Nos dernières nouveautés et articles sur l'IA

Dans cet article, nous expliquons comment les RAG rendent les LLM plus fiables, efficaces, dignes de confiance et flexibles, en plongeant dans les différents composants de son architecture.

In this article, we cover how RAGs make LLMs more reliable, efficient, trustworthy and flexible, by diving into the different components of the architecture, from the embedding model to the LLM.

Learn how to easily build a recommender system based on semantic similarity with LLMs and Vector Databases!

An introduction to Causal Inference, why it is needed in data science and how Machine Learning can help, with real-world applications and exciting research directions.

Learn how to monitor the drift of your ML models and make sure that it never gets out of control!

Exploring LLMs: Unveiling profound text generation via embeddings & attention, while navigating challenges in data use.