chitchcock

Stevey's Google Platforms Rant

I was at Amazon for about six and a half years, and now I've been at Google for that long. One thing that struck me immediately about the two companies -- an impression that has been reinforced almost daily -- is that Amazon does everything wrong, and Google does everything right. Sure, it's a sweeping generalization, but a surprisingly accurate one. It's pretty crazy. There are probably a hundred or even two hundred different ways you can compare the two companies, and Google is superior in all but three of them, if I recall correctly. I actually did a spreadsheet at one point but Legal wouldn't let me show it to anyone, even though recruiting loved it.

I mean, just to give you a very brief taste: Amazon's recruiting process is fundamentally flawed by having teams hire for themselves, so their hiring bar is incredibly inconsistent across teams, despite various efforts they've made to level it out. And their operations are a mess; they don't real

jpravetz

#------------------------------------------------------------------------
# encoding: utf-8
# @(#)product_generator.rb	1.00 29-Nov-2011 16:38
#
# Copyright (c) 2011 Jim Pravetz. All Rights Reserved.
# Licensed under the MIT license (http://www.opensource.org/licenses/mit-license.php)
#
# Description:  A generator that creates product, products and
#		ingredients pages for jekyll sites.  Uses a JSON data
#		file as the database file from which to read and

jboner

Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD

davetrux

adb shell setprop log.tag.SQLiteLog V
adb shell setprop log.tag.SQLiteStatements V
adb shell stop
adb shell start

richp10

// This systemd runs iptables-restore on boot:
[Unit]
Description=Packet Filtering Framework
DefaultDependencies=no
After=systemd-sysctl.service
Before=sysinit.target

[Service]
Type=oneshot
ExecStart=/usr/sbin/iptables-restore /opt/docker/scripts/iptables/iptables.rules

uzyexe

coreos:
  units:
    - name: newrelic.service
      command: start
      content: |
        [Unit]
        Description=newrelic
        Requires=docker.service
        After=docker.service
        

errordeveloper

#cloud-config
write_files:
  - path: /etc/weave.core-01.env
    permissions: 0644
    owner: root
    content: |
      WEAVE_LAUNCH_ARGS=""
      PINGER_LOCAL="10.0.1.1/24"
      PINGER_REMOTE="10.0.1.2"
      GREETER_ADDRESS="10.0.2.1/24"

tsertkov

#cloud-config

coreos:
  units:
    - name: systemd-sysctl.service
      command: restart
    - name: create-swap.service
      command: start
      runtime: true
      content: |

akarnokd

import java.util.*;
import java.util.concurrent.atomic.AtomicLong;

import rx.*;
import rx.Observable.OnSubscribe;
import rx.Observable;
import rx.exceptions.*;
import rx.internal.operators.*;
import rx.internal.util.RxRingBuffer;
import rx.internal.util.unsafe.MpscLinkedQueue;

honnibal

"""A stripped-down MLP example, using Theano.

Based on the tutorial here: http://deeplearning.net/tutorial/mlp.html

This example trims away some complexities, and makes it easier to see how Theano works.

Design changes:

* Model compiled in a distinct function, so that symbolic variables are not in run-time scope.
* No classes. Network shown by chained function calls.