Algorithms: Past interview algorithms - FANG

 1. 给一堆二维坐标，这些坐标点能组成一条线，求输出最少的点能还原这条线

2. 利口耳期酒，需要输出所有的完全平方数的数字，而不是多少个
3. 第一象限 给一堆点 让你找一个最小正方形能把包含的离原点最近的k个点，followup是找这样的长方形
4. excel类似的功能，需要支持set和get，
- set 就是给你一个col key和它的value, 它的value可以是一个int，也可以是一个reference，指向其他的column
- get 就是给你col key 需要你能resolve它的value

2. 二维空间，给一堆平行于坐标轴的长方形，如果两个长方形相交，就算是属于一个group，求问有几个group。做法就是Union Find，相交的长方形就union为一个group
3. 给一堆各种颜色的球以及个数，比如绿球200个，蓝球300个，红球500个，装在一个不透明的袋子里，让你写一个函数模拟从袋子里拿球再放回去的操作，函数返回拿到球的颜色
4. 酒似遛的变体，stack的模拟操作，这个stack push的rule是必须先放k, 才能放k+1，输入是0到n的permutation，代表pop出stack的顺序，问你给定的输入是否能实现
5. 设计，群聊，侧重点在于清楚的描述你设计的系统每个组建的功能，以及组建之间的通信，以及数据结构

 刷题网：意思琪琪

2. BQ:  team has different opions.  handle when one teammate leave during project.   handle un-resonable request/task from manager.

3.刷题网：其义务

4. most challenging proj.  刷题网：伊尔无九  

5. 2-d 01 矩阵 找最大陆地面积，0=水 1=地，陆地只能上下左右连接，斜着不算连接.
follow

第一轮：类似吾儿霸，就用了个壳，负载平衡follow up 1, 如果这里面的权重可以改, 怎么搞，要最好的complexity

follow up 2, 怎么测试，现实场景如何验证这个算法

第二轮： 有一数组都是一个个字符串，如果有一个字符串满足一个pattern，假设你有这个检查符合pattern的方法存在， 输出给定前后半径的所有字符串
follow up 1, 把数组换成数据流
应该有follow up2，没太记清楚，主要我也没有时间写了

面的l4, 狗屎运比较偏简单;
走过路过，求好心人施舍点大米😂
（没有设置限制，如果看不到可能是论坛默认。。试试手机版）

----
第1轮：李寇 意思二三； follow-up：还是取数组头和尾k次，新加入multiplier int[k], 每次也从multiplier 按序取出数相乘算结果，求max，例子：k=2, array [3,2,1,4], multiplier [1,2], 第一次取结果：4*1， 第二次取 3*2, 总共10；用的dfs + memorization

第2轮：最近常见的简单雇主树结构；给adjacent list (有向图)
问1： 什么情况下valid：graph 中只有一个disjoint set并且没有cycle， 不在意是否indegree>=2
问2: Valid 下求某个人的分数，即此subtree的count
问3: Validate given graph，用topology sort

1～4
- behavior 就是一般的题目，比如如何handle意见不同的情况。我是结合我实际情况回答的。总之一个原则：communication solves all the conflicts
- 三零一，还有一个ez的题目，具体我不太记得了。
- TicTacToc用android写的变种，我用了一些jetpack的东西，比如viewmodel和livedata
- android写service。算法997？还有一个现出的题目dp，这个我好像当时现场推出来，没见过原题。

5. 三叔，一个ez的题目，然后来了一个我没见过的题目。估计这轮弱。
如果有人知道请告诉下我。
大意是有1～n，可以组合成1,[1,2],[2,1],[1,2,3],[2,1,3],[3,2,1]...
如果把结果放在一个1d的array里，结果是什么？
我用了一个很naive的做法。但是貌似不符合要求。

第一轮利口846
第二轮利口1182 要求pre compute o（n），follow up二维color矩阵，要求pre compute o（mn），之后query o（k），k为query次数
第三轮bq
第四轮利口16

第一轮1240 given a rectangle x*y, minimum numbers of squares to fit in the rectangle第二轮 design a parking lot
第三轮 flip an array of 1, 0. minimum moves for flipping all. O(n)
第四轮 要斯而散 还有一个follow up，问增加一个array of K len, 每次选的数字要乘以对应的arrayK 里的数，求最大sum

第三轮：
给一个matrix，每个row只能选一个数，如果选第i行第j个元素，第i+1行第j+1的元素，那这两个元素之间有penalty： （j + 1 - j） = 1; 让求最后最大和是多少。思路： dp可以是O（mn^2）的m是行数，n是列数。大哥问能不能优化时间到O（mn），其实不太知道，大哥疯狂带着我做，最后一个for loop是O（n）可以用两个left[] 和 right[]预处理最大数。

