What happened?
NVIDIA CEO Jensen Huang recently predicted at the CES exhibition that it might take 15 to 30 years for “very useful quantum computers” to be available on the market. This statement caused a stir the following day and led to a sharp drop in the stock prices of several quantum computing companies.
Alan Baratz, CEO of quantum computing system provider D-Wave, refuted Huang’s prediction about the timeline for the development of quantum computers and emphasized that D-Wave’s quantum computers are already being used in commercial applications.
Baratz pointed out that Huang’s comments may be applicable to gate-based quantum computers, but not to the annealing approach used by D-Wave.
Shouting water freezes! Huang Renxun’s statement caused a plunge in quantum concept stocks
When asked about NVIDIA’s quantum computing strategy, Huang Renxun stated on Tuesday that while NVIDIA can manufacture the traditional chips required for quantum computers, the number of qubits required for these computers would be a million times more than the current amount. He also predicted that it might take 15 to 30 years for “very useful quantum computers” to be available on the market. This statement caused market panic and further led to a significant decline in the stock prices of several quantum computing companies.
Among them, quantum computing chip developer Rigetti Computing fell by 45.41%, quantum computing product provider Quantum Computing fell by 43.34%, quantum computing software and hardware company IonQ fell by 39%, and quantum computing system provider D-Wave experienced a sharp drop of 36.13% on Wednesday.
Looking back at 2024, the four companies mentioned above, Rigetti, IonQ, Quantum Computing, and D-Wave, all experienced explosive growth of 1,449.4%, 237.13%, 1,712.51%, and 854.44% respectively. Google’s quantum computing chip Willow, showcased at the end of last year, became a major factor driving the surge in quantum concept stocks.
Alan Baratz, CEO of D-Wave, responded to Huang Renxun’s remarks in an interview with CNBC, stating that they were “completely wrong” and emphasizing that D-Wave’s quantum computers are already being used in commercial applications and are not distant and unattainable.
Baratz gave examples of companies like Mastercard and NTT Docomo in Japan, which are already using D-Wave’s quantum computers in their actual business operations.
Baratz emphasized that these applications are not for 15, 20, or 30 years in the future, but for “now, today.”
Jensen Huang has a misunderstanding of quantum. While he might be right about other quantum companies, he is dead wrong about D-Wave. There is more than one approach to building a quantum computer. D-Wave took a different approach, which has allowed us to become commercial today…— Alan Baratz (@Alan_Baratz)January 8, 2025
The Quantum Computing Route Debate: Annealing Approach vs. Gate-Based Quantum Computers
Quantum computing aims to solve problems that traditional processors find difficult to handle, such as decoding encryption, generating random numbers, and large-scale simulations. Companies including NVIDIA, Microsoft, IBM, Google, as well as startups and academia, have been devoted to the development of quantum computing for decades.
Baratz acknowledged that “gate-based quantum computers” may still take decades to achieve. However, he emphasized that D-Wave uses the “annealing approach,” which can already be deployed in applications. He stated that Huang Renxun’s comments are “completely wrong” when it comes to the annealing approach.
Although stock prices experienced a significant decline on Wednesday, as of January 9th, D-Wave’s stock price has still risen over 615% within a year, with a market value of $1.6 billion (approximately NT$53 billion).
Baratz stated that the D-Wave system can solve problems beyond the capabilities of the fastest NVIDIA system and expressed his willingness to meet with Huang Renxun anytime to help fill in the gaps in his knowledge.
What is Quantum Annealing?
Quantum computers can be divided into two main categories: quantum annealing and gate-based quantum computers. The main difference lies in whether they have “logic gates.” The former does not and is only used to solve specific problems, while the latter is closer to the classical computers we currently use and can achieve general-purpose computation through various logical gate operations.
Quantum annealing is an algorithm that uses quantum mechanical effects to find the optimal solution to complex problems. It is particularly good at solving “combinatorial optimization problems,” which have many possible solutions but are difficult to find the best solution for.
For example, it is like finding the lowest point in an area with varying terrain heights.
Classical Method: Slow Descent
Continuing the metaphor of finding the lowest point in the terrain, the classical computer’s approach to problem-solving is like rolling a ball slowly down a slope until it reaches a low point. However, the problem is that the terrain may have many local low points (like small valleys), and once the ball rolls into one of these valleys, it may stop and not be able to find the true lowest point, which is the optimal solution.
Quantum Method: Direct Tunneling
On the other hand, quantum annealing utilizes the “quantum tunneling effect” in quantum mechanics. Imagine that the ball is no longer just rolling along the surface of the terrain but can also “tunnel through” some small hills to reach lower places. This is because in the quantum world, particles have a certain probability of tunneling through barriers, even if they don’t have enough energy to “climb” over them.
How Does It Differ from Gate-Based Quantum Computers?
Gate-based quantum computers, unlike quantum annealing, are more like “general-purpose quantum computers” that can perform a broader range of quantum algorithms. These two approaches differ in terms of technical implementation and application areas. It’s like comparing a digger specifically designed for excavation (quantum annealing) with a computer capable of performing various tasks (gate-based quantum computer).
Why is Huang Renxun not optimistic about the short-term availability of quantum computers?
Huang Renxun pointed out that quantum computers (or gate-based quantum computers) won’t be available for at least 30 years due to several difficulties that are still hard to overcome. These include the instability of qubits, which are easily affected by minor environmental disturbances such as temperature and electromagnetic fields, leading to computational errors and resulting in high hardware construction and maintenance costs.
In addition, the number of qubits currently possessed by gate-based quantum computers is still limited and far from sufficient to solve complex real-world problems. To achieve practical quantum computing, thousands, millions, or even billions of high-quality qubits are required.
At the same time, due to the unclear commercialization model, many companies and research institutions find it difficult to afford significant investments, which is one of the practical issues they currently face.
In comparison, quantum annealing has already shown some potential applications in certain types of optimization problems, such as financial modeling, logistics optimization, materials science, and AI, and is relatively easier to implement in hardware. This is also why D-Wave has been able to launch a commercial quantum annealing computer.
In addition to D-Wave, Fujitsu has also developed a technology called “Digital Annealer,” which simulates the operation of quantum annealing. Although it is not a true quantum computer, the Digital Annealer can provide faster speeds than traditional computers when solving certain optimization problems. Fujitsu provides hardware, software, and cloud services for the Digital Annealer and collaborates with various industries for applications in logistics optimization, materials development, and other fields.
This article is authorized for reprinting from: Digitimes
Source: CNBC, CASE, Technology Shadow, National Experimental Research Institute, QM ware
