[ergodic]

> it might be great to have a human readable and tweakable solution (assuming you have the resources) but for something like recognising handwritten digits from images, not so much.

Agree, but with black-box I meant not something that is opaque to my grand-mother but partially opaque to engineers that implement MLP machine learning applications and the tech-lead that takes the decisions. The thing is that even research people (or maybe specially them) tend to positively bias things they do not completely understand (so I think, maybe its just me ;)). That is what I meant with black-box delusion. As you say only time will tell.

Regarding DBNs, again, the case of ASR uses DNNs which is to say big-fat MLPs. The model is handled as a DBN only for pre-training, and layer-wise pre-training does a similar job anyway.

[SiVal]

Regarding the "black-box delusion", it's not just you. You see a magician do a trick, and it's amazing. Then he explains how it is done, and the excitement vanishes. Oh, that's all it is, no big deal.

Any sufficiently advanced technology is indistinguishable from magic, and who knows what wonders magic might accomplish? But once you understand the "trick", it's obvious that it can't do much more than what it's doing. Oh, well. The magic is gone.