给一个Oncall表 {张三：1 - 5， 李四： 5 - 7， 王五： 2 - 10} 这个格式是 “谁：什么时候”
              要求返回一个格式为“时间段：谁（们）”的表。比如上面的例子的return就是：
              1 - 2 张三
              2 - 5 张三 王五
              5 - 7 李四 王五
              7 - 10 王五
              return type没有规定，总之这个return能找某时间段有谁在Oncall

第三轮： 国人大哥。人很nice. 一直鼓励我，引导我。给两个string, 叫他们old和new吧，比较他们，已知old是通过改变了一个substring变成new的，分析出old是怎么变成new的。
              return三个东西，变化的种类（增加，减少，替换），变化的开始位置（some index in the old string）, 变化的部分是什么（从什么变成什么）

              例子1： old: "aaabb"    new: "aaaccbb"
                           old通过在index = 3 的位置增加了一个"cc"变成new
              例子2： old: "aaaccbb"   new: "aaaddbb"
                           old通过在index = 3的位置把"cc"替换为"dd"变成new
              例子3： old: "aaaccbb"   new: "aaac1234"
                           old通过在index = 4的位置把"cbb"替换为"1234"变成new
              需要自己去多问clarification questions。问的越多信息越多，比如讨论return type

题目内容：让我写一段代码来返回一个迷宫，没了。其他基本啥也没给，不是他不给信息，而是本身就不给什么限制，自由发挥。和面试官讨论能获得好的方向，比如，Input是什么, 迷宫要怎么表示，这个迷宫有几个解等等。
               input: 迷宫的宽，迷宫的高，起点，终点
               output: 一个设计好了的迷宫

酒肆刘 -- follow up, O(1) space

拔散散 -- 变体，如果给的index， source不match就throw，有overlap也throw。 因为都两个case都throw，我认为time complexity是O(S), visiting each char const time, 面试官似乎不太同意-- follow up， 把loop对换，用原string做main loop，two pointers搞定

只有一个根的DAG, 求最长路径长度
-- followup, 多个根
-- followup, 求最长路径

第一轮: 算法 给你一包色子, 每个色子只有两个面, 点数从1-6. 两个色子如果有一端的点数相等就可以连起来. 比如4-1 和6-1 可以连成6-1-1-4 (色子可以左右置换后连) 求给定的这包色子中 能连起来最长的色子数是多少

1. 世界杯淘汰赛阶段，每个球队夺冠的概率。
已知有个表格知道16强两两之间胜负的概率，以及一个16强对阵表。
求输入任意一个球队，返回这个球队最终夺冠概率。
2. 知道两条rule， #1 朋友的朋友是朋友， #2 敌人的敌人是朋友。
给你一串输入:  1 2 F, 2 3 F,  4 5  E,  5 6 E, 等等。。。  
前面两个数字表示两个人，第三个f, e 表示关系。
根据两条rule，构建出所有隐藏的关系。
3. 已知
    “key1” -> "3489"  
    "key2" -> " %key1% is awesome!"
    .....
   给任意一个statement = “ %key1% !!!!! %key2% !!!!!!”  把其中%% 里面的内容替换成value。 注意多层嵌套替换
4. 一个二叉树，把所有子节点的value挪到根节点需要多少move。  
move 的定义： 子节点的一个value，移动到上一层算一个move，再移动到上一层，又算一个move。
follow up， 如果要求每个子节点必须保留value=1，其余都move到根节点，需要多少move

Leetcode 1194 and 979

465. Optimal Account Balancing

Actionable Items

It is so much fun to go over those interview algorithms. I do learn a few good algorithms. I think that I should break into more blogs about those algorithms. I like to learn one by one. 

The Best Recruiter at Google | Talent Connect San Francisco 2014

 Here is the link. 

