Re: name. Fold and bend are indeed called fold and unfold in Haskell and traditional functional programming literature.
I wonder if bend has to do with how we manipulate the computation's interaction graph while evaluating a bend. There might be some bending of wires!
Re: code example
In the code example, x=0 is the seed value. tree = fork(0) must mean "fork off to evaluate the bend at the seed value". In that first fork, we fork twice with the value x=1, to get the left and right subtrees of the top level node. We then fork four instances of x=2, eight instances of x = 3, and finally get our balanced binary tree with eight 7s.
Note this is guesswork. I don't know what the ![a, b] syntax means, and I haven't read much of the guide.
Appendix: Notes on Fold Vs Bend
I wrote these for an earlier draft while reminding myself about these operations. I include them more for my benefit, and in case they help you or the audience.
Fold and bend are categorical duals, aka catamorphisms and anamorphisms. One takes a monadic value and reduces it into an ordinary value. The other takes an ordinary value and expands it into a comonadic value.
Fold starts with a value in an inductive data type, and then replaces its constructors with a function. For example it takes a list (1:2):3, and replaces the constructor : with the function `+`, to get (1+2)+3 = 6
Bend starts with a seed value and a function taking values into constructor expressions for a conductive data type. It then grows the seed into a potentially infinite AST. For example the seed value 1 and the function f(x:xs) = (x+1) : (x:xs) gives us the infinite lazy list [1, 2, 3, ...]
Quality of life improvements are much much more important than understandable models of speech, so we should live with, appreciate, and work to interpret and improve the current generation of complex neural TTS models.
I depend on TTS to overcome dyslexia, but I also struggle with auditory processing disorder that causes me to misunderstand words. As a result , classical TTS does not help me read faster or more accurately than struggling through my dyslexia. It causes me to rapidly fatigue, zone out, and rewind often, in a way that is more severe than when I sight read.
On the other hand, modern neural TTS is a huge enabler. My error rate, rewind rate, and fatigue are much better thanks to the natural tone, articulation, and prosody. I'm able to read for hours this way, and my productivity is higher than sight reading alone. This unlocks long and complex readings that I would never complete by sight reading alone, like papers in history, philosophy, and law. Previously I was limited to reading math, computer science, and engineering work, where I heavily depended on diagrams and math formulas to help me gloss over dense text readings.
The old tech had no impact on my life, given my combination of reading and listening difficulty, since it was not comparatively better than sight reading. But my life changed about 6 years ago with neural TTS. The improvement has been massive, and has helped me work with many non-technical readings that I would previously give up on.
The main issues I see now is not that neural models are hard to understand. For better or worse, we're able to improve the models just by throwing capital and ML PhDs at the problem. The problem I see is that the resulting technology is proprietary and not freely available for the people whose lives it would change.
We should work towards a future where people can depend on useful and free TTS that improves their quality of life. I don't think simple synthetic models will be enough. We must work to seize control of models that can provide the same quality of life improvements that new proprietary models can provide. And we must make these models free for everyone to use!
As an ethical engineer, there is a further duty to also sabotage the organization once we uncover dirt on it. Never for profit. Sometimes for ego. And always because if every engineer took a stand against BS, then the world would be a much better place.
Did you learn your lesson to stay off of the crypto? If not, then that's why you feel nothing. It's part of your continued denial that crypto is pure evil. What's it going to cost you to ditch it, do you think? Another ten grand? More? I'm curious
I wonder if bend has to do with how we manipulate the computation's interaction graph while evaluating a bend. There might be some bending of wires!
Re: code example
In the code example, x=0 is the seed value. tree = fork(0) must mean "fork off to evaluate the bend at the seed value". In that first fork, we fork twice with the value x=1, to get the left and right subtrees of the top level node. We then fork four instances of x=2, eight instances of x = 3, and finally get our balanced binary tree with eight 7s.
Note this is guesswork. I don't know what the ![a, b] syntax means, and I haven't read much of the guide.
Appendix: Notes on Fold Vs Bend
I wrote these for an earlier draft while reminding myself about these operations. I include them more for my benefit, and in case they help you or the audience.
Fold and bend are categorical duals, aka catamorphisms and anamorphisms. One takes a monadic value and reduces it into an ordinary value. The other takes an ordinary value and expands it into a comonadic value.
Fold starts with a value in an inductive data type, and then replaces its constructors with a function. For example it takes a list (1:2):3, and replaces the constructor : with the function `+`, to get (1+2)+3 = 6
Bend starts with a seed value and a function taking values into constructor expressions for a conductive data type. It then grows the seed into a potentially infinite AST. For example the seed value 1 and the function f(x:xs) = (x+1) : (x:xs) gives us the infinite lazy list [1, 2, 3, ...]