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2 MIN READ

Deeplite in the Gartner Report on Tech Innovators in Edge AI

Montreal, November 24, 2020 - In a new report on emerging technologies, the technology research and advisory company Gartner named Deeplite as one of twelve “Edge AI Tech Innovators for 2020.”

The report aims to identify “emerging providers of Edge AI value” with “AI-based or AI-enabling technologies with proven capabilities for optimization and transformation.” Gartner states that Deeplite’s innovative solution was chosen because of the “robust deep neural networks (DNNs) running on highly resource constrained edge devices with high performance and accuracy”. According to the report, Deeplite “enables much greater AI workloads at the edge. This significantly increases the value that AI delivers to the edge, expands the number potential business solutions, and elevates the overall business value and market potential for edge AI.”

 

“Honored to be included in the Gartner Tech Innovators in Edge AI” said Nick Romano, Co-founder and CEO, Deeplite. “Deeplite enables AI for everyday life. Our platform automatically makes other AI models smaller, faster, and more energy efficient, while preserving accuracy, creating highly compact, high-performance deep neural networks that can run at the edge in vehicles, cameras, sensors, drones, phones and many other devices you use every day.”

 

Follow the link to view the full report “Emerging Technologies: Tech Innovators in Edge AI” directly from Gartner.

 

Gartner Edge AI Tech Innovators for 2020

 

About Deeplite

Deploying AI at the edge shouldn’t be hard. Founded in 2018 and based in Montreal, Deeplite is a purpose-built software platform designed to enable AI everywhere. We help AI development teams to focus on building accurate AI models and use Deeplite to create highly compact, high-performance models for production deployment. We address the problem of ever-larger AI models required to be deployed into increasingly constrained devices. Our automated model optimization process can transform inefficient but accurate AI models into models optimized for size, speed, and power consumption for deployment on any hardware platform on any edge IoT device.

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