According to the Zhitong Finance APP, technology companies such as Apple (AAPL.US), Dell (DELL.US), Hewlett Packard Enterprise (HPE.US), and Seagate (STX.US) became the core focus of the U.S. stock market on Tuesday. This follows a recent report released by the well-known Wall Street investment firm Bernstein, which stated that the development trend of artificial intelligence technology, especially the trillion-dollar &#34;super blue ocean&#34; expected from the massive AI inference systems by 2030, should bring long-term benefits to these large tech companies focused on IT hardware and consumer electronics.
Undoubtedly, the global cloud computing giant Oracle, which recently announced a contract reserve of $455 billion that far exceeded market expectations, and the global AI ASIC chip &#34;super giant&#34; Broadcom, which reported strong performance and future outlook last week, have significantly strengthened the &#34;long-term bull market narrative&#34; for AI computing infrastructure sectors such as AI GPUs, ASICs, and HBM. The AI computing demand driven by generative AI applications and AI agents at the inference end can be described as &#34;starry seas,&#34; and is expected to drive the artificial intelligence computing infrastructure market to continue showing exponential growth. The &#34;AI inference system&#34; is also considered by Jensen Huang to be the largest source of future revenue for NVIDIA.
According to Wall Street investment giants Loop Capital and Wedbush, the global investment wave in artificial intelligence infrastructure centered on AI computing hardware is far from over and is only at the beginning. Under the unprecedented &#34;AI computing demand storm,&#34; this round of AI investment wave is expected to reach as high as $2 trillion. NVIDIA CEO Jensen Huang even predicts that by 2030, AI infrastructure spending will reach $3 trillion to $4 trillion, and the scale and scope of its projects will bring significant long-term growth opportunities for NVIDIA.
Apple is the &#34;best entry point for the AI inference revolution,&#34; and Dell benefits from the growth in AI server shipments.
Since September 11, Apple's stock price has performed well, rising more than 5% during this period and recovering all losses from early September. According to pre-order data tracked by Goldman Sachs from Apple.com, globally, the delivery times for all models of the iPhone 17 are longer than those of previous models, highlighting that although the newly released iPhone 17 was criticized by some users for lacking highlights after the launch event, the actual pre-order demand is very strong driven by AI and performance upgrades, with the standard and Pro Max models seeing the most significant increases in delivery times, extended by 8 days respectively. The performance in the mainland Chinese market is particularly outstanding, with average delivery times increasing by 17 days, reaching a waiting period of 27 days.
Apple CEO Tim Cook recently defended the enduring strong influence of the iPhone, stating that even with the emergence of complementary smart electronic devices, the iPhone will remain the core of people's lives in the upcoming fully opened artificial intelligence era.
&#34;Although there are still short-term concerns about an AI bubble in the market, we believe that IT hardware and consumer electronics still have significant upside potential in the long term,&#34; wrote the analyst team from Bernstein. &#34;Although there is a huge uncertainty range in the results, in our baseline forecast scenario for 2030, we conservatively set the scale of enterprise-side inference costs at about $1.3 trillion (implying an expected compound annual growth rate of about 67% during the period from 2025 to 2030)
&#34;We believe that continuous improvement and iterative updates of the model are key leading indicators, and we remind that large-scale capital expenditures may be a lagging indicator. In addition to maintaining a positive outlook on the long-term prospects, we also believe that the recent early signs of the booming development of artificial intelligence remain healthy, and overall we still hold a positive view on this theme,&#34; said the Bernstein analyst team.
As for Apple, the agency stated that this tech giant, which boasts consumer electronics lines such as iPhone and iPad, is &#34;one of the best entry points for the artificial intelligence reasoning revolution.&#34; Bernstein's analyst team believes that under the leadership of Tim Cook, this tech giant has the most optimal layout for artificial intelligence in the sector and is one of the most likely to benefit, but the agency also noted that if Apple's execution is poor, the risks are also the greatest.
According to statistics, the number of active devices in the Apple ecosystem has reached 2.35 billion, which means that once reasoning capabilities are integrated at the system level, developers can &#34;plug and play&#34; to reach a vast number of end users, which is the core engineering advantage of the &#34;artificial intelligence entry.&#34; Apple's AI application tool—Apple Intelligence is designed by Apple to prioritize local operation, only calling larger models through Private Cloud Compute (PCC) when necessary, and moving Apple's terminal security model &#34;to the cloud,&#34; providing verifiable transparency and minimal data residency, which is highly attractive for building sensitive scenarios (personal and enterprise data).
Dell Technologies and HPE are also expected to become long-term beneficiaries of the AI investment theme, as Bernstein believes that the significant expansion of AI server shipments should drive &#34;substantial&#34; profit and free cash flow growth. However, the agency holds a more cautious view on another AI server leader, Supermicro (SMCI.US), believing that the company faces &#34;execution challenges and valuation concerns.&#34;
