SandboxAQ has partnered with NVIDIA to harness the power of quantum simulation platforms in various scientific fields. The partnership aims to leverage artificial intelligence and simulation technologies to support drug discovery, battery design, green energy, and other scientific areas.
The announcement was made from Palo Alto, California, with SandboxAQ Chairman Eric Schmidt expressing his belief that simulation is a highly promising future technological application. He highlighted the role of rapid advances in graphics processing unit hardware and quantum information science in enabling the use of artificial intelligence for specialized applications.
SandboxAQ CEO Jack Hidary emphasized the impact of simulation on GPU use, stating that it will provide insights about the physical world beyond the capabilities of extractive or generative AI. The partnership between SandboxAQ and NVIDIA aims to use quantum platforms for simulating chemical reactions and forecasting scientific developments in modern chemistry, biology, and material science.
SandboxAQ will offer technical advice to NVIDIA on its tensor network offerings, cuTENSOR, cuTensorNet, Quantum Computing, and CUDA libraries. These libraries are crucial for modeling high-dimensional data and have applications in machine learning, data science, financial modeling, fluid dynamics, and quantum chemistry.
NVIDIA’s director of high-performance computing and quantum Tim Costa emphasized the need for powerful accelerated computing platforms in advancing quantum chemistry and molecular modeling. The collaboration with SandboxAQ is expected to provide scientists with the tools to make breakthroughs in material science.
In summary, SandboxAQ’s partnership with NVIDIA aims to leverage quantum simulation platforms to support drug discovery, battery design, green energy, and other scientific areas using artificial intelligence and simulation technologies. This collaboration is expected to provide scientists with new insights about the physical world beyond traditional extractive or generative AI methods by leveraging powerful accelerated computing platforms such as those offered by NVIDIA’s tensor network offerings.