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.
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30 initiative(s) courante(s)
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27
Turn on AI Auto labeling on all M365 documents and communications channelsOur E5 M365 licences grant access to AI based tools in Purview to automatically categorized documents and set labels accordingly. Model training would require attention of an Security/IM expert to make perfect. We may want to create specific AI specific labels to avoid conflicts with officials ones.
Idéation Dirigeant principal du numérique Automatisation et aide à la décision
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32
CTD Anomaly DetectionThe goal of this project is to apply machine learning to detect anomalous oceanographic data, highlighting meaningful physical phenomena in the state of the ocean for closer investigation by scientists. A proof of conept model has been developed to demonstrate feasibility. Further validation is required with the client to verify alignment with the needs of scientists. Client: Pacific Region - Ocean Sciences Division
Pilote Politiques stratégiques Perception et compréhension
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51
EN/FR Translation ModelA large language model that is trained on the Translations Bureau’s and DFO's language-characteristics (i.e. grammar, annotation, syntax, words, scientific term) context. The model’s enables translation to be like those by the Translation Bureau. Training on large database of scientific documents (published by Canadian Science Advisory Secretariat) to understand scientific terminology is currently in progress. MADLAD 400 10B (Initially trained on sample of ~100 translated documents, in progress of additional training with published CSAS documents going back to year 2000)
Pilote Secteur des programmes Interaction et engagement
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53
LLM Document ChatbotLarge language model that can help users ask questions to document sets and get answers, summarize key information, and find data with citations and sourcing., including, from documents with multiple templates using prompt engineering approaches Azure OpenAI GPT4o/4o mini
Développement Secteur des programmes Interaction et engagement
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54
PII & Sensitivity ScoresDetermines the sensitivity of the content of a document based on a trained model and allows for the redaction of the sensitive material in the document. Presidio
Idéation En pause Secteur des programmes Automatisation et aide à la décision
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56
Method Recommendation EngineA large language model reviews a scientist’s objective for collecting data in the field and based on the criteria, the model will provide the best procedure to use for their work
Idéation Secteur des programmes Automatisation et aide à la décision
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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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65
Comprehensive marine substrate classification applied to Canada’s Pacific shelfWe built five regional and one coastwide substrate model for the BC coast using substrate observations and seafloor bathymetry derivatives and oceanographic predictors using Random Forests. Random Forests
Pilote Sciences des écosystèmes et des océans Automatisation et aide à la décision
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71
News topic detection toolUse large language models and topic clustering to read topics emerging in the news and detect which of those topics is relevant to DFO, as well as what knowledge DFO has available to address those topics. Large Language Models
Idéation Sciences des écosystèmes et des océans IA cognitive et générative
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75
Study on the use of Artificial Neural Networks to Predict the Return Timing and Northern Diversion Rate for Migrating Fraser River Sockeye SalmonThe Machine Learning feasibility study compliments the statistical approach by asking whether Artificial Intelligence (AI) methods can be developed to predict salmon behaviour as functions of ocean conditions. classical machine learning models, including linear regression, Ridge regression, and Random Forest
Idéation Sciences des écosystèmes et des océans Automatisation et aide à la décision
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77
Emulator for OPP port models and for relocatable ocean modelling systemUse machine learning to develop an emulator (or similar) for the OPP port models, which would be used to produce forecasts via inference. The inference is expected to be both faster and computationally cheaper than existing solutions. The training process would use existing model output from multi-year hindcasts. Success with a fixed location would graduate to developing a relocatable emulator TBD; could be U-Net or CNN, or based on GraphCast
Idéation 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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79
Biological models to support prioritzing salmon stocks under future climatesThis project fits retrospective, life stage-specific models in a data-driven analytical framework to evaluate functional responses to climate variables across the salmon life cycle and make projections for how stocks will respond to climate change scenarios. This modelling approach is intended to be sufficiently flexible to incorporate variability in data quality. Large language models are being used to brainstorm modelling approaches and debug code. AI is not being tasked with developing these models. Large Language Models
Idéation Sciences des écosystèmes et des océans IA cognitive et générative
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99
Improved freshwater runoff modelling in Eastern Canada to drive ocean modelsUse Neural Networks to post-process streamflow simulations from the WRF-Hydro model, improving their agreement with observational data. These neural networks are applied as a downstream calibration step. Builds synergy between traditional calibration methods and modern AI techniques in hydrologic modeling.
Pilote Sciences des écosystèmes et des océans Automatisation et aide à la décision
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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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110
Mercator Collaboration on Digital Twins of the OceanKnowledge exchanges with ECCC and Mercator Océan International on use of AI for ocean modelling, in the context of Digital Twins of the Ocean.
Pilote Sciences des écosystèmes et des océans Infrastructure et habilitation
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111
Digital Twins of the Ocean Task TeamNational exchanges on topics relating to ocean modelling for development of Digital Twins of the Ocean, including use of AI for modelling and products.
Pilote Sciences des écosystèmes et des océans Infrastructure et habilitation
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112
ECCC exchanges on use of AI for ocean modellingExchanges with ECCC on implementation of machine learning methods for operational ocean forecasting, including potential uses for DFO models.
Pilote Sciences des écosystèmes et des océans Infrastructure et habilitation
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113
Improving forecasting for high-priority portsResearch into feasibility of improving accuracy and timeliness of short-term forecasts for coastal regions by combining traditional and AI modelling methods.
Pilote Sciences des écosystèmes et des océans Automatisation et aide à la décision
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132
Salmon Scale AgingA model using computer vision to look at images of salmon scale and predict the age of salmon and also explain how it arrived at its prediction.
Pilote Sciences des écosystèmes et des océans Perception et compréhension
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134
LLM Document ChatbotLarge language model that can help users ask questions to document sets and get answers, summarize key information, and find data with citations and sourcing.
Développement Sciences des écosystèmes et des océans Interaction et engagement
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135
PII & Sensitivity ScoresDetermines the sensitivity of the content of a document based on a trained model and allows for the redaction of the sensitive material in the document.
Pilote Sciences des écosystèmes et des océans Automatisation et aide à la décision
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137
Method Recommendation EngineA large language model reviews a scientist’s objective for collecting data in the field and based on the criteria, the model will provide the best procedure to use for their work
Pilote Sciences des écosystèmes et des océans Automatisation et aide à la décision
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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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152
Data Validation ToolUse large language models to help detect errors in data transcribed using optical character recognition. Apply validation rules to propose corrections and normalize data into a standardized format.
Pilote Sciences des écosystèmes et des océans Automatisation et aide à la décision