[비즈한국] "Depending on who you ask, the commercialization of a truly useful quantum computer could take anywhere from 15 to 30 years." Jensen Huang, CEO of Nvidia, made these remarks during an analyst meeting at CES on the 7th (local time) when asked about the development of quantum computing, which is still in its early stages. He added, "I think many of us would agree on a timeline of about 20 years." This analysis suggested that it would take decades for quantum computers to be put to practical use. Following Huang's statement, shares related to quantum computing—such as IonQ, Rigetti Computing, and D-Wave—plunged simultaneously on the New York Stock Exchange.
Alan Baratz, CEO of D-Wave Quantum, appeared on CNBC the day after Jensen Huang's comments, retorting that his prediction was "completely wrong." He argued, "The reason he is wrong is that D-Wave is currently operating commercially."
Quantum computing has been called the "computer of dreams" for decades because its calculation speed is vastly faster than computers currently in use. While ordinary computers use bits—which hold a value of either 1 or 0—as the smallest unit of information storage, quantum computers use qubits, which can exist in states of 1 and 0 simultaneously. Quantum computers utilize a phenomenon called "quantum entanglement." A qubit consists of two quantum particles rotating in different directions. Even if these quantum pairs are placed far apart, changing the rotation direction of one immediately changes the other. This is known as "quantum entanglement," and this phenomenon enables diverse information processing, allowing calculations that would take a supercomputer one year to complete in just one second.
Because quantum computers perform non-deterministic calculations unlike existing computers, they are useful for code-breaking, simulations, weather information processing, and pattern analysis. For this reason, since the advent of Bitcoin, they have drawn attention from investors as a rival to cryptocurrency, raising the possibility that they could decrypt all the Bitcoin in the world.
On December 10 last year, Google announced its quantum chip, Willow. As it solved a problem in five minutes that would take a current supercomputer $10^{25}$ years to solve, quantum computing-related stocks soared. Google's Willow chip overcame the limitation of not being able to increase the number of qubits due to quantum error correction issues, showing five times the performance and stability compared to the previous generation chip. On the day Willow was unveiled, the prices of cryptocurrencies like Bitcoin plummeted.
Quantum computing, along with artificial intelligence (AI), has been highlighted as a next-generation innovative technology that will change the world. U.S. policy authorities have even designated AI and quantum computing as national strategic industries. However, a single word from Jensen Huang caused quantum computing-related stocks to shake violently. In particular, IonQ, a representative U.S. quantum computing stock, plummeted more than 30%, and the "Leverage Shares 3x Long IONQ" exchange-traded product (ETP) from UK asset manager Leverage Shares entered delisting proceedings, causing significant losses for investors.
Choi Bo-won, a researcher at Korea Investment & Securities, stated, "Until representative products and services are commercialized and made concrete, quantum computing-related stocks are bound to repeat sharp fluctuations based on earnings reports and remarks made by major IT firms at events." Park Woo-yeol, a researcher at Shinhan Securities, also advised, "Even among scientists, there is no consensus on quantum mechanics, and although it is a concept difficult to understand intuitively, investors are already embracing it. The annualized volatility of individual quantum companies is at the 90% level, which is higher than the 50% level of crude oil or crypto investments known for being high-risk. Therefore, it is necessary to reduce volatility through basket investments using ETFs."
There is no disagreement among experts on the prospect that quantum computers will drastically advance AI technology. However, it is also clear that because it is difficult to control quantum particles as desired, more time is needed until technical issues are resolved. Therefore, investments in quantum computing should be approached based on a long-term vision. While it is expected that it will take time for the technology to be commercialized, the pace of technological progress may be faster than predicted. Rather than concentrating investments in individual companies, it is important to reduce the volatility risk of specific firms by investing in basket products like ETFs. This allows one to expect more stable results than high-risk, high-return investment methods. Additionally, investing primarily in large IT companies that have already invested massive capital into quantum computing research—such as IBM, Google, and Microsoft—can be a good choice. These companies hold various revenue sources beyond quantum computing commercialization, making risk management easier.
Regarding timing, it is important to pay attention to the moments when major technical milestones, such as increases in qubit counts and improvements in error correction technology, are announced. Such announcements significantly increase the price volatility of related stocks and can act as short-term investment opportunities. Since quantum computing-related stocks are characterized by high volatility, one can expect long-term returns through bargain hunting during price drops, but this must be supported by sufficient research and analysis. Because quantum computing and AI technology are deeply interconnected, it is also good to take an interest in AI-related companies, as the convergence of AI and quantum computing is highly likely to become the core of future innovation.
It is advisable to approach quantum computing investments from a long-term perspective while steadily monitoring technological developments and market signals. Rather than being overly tied to short-term fluctuations, it is necessary to look at the big picture of the industry and set up a systematic investment plan. Until technical issues are solved and concrete commercialization cases appear in the market, choosing an investment strategy that prioritizes stability from a long-term investment perspective is the wise approach.