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Boost the Power Delivery Potential of USB-C Ports with Protection Switches

Boost the Power Delivery Potential of USB-C Ports with Protection Switches

Learn how innovative technologies like protection switches will be crucial in transitioning to high-power delivery of USB-C ports.


The Hidden Cooling Bottleneck Inside Liquid-Cooled AI Data Centers

The Hidden Cooling Bottleneck Inside Liquid-Cooled AI Data Centers

Learn how liquid cooling eliminates system airflow, creating a hidden thermal bottleneck for 'left-behind' components like memory and SSDs. Targeted micro-cooling is required to restore system balance.


Breaking the Thermal Wall Using Monolithic Ceramic Cooling for Power Electronics

Breaking the Thermal Wall Using Monolithic Ceramic Cooling for Power Electronics

Learn how monolithic ceramic cooling using Selective Laser Reaction Sintering (SLRS) eliminates the "thermal wall" in high-density power electronics by creating single-piece, reliable heat exchangers.


Case Study: A Low-Cost, Low-Profile 6kW, 800 V to 12.5 V DC-DC for AI Power

Case Study: A Low-Cost, Low-Profile 6kW, 800 V to 12.5 V DC-DC for AI Power

Learn how GaN technology enables a low-cost, low-profile 6 kW, 800 VDC to 12.5 VDC converter using an ISOP LLC topology. This meets the design needs of next-gen, MW-scale AI server infrastructure.


The New Moore’s Law: Why Optical Computing Could Redefine Scaling for AI

The New Moore’s Law: Why Optical Computing Could Redefine Scaling for AI

Optical computing is the "New Moore's Law" for AI. It solves electronic scaling limits, offering higher speed, lower power, and efficiency gains proportional to problem size for matrix operations.


Edge AI’s Next Battlefield: Development Tools

Edge AI’s Next Battlefield: Development Tools

Learn why the best silicon is useless without the right AI developer tools.


Solving the QLC NAND Flash SSD Scaling Challenge

Solving the QLC NAND Flash SSD Scaling Challenge

Learn how to solve QLC NAND's endurance, ECC, and performance issues for hyperscale. The approach blends a PCIe Gen5 controller with hardware-accelerated LDPC, PerformaShape QoS, and more.


Security and Upgradeability: Key for Moving From Proof-of-Concept to Product

Security and Upgradeability: Key for Moving From Proof-of-Concept to Product

We examine the software used in a 2025 object detection demo and the lessons it holds for developing new edge AI products.


How Machine Learning Is Shrinking to Fit the Sensor Node

How Machine Learning Is Shrinking to Fit the Sensor Node

Learn how “right-sized” machine learning enables edge devices to make critical decisions locally, improving reliability and reducing reliance on cloud connectivity in remote, volatile environments.


Design for the Future: How UALink Interconnects Empower Next-Gen AI Systems

Design for the Future: How UALink Interconnects Empower Next-Gen AI Systems

Learn how UALink offers an open, high-speed interconnect for AI accelerators, that enables scalable, low-latency, and energy-efficient AI systems for next-gen workloads.


Beyond Copper and Optical, a New Interconnect Eyes Next Gen Data Centers

Beyond Copper and Optical, a New Interconnect Eyes Next Gen Data Centers

Both copper and optical interconnects face limitations as choices for next gen data centers. Learn how a third option promises to enable scaling up AI clusters in data centers for years to come.


AI Inferencing in Data Centers: Breaking the Efficiency-Cost Tradeoff

AI Inferencing in Data Centers: Breaking the Efficiency-Cost Tradeoff

Training and inferencing comprise two crucial aspects of AI processing in datacenters. Learn the differences between the two, and the cost-efficiency issues involved.


How To Streamline the IoT Security Lifecycle

How To Streamline the IoT Security Lifecycle

Security in IoT systems is both an end-to-end problem and a lifecycle challenge. In this article, learn cost-effective ways to craft an enduring, secure IoT implementation.


Crafting a Silicon Lifecycle Management Strategy for HPC and Data Centers

Crafting a Silicon Lifecycle Management Strategy for HPC and Data Centers

As data center computing and HPC advances, the stakes for ensuring reliability are high. Learn how to develop a silicon lifecycle management (SLM) strategy that ensures a successful future for your designs.


Understanding How CXL 3.0 Links the Data Center Fabric

Understanding How CXL 3.0 Links the Data Center Fabric

The CXL data protocol is essential for meeting the interconnect needs of today’s data centers. Learn the key elements and benefits of this protocol, along with what’s new in CXL version 3.0.


System Challenges of Generative AI Inference Acceleration

System Challenges of Generative AI Inference Acceleration

When you look under the hood of generative AI processing, the system design challenges are many. Learn how efficiency, power consumption, and memory issues all come into play.


Understanding the Compute Hardware Behind Generative AI

Understanding the Compute Hardware Behind Generative AI

Generative AI tools like ChatGPT have had a huge impact in numerous sectors of society. As engineers, it’s helpful for us to understand the computing technology that makes it possible.


Increasing the Accessibility of Machine Learning at the Edge

Increasing the Accessibility of Machine Learning at the Edge

"Edge intelligence" is becoming more accessible—even to those designers without formal data science training—as new hardware becomes available.


Adding an ISP and Machine Learning Acceleration to the i.MX 8M Family

Adding an ISP and Machine Learning Acceleration to the i.MX 8M Family

Learn how the i.MX 8M Plus applications processor enables edge computing, speeding up machine learning for a variety of applications including industrial tasks.


The Importance of Reliability Verification in AI/ML Processors

The Importance of Reliability Verification in AI/ML Processors

With the adoption of artificial intelligence and machine learning in a wide variety of applications, reliability verification of AI/ML processors is critical since failures can have major consequences for the validity and legitimacy of AI/ML technology.