The Brain Center at the Indian Institute of Technology Madras (IIT Madras) is at the forefront of neuroscience research using cutting-edge artificial intelligence (AI) technology. According to a recent report from NVIDIA, the brain center is collaborating with NVIDIA to leverage visual question answering (VQA) and multimodal search to improve accessibility and analysis of brain imaging data.
Neuroscience Knowledge Exploration Framework
An innovative framework developed by IIT Madras allows researchers to link brain imaging data with the latest neuroscience research. This is achieved through a comprehensive processing pipeline that integrates VQA models and large language models (LLMs). This framework allows researchers to explore developments associated with specific brain regions and states, providing a new dimension to understanding brain structure and function.
The heart of this process is the collection and Q&A section. In the collection phase, neuroscience publications are indexed into a knowledge base, and in the Q&A phase, a Retrieval-Augmented Generation (RAG) pipeline is used to filter and retrieve relevant content, allowing users to interact with the knowledge base. This multimodal interaction enhances the depth and accuracy of research insights.
Visual question answering and multimodal search
The framework allows users to input images of brain regions and query specific details about them. Provides detailed answers using advanced VQA models such as Llava-Med. This functionality is further expanded with a cross-image search feature still in development, which aims to enable searches based on visual similarity.
Take advantage of NVIDIA technology
NVIDIA’s technology stack is essential to the success of the framework. Tools like NVIDIA NeMo Retriever and NeMo Guardrails increase search accuracy and ensure user-generated content is relevant. The framework leverages a fine-tuned embedding model to improve search accuracy by over 15%. NVIDIA’s infrastructure also supports efficient inference speeds, which are critical for handling concurrent user queries.
NVIDIA AI Blueprint for Multimodal PDF Data Extraction further complements this framework by accurately parsing neuroscience publications, enriching the data available for analysis.
Applications and Implications
Examples of applications of the framework include identifying brain regions in images and searching for similar tissue samples. This capability promises to advance neuroscience research by providing accurate and accessible data for analysis, potentially leading to breakthroughs in understanding complex brain functions and states.
Through this collaboration, IIT Madras and NVIDIA are not only pushing the boundaries of neuroscience research but also paving the way for life-saving discoveries by making complex data more accessible and understandable.
For more information, visit the NVIDIA blog.
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