Semiconductors
As AI workloads move to the edge and space, the challenge of securing Terabit Ethernet and preventing hardware-level breaches has become a top priority for chip designers.
Semiconductors
As the industry moves toward the sub-2nm node, engineers face a paradox: shrinking features can lead to diminishing returns without radical new approaches to variation management and workload-specific hardware.
Semiconductors
Researchers from Stanford and Google have developed 'ITHICA,' a new approach to detecting Silent Data Corruptions (SDCs) in CPUs. As chip nodes shrink, these hardware 'flips' are becoming a major threat to the reliability of hyperscale AI data centers.
Semiconductors
As large language models move from training to inference, the underlying hardware architecture is evolving. New research into SRAM-based pipelines suggests a path toward drastically faster and more efficient AI serving.
Semiconductors
The industry is shifting toward heterogeneous integration and chiplets to overcome the physical limits of monolithic silicon. New roadmaps are required to manage the cooling and power delivery challenges of these complex stacks.
Semiconductors
As AI models grow more complex, the hardware supporting them is evolving toward 3D integrated circuits (3D-ICs). Managing power integrity in these stacked architectures is now the primary challenge for semiconductor designers.
Semiconductors
High-density 3D-IC architectures are becoming essential for AI scaling, but they present unprecedented challenges in power integrity and delivery.
Semiconductors
The semiconductor industry is shifting toward 'Agentic EDA,' utilizing AI agents to navigate the vast complexity of chip design reaching billions of violations.
Semiconductors
AI chip design is entering a new era of complexity, requiring advanced 3D packaging and 'silicon-to-system' collaboration. Engineers are moving beyond simple logic to focus on interconnects and thermal management as the main hardware bottlenecks.
The Un-Engineering Lens
What Auto China 2026, DeepSeek V4 and Tesla’s Q1 just quietly agreed on — and why the TOPS race is over. April 22–26, 2026 looked like three unrelated events. Tesla reported Q1 earnings on Tuesday. DeepSeek dropped V4 on Hugging Face on Friday. Auto China 2026 opened in Beijing
Semiconductors
The semiconductor industry is turning to deep learning and AI-driven metrology to enhance chip yields at the nanometer scale. Advanced inspection systems are now capable of detecting sub-microscopic defects that previous generations of hardware would have missed.
Semiconductors
As AI moves toward edge and local agentic models, the semiconductor industry is focused on HBM4 validation and PCIe 8.0 to overcome the data bottlenecks of the next generation.