Historically, symbolic programming has dominated, where developers use symbolic code to express logic for tasks or problem-solving. However, the rapid adoption of LLMs has sparked interest in a new ...

Deep symbolic regression (DSR) is a deep learning algorithm for symbolic regression--the task of recovering tractable mathematical expressions from an input dataset. The package dsr contains the code ...

Machine learning for large teams (evolving and sharing ML code, reusing ML techniques, etc.); Daily programming tasks in Python (advanced binding capabilities, mutability, etc.). PyGlove has been ...

Imandra Inc., a pioneer in neurosymbolic AI and automated logical reasoning, today announced the launch of CodeLogician, a cutting-edge LangGraph agent that transforms source code into precise ...

However, existing DL-based solutions for learning program representations have limitations - they either cannot capture the deep, precise program semantics or suffer from poor scalability. We present ...

That's when mathematicians John G. Kemeny and Thomas E. Kurtz successfully ran the first program written in their newly developed BASIC (Beginner's All-Purpose Symbolic Instruction Code ...

DUBAI, UAE, Oct. 4, 2023 /PRNewswire/ -- In a significant leap towards bringing advanced emotional intelligence to AI, Source Code Technology (SCT) will unveil Symbolic Language at the prestigious ...

In many modern LLM applications, such as retrieval augmented generation, prompts have become programs themselves. In these settings, prompt programs are repeatedly called with different user queries ...