New workload demands are turning data handling into a system-level design challenge rather than a back-end afterthought.

As I mentioned in the first article in this series, System Design For The AI Era: AI Data Centers Requires A Holistic Approach, data centers are the heart of the AI era. However, the exponential ...

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 ...

News cycles are increasingly dominated by debates about AI’s impact on power systems, consumer energy prices, grid emissions and grid resilience.

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 ...

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 ...

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 ...

Rather than positioning sustainability as a branding exercise, MBT’s approach reflects a practical engineering response to a ...

To complete the above system, the author’s main research work includes: 1) Office document automation based on python-docx. 2) Use the Django framework to develop the website.

Innovative CLIQ system removes lighting as a construction bottleneck by dramatically reducing labor time and operating ...