Research

Privacy-First

Decentralized Learning

In the ever-progressing field of Large Language Models (LLMs), there has been a significant shift towards addressing the critical concerns of data privacy and over-centralized model learning. As these models become more intricate and widely used, the necessity of handling sensitive information securely and distributing the learning process becomes paramount.

AI Agents

In the ever-progressing field of Large Language Models (LLMs), there has been a significant shift towards addressing the critical concerns of data privacy and over-centralized model learning. As these models become more intricate and widely used, the necessity of handling sensitive information securely and distributing the learning process becomes paramount.

Human-AI

Collaboration

LLM-powered knowledge agents offer unprecedented capabilities in various applications ranging from personal assistant to autonomous research and data analysis. As these agents grow in complexity and ubiquity, their ability for problem-solving and global planning is the key to user experience.

Continuous

Learning

The concept of continuous learning represents a pivotal advancement in the development and application of Large Language Models (LLMs), addressing the need for these models to adapt and evolve in response to ever-changing data landscapes. This area of research is particularly crucial in ensuring that LLMs remain relevant, accurate, and efficient in real-world applications.