Current LLMs like GPT-4 struggle with nuanced medical queries in Indian languages due to a fundamental bias in their English-heavy training data. GoDavaii aims to bridge this gap by developing advanced Health AI for over 22 Indian languages, focusing on making medical knowledge contextually relevant and accessible across diverse linguistic backgrounds.
The article details the challenges of building health AI that truly understands the nuances of India's 22 official languages, exemplified by the complexity of interpreting a simple phrase. On Day 48 since launch, GoDavaii is tackling immense linguistic complexities to create an AI that goes beyond English-first solutions.
Most Health AI models, built English-first, fail to provide accurate medical information when users query in native non-English languages due to broken translation layers. GoDavaii addresses this by reasoning natively in 22 Indian languages, offering a more effective solution for a billion people.
This text analyzes a seminal 2021 paper demonstrating AI model training on distributed healthcare data using blockchain, ensuring raw data privacy. It acknowledges the effectiveness of HPE Swarm Learning but questions its architectural limits and the unit of sharing.
The content discusses how English-first Health AI struggles to process queries in native languages like Marathi, leading to inaccurate responses. It emphasizes the need for AI that can reason natively in multiple languages for effective healthcare support.
The article reveals that most Health AIs are English-first, leading to failures in processing medical queries in languages like Marathi. It criticizes the "English-first with a bolted-on translation" approach and introduces GoDavaii as an AI that reasons natively in 22 Indian languages.
Existing English-first Health AI poorly handles medical queries in languages like Bengali, often suggesting rephrasing in English. In contrast, GoDavaii reasons natively in 22 Indian languages, providing accurate and culturally relevant medical advice.