Artificial intelligence (AI) is a discipline of computer science that aims to create systems or machines capable of performing tasks that normally require human intelligence. This includes in particular:
• Learn from experience
• Reason and solve problems
• Understand natural language
• Perceive the environment (vision, sounds...)
• Make decisions
• Demonstrate creativity (increasingly present since 2022-2023)
Here is a common definition of AI in 2026:
"AI is the ability of a machine to simulate intelligent behaviors, particularly through learning from data rather than explicit programming of all rules."
Artificial intelligence is a discipline that has several branches. Here is a summary table presenting the different branches of AI as well as concrete examples in 2026.
| Branch | Main description | Very concrete examples in 2026 | Current significance |
| Machine Learning – ML) | Machines learn from data without being explicitly programmed for each case | Fraud detection, Netflix/Spotify recommendation, advanced weather forecast | Fundamental – socle of almost all modern AI |
| Deep Learning – DL) | ML subset using deep artificial neural networks (many layers) | Image recognition, voice recognition, almost all generative AI | The technique that has changed everything since ~2012 |
| Generative AI | Creates new content (text, image, video, audio, code, 3D...) from instructions | ChatGPT, Claude, Gemini, Midjourney, Runway Gen-3, Flux.1, Veo, Suno, Udio, Luma Dream Machine... | The most visible and invested branch in 2025-2026 |
| Natural Language Processing (NLP / NLProc) | Understand, generate and manipulate human language | Translators (DeepL, Google Translate), chatbots, sentiment analysis, automated summary, voice assistants | Very advanced thanks to the large language models |
| Computer Vision | Make machines understand and interpret images/videos | Facial recognition, autonomous cars, medical diagnostic imaging, industrial quality control | Very industrially mature |
| Intelligent robotics | Combine AI + perception + physical action | Humanoid robots (Figure 01, Tesla Optimus, 1X, Apptronik), autonomous drones, collaborative robotic arms | In very strong acceleration in 2025-2027 |
| Multimodal AI | Models that understand and generate multiple data types at the same time (text + image + sound + video...) | GPT-4o, Gemini 1.5/2, Claude 3.5/4, Grok with vision, Llama 4 (if out), etc. | The big trend 2024 2026 |
| Reinforcement Learning – RL) | Learn by trying and receiving rewards / penalties | AlphaGo/AlphaZero, robots that learn to walk, industrial optimization, AI video games | Very powerful but still difficult to stabilize on a large scale |
| Planning & symbolic reasoning | Reason logically, plan complex sequences of actions | Planners for logistics, games, advanced math problem solving | Comes back in force with the "reasoning" techniques of LLM (chain-of-thought, o1-like) |
| AI agents / agentive systems | autonomous AI that can chain multiple tools, take initiatives, work on multiple steps | Autonomous personal assistants, research agents, code agents (Devin-like), "AI employees" | The great fashion of late 2025 – early 2026 |