Processor IP brings generative AI to edge devices

What happened

BrainChip's Sequora processor IP core runs generative AI and large language models (LLMs) directly on battery-powered edge devices, such as earbuds and sensor nodes. It pairs with the company's Akida neural processor IP to handle complementary AI workloads: Akida processes streaming sensor data including vibration, audio, radar, raw RF IQ data, and biological signals, while Sequora runs generative and sequential AI tasks, from on-device LLM inference to voice-to-voice interaction and AI agents. Sequora is optimized for state-space models (SSMs), which maintain a fixed-size state to represent input history, keeping memory requirements constant regardless of sequence length, an architecture suited to generative AI workloads on resource-constrained edge devices. It uses a unified multiply-accumulate (MAC) array for both signal processing and neural-network computation, eliminating the need for a separate DSP preprocessing stage, and its instruction-set architecture (ISA) allows new algorithms to be deployed through software updates. Sequora is available now as licensable semiconductor IP, delivered as process-portable, fully synthesizable RTL; the package includes verification IP, synthesis scripts, and an SDK with a compiler, C++ runtime library, and model zoo.

Impact and signal

Affected components and suppliers

Source and time

Source: EDN · 10/21/2026 · View original source