With more than 2 million applications a year, Google has become the most sought-after workplace in the world. Laszlo Bock, Senior Vice President, People Operations at Google, reveals the secrets and pitfalls of Google's "self-replicating talent machine," and how any organization can become a great place to work. Continue your talent acquisition transformation at Talent Connect 365: http://linkd.in/1s8SWeG

This talk suggests: > Never compromise on quality (it will kill culture and drive away the best) > Use science, structured interviews (to kill bias) > Give them a (bigger) reason to join (meaning) my further notes: 1) set a high standard (don't compromise, stay the course) 2) remove hiring managers from the hiring decisions (eliminate critical bias) 3) Use Assessment (Interviews aren't reliable ) 4) Job criteria: Cognitive Ability (problem solver, curious) , Leadership, Culture Fit, Role-related knowledge (a little confusing because he said "interviews are unreliable") 5) Structured interviews (same for everyone) -- hypotheticals/situational & behavioral 6) How you can Convince them to join: comes down to MEANING in Life (then the sales pitch for Google started and they almost lost me) 7) Find out how to meet your target market and creatively (around 28:00) <Job v. Career v. Calling> --> 1/3 see it as a calling <4X results if you can find a way to inspire meaning in people's work>

Hiring manager - avoid bias -> tend to hire friends, nephew, and important client's child.

High quality people - how to assess people? Get feedbacks - interview people very well - perform very well

Average - 

Googleyness - bring something new to the organization 

Intellectual humility 

People bring new things to us 

Figure out the rest - you have those three things 

Generalist - not specialist 

Clear standards - some easy grader, tough grader - Love people, every person looks great ...

Structure interviews - Every candidate gets same algorithms similar 

quality response - 

Give candidates the meaning to join 

1. Set a high bar for quality and never compromise
2. Assess candidates objectively ... science FTW
3. Give candidates a reason to join

Leetcode premium: Google - time period - last 6 months - Frequency

 Dec. 2, 2020

Introduction

It is the first day of marathon. I will go over over 50 hard level algorithm and over 50 medium level algorithm on Leetcode premium, Google related algorithms. 

Hard work is needed

Data, Structure, and Science in Hiring at Google | Kerry Cathcart, Staffing Program Manager

 Here is the link. 

Invest early - hiring is the art

data analysis, scientific approach for hiring 

New research and new experience

Four E: 

1. process is efficiency, effective, hiring right people
2. candidate - user experience
3. process - equitable - fair, not biased

Hiring committee

Four attributes:

1. Role related knowledge - day one - varies, level, communication skills, code - day one 
2. General cognitive ability - complex problem at workplace, figure out root cause 
3. Leadership - being a great leader, ability to lead a team - take ownership at work, influence the change, rally the peers around, see a problem and speak up 
4. Good or bad on behaviors 
5. Google culture unique and good ...

6:59 PM/ 40:19 

ownership 

Googleyness 

- Google culture - concrete - what to look for in the interview process 

culture fit - not really explain why

1. behaviors - 
2. seek out feedback to improve
3. ambiguity - wait for more info, or figure out what to do

13.05

Two kinds of questions to ask 

Behavioral 

Hypothetical 

Behavioral 

- Past focused

- Often begin with "Tell me about a time when "

- Useful to understand the impact a candidate has had in previous roles

Hypothetical 

Future focused

Often begin with "Image that..."

Useful to assess capacity for innovation in Google context

Dig into ...

What steps 

What resources

What do you do differently? 

Feedback - team member does not perform 

Drill up the information

What kind of information you gather? 

Think about assess the candidate

Rubics - assess 

Prioritize a portfolio of projects, cross organization 

Trap - first decent candidate to see

General hire or no hire - 

very detail interview feedback - take notes of specific answers 

Test candidate to get things done - company wide initiative 

20:00/ 40:19

Making hiring decisions by committee 

Benefits for Google long term 

Double down this - unconscious bias training - fairly and consistently 

My team - senior lead - feedback and continue to improve 

Keep the hiring trend and leadership - hiring is every one's job, not recruiter's 

Senior leaders - hiring committee - quality of work

Research shows three things to improve: 

1. Duration of the process, how quickly it can give the offer to the candidates
2. Candidate knows what to expect and how to prepare for the interview
3. Candidate knows how to make impact for the company 

24% -> 48%, talk about experience about family and friends. 

Leverage you can improve - 

what to expect and how to perform in the interview 

Really benefits - concrete how to make contributions 

This is really you can do for us. 

How to measure candidate's experience? 

80% - not offer a job - recommend to the friends - 

7 benefits to go to office to work

Dec. 2, 2020

I like to talk about good things about working in the office instead of working remotely. 

I think that life is so beautiful to walk to office building, and then start to enjoy the art of lighting. 

Taking selfie

I need to take some selfie since I am aging. It is most challenge life to build wealth and play stock market in 2020. My weight just went up to 200 lb, I did not notice since I was too busy with so many things. 

I like to slow down and enjoy the weather, and all I can enjoy as a software programmer. 

Fitness is very important and there are so many ideas I can try to work on my weight control as well. 

I will load 7 selfies and talk about one benefit each time. 

