#edge ai
Edge Ai: 25 AI articles covering edge ai news, analysis, and research
Articles
Turning Edge AI Data Into Real-Time Actionβ9
Edge AI moves from concept to production in 2026. Explore TinyML, hardware acceleration, and real-time pipelines turning edge data into instant action.
AI-Defined Vehicles Push Compute, Memory, and Validation Limitsβ10
As vehicles become defined by AI, chip designers face rising demands for compute, memory bandwidth, and rigorous validation across the automotive semiconductor ...
The Hidden Challenges of Edge AI Designβ9
Edge AI design hides tough challenges in power, memory, and model compression. Learn the trade-offs engineers must solve for real-time, low-latency inference.
Designing Physical AI Systems Under Real-World Constraintsβ9
Physical AI systems must work reliably under real-world power, latency, and safety constraints. Learn how to design hardware and models together for deployment.
PrismML Brings Its Tiny LLMs to Qualcomm-Powered Smart Glassesβ8
PrismML's 1-bit Bonsai LLM runs locally on Qualcomm Snapdragon AR1 Gen 1 smart glasses, shrinking models 4x while keeping near-full benchmark performance.
Chip Industry Technical Paper Roundup: September 22, 2026β9
Curated semiconductor research digest for September 22, 2026, covering chiplets, advanced packaging, AI-driven EDA, GAA scaling, edge AI, and hardware security.
How 60 GHz Radar Improves Low-Power Presence Sensing in IoT Devicesβ10
60 GHz radar enables accurate, low-power presence sensing in IoT devices, detecting stationary people while preserving privacy and cutting energy use.
Hardware-Software Co-Design in the AI Era: A 2026 Perspectiveβ9
Hardware-software co-design is reshaping AI computing by 2026, enabling domain-specific architectures, chiplets, and AI-driven design automation for faster, eff...
Building Trust Into Physical AI Systemsβ9
Discover how physical AI systemsβrobots, autonomous vehicles, and industrial gearβbuild trust through safety, transparency, and robust verification for real-wor...
Humanoid Compute and Security: A More Complex Challenge Thanβ9
Humanoid robots demand far more complex compute and security than autonomous vehicles, requiring distributed processing, real-time safety, and robust defenses.