AI Drives DeFi into the Mainstream: Looking at the Development Prospects of DeFAI from DeepSeek

With the rapid development of artificial intelligence technology, whether the Web3 field can benefit from it is no longer a question. The real focus is: which Web3 track can seize the AI dividend the fastest, and how to maximize the use of AI to achieve breakthroughs. Decentralized Finance (DeFi) is undoubtedly one of the most promising areas, and the intersection of the two - DeFAI (DeFi+AI) - is becoming one of the fastest-growing tracks in the crypto economy.

The essence of DeFAI is to make AI the "autopilot" of the on-chain world. Currently, the complexity of DeFi has always been a barrier for ordinary users to enter, while DeFAI is expected to simplify the user experience through AI, attracting more mainstream users. They can analyze on-chain data in real time, helping to complete complex strategies such as cross-chain arbitrage, dynamic staking, and flash loan combinations, and even participate in protocol upgrades through DAO governance. Just like search engines allow ordinary people to access the internet without understanding TCP protocols, DeFAI will enable every novice user to have hedge fund-level asset management capabilities.

Currently, some DeFAI projects have emerged. As a well-known DeFi developer, someone has led the development of algorithmic stablecoin Wonderland, decentralized lending AbracadabraMoney, and DEXWAGMI. Today, the project he founded, focusing on AI-driven DeFi automation tools, has launched a TypeScript-based solution aimed at integrating into DeFi protocols, enabling agents to manage on-chain interactions with unprecedented security and ease.

DeepSeek R1: Redefining Open Source AI

DeepSeek R1 is a new type of LLM based on extensive text training, optimized for reasoning and contextual understanding. Its prominent features include:

• Efficient architecture: Utilizing a new generation parameter structure to achieve near-top performance in complex reasoning tasks without the need for a large GPU cluster.
• Low hardware requirements: Designed to support a small number of GPUs or even high-end CPU clusters, lowering the barrier to entry for startups, independent developers, and the open-source community.
• Open source license: Unlike most proprietary models, its permissive license allows companies to integrate directly into products, promoting rapid adoption, plugin development, and professional fine-tuning.

This trend of AI democratization evokes the early stages of open source projects like Linux, Apache, and MySQL, which ultimately drove exponential growth in the tech ecosystem.

Value Proposition of Low-Cost AI

Accelerate Popularization

When high-quality AI models achieve economic operation:

• Small and medium-sized enterprises can deploy AI solutions without relying on expensive proprietary services.
• Developers can freely experiment, from chatbots to automated research assistants, achieving innovative iterations within budget.
• Emerging market companies can seamlessly access AI solutions to bridge the digital divide in industries such as finance, healthcare, and education.

Inference Democratization

Low-cost reasoning not only drives usage but also democratizes reasoning:

• Localization model: Small communities can train DeepSeek R1 using specific language or domain corpora (such as specialized medical/legal data).
• Modular Expansion: Developers and independent researchers can build advanced plugins (such as code analysis, supply chain optimization, on-chain transaction verification) to overcome permission bottlenecks.

Overall, cost savings spur more experimentation, thereby accelerating overall innovation in the AI ecosystem.

Jevons Paradox: Why Efficiency Improvements Drive Up Consumption

The Jevons Paradox states that improvements in efficiency often lead to an increase in resource consumption rather than a decrease. In the context of DeepSeek R1:

• The low-cost model reduces hardware requirements, making AI operation more economical.
• The result is more businesses, researchers, and enthusiasts launching AI instances.
• Although the operating costs of a single instance have decreased, the surge in total volume may drive up overall computing power consumption (and costs).

However, this is not a negative sign. The widespread use of models like DeepSeek R1 marks a surge in successful popularization and application, which will drive:

• Ecological Prosperity: More developers improve open-source code functions, fix vulnerabilities, and optimize performance.
• Hardware Innovation: GPU, CPU, and dedicated AI chip manufacturers respond to surging demand, competing in terms of price and energy efficiency.
• Business Opportunities: Builders in areas such as analytical tools, process orchestration, and professional data preprocessing will benefit from the surge in AI usage.

