Logical Intelligence Achieves 76 Percent on Putnam Benchmark, Highlighting Shift Beyond Large Language Models to Language-free, Mathematically Grounded Models
Over the last decade, artificial intelligence (AI) has been largely built around large language models (LLMs). These systems are based on a language and guess words in a chain in the form of tokens. As a result, they frequently hallucinate and require vast compute and power infrastructure to solve tasks. The moment systems like public safety, national infrastructure, and industrial automation need logic, LLMs break and introduce safety risks. Token-free language independent models represent a new direction for AI. They do not predict words. They search for correct solutions and require less compute. Logical Intelligence is the first company building exclusively around mathematically derived, non autoregressive EBM (Energy Based Model) reasoning.
