[visarga]

> how on earth are you going to think of ANY elephant, let alone my elephant?

Both brains sensors are calibrated on the same images, then a common representation can be found as intermediary. It has been done with neural nets translating into a common intermediary language, thus needing N encoders/decoders instead of (N-1)^2 separate networks. In the easiest case it can be a simple linear transform to map one vector space into another.

[djohnston]

wouldnt you need a distinct transformation for every thought?

[visarga]

the transformation of brain signals to the common space can be a neural net - and since neural nets are non-linear they can adapt to the inputs

you'd need to train a bidirectional adapter for every person instead of (N-1)^2 adapters for each pair of people

[djohnston]

got it, thanks for the clarification