AI Data Centers And Auto Industry Converge On Same Issues
The EV revolution relies on battery innovation, while AI data centers need a range of new energy solutions to play nice with the grid. Both sectors...
Defending Against AI-Enabled Data Fusion
As multimodal AI fuses data from billions of devices, attackers can weaponize detailed digital twins of people or systems.
Fine-Tuning Humanoid Vision And Movement
Ongoing innovations are enabling humanoids to see and move more like humans; smell and taste are next.
Wi-Fi Flies Higher As Edge AI Build-Out Takes Root
Chip and system designers scramble to leverage existing and future standards as edge AI increases demand for faster data movement and greater relia...
Orbital Data Centers Are Souped-Up Satellites – For Now
Satellite constellations with extra onboard compute are several steps away from handling full AI workloads for people on Earth.
Keeping Security Algorithms Current Is Getting Harder
As threats evolve faster, protecting security algorithms from design through manufacturing and across the supply chain is becoming more difficult.
AI-Defined Vehicles Increase Pressure On Auto Ethernet Re...
Time-sensitive networking and MACsec allow Auto Ethernet to handle safety-critical functions and enable real-time processing for AI-enabled feature...
Building AI Without Guardrails
The semiconductor ecosystem is wrestling with fragmented standards, IP exposure, and the urgent need for runtime assurance.
Humanoid Touch And Voice Are Improving Rapidly
General-purpose humanoid robots need all their senses to function equally well; vision and movement are the farthest along, but others are catching...
Next-Gen Batteries Require Impedance Data And Active Bala...
Battery management systems are growing increasingly smarter with innovations in software and hardware that enable more accurate estimation of batte...
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AI Workloads at the Edge: Ensuring Performance, Privacy, ...
There are challenges and solutions for processing AI workloads on-device to achieve consistent performance, reduce costs, and enhance data privacy ...
Optimizing AI Workloads For Edge Computing
Performance enhancement, cost reduction, data security, and improved energy efficiency are the end goals for optimizing AI workloads at the edge.
Moving AI Workloads To The Edge
There are benefits and challenges of processing AI workloads on-device to enhance performance, reduce costs, and ensure data privacy.
Physical Access Control Raises New Security Concerns
Small language models, longer device lifetimes, and thermal manipulation make securing hardware much more challenging.
Security Tradeoffs: A Difficult Balance
Lack of security metrics, and the increasing adoption of chiplets, 2.5D architectures, and AI all complicate security.
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DFT In Automotive
What's needed to ensure reliability of automotive chips, and why it’s about to get even tougher.
Wi-Fi 7 Moves To The IoT
What's behind the widespread adoption of extremely high-throughput wireless.
Preparing For The Quantum Computing Age
Designing chips and systems to withstand brute-force attacks by quantum computers.
Conversing With Your Dishwasher
How on-device AI can improve interactions with machines.
Changes In Motor Control
Why motors are becoming quieter, more efficient, and more secure.
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