Neural network news focuses on advancements in AI architectures and their implementation in electronics hardware. Developments include optimized neural processing units (NPUs), edge AI integration, and machine learning algorithm improvements enhancing device intelligence. These technologies enable smarter sensors, autonomous systems, and real-time data analysis across industries. For Electronics Weekly readers, neural network updates offer critical knowledge on hardware-software co-design, performance optimization, and emerging applications shaping the future of intelligent electronics products.
Ambient Scientific is demonstrating AI applications running on coin cell batteries at Electronica India this week, using combined analogue and digital processing to save power. Locally-processed local fall detection, voice recognition and face ID will be running on its ‘GPX10 Pro’ IC. Inside, AI processing is performed in two sets of five cores (called ‘MX8’) in two separate power domains. ...
Renesas is aiming at edge computing applications that need AI and up to two displays with its latest MCU. The top-end 64-bit RZ/G3E has a 1.8GHz quad-core Arm Cortex-A55, a 512Gop/s Ethos-U55 NPU for AI and a Cortex-M33. External memory is handled via a 32-bit LPDDR4/LPDDR4X bus with ECC. “This architecture runs AI applications such as image classification, object recognition, ...
Renesas has introduced a high-end AI MCU family with triple processors and security. The highest spec devices in the ‘RA8P1’ microcontroller family combine a 1GHz Arm Cortex-M85 processor with a 256 MAC/cycle 500MHz Arm Ethos-U55 neural processing unit and a 250MHz Cortex-M33 CPU. “This combination delivers CPU performance of over 7,300 CoreMarks and AI performance of 256Gop/s,” according to the ...
DeepX is to start production of its DX-M1 neural processor unit IC in the second quarter of this year, according to the company, which claims for it “the highest power-efficiency and performance efficiency in the world”. The company has published ResNet-50 figures in support of these claims: >10Top/s/W and 60frame/s/Top/s. Total capability per IC is 25Top/s. It is due to ...
The IEEE’s International Solid-State Circuit Conference in San Francisco featured an overview of next-generation high-performance CPUs. AMD revealed aspects of Zen 5, its x86-64 microprocessor for desktops and laptops. Built on TSMC’s 4nm FinFET process, the 55mm2 eight cores have a total of 8.6bn transistors. Each core has a 1Mbyte private L2 cache and there is 32Mbyte of shared L3. ...
Alif Semiconductor has integrated Arm’s Ethos-U85 neural processing unit (NPU) into its second generation of its ‘Ensemble’ microcontrollers for AI and machine learning. It is “the world’s first implementation of the Ethos-U85 in an endpoint AI MCU”, according to Arm IoT general manager Paul Williamson. “With Alif’s high bandwidth memory and power management, [the new parts] support NPU operators required ...
TDK has created a spin-memristor for analogue neural networks, and built a network that can separate three types of sound in real-time. It has been collaborating on memristors with French research lab CEA since 2020, and has now announced a collection of memristors packaged in an IC (described as ‘three elements by two sets’, photo). Semiconductor process behind this IC ...
BrainChip has created <1mW neural processing core intellectual property for speech, audio and vital signs analysis. Called Akida Pico and described as event-based co-processor, it is intended for “voice wake detection, keyword spotting, speech noise reduction, audio enhancement, presence detection, personal voice assistant, automatic doorbell, wearable AI and appliance voice interfaces”, according to the company. As a co-processor, it would ...
Aaeon is aiming at in-vehicle surveillance systems for busses and law-enforcement with a PC built around Nvidia’s Jetson Orin NX artificial intelligence processor and equipped with eight power-over-Ethernet ports. Called Boxer-8658AI, there are two versions: one with a hex-core Cortex-A78AE v8.2 64bit CPU and 8Gbyte of LPDDR5 memory, and the other with 16Gbyte and an octa-core processor. “For in-vehicle or ...
Ceva has announced a neural network processing core aimed at SoCs needing to run TinyML models. There are two versions: NPN32 with 32 int8 MACs NPN64 with 64 int8 MACs “Both of which benefit from Ceva-NetSqueeze for direct processing of compressed model weights,” according to the company. “NPN32 is optimised for most TinyML workloads targeting voice, audio, object detection and ...
