itrackmine's comments

itrackmine | 14 years ago | on: Why must you laugh at my back end?

Just wanted to add: this is all imo. :)

itrackmine | 14 years ago | on: Why must you laugh at my back end?

nhashem, wow you really hit the nail on the head. So accurate it's scary. I too, thought I was the only one who put DOING before "ramping up and learning some stuff so that I can maybe do some things a few weeks from now." And of course Pud for the courage to be honest about how he's working.

So many times in startups and new endeavors, getting things out is far more important than doing it "right". It's stinky, but it's a reality. If your checkbook, bills and time say one thing but your code says another, your checkbook/bills/time win - always. And the person who can pump out more working (working, not necessarily pretty/proper code-wise or stack-wise) apps wins (even if they lose, they win, based on odds - more attempts means more possible chances at winning).

itrackmine | 14 years ago | on: Things I’ve never heard a successful startup founder say

This made me lol while taking a swig of my lemonade...point for you ;p "I'm so glad I spent so much time on Hacker News."

...ok, not a constructive reply other than: laughter generates beneficial chemicals in the brain and it's good to be good to others...thanks! carry on. :)

itrackmine | 14 years ago | on: "When you're done talking, stop"

imo this is key: "Basically we were told, when you're done talking, stop, and don't let that pause goad you into say something stupid." And, unfortunately, something I'm still working on.

itrackmine | 14 years ago | on: Higgs boson 'hints' also seen by US lab

If anyone is interested, this is a great book for the hobbyist curious about this sort of thing: "The Fabric of the Cosmos: Space, Time, and the Texture of Reality" by Brian Greene

itrackmine | 14 years ago | on: Machine Learning Fairy Dust

Yea, that's going to continue to be the case until someone (cough us, cough) figures out that what you look at or buy on one occasion might not actually be something you're interested in. Specifically speaking of //items//, this is really a huge issue that is so huge that it's almost become laughable in the sense that nearly all the recommendations via "machine learning" (Collaborative Filtering, Trust Systems, etc) nowadays end up being so tainted that they are worthless - to you, and to the companies spitting them out. I call it "Recommendation Blindness" (copyright 2008...20% on usage...etc...etc..sue you..etc.....I'm just kidding of course).