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De retour à l’OL ces dernières saisons, Corentin Tolisso et Rachid Ghezzal étaient déjà là en 2016. Ironie de l’histoire, les deux joueurs sont les seuls absents de ce dimanche soir pour le match anniversaire. Parfois, les choses sont bien faites. D’autres, les coups du sort empêchent que le scénario ne soit totalement parfait. Ce […] L’article Rescapés de 2016, Tolisso et Ghezzal manqueront la fête au Parc OL est apparu en premier sur Olympique & Lyonnais.

Companies of all sizes are looking to hire workers who know how to use AI.Sebastien Bozon/Getty ImagesDo you know what LLM even is? How about a GPU? A new vocabulary has emerged with the rise of AI.From AGI to prompt engineering, new terms and concepts are being created seemingly every day.Use this glossary of AI-related terms to speak about this technology with authority.It's becoming increasingly impossible to ignore AI in our everyday lives.That doesn't mean it's always easy to understand. From agentic AI to UBI, tech CEOs, Wall Street, and politicians increasingly sound like they are speaking another language.Even if you don't use AI in your day-to-day life, chances are your bank, your doctor, the streaming service you're using, and maybe even your car do.Here's a list of the people, companies, and terms you need to know to talk about AI, in alphabetical order.The AI terms you need to knowAgentic: A type of artificial intelligence that can make proactive, autonomous decisions with limited human input. Unlike generative AI models like ChatGPT, agentic AI does not need a human prompt to take action — for example, it can perform complex tasks and adapt when objectives change.AGI: "Artificial general intelligence," or the ability of artificial intelligence to perform complex cognitive tasks such as displaying self-awareness and critical thinking the way humans do.Alignment: A field of AI safety research that aims to ensure that the goals, decisions, and behaviors of AI systems are consistent with human values and intentions.Bias: Because AI models are trained on data created by humans, they can also adopt the same fallible human biases present in that data. There are a number of different types of bias that AI models can succumb to, including prejudice bias, measurement bias, cognitive bias, and exclusion bias — all of which can distort the results.Capability overhang: The term, credited to Microsoft Chief Technology Officer Kevin Scott, for the gap between what AI models are capable of doing and what applications are tapping in terms of the models' potential.ChatGPT: OpenAI's signature chatbot that launched to significant fanfare in 2022 and is often credited for kickstarting the AI race. As of 2026, OpenAI is facing concerns that rival AI tools may be surpassing ChatGPT's capabilities. GPT stands for Generative Pre-trained Transformer.Claude: Anthropic's flagship model was first launched in March 2023. While Anthropic's core focus is on the enterprise business, Claude has been lauded for its ability to write code. In early 2026, Anthropic added healthcare and more general-focused tools to Claude.Compute: The AI computing resources needed to train models and carry out tasks, including processing data. This can include GPUs, servers, and cloud services.Data centers: Large warehouses filled with tens, if not hundreds, of thousands of advanced computer chips and graphics processing units, used to handle large amounts of data, storage, and complex processing required to power AI models. Unlike older iterations, AI data centers require significantly more space and energy because of the widely held assumption that AI models learn best at a massive scale.Deepfake: An AI-generated image, video, or voice meant to appear real that tends to be used to deceive viewers or listeners. Deepfakes have been used to create non-consensual pornography and extort people for money.Distillation: The process of extracting the reasoning process and learned knowledge of a larger, existing AI model to a new, smaller AI model — essentially, copying an AI model to start your own.Doomer: A derisive term for AI skeptics who express reservations about either the potential risks of AI development (developing technology that could turn against humanity) or even just pessimism that AI will achieve lofty ambitions like creating models capable of human-like reasoning.Effective altruists:…