{"id":3438,"count":36,"description":"Artificial intelligence is no longer a research curiosity \u2014 it is reshaping how products are built, how content is produced, and how decisions are made at every level of a digital organisation. This category gathers practical resources on AI and machine learning drawn from real professional experience: prompt engineering, LLM integration, generative AI workflows, NLP pipelines, semantic search, and the organisational challenges that come with deploying AI in production. Whether you are a developer exploring Python libraries such as LangChain or Hugging Face, a product manager evaluating AI tooling for your team, or a journalist trying to understand what AI coordination actually means inside a media company, you will find concrete, use-case-driven content here. Articles cover both the technical layer \u2014 model fine-tuning, API calls, vector databases, RAG architectures \u2014 and the strategic layer: governance, adoption barriers, and the gap between AI hype and measurable outcomes. This is not a blog of predictions; it is a record of what works, what fails, and what is worth trying next.","link":"https:\/\/flaven.fr\/category\/ai-machine-learning\/","name":"AI & Machine Learning","slug":"ai-machine-learning","taxonomy":"category","parent":0,"meta":[],"_links":{"self":[{"href":"https:\/\/flaven.fr\/happy-api\/wp\/v2\/categories\/3438","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/flaven.fr\/happy-api\/wp\/v2\/categories"}],"about":[{"href":"https:\/\/flaven.fr\/happy-api\/wp\/v2\/taxonomies\/category"}],"wp:post_type":[{"href":"https:\/\/flaven.fr\/happy-api\/wp\/v2\/posts?categories=3438"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}