Comment utiliser l’IA en 2026 : la Méthode Complète !

Comment utiliser l’IA en 2026 : la Méthode Complète !

by Ludo Salenne

Applied Sciences & Engineering AI — News & Applications UYComputer scienceUYQArtificial intelligence (AI)
🎙 Ludo Salenne 👥 267K 📅 April 30, 2025 ⏱ 27 min 👁 111K 📄 tutorial 🧭 2026-08-21
Available in: English (current) Français

Keywords

multi-AIhallucinationdeep researchNotebookLMGenspark

Summary

The video presents a comprehensive method for using AI effectively in 2026, focusing on reducing hallucinations and biases by leveraging multiple AI models from different regions. The creator, Ludo Salenne, demonstrates a workflow: first, he asks the same detailed question to ChatGPT (US), Qwen (China), and Mistral Le Chat (France), each with web search and deep research capabilities. He then collects the three responses as PDFs and imports them into Google’s NotebookLM, which synthesizes the information and allows for further source discovery. NotebookLM can generate a structured audio podcast in French, a feature recently added, and also produce a slide deck script. This script is then fed into Genspark AI to create a professional presentation. The method emphasizes providing rich context and using specific keywords to guide the AI. The video is practical, with live demonstrations, and aims to help professionals get reliable, actionable results from AI without extensive manual verification.

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Critical Evaluation

Value of the Information & Strength of the Argument

The video offers high practical value by presenting a concrete, replicable workflow that addresses a common pain point: AI hallucinations and biases. The argumentation is based on the creator’s extensive experience (12,000+ people trained) and live demonstrations, which adds credibility. The method of cross-referencing multiple AI models from different cultural and technological backgrounds is a sound approach to mitigate bias, though it is not scientifically proven. The creator clearly explains each step, making the tutorial accessible and actionable. However, the argumentation relies heavily on anecdotal evidence and personal success stories rather than systematic evaluation. The claim that this method makes you better than 99% of users is hyperbolic and not substantiated, but the underlying advice is sound.

Scientific Rigor, Source Quality, Title Accuracy

The video demonstrates a good level of rigor in its methodology: the creator uses multiple AI tools, shows real outputs, and encourages verification through NotebookLM’s source linking. However, the sources cited are primarily the AI tools themselves and the creator’s own resources, with no external scientific references. The description includes links to the tools used (ChatGPT, Qwen, Mistral, NotebookLM, Genspark) and the creator’s own resources, but no academic or institutional sources are provided. The title accurately reflects the content, and the video is well-structured with clear chapters. The creator’s transparency in showing the process live enhances trust, but the lack of external validation limits the scientific rigor.

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Title / Content Match

The title accurately reflects the content: a comprehensive tutorial on using AI effectively in 2026, with a focus on a multi-AI method to improve reliability.

Quality & Reliability

7/10

The video provides a practical, step-by-step methodology for using multiple AI tools to improve reliability and reduce hallucinations. The creator demonstrates the process live, showing real outputs and sources. However, the claims about effectiveness are anecdotal and not backed by formal studies or external validation. The tutorial is clear and well-structured, but the scientific rigor is limited by the lack of empirical evidence and reliance on personal experience.

Chapters

Cited Sources

  • ChatGPT — Used as the American AI model in the multi-AI method.
  • Qwen AI — Used as the Chinese AI model in the multi-AI method.
  • Mistral Le Chat — Used as the French AI model in the multi-AI method.
  • NotebookLM — Used to synthesize and analyze the three AI responses, and generate audio and slide scripts.
  • Genspark AI — Used to create the final slide presentation from the NotebookLM script.
  • Ressources IA gratuites — Creator's free resources including prompts and GPTs.
  • Formation Automatiser ChatGPT — Creator's paid training on automating ChatGPT.
  • Avis clients — Customer reviews of the creator's services.

Concurring Sources

  • NotebookLM — The tool is used as a central hub for synthesizing information and generating outputs, aligning with its intended use.
  • Genspark AI — Used to create presentations, consistent with its features.

External References

Contribution & Novelties

The video’s main contribution is a practical, multi-AI cross-verification workflow that reduces reliance on a single AI model and mitigates hallucinations. It demonstrates how to combine different AI tools (ChatGPT, Qwen, Mistral) with NotebookLM for synthesis and Genspark for presentation creation, offering a complete pipeline from research to polished output. The novelty lies in the systematic integration of these tools and the emphasis on using multiple cultural perspectives to achieve more objective results.

Pour aller plus loin :

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Radar Profile

The radar profile shows high scores in information quantity and quality, reflecting the comprehensive tutorial content. The technical level is moderate, suitable for a broad audience, while reliability is good but not exceptional due to the lack of external validation. The overall balance indicates a practical, well-structured tutorial with strong practical value.

Reliability 7/10

💬 Très positif. Sur les 30 commentaires analysés, les spectateurs expriment une admiration unanime pour la clarté, la pédagogie et l'utilité pratique de la vidéo, avec des remerciements répétés et des éloges pour la qualité du contenu et la nouveauté de la fonctionnalité de podcast en français.