$70 Raspberry Pi AI Kit combines official M.2 HAT+ with Hailo-8L AI accelerator

Raspberry Pi AI Kit Raspberry Pi 5

Raspberry Pi Limited has just launched the “Raspberry Pi AI Kit”  comprised of the official M.2 Key M HAT+ and a 13 TOPS Hailo-8L M.2 AI accelerator module and selling for $70 through distributors. We had seen Raspberry Pi showcase an AI camera at Embedded World 2024, so when I received an email from a representative about a “Raspberry Pi AI Kit” I thought it would be the announcement about the camera. Instead, it’s a kit comprised of existing parts with the most interesting aspects being the price and availability (hopefully) since Hailo-8/8L accelerators are mostly found in more expensive embedded/industrial solutions, and easier documentation to get started. Raspberry Pi AI Kit highlights: Support SBC – Raspberry Pi 5 M.2 HAT+ with PCIe Gen2 x1 interfaces, M.2 Key M support, Hailo-8L AI accelerator with Up to 13 TOPS of performance M.2 2242 form factor Typical power consumption – 1.5W Thermal […]

Hailo-10 M.2 Key-M module brings Generative AI to the edge with up to 40 TOPS of performance

Hailo-10 M.2 module generative AI for the edge

Hailo-10 is a new M.2 Key-M module that brings Generative AI  capabilities to the edge with up to 40 TOPS of performance at low power. It targets AI PCs supporting only the Windows 11 operating system on x86 or Aarch64 targets at this time. Hailo claims the Hailo-10 is faster and more energy efficient than integrated neural processing unit (NPU) solutions found in Intel SoCs and delivers at least twice the performance at half the power of Intel’s Core Ultra “AI Boost” NPU. Hailo-10 module specifications: AI accelerator – Hailo-10H System Memory – 8GB LPDDR4 on module Host interface – 4-lane PCIe Gen 3 Power consumption – Less than 3.5W (typical) for the chip Form factor – M.2 Key M 2242 / 2280 Supported AI frameworks – TensorFlow, TensorFlow Lite, Keras, PyTorch & ONNX The Hailo-10 can run Llama2-7B with up to 10 tokens per second (TPS) at under 5W […]

SolidRun launches Hailo-15 SOM with up to 20 TOPS AI vision processor

SolidRun Hailo 15H Powered Edge AI System on Module

In March last year, we saw Hailo introduce their quad-core Cortex-A53-based Hailo-15 AI Vision processor. The processor features an advanced computer vision engine and can deliver up to 20 TOPS of processing power. However, after that initial release, we didn’t find it in any commercial products with the SoC. But in a recent development, SolidRun has released a SOM that not only features the Hailo-15 SoC but also integrates up to 8GB LPDDR4 RAM and 256GB eMMC storage along with dual camera support with H.265/4 Video Encoder. This is not the first SOM that SolidRun has released. Previously, we wrote about the SolidRun RZ/G2LC SOM, and before that, SolidRun launched the LX2-Lite SOM along with the ClearFog LX2-Lite dev board. Last month, they released their first COM Express module based on the Ryzen V3000 Series APU. Specification of SolidRun’s Hailo-15 SOM: SoC – Hailo-15 with 4 x Cortex A53 @ 1.3GHz; […]

Hummingboard 8P Edge AI SBC combines NXP i.MX 8M Plus SoC with Hailo-8 AI accelerator

HummingBoard 8P Edge AI Kit

Hummingboard 8P Edge AI Pico-ITX SBC combines an NXP i.MX 8M Plus processor – itself with a 2.3 TOPS NPU – with the 26 TOPS Hailo-8 AI accelerator for edge AI applications such as smart cameras and automated optical inspection. The compact board comes with up to 8GB RAM, up to 128GB eMMC flash, two gigabit Ethernet ports including one with PoE, WiFi 5, a MIPI camera interface, HDMI and micro HDMI ports, two USB 3.0 ports, and more. Hummingboard 8P Edge AI specifications: SoC – NXP i.MX 8M Plus quad-core Cortex-A53 @ up to 1.8 GHz with Arm Cortex-M7 @ up to 800 MHz, Vivante GC7000UL 3D GPU, Vivante GC520L 2D GPU, 2.3 TOPS NPU System Memory – Up to 8GB LPDDR4 Storage – Up to 128GB eMMC flash, microSD card slot AI accelerator – M.2 Hailo-8 module delivering up to 26 TOPS Video Output – HDMI and Micro […]

