Data Sovereignty: Designing AI for Local Control
Data in the contemporary world is one of the most valuable assets in the demanding technologies, markets, and society. However, the question of how to govern and control the constantly increasing amount of data in the world also arises. Data sovereignty, therefore, means that the local governments or organizations have the right to decide on the use of data collected in a given geographical area they control.
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.
From Chips to Datacenters: Why Datacenter as a Chip Is Becoming the New AI Architecture
Artificial intelligence workloads are pushing modern datacenters to their architectural limits. As AI models scale across thousands of accelerators, traditional datacenter designs built around loosely coupled servers and software managed coordination increasingly struggle with latency variability, inefficient memory access, and unpredictable performance at scale.