High flying stocks like NVIDIA have caused much debate over whether we are due for a crash. I had a discussion with a software engineer about the current A.I. boom in a tech savvy slack group. He believes that while NVIDA and other stocks are probably not immune to moderate corrections, the secular trend will remain sustainable over the next decade. Here’s an overview and some of his key points.
“It’s a bit ironic in my opinion. For decades, A.I. progress had been stagnant, then moved at a snail’s pace. Now that A.I. is passing Turing tests and making a big impact, people are skeptical.“
The current AI and machine learning boom, which has led to stocks like NVIDIA experiencing significant growth, is being argued to be a bubble similar to the dot-com bubble of 2001.
Here are the reasons why it’s not a bubble and the usage is real.
Corporate investment: Major technology companies, such as Google, Amazon, and Microsoft, are heavily investing in AI and machine learning, further validating the potential of these technologies. This level of corporate investment suggests that the AI and machine learning boom is not solely driven by speculative retail investors, as was the case during the dot-com bubble.
Fundamentals: Companies like NVIDIA have demonstrated strong financial performance, with growing revenues, profits, and cash flows. This is in contrast to many dot-com companies in the late 1990s and early 2000s, which had little or no revenue and were often valued based on speculative future growth. NVIDIA’s growth is driven by its leading position in the GPU market, which is essential for AI and machine learning applications, and its expanding presence in data centers and automotive markets.
Broad applicability: AI and machine learning technologies have a wide range of applications across various industries, including healthcare, finance, transportation, and manufacturing. This broad applicability suggests that the growth in AI and machine learning is not limited to a single sector or market, reducing the likelihood of a bubble. The dot-com boom on the other hand, was at the time fundamentally about limited digital storefronts and communication channels.
“Creating a website in the dot com boom required costly infrastructure and the consumer was still very much tied to brick and mortar. Now, everyone has a computer, reaching users is as simple as loading up a chat bot, co pilot or downloading A.I. software.Furthermore, businesses can deploy A.I. and machine learning to improve their efficiency.”
Technological advancements: The AI and machine learning boom is supported by significant advancements in technology, such as improvements in computing power, data storage, and algorithms. These advancements are not only improving, they are improving at an exponential pace. Not only retail users, but corporations themselves have enabled AI and machine learning to become more efficient and effective, driving increased adoption and investment in the space.
Positioning: For artificial intelligence, internet and connectivity as the base infrastructure is already in place. The data A.I. depends on is abundant and ready to be leveraged. The dot-com boom on the other hand, was positioned very differently. It required both use-case development and infrastructure development simultaneously.
While it’s also important to understand things from a skeptical financial analyst perspective, from a software developer’s perspective at least, these factors suggest that the current AI and machine learning boom, and the growth of stocks like NVIDIA, may not be a bubble similar to the dot-com bubble of 2001. It could represent a secular and genuine shift in the technology landscape, driven by fundamentals, technological advancements, and long-term growth potential.
There are also analysts who lived through the dot com bubble who believe that we are more akin to a 1995 market, rather than a 1999 one. This means we likely have some years to go before A.I. related stocks see a major correction.
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