reckoner2

I think the quote does a great job at explaining why a lot of people have been critical of labeling the recent breakthroughs in Machine learning as real intelligence. Most people define intelligence in comparison to humans. Things like being the best GO player in the world are so specialized that they don't seem very human at all.

Most people will not be impressed by a machine that can master backgammon, chess and poker, despite it being a great technical feat. They would be impressed by one that can successfully teach a 5th grade math class, even though there are hundreds of thousands of people who can do this.

This would require more than teaching the kids math, but also how to deal with the kid who loses a parent during the school year. How to deal with bullying in the class, with misbehaving students. None of it is "specialized knowledge" like playing GO. And we are nowhere even remotely close to this.

When building an automated trading system the first thing you write should be the risk system. Simply having a 'MaxExposure' per exchange doesn't cut it.

This has nothing to do with it being a market-neutral strategy or not. All code has bugs in it, exchanges have hiccups, quotes from many exchanges are notoriously wonky, programs freeze, Internet connections go down, users fat finger inputs etc. This needs a real risk system built into it.

Yet there are few people alive more qualified to comment on this type of work than Scott Aaronson. Plus, most of his criticism is only directed towards the misleading marketing, journalism, and presentations about D-Wave projects.

I've been really enjoying http://course.fast.ai/

Within a few hours of starting the course you'll have submitted an entry into the Kaggle Dogs vs Cats competition that scores in the top 50% of entries and achieves 97% accuracy. It's designed for coders who don't have a PHD in math. It's a very top-down approach, where you only get into mathematical details once you understand the high level models being used.

First, I did a few random 'guided meditations' off youtube (Sam Harris has a popular one) and discovered that I enjoyed it.

After that, I've been enjoying The Mind Illuminated, by John Yates, and I think others on hackernews will as well. It doesn't bother with a lot of the eastern spirituality aspects, but instead focuses on how to become good at meditating and find the most benefits from it.

Sailing: You don't need a boat. Most cities near the water will have some sort of sailing club where for $300 a year you can join and use their fleet of boats. My end goal is to do some sort of week long solo trip.

Rock Climbing: Lots of fun and a great work out.

Meditation: Just getting started with this, but have already seen improvements in concentration and a decrease in anxiety.

Introductory Deep Learning: http://course.fast.ai/ This is probably my favorite course I've ever taken online.

This would be my recommendation as well. It is closer to a textbook, than say a popular science book, but is still a very fun, engaging, and at times pretty funny read.

Similarly to books like GEB, it really exposed me to a whole range of fascinating ideas and topics that I am now interested in.

Just a head's up: for someone well versed in computer science the first two thirds of this book can be pretty dull. The majority of the time is spent explaining first year CS topics in layman's terms. After that it picked up a bit with, for example, showing how randomized algorithms can apply to types of decision making in real life.

I still think it is better suited for those with little to no CS knowledge.