A few weeks ago, we noted that the Brainchip AKD1500 M.2 module could work with the Raspberry Pi 5 using a compatible M.2 HAT+ expansion card to evaluate

A few weeks ago, we noted that the Brainchip AKD1500 M.2 module could work with the Raspberry Pi 5 using a compatible M.2 HAT+ expansion card to evaluate the solution or develop applications using the company’s low-power, low-latency neuromorphic AI technology. To make things even easier, they’ve now introduced the AKD1500 Raspberry Pi 5 Dev Kit that packs a Raspberry Pi 5 8GB, an official M.2 HAT+, and an Akida AKD1500 M.2 B+M-Key card into a metal case. Most ports from the Raspberry Pi 5 are exposed, namely the Gigabit Ethernet port, the four USB connectors, the two HDMI video outputs, and the USB-C port for power. The Raspberry Pi 5 power button and an LED on the M.2 HAT+ are also visible through openings in the metal case. The kit requires a camera for operation, but instead of relying on a MIPI CSI-based Raspberry Pi Camera module, users are [...] The post Brainchip AKD1500 Raspberry Pi 5 Dev Kit enables users to quickly experiment with event-based neuromorphic AI appeared first on CNX Software - Embedded Systems News.

Next-generation edge AI dev kit pairing Raspberry Pi 5 with BrainChip's AKD1500 neuromorphic co-processor for ultra-low-power inference and on-device learning at the edge.

A Neuralink surgical robot is threading brain chips into humans in 2026 clinical trials, restoring neural connections lost to paralysis and ALS. Hope is here.

Correr modelos de lenguaje en audífonos o sensores remotos sin secarles la pila parecía un chiste técnico hasta hace unas horas. Sequora Core IP promete romper esa barrera llevando la IA generativa en dispositivos Edge directamente al silicio comercial, sin depender de servidores lejanos ni de conexiones permanentes a la nube. La firma australiana BrainChip oficializó la disponibilidad de esta arquitectura propietaria para fabricantes de semiconductores, enfocada en procesar agentes inteligentes locales y voz bidireccional consumiendo apenas unos milivatios. El problema habitual de meter modelos grandes en aparatos pequeños no es solo el cómputo, sino también el ancho de banda de la memoria.