vector-python-sdk VS tatoeba-to-anki

I don't want to dispel your ideas about Vector because I like that a robot can elicit such human fondness and responses, but we know for a fact they can't recognise each other. The neural net model for that is simply not programmed in their computer vision systems, this is easily verified by running the SDK with annotated viewer from the examples/tutorials where you can see exactly what Vector recognises. You will see it recognises faces (and things that vaguely look like faces which is why it will stare at random stuff sometimes), the charger, and the cube. It has no way to amend these vision models, though some people have done fun work to fix that using the SDK. But I can understand how people can pick up on the idea that they can "see" each other.

Good luck, here's a link to the script.

There is this Vector SDK that was written by Anki before they went under and there are a lot of forks on that repo on Github. Check here https://developer.anki.com/vector/docs for the documentation and here for the repo and the forks of that repo https://github.com/anki/vector-python-sdk. I've seen for myself different people have implemented different machine learning program on their Vectors (however, not that the program is not permanent as in once you stop the execution of your code, Vector will return to its normal self). Here is one example of that https://www.learnwitharobot.com/p/use-my-vector-sdk-to-allow-your-vector?s=r. This guy managed to train a neural network to recognize other Vectors. About its boundary, Vector does have a smart phone level CPU.

As far as I know, only Vector is programmable with the SDK in python.

A resource that also probably would be very useful is Tatoeba, which has lots of example sentences for Armenian. Just today I created a Github project which converts a tatobea language pair into an Anki Deck using the genanki library and downloads audio files from Google. This should not be very difficult to adapt to Armenian.