Blumind Harnesses Analog for Ultra Low Power Intelligence
By Sally Ward-Foxton, EETimes (February 15, 2024)
Canadian startup Blumind recently developed an analog computing architecture for ultra-low power AI acceleration of sensor data, Blumind CEO Roger Levinson told EE Times. The company hopes to enable widespread intelligence in Internet of Things (IoT) devices.
“The challenge is, we need to have intelligence in the sensor, but we do have a serious power and cost problem,” Levinson said. “And how do we maintain enough flexibility to make this useful?”
Advanced process nodes aren’t cost effective for tiny chips used in tens of hundreds of millions of units in the IoT. Combine this with the fragmentation of the IoT market, the need for application-specific silicon, and the requirement for zero additional power consumption and it’s easy to see why the IoT has been slow to adopt AI, Levinson said.
To read the full article, click here
Related Semiconductor IP
- NFC wireless interface supporting ISO14443 A and B with EEPROM on SMIC 180nm
- DDR5 MRDIMM PHY and Controller
- RVA23, Multi-cluster, Hypervisor and Android
- HBM4E PHY and controller
- LZ4/Snappy Data Compressor
Related News
- Blumind reimagines AI processing with breakthrough analog chip
- Blumind Secures Series A Funding to Accelerate Analog AI Revolution
- POLYN Technology White Paper Looks at Analog Computing for AI
- Ceremorphic Exits Stealth Mode; Unveils Technology Plans to Deliver a New Architecture Specifically Designed for Reliable Performance Computing
Latest News
- CAST Releases First Dual LZ4 and Snappy Lossless Data Compression IP Core
- Arteris Wins “AI Engineering Innovation Award” at the 2025 AI Breakthrough Awards
- SEMI Forecasts 69% Growth in Advanced Chipmaking Capacity Through 2028 Due to AI
- eMemory’s NeoFuse OTP Qualifies on TSMC’s N3P Process, Enabling Secure Memory for Advanced AI and HPC Chips
- AIREV and Tenstorrent Unite to Launch Advanced Agentic AI Stack