Editors’ note: “AI-native systems” is one of today’s most prominent tech buzzwords, yet its meaning remains ambiguous and often inconsistently defined. In this article, Professor Cheng Tan offers a technical perspective on what constitutes an AI-native system, providing both a clear definition and a systematic framework to help understand the technical evolution of AI for systems. … Read more
Systems research prizes efficiency and performance. For the last decade, I’ve worked on ultra-low-latency systems: the goal of Demikernel and its related nanosecond-scale systems (e.g., Cornflakes, Capybara) is to do more with fewer cycles. AI coding has brought the same level of efficiency to building systems, letting fewer programmers write more code. However, it has … Read more
Editors’ note: AI has been actively pushing the frontier of applied formal methods for computing systems. In this article, the Specula team wrote about their experience of evaluating LLMs on modeling system code, the basic capability for agentic model checking, using TLA+, a specification language for concurrent and distributed systems. The article is the 7th … Read more
Editors’ note: Self-Defining Systems is a new paradigm and a new research initiative at the University of Washington with the goal of leveraging the unique abilities of LLMs to accelerate infrastructure agility, while compensating and masking their weaknesses. It envisions a future in which infrastructure can design, validate, and evolve itself with minimal human intervention. … Read more