The demand for electricity in data centers is at an all-time high due to the needs of generative artificial intelligence (genAI) and general AI processing. According to Epoch AI, the compute capacity for training large language models is doubling every nine months, leading to a significant increase in global data center electricity demand by 2026.
To address this energy demand, tech companies are exploring alternative energy sources and ways to reduce the energy consumption of AI technologies. One promising solution is quantum computing, which offers superior processing capabilities and energy efficiency compared to traditional binary systems.
Quantum computing has the potential to revolutionize AI applications, such as accelerating drug discovery and personalized pharmaceuticals. Avivah Litan from Gartner highlights the ability of quantum computing to support AI-based simulations of clinical drug trials, significantly reducing the time required for these trials.
Recent advancements in quantum computing have shown promising results, with generative models outperforming classical models in tasks like generating viable cancer drug candidates. Insilico Medicine, Zapata AI, and the University of Toronto have demonstrated the capabilities of quantum hardware in enhancing AI models.
2024-06-29 03:15:02
Link from www.computerworld.com