Ask HN: AI is going to be big. How should we learn?

#1

Post by truebosko » Mon, Feb 22, 2016, 2:18 AM UTC

It's no doubt that understanding AI and the associated knowledge around it is going to be critical for many software developers to thrive in the next 1-2 decades.

What do you think are the ideal resources to learn today, as a beginner, and how to continue to grow that knowledge?

Re: Ask HN: AI is going to be big. How should we learn?

#2

Post by exolymph » Mon, Feb 22, 2016, 2:20 AM UTC

Some potentially helpful Quora answers: https://www.quora.com/What-is-the-best-way-to-learn-Artifici...

"An Introduction to Behaviour Trees": http://obviam.net/index.php/game-ai-an-introduction-to-behav...

Re: Ask HN: AI is going to be big. How should we learn?

#3

Post by exolymph » Mon, Feb 22, 2016, 2:21 AM UTC

exolymph wrote: post #2

Some potentially helpful Quora answers: https://www.quora.com/What-is-the-best-way-to-learn-Artifici... "An Introduction to Behaviour Trees": http://obviam.net/index.php/game-ai-an-introduction-to-behav...

I don't have any technical knowledge about AI specifically, but my general approach to research is to Google the key term, e.g. "AI for beginners" or "machine learning for beginners", read ~everything that comes up, and go from there. This is a good way to get the necessary base vocabulary in place for deeper searches.

Re: Ask HN: AI is going to be big. How should we learn?

#4

Post by abcampbell » Mon, Feb 22, 2016, 3:10 AM UTC

Well, first, I would try to understand what "AI" you are talking about and why you have so much confidence it will be big.

It's a pretty broad category, and a lot of it is (still) very far from commercialization.

It's almost like asking about "the Internet" in 1992.

Here are some categories that may help to dive into...

-Computer Vision

-Natural Language Processing

AClustering vs classification in machine learning

-Neural nets (convolutional, recursive, hyerparameters and optimizTion techniques)

Read "how to create a Mind" by kurtzweil

Related (but distinct topics)

-Understand rise (and fall) of semantic web

-Open/Linked data

-Relational vs NoSql databases

-distributed/parallel processing (MapReduce ->hadoop-> spark)

*edit - typo

Re: Ask HN: AI is going to be big. How should we learn?

#5

Post by ankurdhama » Mon, Feb 22, 2016, 4:38 AM UTC

The way to start is go to wikipedia and learn and understand all the algorithms that have been developed over the years in this field. You can get a list of all such algorithms on wikipedia. For each algorithm try some examples and see for what kind of problems they work and for what they don't and if possible try to think about why that is so. The goal of AI is to design "general purpose algorithms" that could be applicable to wide variety of tasks.

The other side of AI where people talk about AGI and ASI is nothing but intellectual masturbation at this point.

Re: Ask HN: AI is going to be big. How should we learn?

#6

Post by haxpor » Mon, Feb 22, 2016, 4:51 AM UTC

I would go for "Programming Game AI by example" by Matt Buckland. Also great resource is aigamedev.com.

Re: Ask HN: AI is going to be big. How should we learn?

#7

Post by CuriouslyC » Mon, Feb 22, 2016, 4:51 AM UTC

In terms of gaining a solid understanding of the math and theory underlying most of modern machine learning/AI, the best resource is definitely the book "Information theory, inference and learning algorithms" by David MacKay.

The author is such a stand-up guy, he's made it available for free: http://www.inference.phy.cam.ac.uk/itprnn/book.pdf

Re: Ask HN: AI is going to be big. How should we learn?

#8

Post by tim333 » Mon, Feb 22, 2016, 5:01 AM UTC

From a personal point of view as someone also interested in learning a bit I think building something is often a good way to go. I kind of have a plan one day to hack together the neural network from

http://karpathy.github.io/2015/05/21/rnn-effectiveness/

with some personally selected stock market data to see if it can kick out profitable buy/sells.

(There is some how to stuff in the article under 'Source Code')

Re: Ask HN: AI is going to be big. How should we learn?

#9

Post by matheweis » Mon, Feb 22, 2016, 5:23 AM UTC

tim333 wrote: post #8

From a personal point of view as someone also interested in learning a bit I think building something is often a good way to go. I kind of have a plan one day to hack together the neural network from http://karpathy.github.io/2015/05/21/rnn-effectiveness/ with some personally selected stock market data to see if it can kick out profitable buy/sells. (There is some how to stuff in the article under 'Source Code')

A "good" AI stock trader would in particular require some kind of real-world pseudo real-time data feed (pick your poison; Twitter, FB, news, even generic web crawling)

Anything based purely on the stock charts themselves becomes simply a sophisticated pattern matcher and can't possibly respond to the actual drivers of price movement.

Re: Ask HN: AI is going to be big. How should we learn?

#10

Post by p1esk » Mon, Feb 22, 2016, 5:23 AM UTC

Learn math. To do any serious work in machine learning, you need to have a solid understanding of calculus, linear algebra, and probability theory.

Note that AI is bigger than machine learning, and there's a chance that the future AI will be heavily modeled after a human brain. So it might be a good idea to take a couple of foundational courses in neuroscience.