I saw that too - I'm assuming it means they're indeed using the DNN for stabilization. This has been done several times over the years, but generally with results which only rival PID and don't surpass it, so that's quite interesting. What's odd is that the physical architecture of the drone doesn't really make sense for this, so there must be some tweaks beyond the "spec" model. Hopefully some papers come soon instead of press releases.
They reference ESA's research in "Guidance and Control Nets", and when looking at ESA's page for their "Advanced Concepts Team" [0] they in turn reference ETH Zürich's research in RL for drone control. Specifically [1] this paper from 2023: "Champion-level drone racing using deep reinforcement learning" [2]. They use a 2x128 MLP for the control policy.
[0] https://www.esa.int/gsp/ACT/
[1] https://www.esa.int/gsp/ACT/projects/rl_vs_imitation_learnin...
This is crazy, its dexterity and range of motion could potentially exceed all human modeled systems.