EllanorAI
Advancing the Frontiers of Artificial Intelligence
About Lumina Language Model
Lumina LM is at the forefront of language model research and development, pushing the boundaries of what's possible in artificial intelligence. Our mission is to develop advanced, efficient, and safe large language models that can enhance human capabilities and solve complex problems.
At EllanorAI, we are committed to advancing artificial intelligence through groundbreaking research in natural language processing. We are dedicated to developing AI technologies that are both powerful and accessible, ensuring exceptional performance without compromising efficiency.
Our Technology
Advanced AI Models
Cutting-edge AI models designed to comprehend and generate human-like text with exceptional accuracy across diverse domains
Efficient Training Techniques
Innovative approaches to train large language models more efficiently and with less computational resources.
Lumina LM leverages cutting-edge deep learning techniques and vast datasets to create powerful language models:
- Advanced Language Models: Our models are trained on diverse text data, enabling them to understand and generate human-like text across various domains and languages.
- Efficient Training Techniques: We develop innovative approaches to train large language models more efficiently, reducing computational resources and time required.
Our Models
Current Prototype Model
LuminaLM-2M is our current prototype denoising autoencoder language model featuring 2 million parameters, designed as a compact yet powerful foundation for testing and validating our innovative training methodologies.
- Efficient parameter utilization with only 2M parameters
- Specialized for targeted natural language tasks
- Serves as our experimental testbed to work with Denoising Autoencoder Language Models
Coming Soon
LuminaLM-Base-10B is our upcoming flagship model with 10 billion parameters, featuring groundbreaking self-adaptive capabilities across both text and image modalities.
Self-Adaptive Architecture
The core innovation of LuminaLM-Base-10B is its self-adaptive architecture that dynamically reconfigures its parameters based on input context and task requirements. Unlike traditional models with fixed weights, LuminaLM-Base-10B can:
- Dynamically adjust attention patterns in real-time
- Seamlessly transition between text and image processing modes
- Allocate computational resources efficiently based on task complexity
- Continuously refine its internal representations without explicit fine-tuning
This self-adaptive capability represents a significant leap forward in language model design, enabling more efficient processing and better performance across a diverse range of tasks with minimal specialized training.
Research Areas
Advancing the field of NLP through innovative techniques in language understanding and generation.
Featured Research: Transformer-Squared
The latest paper "Transformer-Squared: Self-Adaptive LLMs" introduces a novel framework that enables language models to adapt to unseen tasks in real time by selectively adjusting singular components of their weight matrices.
Singular Value Fine-tuning (SVF)
This novel parameter-efficient fine-tuning method outperforms traditional approaches with fewer parameters.
Two-Pass Adaptation
This framework employs a two-pass mechanism that identifies task properties and dynamically mixes task-specific vectors for targeted behavior.
Published as a conference paper at ICLR 2025
Our Team
Archit Sood
Co-Founder & CEO
PG Deep Learning Cert. from IIT Kanpur with an MBA from Amity. Built LuminaLM on OpenWebText2.
Aaqib Guru
Co-Founder & CBO
MBA in International Business from Amity University, Mumbai. Expertise in strategy, operations, and GTM execution.
Bodhita Baviskar
Chief of BioMedical R&D
MBA from Amity with a B.E. in Biomedical Engineering from the University of Mumbai. Led a Li-Fi-based vitals transmission project for hospital use.
Dr. Anurag Rana
AI and Data Scientist
Post-Doc & Ph.D. (Applied AI). Expert in AI, soft computing & data science with 13+ years in teaching and research, holding 5 patents and 50+ research papers.
Prof. Dr. Pankaj Vaidya
Chief AI Scientist & Advisor
Ph.D. in AI & Machine Learning with 24+ years of experience. Filed multiple patents and published over 25 research papers.
Nitesh Sharma
Data Engineer
Expert in enterprise software, web applications, SaaS and LMS. Over 7 years as CTO and researcher; co-founder of Maplle Technologies.
Mahesh Kumar
Cloud Engineer
Expert in cloud computing, IT infrastructure, and network administration with over 9 years of experience as an Assistant Professor and System Analyst.
Contact Us
Interested in EllanorAI's research or potential collaborations? Get in touch with us.