Grants and Contributions
About this information
In June 2016, as part of the Open Government Action Plan, the Treasury Board of Canada Secretariat (TBS) committed to increasing the transparency and usefulness of grants and contribution data and subsequently launched the Guidelines on the Reporting of Grants and Contributions Awards, effective April 1, 2018.
The rules and principles governing government grants and contributions are outlined in the Treasury Board Policy on Transfer Payments. Transfer payments are transfers of money, goods, services or assets made from an appropriation to individuals, organizations or other levels of government, without the federal government directly receiving goods or services in return, but which may require the recipient to provide a report or other information subsequent to receiving payment. These expenditures are reported in the Public Accounts of Canada. The major types of transfer payments are grants, contributions and \'other transfer payments\'.
Included in this category, but not to be reported under proactive disclosure of awards, are (1) transfers to other levels of government such as Equalization payments as well as Canada Health and Social Transfer payments. (2) Grants and contributions reallocated or otherwise redistributed by the recipient to third parties; and (3) information that would normally be withheld under the Access to Information Act and the Privacy Act.
$30,000.00
Jul 12, 2021
For-profit organization
Youth Project: Support product development for machine learning and artificial intelligence
974244
This project will contribute to analysis of machine learning and artificial intelligence technology associated with the TheoryMesh product portfolio.
$250,000.00
Jul 1, 2021
For-profit organization
Risk Prediction for Safety Management
974619
The project will build a machine learning (ML) model to aid in the identification of health and safety risk.
$33,625.00
Apr 1, 2019
For-profit organization
Cigarette Smoke Analysis and Testing
925625
Aretas is undertaking the creation of a low cost cigarette smoke detection and monitoring system using machine learning with cigarette smoke training data generated by an artificial smoking apparatus, Aretas sensors and Aretas IoT Cloud platform.
$235,000.00
May 1, 2019
For-profit organization
Intelligent Network Insights Platform
927644
Research and develop an intelligent “insights platform” which uses Machine Learning or other in-house algorithms to automate the derivation of important network insights.
$49,819.00
Aug 1, 2018
For-profit organization
Social Media Object Detection Prototype
911704
The objective of this project is to create a prototype that uses machine learning and AI to analyze social media posts across restaurant social media accounts and platforms for our targeted user base of business travellers.
$340,000.00
Nov 26, 2018
For-profit organization
SaaS (Software as a Service) Platform Automation, Phase 1
916878
Key results are to automate customer acquisition, customer success, reduce support costs, improve retention and improve customer results by leveraging AI (artificial intelligence) and machine learning.
$155,000.00
Sep 11, 2018
For-profit organization
Rattlehub 2.0
917132
Rattlehub Digital is adapting its personal data enrichment platform, called permyssion, for North America and other international locations by incorporating data engineering and content recognition, as well as AI, machine learning, and natural language processing capabilities.
$125,000.00
May 19, 2020
For-profit organization
Automation of Environmental and Operational Inspections for Oil & Gas Producers
949269
The goal of the proposed project is to develop machine learning methods for analyzing images and sensor data at oil well sites in order to alert an operator to anomalous situations, including leaks or potential malfunctions.
$1,496,021.00
Oct 23, 2019
Academia
AutoDefence: Towards Trustworthy Technologies for Autonomous Human-Machine Systems
The AutoDefence Micro-net research objective is to develop trustworthy technologies for autonomous human-machine systems applied in dynamic and contested defence environments.
To address the above practical challenges, the AutoDefence Micro-net will focus on the following three major research themes:
1) Cognitive Platform for Trusted Support: Novel methodologies to design trustworthy decision-support systems will be developed.
2) Cognitive Cycle of Machine Learning: Focus on cognitive load determination for semiautonomous systems in contested environments, autonomous learning systems for defence robots, unmanned systems, reliable target recognition, autonomous decision-support, and real-time battle-field awareness and cognition.
3) Distributed/Networked Autonomous Systems: Development of innovative machine learning and signal processing solutions for attack/intrusion modeling, detection, and isolation focusing on autonomy, distributed cooperation, and event-based nature of multi-agent systems.
$323,400.00
Mar 20, 2024
Academia
Hybrid quantum-classical computing for quantum chemistry and machine learning
1016014
The workhorse density-functional theory (DFT) computational methods are time-consuming and of limited accuracy for strongly correlated systems like the metal-oxides commonly used for catalysis. (Classical) Machine learning (ML) is showing great promise in reducing the number of expensive DFT calculations in the design process. Quantum computing (focusing on hybrid approaches using Noisy Intermediate Scale Quantum (NISQ) computers for parts of the problem) is showing great promise to contribute to opening both bottlenecks by facilitating the use of more accurate quantum chemical methods and accelerating machine-learning approaches beyond the possibilities of classical ML. The proposed research will be directed along two complementary streams: i) quantum computing for quantum chemistry and ii) quantum machine learning.