Registre des initiatives en IA
Toutes les initiatives inscrites au registre sont consultables ici, sans compte. Chaque fiche montre son avancement, ses jalons et l'historique de ses décisions. Les demandes encore en cours de triage n'y figurent pas : elles rejoignent le registre une fois examinées.
IA cognitive et générative
De l'IA qui produit du contenu nouveau, simule la créativité humaine ou soutient le travail de connaissance.
Qu'est-ce que « IA cognitive et générative » ?
Cette catégorie regroupe les systèmes d'IA qui simulent un raisonnement d'ordre supérieur, l'apprentissage ou la créativité, et qui viennent souvent en appui du travail intellectuel ou créatif. Ils peuvent produire du contenu nouveau, synthétiser des connaissances, simuler des environnements ou soutenir des tâches cognitives comme la rédaction, l'analyse ou la réflexion.
| Sous-catégorie | Description | Exemples |
|---|---|---|
| IA générative (texte, images, code) | Créer du contenu à partir d'entrées | Rédaction de rapports, génération de code, création de visuels |
| Gestion des connaissances | Structurer et faire ressortir le savoir institutionnel | Recherche sémantique, résumé de corpus de politiques |
| Simulation et jumeaux numériques | Créer des modèles virtuels de systèmes réels | Simulations d'écosystèmes marins, scénarios de formation |
- Indicateur déterminant
- Si l'IA produit du contenu nouveau, tient un raisonnement de type humain ou engendre des objets de connaissance, elle appartient ici.
- Portée
- Production d'idées, création de contenu, simulation, résumé complexe ou raisonnement.
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34 initiative(s) courante(s)
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229
DFO PB LLM ServiceProvide an approved DFO internal LLM as a service in a PBMM environment. After our team performed a year-long pilot project providing an unclassified internal GenAI models for 14 teams to develop their custom chatbots, we have collected feedback and identified gaps in the availability of GenAI at DFO. One of the biggest gaps was the need for a secure model to be used with private or classified data. Our cloud platform is certified up to PBMM, so we are working to identify, deploy and approve an internal large language model (LLM), as well as make it available to DFO users through API. IT security team is involved in helping us secure and certify the model for use at DFO.
Pilote Dirigeant principal du numérique IA cognitive et générative
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215
Projet pilote d’utilisation de M365 Copilot, pour le programme de Protection du poisson et de son habitat (PPPH / FFHPP)Utilisation de Microsoft 365 Copilot dans le cadre de la modernisation du PPPH Réflexions sur les possibilités d’optimiser les processus du programme en s’appuyant sur l’utilisation de M365 Copilot.
Pilote Dirigeant principal du numérique IA cognitive et générative
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185
IA RadiaExplorer les capacités de l'IA Radia du centre d'innovation en IA ISDE/CRC et la façon dont il peut être exploité dans le travail de notre direction.
Pilote Secteur des programmes IA cognitive et générative
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183
Généralités – Gestion administrativeDraft and Refine Documents: Staff make use of Copilot to generate or refine briefing notes to make these clear and concise. Enhance Collaboration and Workflow Efficiency: By offering suggestions for document formatting, language style, and clarifying content, Copilot helps maintain consistency and accuracy across communications and facilitates more effective interdepartmental collaboration. Meeting notes: After a meeting is recorded, Copilot can transcribe audio to produce a relatively accurate record of the discussion, using natural language processing to identify key points, decisions, and follow-up tasks, and organizing these into relatively concise summaries and action item lists. Conduct Research and Summarize Information: It can quickly extract key points from extensive reports, legislation, or guidelines—helping to synthesize complex information into actionable insights. Support Data Analysis and Reporting: Employees use Copilot to structure performance metrics, track progress against key indicators, and generate reports that inform decision-making. **These functionalities save time, improve comprehensiveness, and can help ensure that critical details are captured.**
Pilote Secteur des programmes IA cognitive et générative
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181
Pacific Aquacutlure Regulations (PAR) Gap AnalysisCopilot is being leveraged to develop engagement tools for a regulatory consultation that are intuitive, builds on best practices and existing requirements, and adopts a tone and approach that is adequate for the general public.
Pilote Secteur des programmes IA cognitive et générative
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180
Analyse des lacunes de la réglementation sur l’aquaculture du Pacifique (RAP)Copilot is being leveraged to analyze written submissions and meeting notes from the Transition Plan engagement process to identify key themes, concerns, and suggestions. It helps summarise large aounts of input that help detect gaps in the feedback - such as missing perspectives, underrepresented topics, or unclear areas - enabling AD to plan more targeted and inclusive future engagement and consultations on the PAR amendments. Copilot also helps to dig into input in a more manageable way.
Pilote Secteur des programmes IA cognitive et générative
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144
Factoid Finder ToolThis completed project used the Factoid Finder extracts text from machine-readable PDFs to create searchable content libraries. Small Language Models are used to implement semantic search techniques, allowing users to search the library for relevant passages within the PDFs.
Pilote Sciences des écosystèmes et des océans IA cognitive et générative
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84
Daily UseDashboard Development, Used the standalone M365 version of Copilot to assist with coding.
Pilote Secteur des programmes IA cognitive et générative
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85
Daily UseBing CoPilot, ChatGPT-4 Emails, documents, speaking points, ideas
Pilote Secteur des programmes IA cognitive et générative
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101
Creating space-time continuous surface chlorophyll fields for northwest Atlantic using neural network methodsNeural network methods are applied to fill the space-time gaps in satellite remote sensing data of surface chlorophyll for the Northwest Atlantic. The generated dataset will be validated and analyzed.
