Sahara Research leads innovations on fair access and ownership to global knowledge capital
Sean Ren
AI development is at an inflection point. On many fronts, AI has begun
to surpass human performance and automate increasingly large portions of
our lives. In the new era, it is critically important to protect the
privacy of users, guarantee the provenance of the data and model, and
establish a decentralized and trustless network of AI and humans.
SaharaResearch
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.
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.
The intersection of human intelligence and artificial intelligence,
particularly in the context of Large Language Models (LLMs), presents
a landscape rich with opportunities and challenges. Understanding the
dynamics of Human-AI collaboration is essential for leveraging the
capabilities of LLMs while addressing potential risks.
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.
