Project Media QA

Project Video QA

We’re excited to introduce Project Media QA, a groundbreaking application for video and audio transcription, summarization, and question answering. By harnessing the power of open-source Large Language Models (LLMs) and Automatic Speech Recognition (ASR) models, both powered by the Groq® LPU™ AI Inference Engine, Project Media QA delivers lightning-fast results that transform the way we interact with multimedia content.

In our fast-paced digital landscape, quick video and audio transcription and is crucial. Project Media QA is the perfect tool for the job with an intuitive interface for recording audio, uploading media files, or loading content from a URL. The application also swiftly transcribes the audio making it searchable and accessible.

But Project Media QA goes beyond transcription. Leveraging the power of LLMs, the application is interactive. Users can ask questions about the transcribed content and receive accurate, context-aware answers. This feature opens up a world of possibilities, from journalists quickly finding relevant quotes in lengthy interviews to researchers efficiently navigating through hours of recorded lectures saving them both valuable time and effort.

Check it out for yourself

Note: By default you are limited to 4 transcriptions / chats per day. Once reached, you can use your own Groq API key to process additional requests. Need a Groq API key? You can create one for free at console.groq.com

About the Authors:

Soami Kapadia is an AI applications intern at Groq. He is currently creating applications and demos using Groq to showcase the true potential of super fast AI inference. He is a junior undergrad studying Computer Science at Michigan State University. You can learn more about him here.

Alec Mcleanis an experienced machine learning engineer with expertise in Natural Language Processing and Computer Vision. He’s currently spearheading efforts to help Public Sector clients harness the Groq LPU for accelerated Generative AI tasks. Previously, he played crucial roles at Booz Allen Hamilton and Amazon Web Services, leading the delivery of advanced machine learning solutions for Federal agencies.