Meta's Muse AI hit by zero-day flaw, OpenAI halts training, Goldman says tech giants need $300B revenue

Muse, the Hottest New AI, Encounters Major Setbacks

Just weeks after its high-profile launch, Meta's new AI assistant Muse—which had briefly revitalized the AI sector—is facing serious problems. The consumer-grade agent has yet to surpass one million daily active users and has already been flagged as "Degraded" by third-party status platform SaaSHub.

Critical Security Vulnerability Exposed

A zero-day vulnerability has been discovered in Muse, potentially allowing attackers to hijack entire Apple Mac computers. macOS security expert Patrick Wardle disclosed the flaw on social media, warning that it enables local malware or attackers to take control of a user's Mac device without their knowledge.

As of now, Meta has not yet patched the zero-day vulnerability, though industry observers expect a fix to be released soon.

Additional Blows

On the same day the vulnerability was disclosed, Amazon officially announced it would prohibit Meta's Muse AI assistant from performing shopping checkout operations on its e-commerce platform on behalf of users.

Performance and Scalability Issues

Muse's operational problems have emerged in parallel with its underwhelming user adoption:

• Daily Active Users (DAU): Fewer than 1 million, falling short of expectations
• Resource Consumption: Actual runtime resource usage is approximately 10 times the internal testing standard
• Status: SaaSHub has marked Muse's operational status as "Degraded"
• Common User Complaints: "Unable to search" is a frequently reported issue
• Stress Test Failure: During a test, the platform attempted to create 120 sub-agents simultaneously; only 33 succeeded, while 87 failed

Industry Analysis

Analysts point out that Muse's problems reflect broader development bottlenecks in the personal AI agent赛道, including:

• General computing capacity
• Memory and storage adaptation
• Browser isolation and security monitoring
• Concurrent task orchestration
• Cost and technical challenges

For Muse to achieve long-term viability, it must overcome three core hurdles:

1. Operational success rate
2. Unit operating cost
3. Commercial user retention

Without breakthroughs in these areas, the product risks becoming a costly technical experiment.

Stock Market Warnings for AI Sector

High AI Revenue Targets for Tech Giants

Goldman Sachs strategist Ryan Hammond has calculated that tech giants including Amazon, Oracle, and Microsoft will need to generate approximately $300 billion in AI-related revenue over the next several years to cover their AI investment costs. Hyperscale data centers remain far from achieving this profitability goal.

Key data points:

• Top hyperscale cloud service providers are expected to see strong revenue growth, with annualized revenue projected to be $70 billion higher by Q2 2026 than pre-AI trends would suggest
• The industry has reported over $1.5 trillion in accumulated backlog orders
• Hammond estimates that AI users would need to spend roughly $1 trillion annually on AI applications for hyperscale operators to achieve meaningful returns on investment and for the application layer to generate strong margins on computing expenditure

Macro Financial Headwinds

According to MarketWatch, a Bank of America report by analyst Michael Hartnett's team released on the 25th reveals concerning market signals:

• The MOVE Index, which measures expected volatility in U.S. Treasury bonds, surged 33% in just two trading days
• Hartnett warns that the U.S. Treasury market serves as the core benchmark for global lending markets; a rapid rise in its volatility is a negative signal for overall financial markets
• If the MOVE Index continues to climb, combined with a significant decline in the iShares S&P Global Financials Index Fund, stock markets will face further downward pressure
• Hartnett also cautioned that even if a U.S.-Iran agreement pushes oil prices down another $10 per barrel, rising Treasury yields could still trigger intensified risk-off selling in equities

Supply Chain Concerns

A separate negative development involving the optical module supply chain has also circulated widely among investors over the weekend.

Broader Implications

According to CCTV News, OpenAI has paused the training, evaluation, and inference (including tool calls) of its latest-generation AI model.

Analysts believe these three major variables will not only complicate the supply chain but also slow the pace of AI infrastructure deployment in the United States. The AI-related stock sectors may face renewed challenges.