BrainChip Introduces AKD1500 Neuromorphic Edge AI Co-Processor
BrainChip Holdings Ltd has unveiled its AKD1500 Edge AI co-processor at Embedded World North America, announced in a press release. The neuromorphic chip delivers 800 giga operations per second (GOPS) while consuming less than 300 milliwatts of power, targeting battery-powered and thermally constrained devices such as wearables and smart sensors.
The AKD1500 integrates with x86, ARM, and RISC-V host platforms using PCIe or Serial interfaces, enabling quick deployment across multiple industries. It is designed for use in defense, industrial, and healthcare applications, with early integrations in AI-enabled sensing products from Parsons, Bascom Hunter, and Onsor Technologies.
Built on GlobalFoundries’ 22FDX process technology, the co-processor leverages BrainChip’s Akida neuromorphic architecture, which supports on-chip learning and event-based processing. The AKD1500 is compatible with BrainChip’s MetaTF software tools, allowing engineers to convert and deploy models from TensorFlow and Keras efficiently.
Samples of the AKD1500 are available now, with volume production scheduled for the third quarter of 2026.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like Silicon Brief or Daily AI Brief.
Also, consider following us on social media:
More from Data Centers
Oct 16 EverWind Plans 420 Megawatt AI Data Centre in Nova Scotia Oct 16 Gartner Says $3.5 Trillion in AI Infrastructure Spending Faces Impairment Risk by 2030 Oct 16 KBRA Rated Anthropic BB+ Before $35 Billion Chip Financing Oct 16 China Proposes Export Controls for Advanced AI Models and Chips Oct 16 Hitachi Energy and Ansaldo Energia Partner on Data Center Power SystemsSilicon Brief
Weekly coverage of AI hardware developments including chips, GPUs, cloud platforms, and data center technology.
Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
Read moreYou may also like
Ezurio Introduces BL54LM20 Modules With Edge AI
QBit Unveils Robotics and Drone Chip Roadmap
Xsight Labs Introduces 25 Watt E1L DPU for Edge Systems
BIOSTAR Shows Edge AI Systems at Tech Week Singapore 2026
Ricursive Intelligence Details AI System for Chip Design
Daily AI Brief: the AI news that matters, in your inbox.