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OmniML Raises Fund to Accelerate AI Computing on Edge Devices

Artificial Intelligence (AI) , Machine Learning (ML), Natural Language Processing (NLP), Deep Learning (DL), AI Model, AI-powered Solutions, Digital Transformation, ML Model, Natural Language Understanding (NLU), AI News, Artificial Intelligence News
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Smaller and faster machine learning model developer, OmniML enhances the use of artificial intelligence (AI) on edge devices using a $10 million seed fundraising, in the round led by GGV Capital along with other investors like Qualcomm Ventures, Foothill Ventures, and a few other venture capital firms. OmniML makes AI more accessible for all by bridging the gap between AI applications and edge hardware.

“OmniML’s leading Neural Architecture Search based platform has the potential to disrupt AI model optimization by creating new models that are efficient to begin with, rather than just compressing models. Their solution offers enterprise customers the ability to build the best AI models for target hardware resulting in significant time and cost savings, as well as improved accuracy. We are excited to invest in OmniML to help make edge AI ubiquitous,” stated Carlos Kokron, Vice President, Qualcomm Technologies Inc. and Managing Director, Qualcomm Ventures Americas.

Smaller, scalable machine learning (ML) models on edge devices can now conduct AI inference at levels that are currently unattainable outside of data centers and cloud settings thanks to OmniML. Many important ML jobs on edge devices have already shown orders-of-magnitude improvements using OmniML’s methodology.

OmniML Co-Founder and CEO, Di Wu, Ph.D.  stated “AI is so big today that edge devices aren’t equipped to handle its computational power. That doesn’t have to be the case. Our ML model compression addresses the gap between AI applications and edge devices, increasing the devices’ potential and allowing for hardware-aware AI that is faster, more accurate, cost effective and easy to implement for anyone, on diverse hardware platforms.”

The innovation by OmniML will enhance the implementation of AI on the edge by reducing the expensive bottlenecks between AI applications and the demand they impose on hardware. ML models don’t need to be manually automated for particular devices, resulting in the speedier deployment of high-performance, hardware-aware AI that can operate everywhere.

OmniML provides AI-enabled advanced computer vision for security enhancements and situational awareness for the clients from the smart camera and autonomous driving. This technology has the potential to improve the retail consumer experience while also assisting in the detection of safety and quality control issues in precision production.

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