AI server giant Dell, along with its major competitor Supermicro, has recently been ramping up production capacity to manufacture AI server clusters equipped with NVIDIA's latest version of AI GPUs—namely the Blackwell-based B200/GB200, as well as the more advanced BG300 AI server clusters, to win larger-scale business from companies building and using artificial intelligence applications. Many generative AI applications that drive models like ChatGPT, Claude, and Sora require immense data processing capabilities and increasingly expanding hardware AI computing resources.
Through years of close cooperation with NVIDIA, Dell utilizes the latest NVIDIA GPUs and integrates a full suite of CUDA acceleration tools to provide powerful GPU acceleration capabilities for AI training/inference workloads, which are essential technical components for global enterprises to deploy AI technology. Therefore, Dell's deep partnership with NVIDIA ensures the highest priority for optimal integration and performance optimization of hardware and software.
The two storage giants—Seagate and SanDisk are also favored by Bernstein
In addition, Bernstein's analyst team pointed out that the massive demand for AI reasoning computing power has undoubtedly led to a long-term surge in data storage demand, and the agency believes that Seagate (STX.US) and SanDisk (SNDK.US) are likely to be seen by the market as the storage product providers that benefit the most from the surge in storage demand
As of Monday's close on Wall Street, NAND flash memory leader SanDisk has seen an astonishing 500% increase in its stock price this year. Storage giant Western Digital, which provides hard disk drives (HDD) and NAND flash/SSD products, has risen 128% during the same period. One of its largest storage competitors, the global HDD leader Seagate Technology, also recorded a strong increase of 148%.
Amid an unprecedented wave of AI infrastructure frenzy, with large enterprises and government departments investing heavily in AI, the demand for core storage chips closely related to artificial intelligence training/inference systems remains extremely robust, driving significant revenue growth in Micron's data center business, including HBM storage systems, server-level DDR5, and enterprise-level SSDs.
As breakthrough AI applications such as AI agents penetrate various industries worldwide, leading to massive &#34;AI inference computing power demand,&#34; the future prospects for demand in AI computing infrastructure fields, including AI chips, HBM storage systems, enterprise-level SSDs, and high-performance networking and power equipment, remain vast. The urgent need for companies to improve efficiency and reduce operating costs has recently greatly accelerated the widespread application of two core categories of AI application software—generative AI applications and AI agents. The emergence of AI agents signifies that artificial intelligence is evolving from an information assistance tool into a highly intelligent productivity tool.
AI agents, represented by OpenAI Deep Research and Manus, can automate repetitive tasks, perform big data analysis and summarization based on incredibly powerful AI large models, provide real-time monitoring insights, and make appropriate decisions in extremely complex situations in a very short time, thereby enhancing operational efficiency for businesses. The logic of efficiency improvement is fundamentally similar for personal learning and work efficiency. AI agents can also efficiently participate in all phases of large projects across various fields globally, significantly accelerating project progress.
&#34;We expect data center storage to continue growing at a compound annual growth rate of about 23% until 2030, with both HDD and NAND manufacturers benefiting significantly from the sustained surge in storage demand driven by AI inference,&#34; wrote Bernstein's analyst team. &#34;In the [hard disk drive] sector, the relatively stable oligopoly should bring robust profit and free cash flow growth, with Seagate, which leads in HAMR technology, in the best position. In NAND, as the 'new storage paradigm' fully penetrates, SanDisk should achieve significant profit growth.&#34;
Finally, the institution also provided exclusive insights and comments on the quantum computing revolution, stating that the established American tech giant IBM (IBM.US) may ultimately become an industry leader in the field of quantum computing. &#34;Although seen as a traditional player on the decline, IBM's substantial investment in quantum computing innovation is beginning to yield some returns, driving the institution's performance back onto a growth track,&#34; analysts wrote in a report

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Bernstein released a research report stating that artificial intelligence will drive long-term benefits for technology companies such as Apple, Dell, and Seagate, with an expected trillion-dollar market for AI inference systems by 2030. The demand for AI computing infrastructure is surging, and investment scale could reach $2 trillion. NVIDIA CEO predicts that AI infrastructure spending will reach $3 trillion to $4 trillion, with Apple seen as the best entry point for the AI inference revolution, and its stock price has risen over 5% since September 11

- Major tech companies like Apple, Dell, HPE, and Seagate are in focus as Bernstein highlights the potential trillion-dollar AI market by 2030, benefiting IT hardware and consumer electronics firms.  
- The report emphasizes the exponential growth in AI infrastructure demand, predicting a $2 trillion investment wave, with Nvidia's CEO forecasting $3 to $4 trillion in AI spending by 2030.  
- Apple is seen as a key player in the AI revolution, with strong pre-order demand for the iPhone 17, while Dell and HPE are expected to benefit from increased AI server shipments.

Bernstein outlines the 2030 technology landscape: AI reasoning dominates the trillion-dollar blue ocean, betting on Apple, AI servers, and storage