In mid-September 2026, the global artificial intelligence (AI) industry reached a dual turning point in both technology and capital deployment. Regarding the capital market, Silicon Valley venture capital firms are shifting their focus from pure software applications to "Deep Tech" sectors, such as semiconductors and robotics, involving billions of dollars. According to market observations, these hardware technologies, which require long-term research and development and are capital-intensive, are now viewed as the core infrastructure supporting the operation of large language models (LLMs) and future AI development.

On the industrial application side, xAI founder Elon Musk publicly released the latest technical roadmap via social media on September 17, officially predicting that Grok 5 will feature 2.5 trillion parameters and claiming that the model will serve as the final destination for achieving Artificial General Intelligence (AGI).

Facts confirmed by multiple sources indicate that the momentum of AI industry development has shifted entirely from simple software development to an extreme pursuit of computing power and hardware infrastructure. Silicon Valley venture capital data shows that hardware companies have accounted for nearly one-third of total U.S. venture capital allocation this year, primarily because the training and inference processes of LLMs have led to an exponential increase in demand for advanced chips and data center hardware. At the same time, Musk revealed xAI's technical evolution strategy, emphasizing that Grok 5 will fully transition its underlying architecture to a C++ software stack, aiming to squeeze out hardware performance to meet massive computing demands—a move that aligns with the trend of Silicon Valley capital flowing into hardware infrastructure.

However, there remain significant differences in the processes and definitions of AI development across various sectors. Although Musk has publicly claimed that Grok 5 will be the completed form of AGI and has admitted that the current version, Grok 4.7, still has technical flaws and room for improvement, academia and the industry have yet to reach a consensus on the specific definition and timeline for achieving "AGI." Furthermore, despite the billions of dollars Silicon Valley venture capital has invested in deep tech, these investments are largely long-term R&D in nature, and whether they can be converted into commercially profitable products in the short term remains to be verified by the market.

Meanwhile, reports from the Taiwanese financial sector indicate that AI-driven exports and semiconductor demand have become key drivers of economic growth. However, whether these hardware advantages can continue to translate into profit momentum for the banking industry remains influenced by both global geopolitics and expectations of moderate economic growth.

This wave of AI-driven hardware resurgence and technological competition has had a profound impact on North American and global supply chains. In North America, as large tech companies see a surge in demand for computing power, energy supply and data center construction have become the focus of policy and industry. For instance, energy companies such as Engie North America are playing an increasingly critical role in power infrastructure to meet the massive demand for stable electricity from AI computing centers. For Taiwan, the launch of investment attraction projects like the Taoyuan Asia Silicon Valley Research and Development Center indicates that the government is attempting to extend Taiwan's advantages in semiconductor front-end manufacturing into an AI application innovation hub to cope with the reconfiguration of global supply chains.

Despite high market sentiment, analysts warn against over-interpreting the technical declarations of a single company. While Musk’s expectations for Grok 5 have sparked significant market attention, the realization of AGI involves complex cognitive science and computational limits, which cannot be achieved solely by increasing parameter scale. Furthermore, although venture capital is flooding into the hardware sector, deep tech startups face extremely high technical barriers and long investment recovery periods. If global economic growth falls short of expectations or geopolitical issues lead to supply chain disruptions, the construction progress of related hardware facilities may be affected. Investors should pay attention to the gap between technical indicators and actual commercial implementation to avoid blindly chasing market trends.

Future observations will focus on three areas: First, whether xAI can complete the training of Grok 5 as scheduled and verify its AGI capabilities, which will directly affect the pace of the global AI arms race; second, whether the billions of dollars in venture capital invested by Silicon Valley in the semiconductor and robotics sectors can spawn next-generation hardware architectures with market competitiveness; and finally, the progress of North American energy policy and data center construction, particularly whether power supply will become a bottleneck limiting the expansion of AI computing power. These factors will collectively determine the development trajectory and market landscape of the global AI industry in the second half of 2026.