BrainChip has recently opened preorders for their Akida Edge AI Box, built in partnership with VVDN Technologies. This box features an NXP i.MX 8M Plus SoC and two Akida AKD1000 neuromorphic processors for low-latency, high-throughput AI processing at the edge. The system features USB 3.0 and micro-USB ports, HDMI, 4GB LPDDR4 memory, 32GB eMMC with up to 1TB micro-SDXC expansion, dual-band Wi-Fi, and two gigabit Ethernet ports for external camera connections, all within a compact, passively-cooled chassis, powered by 12V DC. BrainChip Akida Edge AI Box Specifications: Host CPU – NXP i.MX 8M Plus Quad SOC with 64-bit Arm Cortex-A53 processor running at up to 1.8GHz AI/ML Accelerator – Dual Brainchip AKD1000 (Akida Chip) over PCIe for efficient AI processing Memory – 4GB LPDDR4 Storage 32GB eMMC flash MicroSD card slot for additional storage options Display Output – HDMI output supporting up to 3840 x 2160p30 resolutions with a pixel clock […]
$499 BrainChip AKD1000 PCIe board enables AI inference and training at the edge
BrainChip has announced the availability of the Akida AKD1000 (mini) PCIe boards based on the company’s neuromorphic processor of the same name and relying on spiking neural networks (SNN) which to deliver real-time inference in a way that is much more efficient than “traditional” AI chips based on CNN (convolutional neural network) technology. The mini PCIe card was previously found in development kits based on Raspberry Pi or an Intel (x86) mini PC to let partners, large enterprises, and OEMs evaluate the Akida AKD1000 chip. The news is today is simply that the card can easily be purchased in single units or quantities for integration into third-party products. BrainChip AKD1000 PCIe card specifications: AI accelerator – Akida AKD1000 with Arm Cortex-M4 real-time core @ 300MHz System Memory – 256Mbit x 16 bytes LPDDR4 SDRAM @ 2400MT/s Storage – Quad SPI 128Mb NOR flash @ 12.5MHz Host interface – 5GT/s PCI […]
BrainChip AKD1000 SNN AI SoC gets Raspberry Pi and x86 development kits
BrainChip has introduced two development kits for its Akida AKD1000 neuromorphic processor based on Raspberry Pi and an Intel (x86) mini PC in order to enable partners, large enterprises, and OEMs to begin testing and validation of the Akida chip. BrainChip Akida neural relies on spiking neural networks (SNN) which enable high-performance, real-time inference at ultra-low power, notably much lower power than traditional AI chips relying on CNN (convolutional neural network) technology. Akida Development Kit based on Raspberry Pi CM4 Specifications: SoM – Raspberry Pi CM4 or CM4 Lite with SoC: Broadcom BCM2711C0 quad-core ARM Cortex-A72 (ARMv8-A) 64-bit @ 1.5GHz plus Broadcom VideoCore VI GPU RAM – 1GB, 2GB, 4GB, or 8GB LPDDR4 SDRAM Storage – MicroSD card for CM4 Lite, or 2GB to 32GB eMMC for CM4 Networking – Optional 2.4 GHz and 5 GHz 802.11b/g/n/ac Wi-Fi, Bluetooth 5.0 LE, Gigabit Ethernet PHY Carrier board – Official Raspberry Pi […]