[manually]

In the days when Sussman was a novice, Minsky once came to him as he sat hacking at the PDP-6.

“What are you doing?”, asked Minsky.

“I am training a randomly wired neural net to play Tic-Tac-Toe” Sussman replied.

“Why is the net wired randomly?”, asked Minsky.

“I do not want it to have any preconceptions of how to play”, Sussman said.

Minsky then shut his eyes.

“Why do you close your eyes?”, Sussman asked his teacher.

“So that the room will be empty.”

At that moment, Sussman was enlightened.

[manthideaal]

With all due respect to Minsky, I find this zen style story a little silly. If Minsky want to say something informative why don't he use formal concepts like Jeffreys priors, mixing time, high dimensional varieties, minimun description length, entropy, etc. Is that style of telling stories a projection from a high dimensional mind to a zero dimensional dumb style space?, is that a PCA reduction from ideas to cliches? I apologize in advance from being harsh, but I am entitle to speak from my heart and I reiterate my appreciation for Minsky's work.

It should be nice using a more informative language for giving advice. If this story is tagged as "popular story for dummies" I would feel we are making real progress.

Just one of Minsky great ideas related to reinforcement learning: The credit assignment problem:How do you distribute credit for success among the many decisions that may have been involved in producing it?, in "Steps Toward Artificial Intelligence" (Minsky, 1961): All of the methods we discuss in this book are, in a sense, directed toward solving this problem.

That book is linked from HN and it has just one comment, so I think that NDNS, no dumb nerd stories, will never become popular.

(1) https://news.ycombinator.com/item?id=10972522

More from (2) Minsky in 1951 built the world's first “randomly wired neural network learning machine,” called the stochastic neural-analog reinforcement computer (snarc)

https://www.geek.com/blurb/marvin-minsky-ai-has-been-brain-d...

A fair paper: Exploring Randomly Wired Neural Network for Image Recognition.

Was Sussan at the edge of envisioning deep learning?, then in fact the room has dissapeared!

[westurner]

Is this an argument in favor of unjustified magic constant arbitrary priors?

[perl4ever]

A sufficiently large amount of random data contains all the magic constants you could want.

[westurner]

Yeah, but cryptographic hashes have some entropy.

[Icathian]

I miss the codeless code. Wish someone would take up that mantle.