Grants and Contributions

This project is a key component of a larger initiative to develop a virtualized ingress monitoring solution to enhance network management and scalability for cable operators. By leveraging software-defined architectures, this solution seeks to optimize performance, reduce operational complexity, and improve cost efficiency. This specific project aims to develop a high-performance proof of concept (PoC) prototype of key elements of the MVP of this solution to validate its scalability and reliability under real-world operating conditions.

Achieving fault-tolerance through brute-force error correction schemes is expected to require a superconducting quantum processor with millions of physical qubits. While recent experiments have successfully demonstrated the feasibility of error-correction in principle, the hardware overhead seems prohibitive for a commercially relevant machine. In this project, the firm will introduce an alternative pathway to achieve fault-tolerance with superconducting qubits that has the potential to significantly reduce the error-correction overhead.

The goal of the collaboration is to use an existing vacuum ultra-violet testing facility at the University of Calgary to perform testing and characterization of an ultra-violet detector planned to fly aboard a future Canadian-led space telescope. Upon completion of the detector testing, design and fabrication work done by NRC collaborators will be incorporated to provide significant upgrades to the laboratory before being used to test a new multi-object spectrometer prototype designed to operate at ultra-violet wavelengths
(UVMOS) – a world first. The test facility will be refurbished for initial low-level testing, before upgrades designed with by collaborators. The newly upgraded lab will then perform higher-level testing of the detector before accepting delivery of the full UVMOS testbench. The final laboratory will then be in a position to serve as a national testing facility for ultra-violet imaging detectors with significant application to both academia and industry.

Visual Defence is currently managing dozens of internal AI projects related to performing various research and business functions which use different machine learning frameworks, environments, data pipelines, architectures and datasets. Under this AI assist project, Visual Defence will review, plan and implement processes and technologies to streamline the management of its AI computing infrastructure and project portfolio, which will allow the company to accelerate and scale its AI capacity.

We are onboarding a new customer success specialist to expand our capacity for onboarding new clients and also focus on ways to improve the user journey

Develop an automated “A(i)ssistant Coach” that provides training analysis using both deterministic and probabilistic methods.

This project will develop an AI-powered content grader that will analyze social posts against the customer's audience profile to provide personalized improvement suggestions, enhancing the quality and engagement.

The Project will support pilot development, testing and optimization of a generative AI model that will integrate into the Manage My Pain solution.

This project involves carrying out hydrological and hydraulic studies related to the development of storm and sanitary sewer master plans and overflow management plans.

Enhancement of Official Languages Program - Promotion of Linguistic Duality