EduPLEx_API
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Recommendation, reporting & analytics
Recommendation, reporting & analytics
  • Experiments report
    • Key concepts
    • Data sources
    • First demonstrator: ESCO ontologies and semantic matching
    • Software design
      • Endpoints Sbert_eduplex
      • Setup Sbert_eduplex
    • AI Applications
    • Conclusions
    • Recommendation
    • Bibliography
  • Recommendation Engine
  • Reporting and predictive analytics
  • LRS User Journey Visualizer
  • AI Tutor - RAG system
    • LLM-augmented Retrieval and Ranking for Course Recommendations
    • Retrieval of course candidates when searching via title.
    • Answer Generation Evaluation
    • Chunk Size and Retrieval Evaluation
    • Chunking Techniques – Splitters
    • Golden Case CLAPNQ
    • Comparative Retrieval Performance: Modules vs Golden Case
    • LLM-based Evaluator for Context Relevance
    • Retrieval Performance Indexing pdf vs xapi, and Keywords vs Questions
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  1. Experiments report

Conclusions

Information retrieval technology has advanced greatly, and current systems continue to improve rapidly. However, there are still technical barriers and constraints to implement fully functional and deployable systems. Training custom neural network (e.g. LLMs) from scratch give the best possible results, but they require large data, specialised hardware, technical human expertise, and they are economically costly. Thus, the most common use of this technology is based on the subscription model with companies such as OpenAI (e.g. ChatGPT).

Given the constraint mentioned above, one common alternative is to use LLMs that have been pre-trained and optimised to carry out tasks within a specific context. Then, these models can be used to train our models as a downstream task.

There are open issues such as privacy, copyrights and IP, bias, and other risks that need to be assessed when implementing AI systems, particularly when new legal frameworks such as the EU AI Act (Regulation (EU) 2024/1689) will affect the deployment of AI systems.

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Last updated 3 months ago