NVIDIA CEO Jensen Huang explains why the AI boom is not like the dot-com bubble

During a recent 'The Minds of Modern AI' roundtable discussion and interview with the Financial Times, editor Madhumita Murgia brought up the question or idea that we're currently living in an 'AI bubble' similar to the dotcom bubble of the 1990s, and that sooner or later it's going to burst and the market will "correct" itself.

For those who need a refresher or were too young to remember the 'dot-com bubble' of the late 1990s, this refers to a time when the stock market and investors saw the rise of the internet and the concept of the "World Wide Web" and decided to invest heavily in dot-com startups and companies. The bubble eventually burst, leaving only a few companies, such as Amazon, intact.

The reason people are comparing the AI boom to the dot-com boom is that they see parallels in the rapid growth and the lack of signs that AI investments are leading to actual profits. In response to the comparison and question posed to NVIDIA CEO Jensen Huang, his initial brief answer is 'no'; the AI boom is not like the dot-com boom because back then, the majority of the fiber was "dark," meaning unused.

• Read more: Ex-Intel CEO CEO Pat Gelsinger says 'Of course' the tech industry is in an AI bubble

Currently, with AI, "almost every GPU you can find is lit up and used." However, that's not all; AI is also significantly different from how software of the past was deployed - because AI requires access to vast amounts of computing power in real-time.

"During the dot-com era, during the bubble, the vast majority of the fiber deployed was dark, meaning the industry deployed a lot more fiber than it needed. Today, almost every GPU you can find is lit up and used. I think it's important to take a take a step back and understand what AI is. For a lot of people, AI is ChatGPT and image generation, and that's all true. That's one of the applications of it. AI has advanced tremendously in the last several years. The ability to not just memorize and generalize, but to reason and effectively think and ground itself through research. It's able to produce answers and do things that are much more valuable now."

Jensen Huang then goes on to explain how the need for computing and the concept of AI factories are fundamentally different from anything resembling the past. And with the rise of AI factories and things like the actual increasing demand for queries, the comparisons to the dot-com bubble are unfounded.

"Software in the past was pre-compiled, and the amount of computation necessary for the software was not very high. In order for AI to be effective, it has to be contextually aware. It can only produce intelligence at the moment. You can't produce it in advance and retrieve it. AI intelligence has to be produced and generated in real time. And so as a result, we now have an industry where the computation necessary to produce something that's really valuable is in high demand and quite substantial. We have created an industry that requires factories."

That said, the AI boom still faces issues related to the increased costs of producing, obtaining, and operating the cutting-edge technology capable of handling the most advanced AI systems, alongside the demand that AI is placing on power grids and power supplies. There are definite challenges ahead, and although comparisons to the dot-com era boom and bubble are not entirely accurate or like-for-like, there is still a sense that not all big AI players will come out on top.