| RESEARCH Quantum, AI spur biological breakthroughs For years, IBM has been at the forefront of quantum computing. At this year’s Think conference, that ambition was on full display. During the opening keynote, IBM CEO and Chairman Arvind Krishna highlighted quantum’s potential with the technology having the capability to unlock new discoveries at an incredibly quick pace — including AI developments.“Quantum can help uncover what AI cannot yet compute, then AI learns from the quantum and can make faster and faster progress on algorithms and on computations to give you a state of where we are,” said Krishna. To showcase the tangible use cases of quantum computing, IBM highlighted a biological research milestone achieved with the Cleveland Clinic and Riken: using two of the IBM quantum computers and two of the world’s most powerful supercomputers, the companies were able to simulate protein complexes spanning up to 12,635 atoms. In October 2024, it was only able to simulate 10. This is important, as the molecules in your body are proteins, or the “workhorse in the cell” that allow people to exist every day, as Serpil Erzurum, EVP and chief research and academic officer at the Cleveland Clinic’s Lerner Research Institute, explained during the keynote. Understanding the 3D structure and motion of a protein is key in biological research, as it helps researchers understand how a drug candidate could bind to a protein and develop effective drugs. Yet, it has remained a challenge as classical computers can only approximate solutions. Erzurum emphasizes that this development is “a moment.” “Everyone will want to see what these structures look like to understand biology, disease, what’s going wrong if it’s not working, and more importantly, what can I make to fit into the three dimensional structure, to change the structure of that protein–because that’s therapy, and that can make a difference in life,” said Erzurum. Another example Erzurum noted is using quantum computing and machine learning to dramatically speed up the identification of which treatments a harmful microbe is sensitive to, potentially saving lives given that infections remain a leading cause of death globally. In a separate Q&A with analysts and select press, Krishna did make it clear that in the next three years, he does not see quantum as replacing either AI or classic CPUs, but rather it will solve problems the two cannot solve, such as the modeling molecules example. While quantum computing ranks among the most cutting-edge technologies available today, so advanced that it can be difficult to fully realize, it is already demonstrating tangible results. Its relevance is also becoming increasingly difficult to overlook, particularly given its potential to address some of the most pressing challenges facing the AI industry, including the growing demand for compute power. That said, it is important to contextualize the technology’s current trajectory: Widespread mainstream adoption and full commercial deployment remain a considerable way off, largely because the hardware required to run quantum systems at scale is still enormously costly to build and maintain.Disclosure: Sabrina Ortiz’s travel to IBM Think was paid by IBM. The Deep View’s coverage is editorially independent from the companies we cover. |
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While quantum computing ranks among the most cutting-edge technologies available today, so advanced that it can be difficult to fully realize, it is already demonstrating tangible results. Its relevance is also becoming increasingly difficult to overlook, particularly given its potential to address some of the most pressing challenges facing the AI industry, including the growing demand for compute power. That said, it is important to contextualize the technology’s current trajectory: Widespread mainstream adoption and full commercial deployment remain a considerable way off, largely because the hardware required to run quantum systems at scale is still enormously costly to build and maintain.