Hailo-8L 13 TOPS AI accelerator targets entry-level edge devices

Hailo-8L AI accelerator

Hailo introduced the Hailo-8 AI accelerator offering up to 26 TOPS in 2020, and we’ve found it integrated into many designs since then. The company has now launched a cost-down version with the Hailo-8L AI accelerator delivering up to 13 TOPS for more cost-sensitive entry-level edge devices, or workloads that do not require the more powerful Hailo-8. Hailo says the Hailo-8L offers low-latency, high-efficiency processing, and is capable of handling pipelines with multiple real-time streams and concurrent processing of multiple models and AI tasks. The new Hailo-8L is compatible with the Hailo-8 and relies on the same Hailo-8 software suite, so they could be integrated into existing designs for cost savings. Hailo-8L key features and specifications: 13 Tera-Operations Per Second (TOPS) Real-time, low latency & high-efficiency AI inferencing on edge devices No external memory required Scalable with simultaneous processing of multi-streams & multi-models Typical power consumption – 1.5W Commercial & […]

Hailo-15 quad-core AI Vision processor delivers up to 20 TOPS for Smart Cameras

Hailo-15 AI Vision Processor

Hailo-15 is a family of AI Vision processors for smart cameras that deliver up to 20 TOPS of AI inference and are able to process deep-learning AI applications such as video analytics. The Hailo-15 appears to build upon the earlier Hailo-8 AI processor with up to 26 TOPS and more limited computer vision capability. The new AI vision processor integrates a quad-core Cortex-A53 CPU sub-system, can handle 4K video streams, and features “advanced computer vision engines”. So the main differences are that the Hailo-15 is a complete SoC / standalone processor and is specifically designed for AI cameras. Hailo-15 highlights: CPU – Quad-core Arm Cortex-A53 processor up to 1.3 GHz or 1.1 GHz (Hailo-15L) DSP – Vector DSP, 256 MACs @ 700 MHz supports up to 350 GOPs AI accelerator / NN core sub-system with dataflow architecture Hailo-15H – Up to 20 TOPS Hailo-15M – Up to 11 TOPS Hailo-15L […]

miriac AIP-LX2160A 16-core embedded platform delivers up to 130 TOPS with 5 Hailo-8 modules

miriac AIP-LX2160A embedded SBC

MicroSys Electronics miriac AIP-LX2160A embedded platform combines a 16-core Cortex-A72 NXP LX2160A networking processor with up to five Hailo-8 AI accelerator modules delivering up to 130 TOPS of AI inference performance. The board supports up to 128 GB RAM, up to 4x SATA hard drives, up to 100GbE connectivity, and appears to be especially suited to applications with multiple IP video streams requiring real-time video analytics. miriac AIP-LX2160A specifications: SoC – NXP Layerscape LX2160A with 16 Arm Cortex-A72 cores @ up to 2.2 GHz AI accelerators – 2x Hailo-8 M.2 AI Acceleration Modules, upgradeable to up to 5 Modules via NGFF M.2 Key M card System Memory – Up to 128 GB DDR4 RAM & optional ECC, up to 3200MT/sec, up to 4 ranks (combined design: 2x discrete & 2x SODIMM) Storage 4x SATA III ports Up to 256 GB eMMC 5.1 flash, additional eMMC device on carrier board Up […]

Vecow ABP-3000 AI Edge gateway combines Hailo-8 AI accelerator with Intel Whiskey Lake processor

Vecow ABP-3000-AI Hailo-8 accelerator

We first discovered Hailo-8 AI accelerator with claims of up to 26 TOPS performance and 3TOPS/W efficiency in October 2020. Since then, we’ve seen several integrate an Hailo-8 M.2 module into their design including EdgeTuring Edge AI camera and Vecow VAC-1000 gateway with a 24-core Foxconn processor. Vecow has now integrated the Hailo-8 AI accelerator into another gateway, but instead of relying on an Arm processor, the Vecow ABP-3000 AI computing system features an 8th generation Intel Core Whiskey Lake processor. Vecow ABP-3000 specifications: SoC – Intel Core i7-8665UE or i3-8145UE quad-core Whiskey Lake processor with Intel UHD Graphics 620; 15W TDP System Memory – 2x DDR4 2400MHz SO-DIMM, up to 64GB Storage – 1x M.2 Key B Socket (PCIe x2/SATA) AI Accelerator – Hailo-8 AI Processor, up to 26 TOPS with TensorFlow, ONNX frameworks support System IO chip – IT8786E Video Output – 2x DisplayPort up to 4096 x […]

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