Big Tech Earnings: AI Spend, China, and Chip Stocks in Focus

This week is set to be a pivotal one for the tech industry as major players like Alphabet, IBM, Intel, and Tesla prepare to release their second-quarter earnings reports. The market is abuzz with anticipation, particularly concerning the significant investments being made in artificial intelligence (AI). Nathan Hager, co-host of Bloomberg Daybreak, and Bailey Lipshultz, a Bloomberg senior equities reporter, joined "Bloomberg This Weekend" to break down what investors should be looking for.

StartupHub data

Companies working on this

Profiles of the companies named in this story, with funding and a one-liner from our database.

OpenAI

Private / $100B+ est

OpenAI is an AI research and deployment company dedicated to ensuring that artificial general intelligence benefits all of humanity.

Meta

$40.1B

Leading social media and technology platform connecting billions of people globally.

Tesla

$7.7B

Designs, manufactures, and sells electric vehicles, battery energy storage, and solar energy products.

Alphabet

$48.0B

AI-driven cloud computing startup for intelligent automation and data insights.

AI Spending and Hyperscaler Investments

Hager set the stage by noting the considerable anxiety surrounding AI spending. "I think one of the first things we're going to learn in terms of the CapEx is... we've seen so much projection into how much of these companies, these four major hyperscalers, are going to be spending over the next year, projecting something like, what, $725 billion," he said. The focus will be on how Alphabet, reporting on Wednesday, frames the investment narrative for the following week's reports from Meta, Microsoft, and Amazon.

The China-US AI Divide

The conversation then shifted to the international AI landscape, specifically the dynamic between the US and China. Lipshultz shared a compelling observation: "With China, you've got a closed state that has a very open approach to to AI. And here, it's the opposite. You've got an open society, and yet these kind of closed-off companies that are doing all the pioneering work on AI." This contrast raises fundamental questions about the future of AI development, including the cost of tokens and the efficiency of different models.

The full discussion can be found on Bloomberg Podcast's YouTube channel.

The debate centers on whether a "race to the bottom" is occurring, particularly regarding the cost-effectiveness of Chinese AI models compared to those from US-based companies like Anthropic and OpenAI. "The argument, David, when you look even at just at the cost of tokens or the cost of performing kind of menial tasks, it's so cheap," Lipshultz noted. However, she also pointed out the ongoing uncertainty surrounding the specific chips powering these products.

Monetization and Open Source Challenges

A key question for the industry is the monetization of AI products, especially when competing with open-source alternatives. Hager highlighted this challenge: "But, Nathan, this goes to the other issue, which is can you really monetize these products? And if you're competing with an open source format, this is, like, the big thing that people are whispering." The massive capital expenditures by hyperscalers are seen as a hedge against falling behind, with companies like Meta and Google reportedly preferring to overspend than underspend in the AI race.

The long-term vision is to see if current AI investments will lay the groundwork for future profitability, much like Cisco's role in building the internet. The question remains what companies like OpenAI and Anthropic will ultimately look like in this evolving market.

Semiconductor Sector Volatility

The conversation also touched upon the recent turbulence in the semiconductor sector. Lipshultz described a sentiment of "relentless optimism" from chip companies, despite a sell-off at the end of the previous week. "It pays to be optimistic. The big question comes back to when does this chip bottleneck no longer exist?" she questioned. The performance of Taiwan Semi, which beat earnings expectations but saw its stock fall, illustrates an environment where expectations are already high, leading to a "price to perfection" scenario.

Intel's significant year-to-date gains were also discussed, with questions about whether the company can capture a portion of the shifting AI spending. If Intel fails to meet the high bar set by its stock performance, profit-taking could ensue.

SpaceX Stock Performance

In a notable pivot, the discussion turned to SpaceX's recent stock performance. Lipshultz noted a sharp downturn since its debut, likening its chart to that of a previous IPO with significant initial excitement followed by a decline. "A dose of realism on investors' part that, you know, what they were sold at the beginning might not be coming to pass, or it's unlikely that it would be guaranteed to to come to pass," she stated. The uncertainty surrounding future earnings reports and share unlocks adds another layer of complexity to the company's valuation.

Energy and AI's Future

Looking ahead, the significant capital expenditures for AI also raise questions about energy consumption. Hager pondered, "How big is the price of energy gonna start factoring into where people think they're gonna pick winners and losers here?" Lipshultz confirmed that this is already a consideration, with the market analyzing what the energy landscape will look like by 2030 and exploring options like nuclear and geothermal energy to address potential bottlenecks. She contrasted China's diversified energy approach with that of the US.

Looking Ahead

As the earnings season kicks off, the market will be closely watching for any indication of how these tech giants are navigating the AI boom, the competitive pressures from China, and the broader economic factors influencing their growth and investment strategies.