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Computing Machinery and Intelligence

I was just reading Quantum Computing since Democrituscache (an excellent book!), when it referred me to Turing's Computing Machinery and Intelligencecache.

This argument is very, well expressed in Professor Jefferson's Lister Oration for 1949, from which I quote. "Not until a machine can write a sonnet or compose a concerto because of thoughts and emotions felt, and not by the chance fall of symbols, could we agree that machine equals brain-that is, not only write it but know that it had written it. No mechanism could feel (and not merely artificially signal, an easy contrivance) pleasure at its successes, grief when its valves fuse, be warmed by flattery, be made miserable by its mistakes, be charmed by sex, be angry or depressed when it cannot get what it wants." ...

It is impressive how even 65 years ago he already captured all the common arguments why computers ...


Iterative Deepening for Talks

When you give a talk, assume your audience knows nothing.

Start with a one minute summary, then go back to the beginning and give the 5 minute version of your talk. Showing an index slide for your talk does not count, those are a joke.

Only now can you give the full version of the talk since now the audience will have all relevant context in the L2 cache of their brain.


Surveillance against Social Change

From illegal to socially accepted:

  1. illegal and immoral
  2. still illegal, but more and more people start doing it
  3. start of decriminalization, grey area
  4. fully legal and accepted by society
  5. the obvious right thing to do

As exemplified by gay rights or marijuana legalization, at various stages of this process.

Broad government surveillance stifles this process by preventing the change from step 1 to 2 and thus hinders social progress.

Freely paraphrased after Bruce Schneier at Defcon 23. Wisdom is due to Bruce, mistakes are mine.


Working Out is like Investing

When investing, you are rewarded for taking risk by an increased rate of return.
When working out, you are rewarded for pushing to your limits and enduring the pain by increased muscle growth and strength.

Only risk that can't be diversified away results in a higher return.
Only pain that can't be avoided by warming up and stretching results in muscle growth.

Invest smart, diversify into low-fee index trackers.
Train smart, warm up and stretch after you are done.


Essential Running Stretches

  • Heel dip. Stand on a curb or a step with the tip of your feet, lower your heel as far as you can, hold for a few seconds, return to upright.

  • Touch your toes. Stand with legs straight, bend down as far as you can and try to touch your toes (or the floor).

  • 正座 (seiza). Kneel on the floor, then sit backwards onto your legs.

  • Leg pull. Alternative for above if the ground is rough. Stand on one leg, pull the back of the other to your bum and hold. Alternate legs.


Adventures in Reinforcement Learning

You may or may not have noticed that I've been working for DeepMind for a while, causing me to get exposed to lots and lots of cutting edge machine learning research. Most of that I can't share here, but there's plenty that's already public.

Reinforcement Learning

Firstly, yes, that's what all the fuzz is about. There's a great book by Sutton and Barto, Reinforcement Learning: An Introductioncache, with an in-progress version of the second edition available for free from their website!

The book is very good at introducing and explaining RL itself, but does not cover how to combine it with function approximation (neural networks). The basic idea is very simple - just implement the action value function with a neural network - but doing it in practice is trickier.

If you want some very basic examples on how to implement such an agent, you ...


Brains, Sex, and Machine Learning

A great explanation of why Dropout is really good for training large neural networks, and why it's actually the same thing your brain is doing:

Recent advances in machine learning cast new light on two puzzling biological phenomena. Neurons can use the precise time of a spike to communicate a real value very accurately, but it appears that cortical neurons do not do this. Instead they send single, randomly timed spikes. This seems like a clumsy way to perform signal processing, but a recent advance in machine learning shows that sending stochastic spikes actually works better than sending precise real numbers for the kind of signal processing that the brain needs to do. A closely related advance in machine learning provides strong support for a recently proposed theory of the function of sexual reproduction. Sexual reproduction breaks up large sets of co-adapted genes and this seems like a bad ...


Reading Drive: The Surprising Truth About What Motivates Us

After mentioning that I was reading Influence to my good friend Adriennecache, she recommended Drivecache as my next book. The theme is quickly explained: While there are three different ways to motivate us - biological urges like hunger or sex, external reward & punishment, and intrinsic reward from performing a task - only intrinsic reward can consistently foster creative behavior.

Pink starts out by showing how traditional external motivation - cash bonuses et al. - overly constrain our focus, interfere with creativity, extinguish internal rewards and even lead to unethical behavior (think doctoring sales numbers to meet a bonus target). Only in special circumstances can external motivation still be useful: If a task is routine and boring to begin with, then there's not much creativity to lose.

He then makes the case for why intrinsic motivation is better suited to our highly evolved and demanding work environments. Everyone who's ever been ...


Relevant Reading

How much of what you read today would you still want to read if it was a week from now? A year? A decade, a century?

Too much of the information hammering us is ephemeral infotainment, not enough brings lasting value.

The test I apply is simple: would I still want to read this if I had to wait a year, even if it was the only thing I could read that day?


Taking Notes

I always thought taking notes was a waste of time. Surely you could just look back at the slides if you forgot something?

But I realized I might have had it backwards all this time. What if you take notes not to have something to refer to, but because it forces you to listen with greater attention and strengthens your memory?

To really take notes you need to understand the subject well enough to pick out the key phrases and concepts in real time, all while the lecturer is speaking on and on. It's similar to how actually doing the exercises in your textbook will make you realize very quickly which parts you've understood, and which parts just sounded vaguely plausible.

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