Lisa Su, CEO of Advanced Micro Devices (AMD), addressed concerns surrounding Big Tech’s substantial investments in artificial intelligence, stating that these outlays are not a gamble but a calculated move to accelerate innovation. Su made these remarks during an interview on CNBC’s “Squawk Box” on Wednesday.
“I don’t think it’s a big gamble,” she affirmed. “I think it’s the right gamble.” The market responded favorably, with AMD shares surging 10% following her comments.
Su emphasized that many of AMD’s hyperscaler clients have significantly increased their capital expenditure over the past year. This surge in investment reflects the perception that AI technology has reached a critical “inflection point,” where companies are beginning to see tangible returns on their investments. This isn’t just about deploying existing AI, but building the infrastructure to train and deploy increasingly complex models.
Her assessment comes against the backdrop of tech behemoths collectively announcing over $380 billion in AI-related spending in their recent earnings reports. These capital allocations are intended to bolster their infrastructure to meet the rapidly growing demand for AI-driven solutions. The “AI arms race,” as some analysts have termed it, is driving unprecedented demand for specialized hardware, particularly in the data center space.
While investors have largely shrugged off concerns about increased spending from trillion-dollar market cap companies, firms with smaller valuations offering similar guidance have faced scrutiny. This divergence highlights a market favoring established leaders with proven track records in AI deployment.
Earlier in the week, Su projected a robust annual revenue growth rate of 35% for AMD over the next three to five years, propelled by what she characterized as “insatiable” demand for AI chips. Further underscoring AMD’s ambitions, she indicated that the company aims to capture a “double-digit” percentage share of the data center AI chip market within that same timeframe. This goal represents a significant challenge, given the current dominance of Nvidia in this space. AMD’s strategy involves leveraging its expertise in both CPU and GPU architectures to deliver optimized solutions for specific AI workloads, targeting areas where it can offer a competitive advantage in performance and efficiency.
Despite the overall positive sentiment, anxieties about a potential AI bubble continue to ripple through the market, fueled by concerns that valuations have become unsustainable. This unease has been exacerbated by recent investment decisions from prominent figures.
Notably, famed short-seller Michael Burry disclosed short positions against software firm Palantir and Nvidia. Subsequently, Burry accused hyperscalers of manipulating earnings by artificially extending the depreciation lifecycle of their capital equipment, labeling this practice as “one of the more common frauds of the modern era.” This accusation raises questions about the sustainability of current growth rates and the true profitability of AI investments.
Adding to the mix, Softbank divested its nearly $6 billion stake in Nvidia in October to support its broader AI strategy, which includes a significant investment in OpenAI. While a source familiar with the matter indicated that the sale was unrelated to valuation concerns, the move nonetheless amplified existing market jitters regarding the long-term prospects of AI-driven investments.
Su acknowledged Softbank’s decision and expressed respect for Masayoshi Son, the CEO of the Japanese conglomerate. “The AI ecosystem is in a place where people are making bets, and people are deciding what bets they want to make, and … which part of the stack you want to make the bets,” Su explained. This suggests diverging views on the most promising areas for investment within the complex AI landscape, ranging from foundational infrastructure to application-specific solutions. The future winners in the AI market will likely be those firms that can accurately anticipate future demand and effectively allocate resources to the most promising growth areas.
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