<div id="readability-page-1">Over the last two years, much of the dialogue surrounding artificial intelligence (AI) has been focused on one core type of computing hardware: graphics processing units (GPUs). The parallel processing capacities of these chips make them particularly well suited to the development and deployment of generative AI. For now, Nvidia is the biggest player in the data center GPU space, with an estimated 88% market share. Savvy investors understand that GPUs are only one variable in the broader AI equation, though. One area that is beginning to attract some attention is quantum computing, where rising star IonQ (IONQ 0.54%) has some designs on becoming the next Nvidia. <h2>Understanding quantum computing</h2> Traditional computers store information and data in binary bits (0s and 1s). Quantum computers, however, use quantum bits (qubits) as the foundation for memory and processing. Qubits can be take the form of different arrangements simultaneously -- this dynamic is known as superposition in quantum mechanics. I know the information above sounds like it came out of a science fiction novel, and you're probably wondering what it even really means. If you think about it, modern computers are pretty much around us at all times. But even with endless information at the tip of your fingers, there are still questions that people and businesses struggle to answer with high accuracy. For example, pharmaceutical companies constantly perform tests in laboratories to develop groundbreaking drugs. Meanwhile, scientists constantly analyze patterns to try to predict weather forecasts or potential changes in climate. But at the end of the day, both of these examples largely rely on prolonged trial and error. Quantum computers have the potential to change that narrative dramatically by leveraging quantum mechanics, which cannot be integrated with traditional computing systems. The primary goal of quantum computing is to solve monumentally complex problems that legacy systems are incapable of, and do so in a matter or days or even minutes. <div><img src="https://imageproxy.pbkrs.com/https://g.foolcdn.com/image//query-b3A9cmVzaXplJnVybD1odHRwczovL2cuZm9vbGNkbi5jb20vZWRpdG9yaWFsL2ltYWdlcy84MDA0MjYvY29kaW5nLWVycm9yLWRlc2lnbi11eC1yZXNlYXJjaC5qcGcmdz03MDA?x-oss-process=image/auto-orient,1/interlace,1/resize,w_1440,h_1440/quality,q_95/format,jpg" width="700" height="463" original-src="https://imageproxy.pbkrs.com/https://g.foolcdn.com/image//query-b3A9cmVzaXplJnVybD1odHRwczovL2cuZm9vbGNkbi5jb20vZWRpdG9yaWFsL2ltYWdlcy84MDA0MjYvY29kaW5nLWVycm9yLWRlc2lnbi11eC1yZXNlYXJjaC5qcGcmdz03MDA"/>Image Source: Getty Images </div> <h2>How IonQ is making a splash in quantum computing</h2> IonQ specializes in a technique called &#34;trapped ion&#34; quantum computing. Each ion is known as a natural qubit, and by trapping them, their quantum states can be manipulated more easily. The main benefits of this malleability feature can lead to reduced error rates, thereby allowing ions to maintain their quantum state for longer periods. In theory, this can help with processing more sophisticated algorithms or complex computing at scale in a seamless fashion. During a recent interview at the New York Stock Exchange (NYSE), IonQ CEO Peter Chapman said that some of the &#34;leading applications&#34; in quantum computing are chemistry and machine learning. Researchers and software developers can access IonQ's quantum computing service through cloud platforms such as Azure, Google Cloud, and Amazon Web Services. This is an interesting business model because, essentially, IonQ is covering the immense costs of capital expenditures (capex) and hardware needed to build a quantum computing platform for its customers. This process allows companies to access quantum computing capabilities more directly, thereby helping them scale at a faster rate. <h2>Will IonQ become the next Nvidia?</h2> While IonQ's ambitions in the quantum computing world are exciting, there are some important details that investors need to be aware of. First, IonQ is far from the only company exploring quantum computing. Other players including IBM, Alphabet (Google), Microsoft, and Rigetti Computing are just a few companies investing heavily into quantum computing mechanics. Considering IonQ is not yet profitable, it's going to be hard for the company to compete with the likes of mega cap tech in the long-run. This leads to my second point. So far in 2024, shares of IonQ have skyrocketed by over 150% -- outpacing every member of the &#34;Magnificent Seven&#34; with the exception of Nvidia. At a price-to-sales (P/S) multiple of 185, it's pretty clear that IonQ stock is overbought and its $7 billion market cap is rooted more in the narrative surrounding AI and quantum computing as opposed to actual business fundamentals. In my eyes, IonQ stock has already experienced an Nvidia-like run, and shares are due for a pullback. To me, IonQ has a long road ahead before it can be even remotely compared to Nvidia's influence and status within the AI arena. </div>

IONQ

NVDA

IonQ is positioning itself as a potential leader in quantum computing, similar to Nvidia's dominance in GPUs. While IonQ's trapped ion technology offers advantages in processing complex algorithms, it faces stiff competition from major players like IBM and Google. Despite a 150% surge in stock price in 2024, IonQ remains unprofitable and its high market cap may be driven more by hype than fundamentals. Analysts suggest that IonQ's stock is overvalued and may experience a correction as it strives to match Nvidia's success in the AI sector.

- The article discusses the growing interest in quantum computing, particularly focusing on IonQ's advancements in the field.  
- IonQ utilizes "trapped ion" quantum computing to enhance processing capabilities, offering services through major cloud platforms while facing competition from established tech giants.  
- Despite a significant rise in stock value, concerns about IonQ's profitability and market position suggest it may struggle to achieve Nvidia's level of influence in the AI sector.

Could IonQ Be the Next Nvidia?