Greenhouse Canada

Applications open to accelerate AI adoption in Alberta’s agricultural sector

November 8, 2020  By Greenhouse Canada

The Alberta Machine Intelligence Institute (Amii) is now accepting applications for participation in the Agriculture Spring 2021 cohort of the previously announced REMI (Reducing Emissions through Machine Intelligence) Program.

The program, made possible through a $5 million investment from the Government of Alberta’s TIER Program, will enable companies to leverage novel applications of artificial intelligence (AI) for projects that will have a measurable impact on emissions reduction in Alberta.

“Leaders in the agriculture sector are embracing technology and making strides towards greater efficiency and more sustainable practices. The opportunities to apply artificial intelligence technologies in the field are vast, from crop science to animal genetics, and we look forward to working with forward-thinking teams as they accelerate their AI adoption strategies,” says Cam Linke, Amii CEO REMI.


Anticipated impacts include a reduction of 2 Mt CO2 equivalents in GHG Emissions by 2030, $110M in new economic activity  by 2025, 10 – 15 AI projects within companies focused on emissions reduction by 2022, and 600+ Albertans trained in both business and technical aspects of AI for GHG emissions by 2022.

Applications close on January 31, 2021. For more information and to download the Program Guide, visit

The program is designed to progress companies, from startups to small and medium businesses to multinational corporations, along the AI adoption spectrum, focusing on GHG reduction projects.  Amii aims to accept all companies, at any stage of AI adoption, looking to participate in the REMI program. Based on a company’s current level of AI adoption, team composition, and near-term GHG reduction goals, they will be placed in an appropriate program stream.

Stream 1: Exploring & Initiating 
  • Companies participating in Stream 1 will take part in Phase 1 and, upon completion, meet with the Program Manager to evaluate the opportunity to progress to Phase 2 and Phase 3.
  • Stream 1 includes program activities focused on ‘upskilling’ team members to be AI champions within their organization. Participants will be provided with tools and resources to share their AI knowledge and facilitate AI-focused discussions across the company.

Stream 2: Implementing & Operationalizing 

  • Companies participating in Stream 2 are pre-approved to participate in Phase 1, 2 and 3.
  • Stream 2 includes program activities focused on accelerating the rate of AI adoption, building on the existing AI resources found within the company. As such, Phase 1 activities will include more hands-on guidance from Amii scientists and educators with a focus on executing Phase 2 and Phase 3 projects.

Agriculture Spring 2021 programming begins on March 15, 2021 and includes three phases:

  1. Foundations: Participants gain foundational AI knowledge and create a roadmap for potential AI projects focused on GHG reduction. This programming phase includes hands-on training opportunities and facilitated sessions with a multi-disciplinary team of project managers, scientists, educators and domain experts.
  2. Commitments: Companies define, specify and scope a machine learning (ML) project; and mitigate the risk of introducing AI and ML projects into various operations, processes and business lines.
  3. GHG Reduction: Teams advance a selected ML emission reduction project to a proof-of-concept model, and upon graduation, can broadly apply new skills and knowledge in AI and ML to further increase business effectiveness in areas outside of emission reduction.

Key Program Dates

  • November 4, 2020: Applications for Agricultural Program Spring 2021 open
    • Rolling intake commences
  • January 31, 2021: Applications close
  • March 15, 2021: Program Phase 1 begins
  • April 26, 2021: Program Phase 2 begins
  • July 12, 2021: Program Phase 3 begins
  • November 15, 2021: Program graduation

Source: Alberta Machine Intelligence Institute

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