The AI Investment Frenzy: A Survival Battle Behind Tech Giants' Spending Spree

The AI Investment Frenzy: A Survival Battle Behind Tech Giants' Spending SpreeThis week, tech giants have been caught in a whirlwind of AI investment-driven drama. Nvidia's stock price has been on a rollercoaster ride, plummeting 7% on Tuesday, only to soar nearly 13% the next day, adding $330 billion to its market cap and sending other tech stocks on a similar wild ride

The AI Investment Frenzy: A Survival Battle Behind Tech Giants' Spending Spree

This week, tech giants have been caught in a whirlwind of AI investment-driven drama. Nvidia's stock price has been on a rollercoaster ride, plummeting 7% on Tuesday, only to soar nearly 13% the next day, adding $330 billion to its market cap and sending other tech stocks on a similar wild ride. On Thursday, Nvidia plunged again by almost 7%. Behind this volatility lies the market's apprehension about AI investment returns and tech giants' determined commitment to "burning money" in a decisive battle.

The Shadow of Cost Behind the Volatility

Nvidia's wild fluctuations even eclipsed Bitcoin, with its 30-day implied volatility surging from 48% to 71%, while the Bitcoin DVOL index dropped from 68% to 49%, reflecting the market's anxiety about AI investment. As tech giants released their earnings reports, investors discovered that despite the staggering AI capital expenditure, revenue growth did not surpass expectations, failing to match the massive investment. Market patience began to wane, leading to a tech stock downturn.

Tech Giants' "Burning Money" Declaration

In the face of market concerns, tech giants have unequivocally declared their commitment to "burning money" in their AI endeavors. Meta released its second-quarter earnings, exceeding revenue and earnings expectations, but capital expenditure fell slightly short of projections. The upper limit of its full-year capital expenditure remained unchanged, but the lower limit was raised by $2 billion. Meta emphasized that capital expenditure would significantly increase by 2025 to support AI research and product development.

Microsoft also firmly stated its intention to continue increasing AI spending, with second-quarter capital expenditure rising by 77.6% year-on-year to $19 billion, nearly all allocated to AI-related areas. The company expects its annual capital expenditure to surpass $50 billion in fiscal 2024.

AI Investment Fuels Performance Growth

Tech giants have meticulously explained the benefits of AI investment during conference calls, attempting to alleviate investor concerns. Microsoft highlighted the impact of AI on Azure, noting that its Azure AI cloud service customer base increased by nearly 60% in the recent quarter, with average customer spending also rising. The company also explained the reason behind Azure's limited capacity, citing the high demand for AI GPU servers that is expected to persist until the end of the year, a testament to strong business demand for AI.

Meta emphasized how AI is driving growth in its advertising business. Mark Zuckerberg, during the earnings call, stated that AI has improved recommendation capabilities, helping people find more valuable content and enhancing the effectiveness of advertising experiences. These products have been scaled, resulting in a 22% increase in Meta's advertising revenue in the second quarter, twice the growth rate of competitor Google.

Analysts point out that AI strategies have helped Meta rise from its two-year slump, utilizing AI to rebuild its advertising technology stack, revamp the user interface, and boost user engagement, ultimately reflected in revenue and profit growth. Meta has successfully integrated AI into its ecosystem, overcoming previous concerns.

Sundar Pichai, CEO of Google's parent company Alphabet, also stated that the company had analyzed every dollar invested in AI and observed the significant momentum generated by these investments.

Strong Performance of Chip Stocks

Tech giants' resolute commitment to AI is bound to further increase hardware spending, including chips, benefiting Nvidia and other chip companies. US tech stocks witnessed a significant rebound, with Nvidia surging 13%, Broadcom jumping 12%, ASML ADR rising 8.89%, and Qualcomm closing over 8% higher.

Chip giants are also riding the AI wave to accelerate growth. AMD delivered outstanding second-quarter results, with data center revenue doubling and AI chips in high demand, surpassing the $1 billion milestone in quarterly revenue. Taiwan Semiconductor Manufacturing Company (TSMC) experienced a strong second quarter across the board, exceeding expectations in sales, net income, and gross margin.

TSMC CEO C.C. Wei stated that the company will more than double its production capacity for CoWoS, its advanced chip packaging technology, by the end of 2024. However, even with this expansion, demand is expected to outpace supply until 2025 or 2026.

AMD CEO Lisa Su also raised the company's 2024 revenue forecast for AI data center GPUs from $2 billion to over $4.5 billion. She further pointed out that despite increased production in the second half of the year, the AI GPU supply chain will remain "tight" until 2025.

AI Investment Has Become a Survival Issue

The market's apprehension about AI investment returns might be overlooking a crucial point: this is not just about incremental revenue generated by specific AI capabilities but rather a complete restructuring of the entire computing platform, akin to the shift from mainframes to personal computers in the 1980s. In this new era of AI computing, every company must upgrade its infrastructure to stay competitive.

For businesses, AI investment has become a survival issue rather than simply pursuing incremental profits. If competitors can provide better customer service through AI chatbots or leverage AI design tools to develop products faster and more comprehensively, companies that refrain from AI investment will face significant challenges.

Deutsche Bank, in its analysis, noted that revenue currently stems primarily from cloud computing businesses where companies train and run AI models. However, outside the cloud domain, signs of investment returns are more qualitative and difficult to quantify with specific numbers.

Tech giants have also expressed their preference for overinvestment rather than underinvestment, recognizing that lagging behind in the tech industry can mean "losing everything." Meta CEO Mark Zuckerberg stated that the company has spent billions of dollars on Nvidia GPUs to develop and train advanced AI models, ensuring Meta's leadership in AI.

Google CEO Sundar Pichai expressed a similar sentiment, acknowledging that AI is expensive but underinvestment poses a greater risk. Google might be overinvesting in AI infrastructure, but even if the AI boom subsides, the data centers and computer chips purchased by the company can be utilized for other purposes. For them, the risk of underinvestment far outweighs the risk of overinvestment.

Conclusion

Tech giants are resolutely "burning money" to build their AI capabilities, benefiting upstream chip companies. However, the market remains apprehensive about downstream monetization capabilities. AI investment is no longer just about chasing incremental profits; it has become a survival issue. Whether tech giants can demonstrate that AI investment can generate tangible returns will be a key question to closely observe in the coming years.