While it’s still very much an emerging field, early providers include QueryPal, Promptable, Rebuff and TrueLens. As prompt ops evolve, these platforms will continue to iterate, improve and provide ...

i don’t think this description of domain specific languages really gets to the concepts that matter. fortran is a good example. it’s not that the features of the language are good for ...

This repository contains the implementation of our research on optimizing Retrieval-Augmented Generation (RAG) systems for technical domains. Our work addresses the unique challenges of precise ...

Across government, a war is being waged in wordplay. It is fought in executive orders, official statements from the White House, press briefings and all manner of communiqués, internal and external.

To this end, we introduce HeurVidQA, a framework that leverages domain-specific entity-action heuristics to refine pre-trained video-language foundation models. Our approach treats these models as ...

For example, a financial institution might use a domain-specific LLM to accurately interpret complex financial regulations, ensuring compliance and providing clear guidance to users.

Mainstream Large Language Models (LLMs) lack specialized knowledge in telecommunications, making them unsuitable for specific tasks in this field. This gap poses a significant challenge as the telecom ...

The chip industry is moving toward domain-specific computation, while artificial intelligence (AI) is moving in the opposite direction, creating a gap that could force significant changes in how chips ...

Networking large language models (LLMs) can enhance space domain awareness and address these challenges. The BRAVO hackathon showcased the transformative capabilities of networked LLMs in space ...