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
- NPU IP Core for Mobile
- NPU IP Core for Edge
- Specialized Video Processing NPU IP
- HYPERBUS™ Memory Controller
- AV1 Video Encoder IP
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
- Jim Keller: ‘Whatever Nvidia Does, We’ll Do The Opposite’
- FlexGen Streamlines NoC Design as AI Demands Grow
- IntoPIX Presents Its New Titanium Software Suite: Empowering AV-Over-IP Workflows With Speed, Quality & Interoperability
- Global Semiconductor Sales Increase 2.5% Month-to-Month in April
- Speedata Raises $44M to Launch First-Ever Chip Designed Specifically for Accelerating Big Data Analytics - Compute's Second Largest Workload