The talk presented a project called Numba MPI, which aims to combine the power of Numba's just-in-time compilation with the MPI standard for distributed memory parallelization in Python. The speakers discussed the advantages of using Python for high-performance computing (HPC) and presented a benchmark showing that Numba compiled code outperforms C++ in certain scenarios. They also explained the challenges they faced in integrating Numba and MPI and how they addressed them through their Numba MPI package. The speakers highlighted the importance of testing and provided information about their CI setup. They concluded the talk by inviting contributions and acknowledging funding.