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.
$99,992.00
Aug 28, 2019
Other
Development of two new editions and one new national standard for mining equipment
CSA2020-001
The purpose is to develop three (3) evidence informed National Standards on mining equipment power trains used in underground mines.
$495,000.00
Mar 26, 2024
Academia
Quantum Error Prevention and Correction using Transformer Model
1016507
The Project employs modern machine learning to accelerate the development of industry-ready quantum computing technologies. To this end, the Project addresses the key bottleneck in quantum computing technologies, quantum errors, by pioneering advancements in quantum error prevention and correction through machine learning methods. Machine learning methods, and in particular transformers, possess the potential to learn and model the patterns and dynamics of quantum errors in individual quantum processor hardware in unprecedented detail and with unprecedented adaptability to individual quantum processors. This opens the prospect of machine-learned quantum error handling strategies that are significantly more complex, and efficient, than the more rigid manually developed methods currently in use.
$30,000.00
Dec 2, 2024
For-profit organization
AI in Satellite Communications
1024483
Commissioning of a Machine Learning Operations Pipeline: Infrastructure and processes to manage data, models, and software are critical to deploying trustworthy and robust artificial intelligence solutions. This project will advance Mission Control’s core Machine Learning Operations (MLOps) Pipeline, including data management, model staging, and cloud and embedded hardware to better serve AI-based solutions to customers in the space industry.
$250,000.00
Oct 15, 2018
For-profit organization
Optimization of supply and demand
914156
Our project aims to optimize supply and demand in our marketplace application relying on data driven decisions.
Machine Learning techniques will be employed to solve specific issues related to pricing, product recommendations and supply management.
We will be creating end-to-end solutions by collecting data, processing it, feeding it into a machine learning algorithm and use the results to power application features.
$262,000.00
Apr 1, 2019
Not-for-profit organization or charity
Innovation York AI Industry Partnership Fund 2019/20
924246
Support up to 12 Canadian SMEs through AI/Machine Learning based collaborative research projects with funding of up to $12K per project. The specific outcome for the SME is expected to be a combination of the following: • Proof of Concept or working prototype • Recommended Machine Learning models and algorithms • Assessment of company’s existing dataset and recommended data strategy
$130,000.00
Apr 2, 2018
Not-for-profit organization or charity
Innovation York AI Industry Partnership Fund
903767
Support up to 8 Canadian SMEs through AI/Machine Learning based collaborative research projects with funding of up to $10K per project. The specific outcome for the SME is expected to be a combination of the following:
• Proof of Concept or working prototype
• Recommended Machine Learning models and algorithms
• Assessment of company’s existing dataset and recommended data strategy
$74,999.00
Mar 1, 2017
Rapid Non-Small Cell Lung Cancer Detection and Phenotypic Subtyping Using Machine Learned Metabolomic Signatures of Blood Specimens from the Manitoba Lung Cancer Tumour Bank
$750,000.00
Dec 1, 2021
For-profit organization
Machine Learning-enabled design tools for the Architecture, Engineering and Construction industry.
985258
RWDI will develop and commercialize a system using machine-learning to provide rapid guidance to architects and engineers in the early phases of building design.
$178,000.00
Aug 14, 2023
For-profit organization
Improvements to Powerlane Scalability
1009008
Increase PowerLane’s* available market across all OEM’s and better utilize Media Management and Machine Learning to drive more value (ROI) into the product.
$30,000.00
Apr 1, 2021
For-profit organization
Assignment Agreement AC 964234- Feasibility for a downtime management system
972091
Create predictive and decision support tools based on statistical, algorithmic and machine learning techniques from raw data now centralized, unaltered and accessible in real time.