Beyond LLMs: Advancing the Landscape of Complex Reasoning

Understand

Since the advent of Large Language Models a few years ago, they have often been considered the de facto solution for many AI problems.

• However, in addition to the many deficiencies of LLMs that prevent them from broad industry adoption, such as reliability, cost, and speed, there is a whole class of common real world problems that Large Language Models perform poorly on, namely, constraint satisfaction and optimization problems.
• These problems are ubiquitous and current solutions are highly specialized and expensive to implement.
• At Elemental Cognition, we developed our EC AI platform which takes a neuro-symbolic approach to solving constraint satisfaction and optimization problems.