
Neural network AI is simple. So… Stop pretending you are a genius - NicoJuicy
https://www.kdnuggets.com/2018/02/neural-network-ai-simple-genius.html
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singhrac
This is a pretty stupid article. No one is pretending that they're a genius,
but this guy is just full of inaccuracies. Let me break it down to save other
people time and energy (I have a little to spare):

1\. "but that complexity comes from repetition and a random number generator"
\- Most of the complexity comes from trying to solve non-convex optimization
problems via SGD. "Repetition" doesn't make sense unless you're talking about
vectorization (you're not), and an rng has little relevance.

2\. "Congrats! You took the above code, and looped the loop again." \- sure,
if that were true then people would have trained deep neural networks in the
90s. Instead we needed researchers (see? geniuses) to invent batch
normalization, highway networks, CNNs, dropout, etc. Also, that's not an
"recursive neural network", that's a recurrent one.

3\. "So you trained a neural network using Nvidia GPUs and moved it to the
phone…" \- this entire section makes so little sense I don't know where to
start. Neural networks are, for the most part, robust to small rng differences
- that's why they have surprising generalizability. I have no idea what this
guy is trying to say about phones and GPUs though.

4\. "What it does well is help you visualize what is happening in those 11
lines" \- well, that's not the point, but I'm starting to understand that this
guy doesn't get it.

5\. "Building a neural network with 1 trait for every word in the English
language would require a network that used as much computing power as all of
Google." \- I'm just going to let that one sit there.

...

"There is neural network code in my tool box."; sure, you sound like you've
imported Tensorflow before (possibly?). But maybe before dismissing an entire
field you should figure out how any of it works.

~~~
wjnc
Agree. Statistics is pretty basic at it's linear algebra core as well. Add
some optimization. You can study most of the theory in a year or two.

It's mastery and smart application that makes all the difference.

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jackconnor
This is a terrible article. He makes a total straw man out of neural networks
by pulling code from an "Intro to Neural Networks in Python" tutorial and
saying "What's so hard about this?" He also doesn't explain it correctly, not
even close. Maybe he should actually do the tutorial.

What's the point of this? That he's as smart as people who build AI? This
person, Brandon Wirtz, needs to work on his self-confidence, not just
intelligence.

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mining
Almost all of that blog post was complete bullshit. Recursive neural net? I
don't understand why that post was written.

~~~
NervousTechno
You can find the difference between recurrent and recursive neural nets on
wikipedia. No need to edit your post then flag someone when they point out how
lazy you are in understanding a simple rant post, pointing out how lazy people
are in understanding the "AI" fads.

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julvo
I assume this article is directed towards people new to neural nets who think
they mastered AI. However, in neural network research noone cares about of the
things the author is making fun of. These are examples from tutorials
beginners learn in the first week, not what experts are remotely concerned
with.

~~~
opless
Agree. I think there's some (a lot?) of context about /why/ the article was
written. It sounds like some[one|thing] has wound the author up.

Also it's a post from another blog... I'd wander over there and try to figure
it out, but lunch beckons...

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zamalek
Anyone who is learning something new is a genius in my opinion - especially if
they are excited about it and want to share their results so that others can
learn.

This is just condescending vitriol.

