Seems like a poorly planned attempt at promoting your own tool.
Looking briefly at the notebook, it seems like a lot of the M5 features were excluded and only item_id was kept: https://nixtla.github.io/statsforecast/examples/aws/statsforecast.html#read-data
M5 has additional features like department, category, store, state and of course the events table. These features are very helpful and would obviously be present in a real life scenario of a retail forecast (among with many others).
The code with parameters to train AWS Forecasts models seems to also be missing from the "reproducible experiment" notebook 😂.
Not sure the study is worth taking seriously. Seems like a quick attempt at marketing rather than a study with any meaningful level of rigor. "My Corolla is faster and cheaper than a Porsche 911 when I use vegetable oil to fuel them and don't show you the Porsche".
Where does your result land on the Kaggle leaderboard?

I think the terminology is more common in the forecasting niche where (especially since the M4, M5 competitions) they started to separate out tree and NN architectures into "ML" and all other methods used for last 50 years are deemed "classical".

where do you see the full experiment? I think only the results table from Amazon is published, no?

would be nice to disclose that the study was sponsored (and conducted?) by StatsForecast...