Analog AI chip startup wants to achieve 1 POPS per Watt: 1000 TOPS/W is ‘within reach’ says firm co-founder as he looks to analog-first Gigabit-sized SLMs

• Blumind debuts ultra-efficient analog AI chip, achieving 10 nJ/inference
• Targeting wearables, healthcare, automotive, and always-on AI
• Scaling for larger models, aiming for 1000 TOPS/W performance

Blumind, an analog AI chip startup, has showcased a chip designed for low-power applications achieving an impressive 10 nJ per inference, setting the stage for the company’s ambition to scale analog computing to new heights.

The company showed off its test silicon for ultra-efficient keyword spotting chip at Electronica 2024, where co-founder Niraj Mathur told EE Times, “What’s been particularly gratifying is that over the last year, there’s been more pull than us pushing.”