Consumer And Med Tech Mushroom As Quantum Closes In


Key Takeaways: Universities and companies are making devices inspired by biology and the human senses to help with health monitoring, semiconductor materials development, human-computer interfaces, and more. When this nascent technology becomes a viable product, government regulations will be needed to ensure consumer safety in tracking or treating their body and the environment. Qua... » read more

Chip Industry Technical Paper Roundup: Jan. 20


New technical papers recently added to Semiconductor Engineering’s library: [table id=515 /] Find more semiconductor research papers here. » read more

Chip Industry Week in Review


Geopolitics Taiwan and the U.S. signed a trade agreement this week, with TSMC and other Taiwanese companies collectively pledging to directly invest at least $250B in investments in advanced semiconductor, energy and AI production and capacity in the U.S.  The agreement also included Taiwan providing another $250B in credit guarantees for additional IC supply chain expansions in the U.S., cap... » read more

Loss Errors in Error-Corrected Circuits Across A Range Of Quantum Hardware Platforms (MIT, Harvard, QuEra)


A new technical paper titled "Leveraging Qubit Loss Detection in Fault-Tolerant Quantum Algorithms" was published by researchers at MIT, Harvard and QuEra Computing. Abstract "Qubit loss errors constitute a dominant source of noise in many quantum hardware systems, particularly in neutral-atom quantum computers. We develop a theoretical framework to effectively detect and correct loss err... » read more

Chip Industry Week in Review


SIA's latest monthly global semiconductor sales report reflects a ~30% YOY increase, hitting a record $75.3B in November 2025. Asia Pacific had a notable 66% increase. Cadence launched its Chiplet Spec-to-Packaged Parts ecosystem to accelerate time to market for chiplet development for physical AI, data centers, and HPC applications. Initial IP partners joining Cadence include Arm, Arteris, ... » read more

Chip Industry Week in Review


Microsoft, OpenAI, and NVIDIA warned about power swings and physical damage to power grids increasing from AI training workloads and jointly proposed a multi-pronged approach to stabilize power in AI training data centers. Meanwhile, Anthropic issued a warning about the weaponization of agentic AI in a new 25-page Threat Intelligence report. Key concerns involve the evolution in AI-assisted ... » read more

Chip Industry Week in Review


The Chinese Academy of Sciences unveiled a fully automated processor chip design system, claiming the potential to accelerate semiconductor development and replace human programmers. Micron Technology plans to expand its U.S. investments to approximately $150 billion in domestic memory manufacturing and $50 billion in R&D, which is $30 billion higher than previously reported. AMD laun... » read more

Review Paper: Challenges Required To Bring the Energy Consumption Down in Microelectronics (Rice, UC Berkeley, Georgia Tech, Et al.)


A new review article titled "Roadmap on low-power electronics" by researchers at Rice University, UC Berkeley, Georgia Tech, TSMC, Intel, Harvard, et al. This roadmap to energy efficient electronics written by numerous collaborators covers materials, modeling, architectures, manufacturing, metrology and more. Find the technical paper here. September 2024. Ramamoorthy Ramesh, Sayeef Sal... » read more

Chip Industry Week In Review


By Jesse Allen, Karen Heyman, and Liz Allan AMD took the covers off new AI accelerators for training and inferencing of large language model and high-performance computing workloads. In its announcement, AMD focused heavily on performance leadership in the commercial AI processor space through a combination of architectural changes, better software efficiency, along with some improvements in... » read more

Security Becomes Much Bigger Issue For AI/ML Chips, Tools


Security is becoming a bigger issue in AI and machine learning chips, in part because the chip industry is racing just to get new devices working, and in part because it's difficult to secure a new technology that is expected to adapt over time. And unlike in the past, when tools and methodologies were relatively fixed, nearly everything is in motion. Algorithms are being changed, EDA tools ... » read more

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