Jan. 24, 2024, 2:14 a.m. | Synced

Synced syncedreview.com

In a new paper ChatQA: Building GPT-4 Level Conversational QA Models, an NVIDIA research team introduces ChatQA, a suite of conversational question-answering models that achieve GPT-4 level accuracies without relying on synthetic data from OpenAI GPT models.


The post NVIDIA’s ChatQA Reaches GPT-4 Performance Without Using Data From OpenAI GPT first appeared on Synced.

ai artificial intelligence building chatbot conversational data deep-neural-networks gpt gpt-4 gpt-4 performance gpt models large language model machine learning machine learning & data science ml nvidia nvidia research openai openai gpt paper performance question research research team synthetic synthetic data team technology

More from syncedreview.com / Synced

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

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Senior Machine Learning Engineer

@ Samsara | Canada - Remote