AI is only in fashion for technology once it isn't bleeding edge. Also, MuZero (the latest in similar game engines that were started from AlphaGo) can learn the game by itself without knowing the rules or having any opening books or Go data which is very different than how traditional Chess engines operate.

> can learn the game by itself without knowing the rules

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.

http://www.catb.org/jargon/html/koans.html

This "Zero-knowledge" style program, be it AlphaZero or MuZero and whatever, is a bad meme.

Adding in little bits of knowledge, such as liberties counting, ladder-reading, and other tricks, allows KataGo to absolutely crush LeelaZero in training speed and practical play in the game of Go. Its no comparison.

These days, no one studying the game of Go is seriously using LeelaZero anymore. Its an obsolete methodology compared to KataGo.

A more familiar example might be fuzz testing. You could fuzz a program by just passing the fuzzer totally random data to mutate, and it's true that this might find a crash that wouldn't be found any other way. However, most of the time you will have much better results, and achieve them much more quickly, if you pass the fuzzer something that looks like an actual expected input to the program.

Zero-knowledge ML is still interesting if your goal is to indisputably demonstrate the act of learning, just not if your goal is to make the smartest program in the least time.

Also, https://en.wikipedia.org/wiki/TD-Gammon

> TD-Gammon is a computer backgammon program developed in 1992 by Gerald Tesauro ... It explored strategies that humans had not pursued and led to advances in the theory of correct backgammon play...

> For example, on the opening play, the conventional wisdom was that given a roll of 2-1, 4-1, or 5-1, White should move a single checker from point 6 to point 5. Known as "slotting", this technique trades the risk of a hit for the opportunity to develop an aggressive position. TD-Gammon found that the more conservative play of 24-23 was superior. Tournament players began experimenting with TD-Gammon's move, and found success. Within a few years, slotting had disappeared from tournament play

I had an AI professor that described artificial intelligence as an agent that operates independently in some environment and reasons probabilistically / mathematically to determine actions, so I made a trading bot that used some simple time series techniques to dictate decision making. She ended up telling me that it wasn't an AI because the algorithms wasn't complex enough. OK... well, then why didn't you just say an AI is really just defined by whether or not the 'agent' is using the newest, shiniest algorithms? I was a little salty about that one lol

> I made a trading bot that used some simple time series techniques to dictate decision making

They were quite right. In no sense is what you are doing AI. People have been using time series techniques to analyze and attempt to predict data since before the computer.

Alright, so when does an algorithm become AI then?