2403 00795 Executing Natural Language-Described Algorithms with Large Language Models: An Investigation
Brains and algorithms partially converge in natural language processing Communications Biology We maintain hundreds of supervised and unsupervised machine learning models that augment and improve our systems. And we’ve spent more than 15 years gathering data sets and experimenting with new algorithms. Businesses use large amounts of unstructured, text-heavy data and need a way to efficiently process it. Due to its ability to properly define the concepts and easily understand word contexts, this algorithm helps build XAI. Symbolic algorithms leverage symbols to represent knowledge and also the relation between concepts. Since these algorithms utilize logic and assign meanings to words based on context, you can achieve high accuracy. Human languages are difficult to understand for machines, as it involves a lot of acronyms, different meanings, sub-meanings, grammatical rules, context, slang,…