
A profile of Geoffrey Hinton (2018) - tosh
https://torontolife.com/tech/ai-superstars-google-facebook-apple-studied-guy/
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strin
> Hinton has said that when he was growing up, his mother gave him two
> choices: “Be an academic or be a failure.” His family tree is branch-
> breakingly weighted with scientists. His great-great-grandfather was George
> Boole, founder of Boolean logic, familiar to anyone who has done a “Boolean
> search.” One of George Boole’s sons-in-law was Charles Howard Hinton,
> Geoffrey’s great-grandfather, a mathematician and sci-fi writer who coined
> the concept of a “tesseract” (a four-dimensional object we can see in the
> 3-D world as a cube—well known to all readers of the classic children’s
> novel A Wrinkle in Time), and who ended up in the U.S.

Interesting fact from reading this that normally gets neglected in media.

~~~
opportune
It's actually quite common.

One of the most tried and true routes to getting into the best academia-
oriented colleges (Harvard, MIT, Caltech, etc.) is to win one of the big
science fairs. I am not sure what they are called or who their sponsors are
these days, but they used be sponsored by Westinghouse, Intel, and Siemens.
Anyway, if you look at bios of winners or semifinalists, they almost always
have a close relative in academia. Which in these competitions is actually a
massive competitive advantage since your relative can get you into labs,
access to equipment, and push you towards fruitful projects they quietly are
guiding from the background.

Same with a lot of the international olympiads, very often the kids come from
intense tiger parent families that are already in academia or do everything
they can to get their kids the best physics/math/whatever tutors (the main
exceptions to this are usually kids in large metro areas going to top magnet
schools).

And then of course once you're in these top academic institutes, your
relatives can further help you network and get into the best labs, show you
how to get the best fellowships and academic internships to set you up for top
grad schools, etc. Plus now that you have a top olympiad/science fair your
credentials will give you a big plus in competing against others without them

~~~
Bostonian
I agree that academics at research universities can provide more opportunities
for their children, but they are also bequeathing genes for higher IQ to their
children, and I'd guess that the genetic influence is at least as strong as
the environmental one. Adoption studies have generally found that the academic
achievement of adoptees is more correlated to the educational level of their
biological than their adoptive parents.

~~~
opportune
That's true, however here I am speaking about the highest level of competition
for the best path into academia (one of the most competitive careers in the
world). Large IQ studies aren't as relevant since the population of people
seriously considering academia who have the ability to act on that is skewed
to the relatively far right side of the distribution

I ran into so many roadblocks when I started seriously looking into going into
academia when I was 16-17; if you don't have top science fairs or olympiads
your chances of getting into top academic undergrads are already at risk,
which has negative compounding effects down the line compared to the positive
compounding effects of those that do get these, especially if you are a white
or asian male. Close relatives of academics and people going to top magnet
schools in major metro areas have huge headstarts compared to everyone else.
Having a good IQ is just one of many requisites into going into academia,
accomplishment-oriented credentials are much more valuable in your early
career than things like regular standardized test scores

~~~
mattkrause
The bit about the competitions specifically doesn’t ring true for me.

Many friends from grad school have tenure-track jobs. None of them, as far as
I know, participated in these contests. I would bet that things effectively
reset once you start grad school and again once you’re in a faculty job.

It is true that academic recognition tends to snowball. Winning your nth grant
or fellowship is exponentially easier than the first one “because you have a
track record.”

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jefft255
I don’t like how they oppose deep learning with « logic based AI ». When
Hinton got great results, he wasn’t competing against logic based AI but
rather other machine learning approaches like SVMs.

~~~
buboard
I dont think he was competing. ANNs and boltzmann machines in the 80s seemed
was an exploratory field not really part of statistical ML. At the time people
were indeed competing with logic-based AI. SVMs came later and even then i
believe, NNs had a different history and were not motivated from competition
to SOTA techniques like SVMs. When the success of trainig came after the
mid-2000s that's when ANNs started being called "ML". At least that's my
memory

~~~
kiterunner2346
Indeed, he wasn't competing. In fact, he wasn't moving; he kept doing what he
had always been doing until, luckily, something, that he had nothing to do
with, changed and allowed NN methods to work better. So I view him as
essentially standing still, frozen in time, like a clock stuck at 6 o'clock.
And, just like that clock, he would inevitably be correct (at least twice a
day). He had nothing to do with the tools (higher memory & CPU speeds) that
made his methods work, he just kept doing the same thing over and over until,
one day, by accident, something important changed: his lab bought newer,
faster computers.

He's not exactly Louis Pasteur is what I'm saying!

~~~
jbay808
We call this "skating to where the puck is going to be".

~~~
kiterunner2346
I call it "doing the same thing over and over again, hoping someday you get
lucky." I think there's a commonly-used expression for that behavior.

Hinton got lucky: something he had nothing to do with changed, making him look
like a stoic hero.

A winning strategy or just a lazy path?

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toxik
I always find it so difficult to read popsci biographies of my own expert
subjects. Hinton did not invent neural networks. Hinton is an amazing
researcher and scholar to be sure, but this is clearly hyperbole.

Edit: I turns out I misread the article, it merely suggests his chosen
approach was neural networks, rather than that neural networks are his idea. I
think honestly it’s written ambiguously by intent.

~~~
52-6F-62
> _In the late ’50s, a Cornell scientist named Frank Rosenblatt had proposed
> the world’s first neural network machine. It was called the Perceptron, and
> it had a simple objective—to recognize images._

This is right in the article. They don't attribute neural networks to
Hinton—they just note that he worked with them.

~~~
TheGrassyKnoll
[https://en.wikipedia.org/wiki/Perceptron](https://en.wikipedia.org/wiki/Perceptron)

