Jakarta, INTI – In the world of technology, quantum computing has become an increasingly captivating topic. IBM CEO Arvind Krishna recently revealed to Time Magazine that within the next three to five years, IBM will achieve major breakthroughs in error correction and quantum coherence time. IBM, which has been investing in quantum hardware development for over a decade, identifies two main challenges: high error rates and loss of coherence.
Challenges in Quantum Computing
Krishna explained that while all computing systems experience errors, classical computers have built-in mechanisms to correct and conceal these errors from users. In contrast, quantum computers are far more susceptible to interference, even from minuscule energy sources. IBM has been striving to overcome this issue by extending qubit coherence time—the period during which a qubit can maintain its quantum state—to one-tenth of a millisecond. IBM's long-term goal is to extend this to one millisecond, which is believed to enable quantum computers to perform calculations impossible for classical computers today.
“We believe that within three, four, or five years—I'm giving myself a deadline until the end of this decade—we will see something extraordinary in this regard, and I am very excited about our team's achievements,” said Krishna.
Applications of Quantum Computing Across Industries
IBM is not only focused on hardware development but also on real-world applications of quantum computing in business. Krishna sees tremendous potential in industries such as materials science, pharmaceuticals, and energy, where quantum computing can lead to groundbreaking discoveries.
“They will derive value from this, whether in material discovery, better batteries, more efficient fertilizers, or more effective drugs. This value will be realized by our clients,” Krishna stated.
IBM aspires to be the leading provider of fully functional quantum systems, positioning the company as a pioneer in the field. Meanwhile, companies like Google, IonQ, and Rigetti are also developing similar technologies with different approaches. Google, for instance, focuses on demonstrating quantum supremacy—the point at which quantum computers surpass classical computers in certain tasks. IBM, on the other hand, opts for a gradual approach, improving hardware performance and reducing error rates before expanding further.
IBM’s AI Strategy: Focus on Small and Efficient Models
In addition to quantum computing, IBM has taken a unique approach to artificial intelligence (AI). Unlike OpenAI and Google DeepMind, which develop large AI models like GPT-4o or Gemini, IBM chooses to build smaller, task-specific models tailored to business needs. Krishna emphasized that bigger is not always better in AI.
“If I have a model with 10 billion parameters and another with 1 trillion parameters, running the larger model would be 10,000 times more expensive. If the improvement is only 1% better, do I really want to pay 10,000 times more? The answer in the business world is almost always no,” Krishna explained.
IBM has chosen to develop smaller yet efficient models, cutting operational costs by more than 90% compared to larger models. This decision is based on IBM’s past experiences, including failures in applying AI Watson for medical diagnoses due to the complexities of the healthcare industry that were not fully understood by IBM.
The Future of AI and Quantum Computing: Where Does IBM Stand?
Krishna compared AI's evolution to the development of the internet, where both large and small companies could benefit from it. He believes that while a few large AI models will require billions of dollars to train, thousands of smaller, specialized models will emerge for various business applications.
Regarding quantum computing, IBM believes that this technology will complement existing systems rather than replace them. “Technology is always additive. Smartphones did not replace laptops. I think quantum will be additive. And just as we helped create mainframes and PCs, perhaps in quantum computing, we will hold the same position for a long time,” Krishna concluded.
Conclusion
IBM continues to invest in quantum computing and AI with a strategy centered on efficiency and practical business applications. Breakthroughs in qubit coherence time and error correction will be crucial for the success of quantum computing in the coming years. Meanwhile, in the AI space, IBM opts for smaller, cost-effective models to provide optimal value for business clients. With this combined strategy, IBM has the potential to become a leader in a new technological era that merges artificial intelligence and quantum computing to create innovative solutions with far-reaching impacts across industries.
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