Pilote Sciences des écosystèmes et des océans IA cognitive et générative
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102
Past, Present and Future Oceanographic Conditions in Canada's MPAs and Marine OECMs (Other Effective area-based Conservation Measures)Downscaling climate models using neural networks for conservation areas. Neural networks allow us to represent coarse resolution climate projections at a much higher spatial resolution across six eastern MPAs.
Pilote Sciences des écosystèmes et des océans IA cognitive et générative
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114
InsightBridge: Executive CSAS SummariesUses AI to convert complex, technical CSAS reports into concise, plain-language summaries tailored for executive decision-makers. Enhances leadership understanding and accelerates informed decision-making by providing easily digestible insights. Ensures executives can quickly grasp critical information without sifting through dense documentation.
Pilote Sciences des écosystèmes et des océans IA cognitive et générative
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115
PublicLens: Science in Plain LanguageLeverages AI to transform highly technical scientific and documents into accessible, plain-language summaries for the Canadian public. Fosters transparency and builds public trust by making scientific and government information easily understandable. Promotes civic engagement by breaking down barriers between experts and everyday Canadians.
Pilote Sciences des écosystèmes et des océans IA cognitive et générative
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123
Fish-Habitat AssociationsExtraction of relevant habitat association info and strengths based on vetted literature input to AI for synthesis. Goal to improve equivalency models used in regulatory decisions. Possible partnership with McMaster University.
Pilote Sciences des écosystèmes et des océans IA cognitive et générative
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168
Development of bespoke data-limited tools using AI coding.The majority of Canadian fish stocks are data limited thus preventing full analytical stock assessments. Data limited tools are therefore the only approach. We are engaged in quick Ai development of custom data limited assessment approaches for exploited fish stocks
Pilote Sciences des écosystèmes et des océans IA cognitive et générative
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170
NFIS Elver Retrieval-Augmented Generation Pilot with CDOSCDOS RAG pilot accept NFIS submission of illegal elver sales proposal. AI model would receive content and asked to summarize or visualize information based on core concepts to draw inference. Pilot only active for 2 months. Governance: Large project of 40 pilots led by CDOS. Assign project lead; document user access. Regular check-ins with IT and management. Guardrails: Restrict to pilot users; apply GC data/privacy standards; conduct ethical reviews and audits. No interne
Pilote Secteur des programmes IA cognitive et générative
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80
Various Built-In AI Features (Co-pilot, ChatGPT, etc)Using built-in AI features and functions in regular workflow operations. This includes LLM's such as ChatGPT, Microsoft Copilot, Gemini, and various others that are integrated directly into the applications already currently being used. Large Language Models
Pilote Sciences des écosystèmes et des océans IA cognitive et générative
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78
Okanagan sockeye life cycle modelUsing LLM (ChatGPT) to support the development of a statistical lifecycle model for Okanagan sockeye. LLMs are not developing the models but are used to brainstorm modelling approaches, debug code, and confirm that written model descriptions in manuscripts are accurate and clear. AI is not being tasked with developing these models. Large Language Models
Pilote Sciences des écosystèmes et des océans IA cognitive et générative
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63
Factoid Finder ToolThe Factoid Finder extracts text from machine-readable PDFs to create searchable content libraries. Small Language Models are used to implement semantic search techniques, allowing users to search the library for relevant passages within the PDFs. Small Language Model and Text Embedder: MS Marco Distilbert Dot-v5 Cross-encoder: MS Marco MiniLM-L6-v2
Pilote IA cognitive et générative
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22
AI Model for Administrative SupportPilot with select staff using MS Copilot for briefing material preparation, data analysis, writing, and translation. Exploring broader access for process automation. Action plan for this initiative: 1. Governance: Assign project lead, document user access. Regular check-ins with IT and management. 2. Guardrails: Restrict to trained users, apply GC data/privacy standards, conduct ethical reviews and audits. 3. Work pr
Pilote Secteur des programmes IA cognitive et générative
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1
Projet pilote de M365 CopilotWe are running the Copilot Licensed pilot to see the use of Copilot as an elevated assistant. We are looking into how productive it can help people perform their work, reduce administratrive tasking We have 300 licenses, but we also have all DFO users available for a smaller version of Copilot that could be leveraged.
Pilote Dirigeant principal du numérique IA cognitive et générative
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5
ITSD knowledge content improvementThe DFO IT Service Desk is leveraging generative AI (usually Copilot) to enhance its knowledge base articles and Assyst FAQs, which is knowledge intended for clients. This includes creating new knowledge articles, validating and improving existing content, translating materials, and tailoring messaging to different audiences.
Pilote Dirigeant principal du numérique IA cognitive et générative
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179
Centre d’excellence en gestion du changement – Assistant IAChange Management Centre of Excellence – AI Assistant: Using a Copilot agent as our dedicated assistant to support the sector by providing answers to questions on change management strategies, services, tools and templates.
Idéation Politiques stratégiques IA cognitive et générative
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182
Traductions de base et traitement des donnéesWe have identified several effective use cases: Processing machine readable data into human readable formats, basic translations, and summarizing large documents and reports into digestible formats. We participated in tests of the DFO Pilot ChatGPT (GPT3) which was available prior to the DFO implementation of MS Copilot. As part of our testing, we identified several effective use cases which apply to both options since they're based on the same under
Idéation Secteur des programmes IA cognitive et générative
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219
Fish-Habitat AssociationsExtraction of relevant habitat association info and strengths based on vetted literature input to AI for synthesis. Goal to improve equivalency models used in regulatory decisions. Possible partnership with McMaster University.
Idéation Sciences des écosystèmes et des océans IA cognitive et générative