LLMs at the Edge: Decentralized Power and Control
First, large language models (LLMs), such as those in the recent GPT-3, have proved crucial in processing and generating natural language and are core in applications like translation, chatbots, and content generation. Nonetheless, LLMs depend on centralized cloud infrastructure, which has drawbacks. Clients of these models demand significant computational power and storage, making real-time response a potential issue and privacy concern as the data is sent to distant servers.
Agentic AI in Healthcare: From Assistance to Autonomy
Healthcare is one of the most data-rich and complex industries in the world. With electronic health
records (EHRs), medical imaging, genomics, wearable devices, and clinical trial data, the
challenge lies not in scarcity of information but in making sense of it at scale. Traditional AI
systems have shown promise in diagnostics, drug discovery, and patient management, but they
largely function as reactive systems providing outputs only when prompted.