Machine learning

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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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Two people collaborate in front of computer screens, one pointing something out to the other. The screens display computer code in a modern office environment.
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AI: “the divide between freelance and in-house developers can be damaging”

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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.
Artificial intelligence | Discover

AI fed on data from gas sensors and smart cameras prevents workplace accidents

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Crowdsourcing cacatoès
Internet of things | Go in-depth

Smartphone data to map the outer atmosphere and monitor urban wildlife

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Digital culture | Explore

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

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Internet of things | Go in-depth

Machine learning for intuitive robots that are aware of their environment

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