Meta (META.US) Muse detonates technology stocks! The Philadelphia Semiconductor Index rose for five consecutive days, and AMD (AMD.US) joined the “trillion dollar club”

The Zhitong Finance App learned that the semiconductor sector of US stocks collectively surged on Monday. Muse, an AI smart device newly launched by Meta Platforms (META.US), was initially sought after by consumers, igniting market expectations of a surge in demand for computing power after large-scale popularization of AI agents, and a massive influx of capital into chip stocks such as AMD (AMD.US), Intel (INTC.US), and Arm (ARM.US).

Among them, AMD surged nearly 10% on Monday, and its market capitalization broke through the $1 trillion mark for the first time; Intel rose more than 12%, and Arm Holdings (ARM.US) surged more than 17%. The Philadelphia Semiconductor Index rose 4.3%, rising for the fifth consecutive trading day.

Meta shares also surged more than 11%, the biggest one-day increase since April 2025. At the time, US President Trump announced the suspension of the tariff measures that had previously disrupted the market for 90 days, driving a sharp rebound in US stocks.

The strong rise in chip stocks also led to an overall rise in major US stock indices. The S&P 500 index rose nearly 1.5% on Monday, the best one-day performance since the beginning of August; the Nasdaq 100 index, which accounts for relatively high technology stocks, rose 2.8% to close at its highest level since June.

In addition to market optimism about AI chip demand, falling oil prices and falling US bond yields also provided support for the stock market, and investors' expectations for progress in ending the war with Iran are heating up.

Muse reaches the top of the App Store AI smart device ignites a new round of computing power demand expectations

The direct catalyst for this round of tech stock gains comes from Meta's personal AI agent Muse, which was launched earlier this month.

After its launch, Muse quickly climbed to the top of the Apple (AAPL.US) App Store free app rankings, showing initially strong consumer demand. This performance has reignited the market's imagination for the popularity of AI agents, and further expanded investors' focus from GPUs required for AI model training to computing resources such as CPUs required for AI agents to operate.

Meta released Muse earlier this month and positioned it as a personal AI agent capable of directly performing tasks on behalf of users. Compared to traditional chatbots that are mainly responsible for generating text or answering questions, Muse can help users complete practical tasks such as online shopping, buying movie tickets, and reserving services.

Wedbush analyst Matthew Bryson said that AI agents rely on a large number of computation-driven applications, and in this market, major computing vendors include Intel and AMD.

This also explains why AMD and Intel are among the chip companies with the most prominent increases in the AI market.

Notably, Meta itself is also an important AMD customer. According to the data, Meta is AMD's second-largest customer, contributing about 5.5% of AMD's revenue. Therefore, if Meta continues to expand investment in infrastructure related to AI agents, AMD may become one of the direct beneficiaries.

However, Muse's rapid expansion has also begun to face resistance from other internet platforms. An Amazon (AMZN.US) spokesperson said the company had blocked Muse AI agents from accessing its retail website on Sunday evening.

From GPUs to CPUs, Wall Street is betting on a new computing power cycle for AI agents

The previous generative AI investment boom mainly revolved around GPU vendors such as NVDA.US (NVDA.US), and after Muse was sought after by consumers, the market began to pay more attention to another type of computing power demand that AI agents may bring.

Compared with traditional chatbots, AI agents not only need to generate answers, but also understand user goals, plan tasks, call different applications and tools, and continuously perform a series of operations. This means that if AI agents end up being adopted by large-scale consumers, the reasoning, task orchestration, and server infrastructure workloads behind them are likely to increase.

Jefferies analyst Jacky He said that as AI agents gain wider consumer adoption, higher AI reasoning, task orchestration, and infrastructure workloads are expected to drive server CPU demand growth.

This logic is driving investors to re-evaluate the value of CPUs in AI infrastructure, and is driving shares of related companies such as AMD, Intel, and Arm to rise sharply.

AMD rose by about 30% in a single month and officially joined the “trillion dollar club”

For AMD, Monday's rise was another landmark, with the company's market capitalization surpassing $1 trillion for the first time. Previously, AMD stock prices were under pressure as investors worried about the continuation of the AI investment boom and the return on huge AI capital expenses. From the June high to the July low, the stock dropped by nearly 26% cumulatively. However, market sentiment has clearly reversed in recent weeks. As of Monday, AMD has accumulated a cumulative increase of about 30% in September, and is expected to record its best monthly performance since May.

As the market capitalization surpassed 1 trillion US dollars this time, AMD also officially joined the “trillion dollar market capitalization club” of the global chip industry. Currently, many semiconductor companies, including Nvidia, Micron (MU.US), Broadcom (AVGO.US), and TSM.US (TSM.US), have reached or exceeded $1 trillion in market capitalization.

According to the data, in addition to the chip companies mentioned above, there are currently 15 listed companies in the world with a market capitalization of at least 1 trillion US dollars.

Judging from broader market logic, the rapid popularity of Muse is driving investors to rethink the AI industry's computing power demand structure in the next stage. AI investments in the past few years have mainly revolved around large model training and GPUs, and as AI gradually moves from “answering questions” to “performing tasks for users,” the importance of infrastructure such as inference, task orchestration, and server CPUs may further increase.

If AI agents such as Muse can further evolve from early consumer popularity to large-scale daily applications, the growth momentum of AI computing power demand may also expand from model training to intelligent workloads that continue to operate, and whether CPU vendors such as AMD and Intel can obtain substantial revenue growth from this trend will be the focus of the market's next phase of attention.