How AI Drives the Development of DeFi: Looking at the Power of Open Source AI from DeepSeek R1

Artificial intelligence is accelerating development in various fields, including Decentralized Finance ( DeFi ). However, the cost and complexity of deploying AI models on a large scale remain major obstacles. DeepSeek R1 has emerged as a new type of Open Source AI model that provides powerful inference capabilities at a lower cost, paving the way for large-scale applications.

This article will explore the breakthroughs of DeepSeek R1 in Open Source AI inference, how low-cost inference drives widespread adoption, the potential impacts of efficiency improvements, and how DeFi can benefit from the popularization of AI.

DeepSeek R1: Redefining Open Source AI

DeepSeek R1 is a new large language model (LLM), optimized for reasoning and context understanding. Its main features include:

• Efficient Architecture: Utilizes a new generation parameter structure to achieve near top-tier performance in complex tasks without the need for a large GPU cluster.

• Low hardware requirements: Supports running on a small number of GPUs or even high-end CPU clusters, lowering the usage threshold.

• Open Source License: A permissive license allows for direct integration into products, promoting rapid adoption and customized development.

This trend of AI democratization is similar to early open source projects like Linux and Apache, which are expected to drive exponential growth in the technology ecosystem.

The Value of Low-Cost AI

Accelerate Popularization

When high-quality AI models achieve economic operation:

• Small and medium enterprises can independently deploy AI solutions without relying on expensive services.
• Developers can freely experiment with innovative projects within the budget.
• Emerging market companies can seamlessly access AI, narrowing the digital divide.

Democratic Inference

Low-cost inference not only drives usage but also realizes the democratization of inference:

• Small communities can train customized models using domain-specific language or data.
• Developers can build advanced plugins, such as code analysis, on-chain transaction verification, etc.

Overall, cost savings will spur more experiments and accelerate the overall innovation of the AI ecosystem.

Impact of Efficiency Improvement

Economic theory suggests that efficiency improvements often lead to increased rather than decreased resource consumption. In the context of DeepSeek R1:

• The low-cost model reduces hardware requirements, making AI operation more economical.
• More enterprises and researchers will launch AI instances.
• Despite the decrease in single-instance costs, the surge in total volume may drive up overall computing power consumption.

However, this phenomenon is not necessarily negative. The widespread use of AI models signifies successful adoption, which will drive:

• Ecological Prosperity: More developers participate in perfecting functions and optimizing performance.
• Hardware Innovation: Chip manufacturers are competing in terms of price and energy efficiency.
• Business Opportunities: Analytical tools, process orchestration, and other fields will benefit from the AI boom.

Impact on DeFAI

DeFAI combines Decentralized Finance with AI automation, enabling agents to manage on-chain assets and execute complex transactions. This emerging field directly benefits from Open Source low-cost AI:

• 24/7 Autonomous: Smart agents can continuously scan the market and adjust strategies, making around-the-clock operation possible at low cost.
• Unlimited Expansion: Low-cost models can control the operational expenses of thousands of agents.
• Customization: Developers can fine-tune AI with DeFi-specific data without high licensing fees.

With DeepSeek R1 lowering the AI threshold, DeFAI will form a positive feedback loop:

• Smart Entity Explosion: Developers create specialized robots, such as yield hunting and cross-chain arbitrage.
• Efficiency Improvement: Optimize capital flow to enhance the overall activity and liquidity of DeFi.
• Industry Growth: More complex DeFi products emerge, coordinated by easily accessible AI.

Ultimately, the entire DeFi field will benefit from the virtuous cycle of "user growth - agent evolution."

Outlook: Opportunities for AI Developers

thriving Open Source community

After the DeepSeek R1 is Open Source, the community can:

• Quick Fix for Vulnerabilities
• Propose inference optimization plan
• Create domain forks (e.g., finance, law, healthcare)

Collaborative development will bring continuous model improvement and give rise to ecological tools.

New Profit Path

AI developers in fields such as DeFi and others can explore new business models:

• Provide enterprise-level custody services
• Integrate advanced features such as compliance review, real-time intelligence, etc.
• Custody smart agent profiles, providing subscription or performance sharing services

Talent Pool Expansion

As the barriers lower, more developers around the world can participate in AI experiments, which will:

• Inspire innovative solutions to real-world problems
• Enrich the Open Source community with new ideas
• Unlock global talent that was previously excluded due to high costs.

Conclusion

The emergence of DeepSeek R1 signifies that Open Source AI no longer requires expensive computing power or licensing fees. It paves the way for widespread adoption, driving hardware innovation, community contributions, and advanced application development. For DeFi, low-cost AI translates to more complex agents, greater accessibility, and an ever-expanding on-chain strategy.

We are standing at the threshold of the future: AI will become a fundamental element of everyday finance, creativity, and global decision-making, driven by open models, economical infrastructure, and community momentum.