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AI Engineering Collective

What are the benefits of RISC-V in AI, ML, and embedded systems?

February 4, 2026 By Jeff Shepard Leave a Comment

The open-source nature of RISC-V brings the benefits of a modular and royalty-free instruction set architecture (ISA) that eliminates licensing fees, can accelerate development, and fosters customization for diverse applications, including artificial intelligence (AI), machine learning (ML), the Internet of Things (IoT), and embedded systems. Automation levels are being increased in many types of applications, […]

Filed Under: AI Engineering Collective, Applications, Artificial intelligence/ML, FAQ, Featured, RISC-V Tagged With: AI, ML, RISC-V

How is physical artificial intelligence used to optimize data center efficiency?

January 28, 2026 By Jeff Shepard Leave a Comment

Physical AI (PAI) in data center power systems uses machine learning for predictive maintenance, energy optimization, load balancing, and physical security. In essence, PAI is being used for data center optimization to support the demands of digital AI (DAI) applications like training large language models (LLMs), running inference for real-time applications, and supporting infrastructure like […]

Filed Under: AI Engineering Collective, Applications, Artificial intelligence/ML, FAQ, Featured Tagged With: AI, data center, PAI

What is an AI governor and how does it relate to physical AI?

January 21, 2026 By Jeff Shepard Leave a Comment

An AI governor is a framework, set of policies, or an oversight mechanism designed to ensure that the development and use of AI systems are ethical, safe, transparent, and compliant with legal and societal standards. The term can also refer to an actual piece of code or circuit (governor logic) used as a safety mechanism […]

Filed Under: AI Engineering Collective, Applications, Artificial intelligence/ML, FAQ, Featured Tagged With: FAQ, PAI

Entry-level AI MCU enables low-power edge inference on one chip

January 15, 2026 By Puja Mitra Leave a Comment

The NuMicro M55M1 AI MCU from Nuvoton Technology, developed in collaboration with the Industrial Technology Research Institute, integrates an Arm Cortex-M55 core with an Arm Ethos-U55 micro-NPU to deliver about 110 GOP/s for edge AI inference. The device includes up to 1.5 MB SRAM and 2 MB Flash with optional HyperRAM and HyperFlash expansion, enabling […]

Filed Under: AI Engineering Collective, Applications, Artificial intelligence/ML, microcontroller Tagged With: MCU, nuvoton

How is physical AI used in autonomous and electric vehicles?

January 14, 2026 By Jeff Shepard Leave a Comment

Physical AI (PAI) in autonomous and electric vehicles (EVs) involves systems that perceive the environment, make intelligent decisions, and execute appropriate actions in real-time, bridging the gap between digital intelligence and physical motion. PAI is autonomous, and electric vehicles can be used for several functions. Initially, it’s helping improve battery management and energy efficiency. In […]

Filed Under: AI Engineering Collective, Applications, Artificial intelligence/ML, Automotive, EV Engineering, FAQ, Featured Tagged With: EV, FAQ, PAI

What are the applications of physical artificial intelligence?

January 7, 2026 By Jeff Shepard Leave a Comment

Physical artificial intelligence (PAI) enables machines to perceive, reason, and act within the real world, bridging the gap between digital AI (DAI), sometimes called virtual AI, and physical action. PAI often leverages spatial artificial intelligence (SAI) technology. PAI applications span numerous industries, from basic automation to autonomous vehicles and complex surgical procedures. PAI applications represent […]

Filed Under: AI Engineering Collective, Applications, Artificial intelligence/ML, FAQ, Featured Tagged With: FAQ, PAI

What is physical artificial intelligence and why is it important?

December 31, 2025 By Jeff Shepard Leave a Comment

Physical artificial intelligence (PAI) refers to AI systems that can perceive, understand, reason about, and interact with the physical world in real time through sensors and actuators. Unlike digital AI (DAI), which operates in virtual domains, PAI powers tangible actions in dynamic, real-world environments. PAI is used in closed-loop systems where the AI model not […]

Filed Under: AI Engineering Collective, Applications, Artificial intelligence/ML, FAQ, Featured Tagged With: FAQ, machine learning, ML, PAI, physical AI

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Featured Contributions

Can chiplets save the semiconductor supply chain?

Navigating the EU Cyber Resilience Act: a manufacturer’s perspective

The intelligent Edge: powering next-gen Edge AI applications

Engineering harmony: solving the multiprotocol puzzle in IoT device design

What’s slowing down Edge AI? It’s not compute, it’s data movement

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Tech Toolbox: Connectivity
AI and high-performance computing demand interconnects that can handle massive data throughput without bottlenecks. This Tech Toolbox explores the connector technologies enabling ML systems, from high-speed board-to-board and PCIe interfaces to in-package optical interconnects and twin-axial assemblies.

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