Capital increase for aiCTX


Baidu Ventures, a global investment firm with $500m under management, has invested USD 1.5M in a pre-A round of the Zurich based startup aiCTX. The funds will be used to accelerate the development of commercial applications of neuromorphic chips.


Established in 2017 in Zurich, aiCTX is developing “full-stack” custom neuromorphic processors for a variety of artificial intelligence (AI) edge-computing applications that require ultra-low-power and ultra-low-latency features including autonomous robots, always-on co-processors for mobile and embedded devices, wearable health-care systems, security, IoT applications, and computing at the network edge.

The technology is based on over 20 years of research in neuromorphic computing hardware developed at the Institute of Neuroinformatics of the University of Zurich and ETH Zurich.

aiCTX has recently received a capital increase of USD 1.5 million from Baidu Ventures, a global, AI-focused investment fund established in 2017 by the Chinese internet search giant. Currently, the firm manages USD 500M across three funds. With a deep belief in AI, BV supports entrepreneurs and companies who are using AI to transform the way we live.

“We are very pleased to have BV with us on the next step of our journey,” said Ning Qiao, CEO of aiCTX. “BV recognized our years of expertise in combining mixed signal neuromorphic designs with ultra-low power and ultra-low latency asynchronous digital circuits in advanced VLSI processes.”

Wei Liu, CEO of BV, commented:  “What distinguishes aiCTX from other neuromorphic startups and the large corporations active in the field, is your unique technology and your product-driven focus. You are developing complete commercial solutions, not simply designing computing fabrics.”The funds will enable the aiCTX to accelerate the development of dedicated neuromorphic chips for specific applications.

EU Horizon2020 fundsThe investment comes after aiCTX received a four-year FET-Proactive H2020 grant from the EU. The startup will explore brain-silicon neural closed loop systems as a step towards designing compact, unobtrusive, brain-machine interfaces.(Press release/RAN)