Author: Zhang Feng

In today's fiercely competitive technological landscape, vigorously promoting the integration of the innovation chain and the industrial chain remains key to enhancing national competitiveness. In the traditional model, the disconnection between "research, industry, and capital" creates a cyclical dilemma. For instance, targeted drug patents from university laboratories require pharmaceutical companies to invest tens of millions in validation due to a lack of shared data infrastructure; a drone team holding core patents is rejected by 27 institutions for lacking "fixed assets," while an automotive company with a production line worth 1 billion yuan is mired in liquidity issues due to a collateralization rate of less than 30%.

As AI large models reconstruct cognition and Web3 reshapes value networks, RWA (Real World Asset digitization) is becoming the key to breaking the deadlock with its characteristics of "asset programmability, capital penetrability, and governance collaboration." It transforms patents, equipment, and data into programmable tokens through a three-step leap of "asset digitization-tokenization-on-chain governance," driving the gene-level integration of the innovation chain and the industrial chain, becoming a new engine for corporate innovation and development.

1. Breakthrough Reconstruction of Traditional Pain Points in Industrial Innovation

Credible Data Infrastructure Ends "Information Silos." For example, a new energy battery laboratory uses an "IoT + oracle" system to put temperature, pressure, and other relevant parameters on-chain in real-time, forming a shared pool with the production line data of partner automotive companies. When energy density reaches a threshold, smart contracts automatically trigger pilot instructions for the automotive company—achieving "real-time alignment" between research and industry for the first time in a credible data flow, shortening the technology conversion cycle by 40%.

Liquidity Layering Activates "Sleeping Capital." For instance, a new drug research and development project valued at hundreds of billions faces difficulties with traditional collateralization, and the amounts are hard to meet. By connecting it to global investors through RWA, it transforms into blockchain-based liquid capital, significantly increasing the early financing coverage for tech companies.

AI Dynamic Pricing Breaks "Valuation Blind Spots." For example, after a self-driving patent token goes live, AI tracks three major dimensions in real-time: technical value (citation frequency by companies like Tesla), industrial progress (pass rate of vehicle testing), and market risk (policy compliance probability), generating dynamic technical scores and risk ratings, making the "early investment, early death" adverse selection a thing of the past.

Smart Contracts Lock in "Programmable Asset Interests." The token for a new materials research project includes a milestone mechanism; when material strength meets relevant standards, corresponding funds are unlocked, and when the yield exceeds specified requirements, related rights are released. Other market revenues are distributed according to sales tiers. Once the profit ratio is confirmed by relevant parties, it can be written into immutable on-chain code, greatly reducing disputes.

Diverse Exit Channels Accelerate "Capital Circulation." Under legal and compliant conditions, holders of medical device patent tokens can choose to trade instantly on global exchanges, pledge to DeFi protocols for stablecoin loans, or exit in bulk through "Medical Technology RWA ETF," potentially compressing the average exit cycle for tech investments from the traditional 7-10 years to 1-2 years.

2. Building a Global Market for Diverse Assets

Integrating Hard Technology Asset Packages Based on Compliant SPVs. For example, an SPV collaborates with universities and enterprises to conduct ownership verification on 50 chip patents and 3 pilot lines, bringing in law firms, accounting firms, and rating agencies as on-chain "trusted nodes" to eliminate "air asset" risks.

Building a Perception Network Based on AI + IoT Data On-Chain. A new energy laboratory deploys hundreds of sensors to continuously collect reaction parameters. An oracle network (like Chainlink) encrypts data hashes on-chain, while AI integrates off-chain raw data to generate a technology maturity curve, supporting the initial pricing of tokens.

Adapting Different Risk Preferences Based on Diverse Assets. By combining research, industry, and finance, three types of tokens can be constructed, such as art pieces, algorithm patents, testing equipment, and order revenues, tailored to different investors or users based on their varying return levels and risk characteristics to create a trading network.

Co-building a Community of Interests Based on DAO Governance. A biopharmaceutical project establishes a "Research and Development DAO," where laboratories, pharmaceutical companies, investors, and patient representatives vote on decisions based on token proportions. DAO treasury funds provide instant settlement for suppliers through DeFi protocols, reducing overall chain funding costs.

3. Constructing a Support Network for the Entire Ecosystem

In the long run, a multi-faceted approach is needed to build an RWA ecosystem support network.

In terms of regulatory sandbox pilots, experimental fields can be established in various regions similar to the Shanghai Free Trade Zone or the Guangdong-Hong Kong-Macao Greater Bay Area, drawing on Hong Kong's digital asset licensing system to explore a "negative list + in-process supervision" sandbox regulatory model.

Regarding digital infrastructure, the government or industry associations can build an integrated infrastructure platform that includes IoT, AI valuation, and auditing tools, reducing the asset on-chain costs for small and medium-sized enterprises by 60%.

In talent cultivation, universities can offer interdisciplinary courses related to digital assets, training composite talents who understand both chip development and smart contract programming, with some predicting a shortfall of 500,000 by 2030.

For cross-border mutual recognition and collaborative regulation, mechanisms can be established with places like Singapore and Dubai to promote the integration of China's 5G patents, new energy technologies, and other RWA assets into the global capital pool, attracting over 100 billion in overseas funds.

4. Making the Integration of the Innovation Chain and Industrial Chain into a Value Chain

The essence of RWA is not merely "asset on-chain," but a systemic-level transformation of the relationship between innovation and industry, redefining the new paradigm of corporate innovation engines. This includes AI's "data insights" dissolving technological uncertainties, such as real-time conversion of research data into R&D assets, using Web3's "value network" to break physical boundaries, such as transforming production capacity into globally circulating revenue certificates, and the "programmability" of token assets reshaping capital logic, allowing research participants to share technological dividends through tokens.

Imagine a scenario where every set of data on the innovation chain and every device on the industrial chain is transformed into programmable, tradable, and governable digital assets through RWA. The closed loop of "technology-industry-finance" could evolve from a disjointed "two skins" into a resonant "one body chain." This would not only be a revolution in capital efficiency but also a new engine for corporate innovation development, as well as an upgrade of the underlying operating system for a country to seize the high ground in technology.

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