Artificial intelligence
AI has a cross-functional role in EDF Group research. We are exploring all the possibilities offered by this technology, to apply it to all our business lines.
Today, the range of applications is wide: AI is used in our industrial activities (non-critical processes, such as procurement or maintenance, etc.), as well as in commercial activities (robots for customer relations).
Tomorrow, the challenge will be to integrate AI into critical processes, such as the operation of a power plant.
Transcription
Expert’s voice: Stéphane Tanguy
Artificial intelligence has a major role to play in digital acceleration. EDF R&D has therefore equipped itself with unprecedented computing and human resources to remove the technological barriers, thereby making a major contribution to the dissemination of AI within all the EDF Group's business. EDF R&D is committed to promote a responsible, more ethical and energy-saving AI.
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The world of AI in 5 keywords
Expert systems, symbolic AI, machine learning, whether supervised or unsupervised, deep learning, neural networks… These are just some of the terms and concepts we hear every day in the world of AI.
But what exactly do they mean? What concepts lie behind them? How can we visualise them?
Nicolas Bousquet, expert research engineer at EDF R&D, Deputy Director of the Sinclair Laboratory and Associate Professor at Sorbonne University, and Yannig Goude, Senior Researcher in Data Science and Statistical Learning, Project Manager and Co-pilot of the Data Innovation Lab at EDF R&D, and Associate Lecturer at the Orsay Mathematics Laboratory, took on the challenge of providing concise, accessible definitions of these key concepts to help us understand the fundamentals of artificial intelligence.
The Data Innovation Lab at EDF R&D
The DIL, or Data Innovation Lab, is a cross-functional initiative at EDF R&D that conducts data science projects based on the maturity of the topics and business needs (Datathon, Data Shaker, Use Cases, Core Platform), drawing on R&D expertise (Data Scientists, Data Engineers) and cutting-edge artificial intelligence methods.
It brings agility and flexibility to projects and challenges, with each project lasting from a few weeks to a maximum of six months and managed dynamically using a “Think Big, Start Small & Fail Fast” approach.
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