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Cas d'utilisationRecherche
Comprendre les méthodologies d'évaluation de l'IA
Utilisez la Recherche approfondie pour décoder les bancs d'essai de LLM : leur fonctionnement, leurs échecs et les métriques à privilégier pour l'évaluation des modèles.
- Recherche
- Recherche approfondie
- Technologie
Aperçu
Les chercheurs, les ingénieurs et les chefs de produit en IA peuvent utiliser Perplexity pour comprendre le paysage en rapide évolution de l'évaluation des LLM. Recherche approfondie tire des informations d'articles universitaires, de la documentation sur les repères et d'analyses de l'industrie pour expliquer non seulement le fonctionnement des repères, mais aussi leurs lacunes, aidant ainsi les équipes à prendre de meilleures décisions quant aux métriques à privilégier lors de l'évaluation des modèles.
Conseil
- Partagez votre contexte de production spécifique (par ex., pipeline RAG, copilote de codage, assistant de soutien) afin que Perplexity puisse faire correspondre ces repères à la suite d'évaluation que vous souhaitez réellement créer
- Renseignez-vous sur les nouvelles approches d'évaluation en cours de développement pour pallier ces limites structurelles dans un contexte prospectif