Fact 1: 

It is my 10th year to work on the same building. I know that it is so important for me to appreciate what I have. Since March 2020, over 10 million people in USA lost their job. 

Fact 2: I remembered that I had hard time to live with hay fever, coughing and sneezing. I did not spend enough hours (40 hours+ at least) to work on hay fever research, and I scared people in the office. I could not go to work since I may sneeze unexpectedly. I decided to take two weeks vacation and learn how to improve hay fever issues in March, 2020. That is a lot of reading and studying, a lot of hours reading and study. 

Fact 3: After I took 2 weeks vacation break, I went back to work; and after one or two weeks, I got another complaint. I need to work on it again. I took another week vacation to figure out. 

I think that lighting is to serve people and make space more efficient for business an leisure use. The art of lighting is to choose good design of various products, and then serve people in different ways, my favorite lights are in-graded, wine-rack, and pendant lights from ceilings. 

1. Daily commute - good exercise, close to nature
2. Office environment - comfortable place to work on projects
3. Compared to home office, there are more collaboration at office
4. More time to take breaks, more time to walk
5. Eat more healthy lunch
6. ...
7. ...

What is get measured, what is to be worked on: My Google 14 set mock interview performance on leetcode.com

Leetcode discuss: 317. Shortest Distance from All Buildings

 Here is the link. 

First practice - C# - BFS - Queue - Case studies - Easy to follow

Nov. 30, 2020
It is a hard level algorithm. I chose to write the solution using BFS algorithm.

Case study
Sometimes there is no solution.

For example,
case 1:
1 , 1, 0
1, 0, 0
There is no way to access the building (0,0) position building. Return should be -1. So it is important to record how many buildings in total first, and then record how many buildings are accessible starting from the position with value 0. Compare two numbers, if any building is not accessible, return -1.

case 2:
How to set visited in the matrix, and make sure to avoid revisit the same position?
1 0 1
0 0 1
0 0 1

Space complexity should not be big concern. I prefer to use a copy of given matrix grid to pass into function to run BFS, and the value will be changed to mark visited.

Two concerns in my design, first is to do not count the same building more than once. The tip is to change the building value 1 to -1, so it can not be counted more than once.

Secondly it is ok to change value 0 to -1 as a way to mark visited land, same value as visited building. No worry about sharing the same value.

Let me walk through one search and see if it can be optimized.

Start from (0, 1) position since the value is 0, and then calculate the smallest distance to any building if it is accessible using BFS. BFS is very powerful tool to ensure the smallest distance is found first and it can be recorded properly.

Add integer array {0, 1, 0} to the queue, and then start BFS search; Dequeue {0, 1, 1}, the position in the matrix is (0,1), and the distance is 0. Check the position is building or not. If it is, then mark visit the building, add distance to total distance, return since it is not allowed to cross the building. If it is land, then add four possible neighbors into Queue, increment distance with value 1.

It is important to walk through the steps by hand, so it is easy to spot issues in the design.
Second step is to add four neighbors of (0, 1) to the queue, third step is to dequeue one by one those four positions.

Left neighbor is with value 1, one building is found, distance+=steps, and mark (0,0) with value -1.
Right neighbor is with value 1, another building is found, distance+=steps, and mark (0, 2) with value -1.
Down neighbor is with value 0, continue to search it's found neighbors.
Up neighbor is out-of-range.

Skip more details afterwards.
I do not think that it is needed to prune the algorithm if all buildings are found. Just let BFS search all possible paths and naturally end.

How to have a smoothly practice?
I have to work on my attention not to mix variables under stress, one tip is to reuse same variable, this way is to avoid mixing variables.

I wrote DFS first, and then I noticed that it did not work. It took me less than a few minutes to change them using Queue. But I do think that I have to pay more attention before I write the code. Think more carefully.

Additional checkings include the following:

1. All buildings are found starting any position with 0 value in the given matrix;
2. Distance is updated if one building is found;
3. Make matrix a copy to pass as a function argument, easy to mark visit using -1, avoid duplicate count of same building;
4. Avoid index-out-of-range error, do not declare valid checking variable after out-of-range check. Since only if it is in the range, then it is safe to check valid value; Put all checkings in one giant statement.
5. I mixed row and col with x and y in my outOfRangeEtc, better to reuse row and col.

public class Solution {
    public int ShortestDistance(int[][] grid) {
            if(grid == null || grid.Length == 0 || grid[0].Length == 0)
                return 0; 
        
            var rows = grid.Length; 
            var columns = grid[0].Length; 
        
            var buildingCount = 0; 
            for(int row = 0; row < rows; row++)
            {
                for(int col = 0; col < columns; col++)
                {
                    if(grid[row][col] == 1)
                    {
                        buildingCount++; 
                    }
                }
            }
        
