Algolux Announces Its Selection to Plug and Play’s Mobility Program From Over 1000 Applicants
Chosen for Unique Approach to Improving Camera-based ADAS and Autonomous Driving Systems
Montreal, Canada, March 22, 2017 – Algolux, Inc., a provider of machine learning optimization platforms for imaging and computer vision systems, today announced it was selected from over 1000 startup applicants by Plug and Play to participate in a 12-week accelerator program for new Mobility solutions.
According to Tractica, the market for computer vision hardware and software is expected to grow to $48.6 billion by 2022 from $6.6 billion in 2015, a CAGR of 33 percent, with the largest growth coming from automotive. As more sophisticated cameras and Computer Vision (CV) algorithms are being integrated into vehicles for Advanced Driver Assistance Systems (ADAS) and Autonomous Driving, the requirement to improve image quality and CV accuracy continues to increase. Compelled by the need to reduce accidents and improve driving efficiency, automotive providers have begun investing heavily to achieve these requirements. But, the current process for tuning these systems is manually intensive and costly, time-consuming, and requires deep expertise.
Algolux takes a novel optimization-based approach by applying machine learning solvers to automate the tuning process against Key Performance Indicators (KPIs), reducing the time needed to achieve the required image quality or CV accuracy from weeks or months down to hours or days. This, in turn, can lead to savings of hundreds of thousands of dollars per system.
“Mobility and the path to autonomous vehicles requires a new approach to ensure the vision systems in these vehicles ‘see’ better for improved safety. We are excited to have Montreal-based Algolux join our Mobility accelerator program here in Sunnyvale as their unique machine learning optimization approach addresses this challenge head on for automotive suppliers and impact a large and quickly growing market”, said Plug and Play’s Mobility Director, Sobhan Khani.
“The embedded camera and vision system market is experiencing explosive growth, and this is led by the automotive industry as the sector most in need of automating their tuning processes against qualitative and increasingly quantitative metrics. By working with Plug and Play’s Mobility accelerator and corporate partners, we look forward to accelerating the adoption of Algolux’s technology within the automotive supplier ecosystem and reducing the complexity of bringing these vision systems to market,” said Algolux CEO Allan Benchetrit.
Algolux provides groundbreaking machine learning technologies that enable the smart optimization of computer vision systems, transforming the development and accuracy of machines that can “see”. Computer vision is at the heart of autonomous cars, ADAS, AR/VR, robotics, drones, IoT, medical equipment, and mobile devices… leading the next wave of market growth and social impact. Developed by an industry-recognized team of machine learning, computer vision, and image processing researchers, our patented CRISP technology addresses the cost, schedule, and expertise challenges that product development teams face in optimizing their imaging and vision systems.
Visit us at https://algolux.com.
About Plug and Play Mobility Accelerator
Plug and Play Mobility provides an ecosystem where startups connect to forward-thinking corporations and VCs. Twice a year, three month programs for 20 early-to-late stage mobility-related startups will be hosted in Silicon Valley – the capital of innovation. Startups will work with engineers of leading automotive manufacturers and suppliers on prototypes and pilots. Alongside this, startups get access to Plug and Play’s international network of investors, corporations, mentors, and advisors. Plug and Play Mobility accepts startups creating solutions in the following technologies: connected car, shared economy, telematics, electrification, security, biometrics, and predictive analytics. Learn more here: https://plugandplaytechcenter.com/mobility/
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