AI want(s) to break free
Nvidia's latest results have been a moment of realization for many investors: Artificial Intelligence is not some distant hype. One should be ready for the consequences. We are.
On May 24th, Nvidia delivered quarterly financial results which sent the stock up by ~24% the following day. The company's revenues beat estimates by 10% (~$700mn), while the revenue guidance for the following quarter came in 53% above expectations (~$3.8bn), both driven by the explosion in demand for GPUs to power Artificial intelligence (AI) workloads.
These results benefited the broader AI sector, with players surging after results that would have otherwise not commanded such a spike (e.g., Marvell ), and others "just" being the targets of investors raising their expectations (e.g., C3.ai ).
Impact on our Investment Case
No more doubts
Nvidia's results were much anticipated, if not even feared. The stock had witnessed an impressive recovery already (+109% YTD on the eve of the results) thanks to the ChatGPT effect: the service, launched in November 2022, is so groundbreaking that it ignited a large rally for AI-related stocks, based on all the potential applications powered by its technology. As analysts had yet to adjust their estimates, which is not an easy thing for disruptive technologies, valuation had risen to a point where these results had become a make-or-break moment. A quite understandable situation, given how some hyped stocks appear only loosely related to AI technologies, leading to some unflattering comparisons with the recent blockchain mania.
Except that the test was passed with flying colors. It is quite rare to witness such a beat-and-raise, especially for a company of this size: Nvidia added ~$230bn to its market cap on that day, i.e., almost twice as much as Intel's entire market cap! Quite a symbolic moment, indeed. Most importantly, these results confirm our view that AI already generates substantial business opportunities, translating into solid cash generation: it is not yet another interesting technology full of distant promises.
What it means for the sector
We agree that Nvidia's competitive positioning is unique, as it benefits from both a leading position in terms of hardware performance and great barriers to entry originating from its CUDA programming interface being the undisputed leader in the Machine Learning ecosystem. But the AI supply chain is not only made of GPUs. Other chips are required, with the gold old CPUs not being dead yet (benefiting AMD), and a large set of additional AI calculators, networking chips and memory systems being necessary to accelerate AI workloads. Beyond this, advanced AI needs training, which itself requires a huge amount of data and a performance cloud infrastructure to manage it (e.g., Datadog ).
Although we do agree that some players positioning further downstream do not have Nvidia's competitive moat, it does not mean that capturing opportunities is impossible for them: there has been no better time, as every company is rushing to integrate AI, now that its major competitive differentiating role has become obvious to everyone. Nvidia is simply the (massive) tip of the iceberg, and the first solid proof of the financial attractiveness of the technology. There will be many more in the future; one just needs to consider all the infrastructure required to run ChatGPT smoothly.
Impact on our strategy
We are no strangers to AI. The Artificial Intelligence & Robotics strategy was launched in 2015, precisely in anticipation of this moment, as we were convinced of the technology's potential impact on modern economies. Nvidia was already a major constituent of the portfolio. More recently, we repeatedly highlighted our belief that generative AI was, in our view, transformational. This conviction is only reinforced by the recent news, and despite the recent rally surrounding AI-related stock, our portfolio's valuation remains quite attractive, with an expected PEG of 1.0x. Additionally, we believe that, unsurprisingly, many analysts are likely still underestimating the impact of AI on the companies they cover, meaning that the "true" PEG is even lower. In other words, the sector's potential is only beginning to unfold, and it is not too late to hop on the departing train.
Nvidia's results represent a watershed moment for the AI sector: they indeed show that the financial impact is not years away, but all too real. This realization is driving a fast paced market rally, but for quality businesses, this is just the beginning of a multi-year opportunity. As we have done since the launch of the certificate in 2015, we will keep focusing on such companies to capture the most of this opportunity.
Companies mentioned in this article
AMD (AMD); C3.ai (AI); Datadog (DDOG); Intel (INTC); Marvell (MRVL); Nvidia (NVDA)
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