Therefore, although the Jevons Paradox suggests that infrastructure costs may rise, it is a positive signal for the overall AI industry, promoting the development of an innovative environment and catalyzing breakthroughs in economic deployment.

The Impact on Decentralized Finance AI

DeFAI combines decentralized finance with AI automation, enabling agents to manage on-chain assets, execute multi-step transactions, and interact with DeFi protocols. This emerging field directly benefits from open-source low-cost AI because:

• Around-the-clock autonomy: The intelligent agent can continuously scan the Decentralized Finance market, bridge assets across chains, and adjust positions. Low inference costs make 24/7 operation financially viable.
• Unlimited Expansion: When thousands of DeFAI agents need to serve different users or protocols simultaneously, low-cost models like DeepSeek R1 can control operational expenses.
• Customization: Developers can fine-tune open-source AI using DeFi dedicated data (price feeds, on-chain analysis, governance forums) without paying high licensing fees.

With the DeepSeek R1 lowering the AI threshold, DeFAI forms a positive cycle:

• Smart Body Explosion: Developers create specialized robots (such as yield hunting, liquidity provision, NFT trading, cross-chain arbitrage)
• Efficiency Improvement: Each agent optimizes capital flow, which may enhance the overall activity and liquidity of Decentralized Finance.
• Industry Growth: More complex DeFi products are emerging, from advanced derivatives to conditional payments, all coordinated by easily accessible AI.

The final result is that the entire DeFi field benefits from the virtuous cycle of "user growth - agent evolution."

Outlook: Positive Signals for AI Developers

thriving open source community

After the DeepSeek R1 is open-sourced, the community can:

• Quick fix for vulnerabilities
• Propose reasoning optimization solutions
• Create domain forks (e.g., finance, law, healthcare)

Collaborative development brings continuous model improvement and spawns ecological tools (fine-tuning frameworks, model service infrastructure, etc.)

New Profit Path

AI developers in fields such as DeFi can break through the traditional API call charging model:

• Managed AI Instances: Offering enterprise-level DeepSeek R1 managed services, equipped with a user-friendly dashboard.
• Service layer construction: Based on open-source models, integrate advanced functions such as compliance review and real-time intelligence for Decentralized Finance operators.
• Smart Agent Market: Custodians with unique strategies or risk configurations for agent profiles, offering subscription or performance-sharing services.

When underlying AI technology can expand to millions of concurrent users without causing vendor bankruptcy, such business models will thrive.

Low threshold = talent pool expansion

As the demand for DeepSeek R1 decreases, more developers around the world can participate in AI experiments. This influx of talent:

• Inspire innovative solutions to solve problems in the real world and the crypto space.
• Enrich the open-source community with fresh ideas and improvements
• Release global talents that were once rejected due to high computing power costs.

Conclusion

The emergence of DeepSeek R1 marks a key turning point: open-source AI no longer requires expensive computing power or licensing fees. By providing powerful inference capabilities at a low cost, it paves the way for widespread adoption from small development teams to large enterprises. Although Jevons' Paradox suggests that infrastructure costs may rise due to surging demand, this phenomenon ultimately benefits the AI ecosystem, driving hardware innovation, community contributions, and advanced application development.

For DeFAI, AI agents coordinating financial operations on a decentralized network will create significant ripple effects. Lower costs mean more complex agents, stronger accessibility, and an ever-expanding array of on-chain strategies. From yield aggregators to risk management, these advanced AI solutions can operate sustainably, paving new paths for crypto adoption and innovation.

DeepSeek R1 demonstrates how open-source progress catalyzes the entire industry, and the same goes for AI and Decentralized Finance. We are standing on the threshold of the future: AI is no longer a tool for a privileged few, but will become a fundamental element of everyday finance, creativity, and global decision-making, driven by open models, economical infrastructure, and unstoppable community momentum.