Giving this example is in itself an appreciation of artificial intelligence. It seems you answered your own question...

P. P. Afxenti , Yes, this time is increasing to accept AI's contribution to experimental and theoretical physics. In practical physics, by automating AI data collection, filtering the noise and identifying the hidden pattern in a large scale dataset is playing a transformative role that would be almost impossible for humans to process alone. Machine learning models are now guiding the design of experiments, adaptation of detector sensitivity, and fasting the discovery of new materials and particles. In high-energy physics, for example, AI has played an important role in analyzing the incidence of conflict in the large headron collider, which is improving signal-to-scrutiny discrimination. In astrophysics, AI helps in detecting exoplanets, gravitational waves and cosmic structures through advanced pattern recognition. In the theoretical side, AI is not replacing physics, but is acting as a powerful accessories. This helps to solve complex difference equations, approximate many-body problems, and the parameter detects spaces that are computable by traditional ways. Nerve networks and symbolic regression are also being used to propose potential new physical laws from data. It does not reduce the centrality of human intuition and logic, but rather expands the scope of investigation and increases it. Thus, AI should be recognized as an integral partner in physics, distinguishing experimental comments and theoretical insights into ways that expedite scientific discovery.