Recently, Google's self-developed artificial intelligence The announcement of external availability of its Tensor Processing Unit (TPU) chip propelled the company's market capitalization to nearly $4 trillion, earning it the moniker of "new AI king." This breakthrough was interpreted by the market as a significant blow to Nvidia . The challenge to the dominance of graphics processing units (GPUs) has injected new momentum into the AI industry, which was shrouded in uncertainty. It has also brought new choices and competitive vitality to the market, marking that the AI industry is developing from a relatively concentrated pattern to a more diversified one.
In my opinion, the impact of Google's move on the AI industry can be viewed from the following three aspects.
From a technological perspective, this reveals the healthy evolutionary direction of the AI industry.
Google's commercialization of its TPU by supplying external vendors is not simply a matter of product competition; it's more like a "catfish effect" in the AI hardware field, further activating the AI market and propelling computing power towards a new, diversified, and symbiotic ecosystem. Healthy technological evolution involves building a mutually supportive technological system, which is the core lesson the "new king of AI" offers to the industry. For the entire AI industry, this reduces dependence on a single supplier, forces industry innovation through technological competition, drives technological progress and cost reduction, ultimately benefiting all participants in the industry chain and providing the most solid foundation for the AI industry.
From the perspective of industry evolution, this is a sign that AI hardware is maturing.
Regardless of whether GPUs or TPUs ultimately prevail, the competition for computing power brings structural benefits to the upstream supply chain, including optical modules and PCBs . Hardware components, driven by technological iterations, have seen unexpected growth. Against this backdrop, leading domestic manufacturers have achieved global competitiveness in customer response speed, mass production stability, and cost control.
As the core carrier for the implementation of AI technology, the maturity of hardware directly determines the depth and breadth of industrial evolution. The computing power of hardware has transformed the concept of "AI in all hardware" into reality. Just as the PC industry evolved after the internet revolution, the maturity of AI hardware is reflected in the dual achievement of technological autonomy and performance breakthroughs, driving the value reconstruction of all terminal devices. Amidst the "AI bubble" controversy, this hardware revolution sends a clear signal: true industrial vitality stems from the dual drive of technological breakthroughs and healthy competition.
From a business perspective, this shows that the competition in AI is shifting from model performance to application implementation.
In fact, Google's breakthrough is an inevitable result of the harvest period for its decade-long closed-loop system of "computing power foundation (TPU) - core model (Gemini) - business ecosystem (search + cloud + terminal)". When hardware can form a synergistic closed loop with models and applications, the AI industry will truly have the ability to create value at scale.
The AI industry is currently at a critical turning point. While competition in computing infrastructure is fierce, the real breakthrough lies in the implementation of applications, which will spawn new supply chains and bring new growth opportunities to relevant partners.
The second half of the AI competition is no longer about comparing parameters in laboratories, but about value creation in industrial scenarios. Of course, application implementation still faces structural challenges such as high costs and data scarcity, but this precisely highlights the necessity of technological updates. Only through large-scale application to spread costs, accumulation of data through scenario practice, and iterative engineering to improve solutions can AI truly complete the transition from technology to application. As the computing power market shifts from relying on a single technological path to multi-technology collaboration, the AI industry is gradually finding the optimal balance between efficiency and innovation in this multi-faceted competition, thus continuously injecting lasting momentum into industrial development.
(Source: Securities Times) daily)
