Network Science and Graph Analytics

Applying Network Science to Networking at IceLab Days The annual IceLab Days meeting, organized by the Integrated Science Lab (IceLab), took place on November 13–14 at Skeppsvik Herrgård. The event fostered collaboration among IceLab members and affiliated researchers while strengthening the social and interdisciplinary work culture. This year, IceLab members turned their tools inward, applying network science to visualize current and potential research overlaps. Bridging Disciplines and Building Connections IceLab’s mission is to connect researchers across disciplines for the love of launching and landing new ideas. Through initiatives like the IceLab Lunch Pitches, the lab has built a reputation for facilitating spontaneous collaborations. However, what about researchers who aren’t actively seeking collaborations? Rubén Bernardo Madrid, a postdoctoral fellow at IceLab and one of the event organizers, tackled this challenge head-on while designing the program for IceLab Days. “Man...

Pi2Day 2025: Launching AI Initiative to Scale Next-Generation App Creation and Platform Utilities Today, Pi released two major features: (1) an AI application platform that intends to solve problems the world faces as AI advances, based on both blockchain and AI technologies, as well as expand Pioneers’ access to contribute to, engage with, and support Pi apps and utilities in the ecosystem; and (2) another platform-level utility allowing Pioneers and businesses to support Pi apps and utilities via a staking mechanism. In addition, various tech and product updates have been released along with a new Pi2Day Ecosystem Challenge, which takes Pioneers through new releases and Pi ecosystem features to obtain digital prizes. Before discussing Pi2Day’s releases, let’s dive deeper into the questions on AI, blockchain, and Pi Network that were posed to the community earlier this week: “How is GenAI related to Pi Network?” Pi’s Solution to an AI-Driven World The ultimate utility of any technolog...

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Global AI Server Shipment Forecasts See a Noticeable Decline Following Geopolitical Tensions & Tariff Uncertainty The AI server market is expected to see a decline in YoY growth forecasts, following the uncertainty from US export restrictions, and disruptions in supply chain from geopolitical tensions. Microsoft, Meta & Google Are Continuing With Their AI Spending With Full Force, But There's a Short-term Slowdown The AI bandwagon is moving around with full force around the globe, particularly in North America, where Big Tech is spending massive revenue on creating AI infrastructure. However, based on a report by TrendForce , the uncertainty around President Trump's tariff policies and the recent geopolitical tensions have revised the global AI shipment forecasts, and have now seen a decline, from 28% to 24.3%. While they are still expected to maintain double-digit growth, the decrease is mainly attributed to the supply chain disruptions with evolving trade polices and ...

Learning interpretable network dynamics via universal neural symbolic regression Discovering governing equations of complex network dynamics is a fundamental challenge in contemporary science with rich data, which can uncover the hidden patterns and mechanisms of the formation and evolution of complex phenomena in various fields and assist in decision-making. In this work, we develop a universal computational tool that can automatically, efficiently, and accurately learn the symbolic patterns of changes in complex system states by combining the excellent fitting capability of deep learning with the equation inference ability of pre-trained symbolic regression. We perform extensive and intensive experimental verifications on more than ten representative scenarios from fields such as physics, biochemistry, ecology, and epidemiology. The results demonstrate the remarkable effectiveness and efficiency of our tool compared to state-of-the-art symbolic regression techniques for network dynam...

Researchers solve silent packet drop problem in multi-node chip interconnects A group of researchers from South Korea has proposed a method to more reliably scale chip-to-chip interconnects. The ever-increasing scale of AI models, such as Meta’s mammoth  Llama 3.1 405B  and Anthropic’s recently released  Claude 4  family of models, requires massive multi-node computing clusters where reliable chip interconnects are crucial. Several methods exist to support chip-to-chip interconnects, but researchers from Sungkyunkwan University and the Korea Advanced Institute of Science and Technology (KAIST) took issue with existing protocols, such as  Compute Express Link  (CXL), Nvidia’s  NVLink , and the recently launched  UALink . They argue that while such protocols might work well for point-to-point links, they become unreliable in multi-node, switched environments (e.g., AI training loads distributed across multiple interconnected systems via a high-speed...