
 Climbing the wrong hill - prakash
http://www.cdixon.org/?p=989
======
thaumaturgy
That's a terrible analogy. Good analogies should provide an honest insight
into a complex situation using a simple imaginary construction. In this case,
there's no reason to assume that anyone's objection to founding a startup has
anything to do with short-term versus long-term goals, and even if there was,
the analogy of the "hill problem" doesn't address that objection at all.

I think it's much more reasonable to guess that this guy's reluctance to do
the startup dance is the result of more complex considerations. His current
job is safe; not glamorous, sure, but safe. He's probably making good money,
and even if he doesn't really enjoy it, he's just found out that other people
actually _want_ him. That can be a powerful motivator by itself.

The startup thing is risky. Talking about it is all well and good, and we can
make startups sound really sexy because they're what _we_ prefer or need to
do, but that doesn't mean that they're really for everyone. People might like
the idea of startups, but when it comes to the actual risk, guesswork, and
extreme hard work associated with them -- not so much.

I mean, hell, I'm working on my second one now, and I couldn't imagine working
for anyone else ever again (or sitting in a cubicle). On the other hand, there
are definitely days that I would love to not have to worry about whether or
not I'll find enough business to pay the rent a couple of months from now. I
haven't had a real get-away vacation in I-don't-know-how-long, and my average
work day is probably around 11 hours long. I honestly don't know how my
girlfriend puts up with it. And, I'm constantly thinking about one business or
the other; it's not like I can just "punch out" at 5 or 6 o'clock each day and
not think about work until the next morning.

So, yeah. Startups aren't all roses, and maybe some people are smart enough to
figure that out _before_ they jump into them.

~~~
ericwaller
I agree that the connection to startup v. career just isn't there, but I
really like the analogy insofar as it concludes that it's worthwhile to
"meander some in your walk (especially early on)," and "randomly drop yourself
into new parts of the terrain."

~~~
billswift
That randomly drop, fits pretty well with some old advice to occasionally try
something REALLY different, if only as a hobby or on a vacation, to help keep
yourself flexible.

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mitko
So is he proposing simulated annealing for finding the best occupation in
one's life ? <http://en.wikipedia.org/wiki/Simulated_annealing>

A person looking for for purpose in life might have much more limitations than
a hill climbing algorithm. He/she also has different advantages than such
algorithm, so I do not think this is very good analogy.

~~~
euccastro
One crucial advantage is that we have the examples of others to follow or
avoid. In this respect, particle swarm optimization (as referred to in another
comment in this post [1]) may be a better model.

[1] <http://news.ycombinator.com/item?id=832163>

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chaosmachine
Reminds me of this:
[http://sethgodin.typepad.com/seths_blog/2005/11/understandin...](http://sethgodin.typepad.com/seths_blog/2005/11/understanding_l.html)

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RiderOfGiraffes
This reminds me, I have written a fairly good, fairly generic hill-climbing
"library" for Python. I did it because I needed something specific quickly,
and it's gradually grown over time. I haven't found anything generally
available that does the same thing, and I was wondering if anyone here can
suggest some existing libraries/modules that I can compare/contrast with
before thinking about tidying up and releasing.

Suggestions?

~~~
conesus
Yes, I can certainly point you in the right direction.

Toby Segaran, author of the highly esteemed and good-read Programming
Collective Intelligence (published by O'Reilly, so you know it's good),
released all of the source code that he talked about in the book. You can find
it all here on his blog: <http://blog.kiwitobes.com/?p=44>.

He talks about hill climbing and variants (random restart, simulated
annealing). He does a great job of explaining the algorithm and the math
behind the hill climbing decisions. For optimization, something hill climbing
is not even the best tool. Look at some of the other optimization strategies
he employs (specifically the genetic mutation algorithm).

I highly recommend buying the book, even if only one chapter currently
interests you. I bet you the other chapters will too. It's on Amazon, and at
B&N if you want it this second.

~~~
RiderOfGiraffes
Brilliant - thanks - I'll check that out.

I do know that hill-climbing isn't always the best strategy - I've got
experience. What I'm lacking is knowledge of people from other disciplines
doing things in an organised and more complete manner. This is a good start.

I've also found AIMA stuff on Google - <http://code.google.com/p/aima-python/>
\- which claimsto be a Python implementation of algorithms from Russell and
Norvig's 'Artificial Intelligence: A Modern Approach'

~~~
euccastro
I haven't done much of a survey, but I stumbled into this and looks promising:

<http://en.wikipedia.org/wiki/Particle_swarm_optimization>

I found this book a very enjoyable read (edit: and a lot less intimidating
than the Wikipedia article!). Be warned, though, that it's one or two chapters
worth of technical detail. The rest goes to motivating the subject and
exploring its philosophical implications. And that is OK, because the
algorithm is actually quite simple.

<http://tinyurl.com/lns85a>

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nico
I liked the 'The Dip' explanation way better: there are some things that are
worth doing and others that are not. Most people do a lot of worthless stuff
just because doing the worthy stuff is harder, even though it might yield a
higher return in the long run.

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jodrellblank
* Imagine you are dropped at a random spot on a hilly terrain, where you can only see a few feet in each direction (assume it’s foggy or something). The goal is to get to the highest hill.*

Who climbs a hill they don't know in the fog, starting already lost and
without navigation kit? Silly computer scientists.

~~~
derefr
I assume the "you are dropped" part is involuntary. The hill-climbing part
just makes sense, so you can get high enough to see where the heck you are.

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ojbyrne
This might actually be a viable analogy if the hills were "fuzzy" - i.e.
changed in height and location over time. Because careers are like that -
often the highest hills get worn down, or moved to other countries.

