Femtosense, in partnership with ABOV Semiconductor, launched the AI-ADAM-100, an artificial intelligence microcontroller unit (AI MCU) built on sparse AI technology to enable on-device AI features such as voice-based control in home appliances and other products. On-device AI provides immediate, no-latency user responses with low power consumption, security, operational stability, and low cost compared to […]
Artificial intelligence
Complimentary version of AI software tool developed for AI and TinyML applications
Renesas Electronics Corporation has launched Reality AI Explorer Tier, a complimentary version of Reality AI Tools software tailored for developing AI and TinyML solutions in the industrial, automotive, and commercial sectors. Reality AI Explorer Tier grants users access to a comprehensive, self-guided evaluation sandbox. It includes the full suite of Reality AI Tools features for […]
How software segregation minimizes the impact of AI/ML on safety-critical software
With the growing use of artificial intelligence and machine learning in safety-critical software, developers are considering software segregation and guardian applications to mitigate functional safety risks. By Mark Pitchford, LDRA The push toward artificial intelligence (AI) and machine learning (ML) in embedded systems raises questions about adapting functional safety processes and tools to achieve compliance. […]
SMARC modules boost performance for industrial and AI applications
Congatec has introduced new high-performance computer-on-modules (COMs) featuring i.MX 95 processors from NXP. This addition expands Congatec’s module portfolio, which includes low-power NXP i.MX Arm processors. The new modules offer straightforward scalability and reliable upgrade paths for energy-efficient edge AI applications with high security requirements. These modules provide up to three times the GFLOPS computing […]
Radiation and fault-tolerant MPUs support AI and ML in space missions
Microchip Technology has launched the first devices in its planned family of PIC64 High-Performance Spaceflight Computing (PIC64-HPSC) microprocessors (MPUs) to support the diverse and growing global space market’s expanding computational needs, including more autonomous applications. The radiation- and fault-tolerant PIC64-HPSC MPUs, delivered to NASA and the broader defense and commercial aerospace industry, integrate widely adopted […]
How is Zephyr used for edge AI and sensors?
Zephyr is a scalable open-source real-time operating system (RTOS) hosted by the Internet of Things (IoT) and embedded technology section of the Linux Foundation. Its modular architecture makes it highly flexible and suitable for use on resource-constrained edge devices and sensors. This article reviews Zephyr’s structure and features, examines how Zephyr supports neural networks and […]
AI SoCs power vehicle cameras in fleet telematics systems
Ambarella, Inc. announced during AutoSens USA, the latest generation of its AI systems-on-chip (SoCs) for in-vehicle fleet telematics systems. Ideal for AI dash cams integrating front-facing ADAS and driver monitoring systems (DMS), the new CV75AX provides up to 2x the AI performance over Ambarella’s prior-generation SoC, enabling the latest transformer neural networks for improved accuracy and reduced false […]
Software bridges gap between AI and hardware for edge devices
Siemens Digital Industries Software has announced Catapult AI NN software for High-Level Synthesis (HLS) of neural network accelerators on Application-Specific Integrated Circuits (ASICs) and System-on-a-chip (SoCs). Catapult AI NN is a solution that starts with a neural network description from an AI framework, converts it into C++, and synthesizes it into an RTL accelerator in Verilog […]
How do AI and ML enhance SASE security?
Secure Access Service Edge (SASE) has emerged as a leading architecture for cloud deployments. Its primary function is to provide comprehensive cloud-based secure access while maintaining seamless access to data and applications for users of cloud computing services. This article compares SASE with a traditional network architecture and then looks at how artificial intelligence (AI) […]
What’s the difference between GPUs and TPUs for AI processing?
Graphic processing units (GPUs) and tensor processing units (TPUs) are specialized ICs that support different types of artificial intelligence (AI) and machine learning (ML) algorithms. This article begins with a brief overview of tensors and where they fit into the mathematics of AI and ML; it then looks at the different structures of GPUs and […]
