French energy giants EDF and Total bet on artificial intelligence

The fossil fuel companies plus electrical systems business Thales have launched a joint research laboratory in Paris-Saclay to develop AI technologies to meet the needs of critical systems such as energy production facilities.
The new facility will focus on AI use in critical systems including power generation infrastructure. | Image: Guilhem Vellut/Flickr

From pv magazine France.

Electrical systems company Thales, state-owned electric utility EDF and oil major Total were among the eight French signatories of a manifesto for an artificial intelligence (AI) industry launched on July 3 at the Ministry of the Economy and Finance.

The manifesto was intended to promote research and development resources to make AI a source of growth and jobs across industrial sectors within an ethical framework.

With that commitment in mind, the fossil fuel companies and Thales have announced the opening of an AI industrial research laboratory. The work to be carried out at the EDF Lab Paris-Saclay research and training center will focus on “AI technologies adapted to the needs of critical industrial systems”, namely, vulnerable systems where malfunctions could have serious consequences.

Critical systems

Among such systems, EDF cited aeronautical applications and energy production facilities. These “indeed require the highest level of requirements in terms of reliability and therefore the development of trusted AI, explicable or even certifiable, which will respond to the laboratory’s research work”, the state-owned electric utility said.

The new laboratory will also develop AI technologies for applications such as task optimization, acceleration of access to information, improvements in industrial efficiency and energy performance and even industrial facility availability.

The partner companies’ research will focus on three key areas: explainability, or transparency of reasoning; reinforcement learning – rewarding AI positively or negatively during learning; and simulation via physical models to optimize system behavior.

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