When we’re children, all the books we read are handed down to us, like the Ten Commandments, by grownups, who seem like, and sort of are, a different order of being from ourselves. They’re the gods of childhood, bigger and older and more experienced; they know more than we do, imparting what wisdom to us they think we can bear, empowered to tell us what to do. I’m over 40 now, no longer by even the most charitable definition a young adult, and I’m starting to realize, in something like panic, that I don’t understand anything, and that nobody else seems to know any more about it than I do. There aren’t any grownups.
I would amend this to say there are a few grownups, and that the next step after noticing one’s ignorance should be to extinguish it if possible.
Another snippet:
Books that unabashedly purport to supply all the answers sell like Hula-Hoops or Viagra. This genre is called “wisdom literature” if it’s old enough to be respectable or “self-help” if it’s by someone who’s still alive and making money off it, and ranges in credibility and earnestness of intention from the Tao te Ching and Aurelius’ Meditations to shameless dogshit like The Secret.
Our views about predictability are inherently flawed. Take something that is often seen as the epitome of randomness, like a coin toss. While it may at first appear that there’s no way to tell whether a coin is going to come up heads or tails, a group of mathematicians at Stanford is able to predict the outcome virtually 100 percent of the time, provided that they use a special machine to flip it. The machine does not cheat — it flips the coin the exact same way (the same height, with the same strength and torque) over and over again — and the coin is fair. Under those conditions, there is no randomness at all.
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For centuries, meteorologists relied on statistical tables based on historical averages — it rains about 45 percent of the time in London in March, for instance — to predict the weather. But these statistics are useless on a day-to-day level. Jan. 12, 1888, was a relatively warm day on the Great Plains until the temperature dropped almost 30 degrees in a matter of hours and a blinding snowstorm hit. More than a hundred children died of hypothermia on their way home from school that day. Knowing the average temperature for a January day in Topeka wouldn’t have helped much in a case like that.
The Human Brain Project sells itself as aiming to “simulate a complete human brain in a supercomputer” but this is clearly bollocks. [,..]
It’s interesting that this claim makes the press kit and the flashy video but the actual report (pdf) has much more sober claims about ‘simulating brain dynamics’ and the like.
But it’s important to realise that while their big sell is nonsense, the project is likely to genuinely revolutionise neuroscience in a way that could push the field light years ahead.
What Markram has realised is that the single biggest barrier to progress in neuroscience is the co-ordination, sharing and integration of data.
Essentially, it’s a problem of information architecture but quite frankly, you can’t sell that to politicians and they can’t sell it to the public. Hence the ‘simulating a complete human brain’ fluff.
Short Online Texts Thread
For 40 Years, This Russian Family Was Cut Off From All Human Contact, Unaware of WWII
When Books Could Change Your Life.
Here’s a snippet:
I would amend this to say there are a few grownups, and that the next step after noticing one’s ignorance should be to extinguish it if possible.
Another snippet:
If Free Will Doesn’t Exist, Neither Does Water
How Much Tech Can One City Take?
The Weatherman is Not a Moron.
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Snippet 2:
What will the billion dollar brain projects do?
Excerpt:
Posner, Thinking about Catastrophe.
Dave Hitt, Name Three (h/t Qiaochu).
Some Alternatives to Bayes’ Rule.
Communication and Deception in 2-Player Games.
A General Theory of Scientific/Intellectual Movements.
Montibeller & Durbach, Behavioral Analytics: A Framework for Exploring Judgments and Choices in Large Data Sets.