Artificial intelligence (AI) processor chipmaker Deep Vision has announced that it raised $35 million in a Series B financing round. Deep Vision, Inc. has developed a comprehensive software development suite for edge computing applications.
By combining the new funding with existing revenue streams, it will help the company expand the capabilities of its AI processor and software tools, as well as support its growing customer base.
The funding was led by Tiger Global, which was joined by Series A investors Exfinity Venture Partners, SiliconMotion, and Western Digital. The last three are also rejoining in the latest round of financing.
Deep Vision’s patented AI processor is called ARA-1, and it delivers high performance, power, and price for camera-based applications like smart retail, driver-monitoring systems, smart city, drones, and factory automation.
The company’s processor is best known for its ability to perform real-time video analytics, but it also provides natural language processing (NLP) capabilities for voice-controlled applications. Along with its processing technology, the company also offers a comprehensive and flexible set of development tools, which enable customers to easily convert their neural network models into highly optimized computation graphs that can be deployed on the ARA-1 chip.
Ravi Annavajjhala is Deep Vision’s Chief Executive Officer.
“This investment is a resounding affirmation of Deep Vision's tactical accomplishments and strategic direction, which are rapidly driving our company into a wide variety of applications in our key target markets,” said Ravi Annavajjhala. “We will now be able to significantly fortify our efforts to continue designing and building the world's most power- and price-efficient AI inference platform as well as flawless software development tools.”
Scott Shleifer is a partner at Tiger Global.
“We are excited to partner with Deep Vision. We believe that the company is positioned for a long runway ahead, with a unique AI processor that combines innovative software and silicon architecture for edge computing,” said Scott Shleifer, partner at Tiger Global.
Linley Gwennap is principal analyst of the Linley Group.
“To improve latency and reliability for voice and other cloud services, edge products such as drones, security cameras, robots, and smart retail applications are implementing complex and robust neural networks. We expect 1.9 billion edge devices to ship with deep learning accelerators in 2025,” said Gwennap. “Within these edge AI applications, we see an increasing demand for more performance, greater accuracy, and higher resolution. This fast-growing market provides a large opportunity for Deep Vision's AI accelerator, which offers impressive performance and low power.”