NeuroBlade raise fund to suppory new AI chip development

1 min read

Israeli startup NeuroBlade has completed a $23-million funding round A, led by Marius Nacht, Co-founder of Check Point Software Technologies, and new investor Intel Capital along with existing investors StageOne Ventures and Grove Ventures.

In addition to the $4.5m raised previously, this funding will be used by NeuroBlade to scale its workforce and ramp up its marketing efforts in order to bring the first generation of its AI chip to the market.

Founded in 2017 by Elad Sity, CEO and Eliad Hillel, CTO and VP Product Strategy, NeuroBlade raised its initial capital while in stealth mode from StageOne Ventures and Grove Ventures, headed by Dov Moran, the inventor of the USB flash drive and Co-founder of M-Systems.

The AI processor market segment is currently led by Nvidia and Intel but is becoming more crowded as more startups develop processors for different market segments, as well as large corporations that are developing processors for their own needs. AI chips are used in a wide range of applications, including image and speech recognition, video analysis and autonomous driving, among others.

The deployment and use of AI is still limited by factors such as size, price, throughput or performance of these chips. The NeuroBlade chip is designed with different technology and architecture and, according to NeuroBlade, the chip is meant to run several neural networks and multiple complex algorithms at the same time. Its main advantage, according to the company, is that it is able to also solve tomorrow’s problems, not just the relatively “simple” problems computers grapple with today.

Elad Sity, CEO and Co-founder of NeuroBlade, said: “'We started out slightly over two years ago with an ambitious idea how to solve AI’s computational challenges. Our core team has grown stronger over the past two years, creating a solid foundation for the upcoming growth.”

Tal Slobodkin, Partner at StageOne VC, commented: “The chip developed by NeuroBlade will allow running AI algorithms on par with the performance of market-leading chips but at a smaller size or with significantly better performance at similar throughput and size. NeuroBlade’s technology targets servers and is also relevant to end devices, such as security cameras, laptops, cars, multimedia and more.”