing as a digital economy innovation hub by 2027. The plan also focuses on developing blockchain infrastructure and software for cryptography and distributed systems.

Beijing's initiative aligns with China's national blockchain roadmap, which aims to establish a comprehensive blockchain infrastructure by 2029. This involves integrating blockchain into key industries and developing standardized protocols for data sharing across the country.

While blockchain currently lags behind AI in job creation, Bitget Research projects blockchain could generate over 1 million jobs by 2030 if adoption accelerates to match AI's growth pace, potentially reaching 1.5 million roles with enterprise integration and regulatory support.

Regulatory clarity (e.g., EU's MiCA framework), enterprise adoption by institutions like JPMorgan and Visa, and $100B+ annual VC funding parity with AI are critical to unlocking blockchain's projected 1.5 million jobs by 2030.

Blockchain enhances security by providing an immutable and real-time ledger of transactions, reducing the risk of data breaches and human error. It shifts financial security from a reactive model to a proactive defense system, ensuring that every transaction is permanently recorded and independently verifiable.

Transparency is crucial as blockchain provides a public and immutable record of transactions, allowing for real-time audits and reducing the potential for fraud. This transparency helps in maintaining data integrity and accountability, which are essential for restoring trust in financial markets.

AI plays a significant role in the current tech boom by driving advancements across various sectors such as healthcare, finance, and education. It has transformed industries with tools like ChatGPT and Google's Bard, enhancing productivity and innovation[1][5].

The article does not provide specific details on how blockchain is being legitimized. However, the general trend in blockchain involves increased adoption and recognition across industries, often through regulatory clarity and strategic partnerships[4].

The integration of AI and blockchain technology offers several benefits, including decentralizing data ownership, enhancing security, and providing transparent and tamper-proof AI operations. This convergence can mitigate centralization issues, promote privacy, and create new financial market opportunities (Crawley, 2025; Marr, 2025; Reflexivity Research, n.d.)

Decentralized AI addresses concerns about data privacy and centralization by allowing individuals to maintain ownership of their data and contribute it anonymously for AI training. This approach ensures privacy and encourages the development of more diverse and unbiased AI models. Additionally, blockchain technology provides a transparent and tamper-proof record of data exchanges and model interactions (Reflexivity Research, n.d.; Oasis Network, 2024)

Web3 technology, particularly blockchain, enhances transparency and trust in AI by creating an immutable record of operations, making AI processes traceable and transparent. This allows users to follow an AI's decision-making path, fostering trust not easily achieved in traditional AI models. Additionally, Web3 enables decentralized data control, allowing users to own and manage their data securely, which mitigates privacy risks and promotes accountability in AI applications.

Blockchain technology plays a crucial role in ensuring accountability and reducing biases in AI by providing a secure, decentralized, and transparent framework for data management and AI decision-making processes. It allows for the creation of an immutable record of AI operations, which helps in tracking and verifying the data used to train AI models, thereby enhancing the integrity and reliability of AI outputs.

Blockchain enhances the security and transparency of AI systems by providing a decentralized, immutable ledger that ensures data integrity and prevents tampering. AI algorithms can analyze blockchain data to detect anomalies and predict potential threats, further enhancing security. This integration also promotes transparency by allowing stakeholders to track data origins and usage, ensuring accountability in AI decision-making processes.

Blockchain supports the growth of AI and robotics by providing a secure and transparent foundation for data management. This enables AI systems to operate on reliable data, enhancing their performance and decision-making capabilities. Additionally, blockchain ensures accountability and trust in AI-driven processes, which is crucial for the development of responsible and innovative AI applications.

The VRC-20 token standard is a new protocol introduced by Vana, a decentralized AI data liquidity network, aimed at ensuring fair and transparent data token transactions. It builds a liquidity-driven data economy market and promotes DataFi by requiring DataDAOs to issue tokens that comply with VRC-20 standards to access liquidity support. This standard enhances the tradability and liquidity of data tokens, making them more accessible to a broader range of participants in the Vana ecosystem.

With the introduction of the VRC-20 standard, rewards in the Vana ecosystem are no longer distributed directly to DataDAOs. Instead, they flow into liquidity pools. This change allows any DataDAO that meets the VRC-20 standards and integrates with the Vana ecosystem to be eligible for liquidity support, expanding beyond the initial top 16 DataDAOs.

The integration of blockchain technology into the US Treasury could enhance transparency and efficiency by allowing real-time tracking of federal spending and safeguarding data through decentralized systems. This could potentially reduce fraudulent payments and increase accountability in government transactions.

The potential risks include increased inflation, slower transaction processing times, and the destabilization of the US dollar as a global currency standard. Additionally, there are concerns about the speculative nature of cryptocurrency markets and the potential for a dangerous bubble that could negatively impact taxpayers.

The Hoodi testnet is designed to provide a stable environment for testing validator exits and staking operations, particularly in preparation for the Pectra upgrade. It aims to mimic the Ethereum mainnet closely, offering a realistic testing ground for validators and staking providers.

Hoodi is specifically focused on validator testing and staking operations, offering a more realistic environment similar to the Ethereum mainnet. In contrast, Sepolia is primarily used for application and tooling development, while Holesky, despite its challenges, remains operational for testing other Pectra features until September 2025.

Metadata in Web3 refers to supplementary data generated during online activities, such as transaction details and IP addresses. It is a concern because this data can be used to track user activity, compromising privacy and anonymity. In decentralized systems like Web3, metadata exposure can be particularly problematic as it may be accessible to anyone, not just centralized entities[3][4].

Improving metadata privacy in Web3 requires the development and integration of privacy-enhancing technologies. Users can currently use tools like VPNs, but more robust solutions, such as mixnets and encryption, are needed. Additionally, users must demand privacy from service providers to drive change[1][3].

Centralized data infrastructure contradicts Web3's core principle of decentralization by relying on a few powerful entities to manage data, which can lead to single points of failure and undermine trustless and permissionless interactions. Decentralized infrastructure is essential for maintaining Web3's integrity and benefits like censorship resistance and security[1][3].

Transitioning to decentralized infrastructure enhances accessibility, reduces costs, and fosters innovation in AI and research. This shift supports the emerging tech economy by promoting open data, improving scalability, and ensuring that data control remains with users rather than centralized authorities[2][5].

Quantum computers pose a significant threat to blockchain security by potentially breaking the cryptographic algorithms used to secure transactions and data. Algorithms like RSA and ECC, which are commonly used in blockchain, can be compromised by quantum computers using algorithms such as Shor's algorithm, which can factor large integers exponentially faster than classical computers.

To secure blockchain networks against quantum attacks, experts recommend adopting post-quantum cryptographic algorithms such as lattice-based or hash-based cryptography. Additionally, implementing hybrid cryptographic models and quantum-safe consensus mechanisms can enhance security. Upgradable protocols also allow for seamless transitions to future quantum-resistant protocols.