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AI is playing a key part in reshaping and developing businesses, and in improving people’s daily lives. Different concepts, tools and technologies that use algorithms—such as blockchain, machine and deep learning, natural language processing, generative AI, etc.—are beginning to show exciting possibilities that will support and optimise human intelligence. If guided by an ethical and responsible approach, this field can offer numerous rewards.

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Explainability of artificial intelligence systems: what are the requirements and limits?

• Faced with the human and social challenges associated with machine learning techniques, it is essential to understand what explainability entails and its requirements, as well as the legal obligations and limitations surrounding it.
• Work on these subjects has taken on considerable importance given the human and social risks posed by the use of machine learning techniques, in particular deep neural networks or, more recently, large language models.
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Data and AI Ethics Council, guarantor of responsible AI at Orange

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A group of people is attending a presentation of BrainBox AI at the Orange OpenTech event. Two presenter stands in front of a screen displaying graphs and information on the topic. The participants are listening attentively and appear engaged in the discussion.
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BrainBox AI to cut commercial real estate emissions by up to 40%

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A group of mining workers is listening to a colleague who is explaining something. They are wearing yellow safety helmets and masks. The environment is dark, with rocky walls visible in the background. The guide is using a headlamp to light his way.
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AI fed on data from gas sensors and smart cameras prevents workplace accidents

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Orange OpenTech 2024: AI is here

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Factiverse: reliable AI fact-checking in more than 100 languages

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Machine learning for intuitive robots that are aware of their environment

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