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melipone

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"Machine learning explained to my girlfriend" is a show stopper. How can we have this kind of sexist attitude in 2016?

I will denounce all such posts. This is not PC, it's stopping bigotry wherever it lives.

What I got was that the rapid emergence of biological feedback was essential for regularizing climate which in turn enabled life on earth to evolve. In a way, life itself enabled life on earth. It's the rarity of this emergence that is important rather than the rarity of intelligent life. Another thing I got is that life itself will destroy life the way climate change is going :-)

Lisp has been around a while. Java has been around a while. Clojure is the perfect combination and I predict it will be around a while. It's exhilarating to program in Clojure. That's the only word I can find to describe what I feel to program in that language.

I like that the article mentioned the difference between privacy and secrecy. I've been struggling with that for a while. What is private is secret but what is secret (a secret recipe, for example) is not necessarily private. But in some cases, a secret can be considered private (a secret love affair, for example). I'm confused...

IMHO, it's not which accents are strong enough. It's the baggage that an accent brings. Yes, people pattern match an accent but not just the words. For example, the content of what a woman with a strong French accent says will be diluted with thoughts of sexiness instead of being taken seriously (except Christine Lagarde :-)). In this sense, the validity of PG's claim is not cut and dry. There are other factors.

Lisp is "cognitively" different from, say, c, Java, and python. It's like learning a new language. How long will it take you to be fluent in Arabic? It takes 5 years. But the best part is that after 5 years, you won't forget it.

I've managed to work for 10 years in Lisp. Then, I had to work in Java. After another 10 years of Java, I took up Clojure very easily.

How will this help "paving the way for Artificial intelligence"? We already have neural networks as a computational metaphor for the brain. I doubt we will find new metaphors. I doubt we will learn new computational tricks. Please enlight me on this issue.