Gartner organized its 10 technology trends around three stages that enterprises must work through to transition from running static code to orchestrating autonomous machine workers, managing sensory AI, and enabling sovereign computing. The first stage, which Gartner says is underway now and will consume the next one to three years, is to “leverage the nontextual AI frontier.” That phase includes the firm’s first three strategic technology trends, among them Large Quantitative Models (LQM).
Large Quantitative Models (LQM)
Gartner defines Large Quantitative Models as “modular, hybrid neural network architectures built to process and analyze quantitative data.” The firm says LQMs use existing mathematical formulas, methods and algorithms to model complex systems. Compared with large language models (LLMs), LQMs are designed explicitly for numerical reasoning and require significantly less memory, storage and compute, the firm says.
Gartner presents LQMs as part of the nontextual AI frontier that frames the firm’s near-term strategic technology trends.
