Observations (or conclusions if you prefer)
- Need for AI/Machine Learning in physics, lots of ongoing activities
- To solve many complex problems and facilitate discoveries, multidisciplinary efforts efforts are required involving scientists in physics, statistics, computational science, applied math and other fields.
- There is a need for focused AI/ML learning efforts that will benefit accelerator science and experimental and theoretical programs
- How do we develop insights, competences, knowledge in statistical learning that can advance a given field?
- For example: Can we use ML to find out which correlations are relevant and thereby diminish the dimensionality problem in standard many-body theories?
- Can we use AI/ML in detector analysis, accelerator design, analysis of experimental data and more?
- Can we use AL/ML to carry out reliable extrapolations by using current experimental knowledge and current theoretical models?
- The community needs to invest in relevant educational efforts and training of scientists with knowledge in AI/ML. These are great challenges to the CS and DS communities
- Quantum computing and quantum machine learning not discussed here
- Most likely tons of things I have forgotten