When governance is engineered into how data is created and used, it accelerates access, experimentation, model development ...

Modern control system design is increasingly embracing data-driven methodologies, which bypass the traditional necessity for precise process models by utilising experimental input–output data. This ...

As companies rely more heavily on real-time analytics and AI-driven tools, data engineering is evolving into a role that ...

The semiconductor industry enters 2026 amid a fundamental transformation as AI continues to expand faster than any previous compute wave. SoC design teams are confronting a level of complexity that is ...

When synthetic data and digital twins are combined, the result is a technological synergy that unlocks design potential, accelerates prototyping and expands the limits of creativity. In the field of ...

The rapid escalation of AI/ML workloads—driven by increasingly large language models—is reshaping high-performance computing and AI data center architectures. Real-time inference and large-scale ...

Why it matters: Operating data centers requires a lot of energy, and the enormous amount of water used to cool them is a growing environmental concern. As the expansion of AI data centers exacerbates ...

Validates the performance of AI infrastructure by emulating real-world workloads Evaluates how new algorithms, components, and protocols improve the performance of AI training Adjusts and optimizes ...

Data centers and high-performance computing (HPC) are the primary enablers of today’s power-hungry AI-driven technology, but chip designers, EDA vendors, and the data centers themselves have a long ...

AurenixAI uses advanced artificial intelligence to power modern trading systems, improving speed, accuracy, and smarter data-driven decisions in fast-moving financial markets.