The capital market's fascination with AI shows no signs of diminishing. This is clearly reflected in the performance of listed large-scale model developers and the persistent interest from investment institutions in companies such as DeepSeek and Kuaishou Kling. Despite the enduring enthusiasm for AI concepts in the capital market, the focus of industry participants has transitioned from leveraging early-mover advantages to competing on current implementation and application fronts.

AI elements are increasingly permeating traditional industries, with a surge in the incubation and innovation of AI models. AI has evolved from its initial phase of capital infusion to a stage of self-sustaining growth. On one hand, this signifies the continuous maturation and enhancement of AI; on the other, it underscores that AI's future hinges on deep commercial integration. As AI enters a new cycle, industry players are expanding their focus beyond traditional metrics and benchmarks to addressing real-world challenges.

The new challenge for industry participants lies in integrating AI with various sectors and creating novel business models that cater to evolving demands. This not only pertains to AI's own advancement and upgrading but also to the industrial transformation it sparks. Identifying innovative solutions in this new AI cycle is crucial for achieving fresh growth.

AI Begins to Unleash Increasing Potential

Previously, discussions about AI revolved around capital and technology. The growth prospects of AI developers and the technological prowess of AI products were primary considerations. As AI matures and gains broader acceptance following initial educational phases, it has transformed from a mere spectacle to a sustainable source of value and dynamism.

In this context, AI is demonstrating escalating potential. On one hand, it significantly boosts production and living efficiency; on the other, it continuously generates new business models. AI's influence now extends beyond its own domain to encompass more fields and scenarios.

As AI showcases more potential, it attracts increasing capital and fosters deeper industry connections. For AI developers, the pivotal issue in this new cycle is how to consistently unleash new potential and empower more industries and scenarios, triggering industrial iteration and upgrading to generate greater value.

At this juncture, the true test for industry players is achieving a harmonious interplay between AI's commercial value and capital input-output. Only those who strike this balance and continuously unlock AI's greater potential can achieve fresh growth in this new phase.

AI's Iteration and Evolution Gain Momentum

If early AI development resembled sparks, current AI can be likened to a thriving garden. The pace of AI's iteration and evolution, as well as the emergence of AI products, has accelerated significantly. As AI enters this new cycle, industry players must adopt fresh strategies to navigate these changes.

Previously, attention centered on AI's parameter strength and product iteration speed. Now, with AI's rapid development, the focus has shifted to the depth of product-commercial integration and the magnitude of AI's value.

Therefore, AI developers must not only monitor traditional indicators but also contemplate how to maximize their value and address real-world industry challenges. Only by aligning AI's iteration speed with its value demonstration can AI take root in industries rather than remaining a fleeting phenomenon.

Thus, AI's accelerated iteration and evolution now also hinge on how swiftly AI can penetrate industries and unleash its value. Only then can AI's frontend and backend truly resonate, providing tangible long-term returns to the capital market beyond mere rhetoric.

AI Emerges as Infrastructure in the New Industrial Era

Another key reason for the sustained capital fervor in the AI sector is AI's emergence as a new type of infrastructure, supplanting the internet in the new industrial era. In essence, AI is becoming a ubiquitous feature across nearly all industries.

This assessment stems from the fact that AI is not just a concern for tech developers but also for traditional industry players. Phenomena such as smart manufacturing, intelligent logistics, smart healthcare, and intelligent transportation all reflect this trend. Behind these phenomena, AI is transforming not only internet-based tech industries but also traditional sectors like manufacturing, logistics, healthcare, and education.

As AI becomes a common focus for internet and traditional industry players, seemingly disparate industries are now interconnected through AI, revealing the potential for digital-physical integration. If we consider this era of deep industrial integration as the new industrial era, then AI is precisely the new type of infrastructure for this era.

For capital players, seizing the opportunity of AI becoming new industrial infrastructure and identifying developers who can implement their products in more industrial scenarios through capital investment may yield far greater prospects than traditional sector or player investments. This explains the sustained high capital market enthusiasm for AI as it enters a new cycle.

Conclusion

Although AI's deployment has long surpassed its early "angel round," capital investment in AI remains highly enthusiastic. Behind this fervor, we witness AI entering a new cycle. In this cycle, the true test for industry players is not just AI parameters but their ability to implement AI in specific industrial scenarios and make it the infrastructure for the new industrial era. For players, leveraging AI as a catalyst to drive industrial transformation and upgrading, thereby unleashing greater value, may be the key to continuing to attract attention from primary and secondary markets.