SandboxAQ has announced a collaboration with Nvidia to combine its large quantitative models (LQMs) with the Nvidia CUDA-accelerated Density Matrix Renormalization Group (DMRG) algorithm. According to SandboxAQ, the combined technologies will make it possible to perform “highly accurate quantitative AI simulation of real-life systems” that go “beyond what large language models and other AI models can currently do.” The company also claims computing speeds of more than 80x for these simulations with Nvidia’s technology compared to computing on traditional 128-core central processing units.
Nadia Harhen, general manager for SandboxAQ’a AI simulation division, told GEN in an interview that the combined technologies will support computational chemistry applications in multiple industries including biopharma, chemicals, and materials sciences. SandboxAQ already has customers in some of these spaces who rely on their equation-based computing technology, which forms the crux of the company’s business. The technology uses complex physics-based calculations to generate the data needed to train SandboxAQ’s LQMs based on various inputs including real-world observations and physical properties of various molecular structures.
These models can predict molecular behavior and generate molecular structures with desired properties. “Equation-based computing is a highly efficient way of programming computers,” Harhen said. This compute paradigm makes it possible “to creat.