In the latest announcement, French multinational company-Thales has announced to open an AI industrial research laboratory in order to focus on critical systems such as energy production facilities.
Sources state the new facility will be dedicated to application of AI in critical systems such as in power generation infrastructure.
Earlier last year in July 3, the state-owned electric utility EDF and French multinational integrated oil and gas company- Total together with Thales were among eight French signatories of a manifesto for an artificial intelligence (AI) industry sponsored by the Ministry of the Economy and Finance.
The previously launched manifesto was established to endorse research and development resources, thus promoting the use of AI a significant source of growth and for jobs in industrial sectors and within an ethical framework.
The latest venture of an AI laboratory is a further commitment towards this intended goal. Sources suggest the work will be undertaken at the EDF Lab Paris-Saclay research and training center and will further focus on “AI technologies adapted to the needs of critical industrial systems,” especially vulnerable systems with special focus on malfunctions with serious consequences.
Furthermore, EDF said it will also undertake aeronautical applications and energy production facilities with regards to the latest development. “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,” commented the state-owned electric utility.
According to reports, the new laboratory will apply AI technologies for applications such as task optimization, acceleration of access to information, improvements in industrial efficiency and energy performance, industrial facility availability, among others.
In addition, the research of the partner companies 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.