Streamlined development platforms are now critical to edge AI deployment as larger AI/ML models raise complexity, time, and cost across embedded workflows.

FPGAs also provide hardware adaptability, deterministic processing, and high-speed I/Os, making them suited for physical AI applications. The growth of physical AI, which require a much richer set of ...

As these apps become broader team tools, the scale and breadth of the interaction start to matter. Users are working through more test and simulation data, and more of the value comes from the ...

Cadence Design Systems Inc. has introduced the Maestro AI Model Portfolio, a collection of domain-specialized artificial intelligence models designed to power agentic workflows across semiconductor ...

On Variscite’s i.MX 93 and i.MX 95 SoMs, the implementation can leverage the processor’s security architecture, including NXP’s EdgeLock Secure Enclave as the root of trust. This approach allows ...

Cooling failures remain the second-leading cause of data center outages. Downtime is now more costly than hardware loss, making early detection critical. The ability to detect leaks at the source and ...

Axiado Corporation has announced a collaboration with Arm to integrate its Data Center Secure Control Module (DC-SCM) cards into the Arm AGI CPU server platform. The integration combines ...

Artificial intelligence is reshaping data center architecture by changing where system bottlenecks occur. For years, networking discussions focused primarily on scale-out communication between servers ...

Qorvo Inc. has introduced an X-band RF front-end solution designed for active electronically scanned array (AESA) radar systems. The architecture combines transmit drive, receive performance, and RF ...

Microchip Technology Inc. has expanded its data center portfolio with new connectivity, storage, and acceleration capabilities designed to meet the performance, security, and scalability needs of AI ...

Silicon Labs has expanded its developer platform with new tools for AI-assisted embedded development, hardware and software validation, open-source collaboration, and edge AI lifecycle management.

Artificial intelligence is rapidly moving from the data center to the edge. Personal electronic devices, industrial controllers, cameras, vehicles, and a multitude of connected devices more frequently ...