March 13, 2024, 3:02 a.m. | Adnan Hassan

MarkTechPost www.marktechpost.com

The quest for models that can think, reason, and generate outputs similar to a human’s capacity for complex problem-solving has been paramount. Large language models (LLMs) are at the forefront, designed to mimic human-like understanding and articulation of ideas. Despite remarkable achievements, these models often grapple with the challenge of maintaining factual accuracy over extended […]


The post Retrieval Augmented Thoughts (RAT): An AI Prompting Strategy that Synergies Chain of Thought (CoT) Prompting and Retrieval Augmented Generation (RAG) to Address …

ai paper summary ai shorts applications artificial intelligence capacity chain of thought editors pick generate horizon human language language model language models large language large language model large language models llms problem-solving prompting quest rag rat reason reasoning retrieval retrieval augmented generation staff strategy tasks tech news technology think thought thoughts

More from www.marktechpost.com / MarkTechPost

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne