Part 4/7:

The conversation shifts to the current practical implications of these large quantitative models. With companies like SandboxAQ—spun out from Google—investing significantly to develop their LQMs, the potential of these models is being realized today. For instance, UCSF is employing SandboxAQ's software to support drug advancements for neurological diseases, marking a successful application of LQMs in real-world scenarios.

The data underpinning these models differs fundamentally from that of LLMs. Rather than drawing insights from vast corpuses of text data on the internet, LQMs focus on the dynamic relationships inherent in chemical and atomic interactions. This specialization positions LQMs for immediate utility in industries necessitating rigorous quantitative analysis.