The basicsAI glossary
Machine learning
The big family: instead of hand-coding rules, you let the machine learn from examples. Deep learning is one branch of it.
In other words
Learning to recognise a cat by looking at 10,000 photos, rather than by reading its definition.
Alyriaz articles that mention it
- Claude runs 26% of the research that builds Claude
Anthropic has published figures on the share of its own research driven by its models: 26% in August against less than 1% in February. We analyse what this figure measures and what it implies.
- AI, machine learning, deep learning: what contains what?
Artificial intelligence, machine learning, deep learning, generative AI: these terms refer to nested sets, not synonyms. Let's clarify once and for all, with concrete examples.
- What is reinforcement learning? Learning through trial, error, and rewards
Reinforcement learning involves learning through interaction and reward rather than by imitating examples. We explain the principle, its spectacular successes, and why it lies at the heart of current AI behaviour.
- AI and climate: beyond data centres, what it actually enables
The debate on AI and climate often narrows to data centre consumption. We look at the other side of the ledger, the uses that genuinely cut emissions, and why the balance remains impossible to strike today.
- AI in the fields: the sector where it advances without anyone talking about it
Agriculture is one of the sectors where AI delivers concrete, measurable results, far from the media coverage. We take a look at the uses that work, their environmental benefits, and the dependencies they create.