            // make sure buidling found == buildingCount
            // distance - BFS - minimum
            var minDistance = Int32.MaxValue; 
        
            for(int row = 0; row < rows; row++)
            {
                for(int col = 0; col < columns; col++)
                {
                    var current = grid[row][col];
                    if(current != 0)
                        continue; 
                
                    var found = 0;                 
                    var distance = 0; 
                
                    var gridCopy = new int[rows][];
                    for(int row1 = 0; row1 < rows; row1++)
                    {
                        gridCopy[row1] = new int[columns];
                    }
                
                    for(int row1 = 0; row1 < rows; row1++)
                    {
                        for(int col1 = 0; col1 < columns; col1++)
                        {
                            gridCopy[row1][col1] = grid[row1][col1];
                        }
                    }
                
                    runBFS(gridCopy, row, col, ref found, ref distance);
                
                    if(found == buildingCount)
                    {
                        minDistance = Math.Min(minDistance, distance);
                    }
                }
            }
        
            return minDistance == Int32.MaxValue? -1: minDistance; 
        }
    
        private void runBFS(int[][] grid, int row, int col, ref int found, ref int distance)
        {
            var rows    = grid.Length; 
            var columns = grid[0].Length; 
        
            var queue = new Queue<int[]>(); 
            queue.Enqueue(new int[]{row, col, 0});

            while (queue.Count > 0)
            {
                var count = queue.Count;

                for (int i = 0; i < count; i++)
                {
                    var node = queue.Dequeue();

                    var x = node[0];
                    var y = node[1];
                    var steps = node[2];

                    var outOfRangeEtc = x < 0 || x >= rows || y < 0 || y >= columns ||
                     grid[x][y] == 2 || grid[x][y] == -1;
                    if (outOfRangeEtc)
                    {
                        continue;
                    }

                    if (grid[x][y] == 1)
                    {
                        grid[x][y] = -1;
                        distance += steps;
                        found++; 
                    }
                    else
                    {   // mark visit
                        grid[x][y] = -1;

                        queue.Enqueue(new int[] { x, y - 1, steps + 1 });
                        queue.Enqueue(new int[] { x, y + 1, steps + 1 });
                        queue.Enqueue(new int[] { x - 1, y, steps + 1 });
                        queue.Enqueue(new int[] { x + 1, y, steps + 1 });
                    }
                }
            } 
        }
}

14 set Google mock onsite interviews - Leetcode

 Dec. 1, 2020

Introduction

It is the first time I learn the value of $150 US dollars value. I paid subscription, and then I took the time to complete 14 set of Google mock onsite interviews. I failed and learned so many algorithms in less than one month. 

14 set Google mock onsite

What do I learn most from Google onsite preparation?

 Dec. 1, 2020

Introduction

I am thinking about what I learn most from Google onsite interview preparation. I just could not believe that I want to get an offer after three Amazon onsites, two facebook onsite, my first Google onsite. Time is up, and I just cannot finish another 14 set Facebook mock onsite interviews, over 10 Microsoft mock interviews, and 10 Amazon mock onsite interviews. 

What do I learn most from Google onsite preparation?

I just could not believe that I spent first five months to learn how to invest. I like to show my Leetcode submission history. 

I will figure out in last week preparation. It is my favorite project to work on. 

How to Lead 60,000 Employees | Laszlo Bock, Google's Former People Chief

 Here is the link. 

Laszlo Bock is a Senior Advisor at Google and the author of "Work Rules!" During his tenure at Google, he led Google's people function, and was responsible for attracting, developing, retaining, and delighting "Googlers." Under his leadership, Google was named the Best Company to Work For more than 30 times around the world, and received over 100 awards as an employer of choice. In 2010, Bock was named "Human Resources Executive of the Year" by HR Executive Magazine. At a special IVY Ideas Night in 2015, Bock shared insights from his new book and talked about the essentials of good leadership. IVY is the world's first Social University. To learn more, please visit www.ivy.com.

Transparency

collaborate, not driven by the fear

take the person out-of-job - open things up

Google's 10 design principles via Laszlo Bock

 Here is the link. 

1. Focus on people
2. Every millisecond counts
3. Simplicity is powerful
4. Engage beginners and attract experts
5. Dare to innovate
6. 
   

Google interview preparation: Ten things we know to be true

 Here is the article. 

My notes from the following 10 things: 

1. Placement in search is not distracting - talk about my experience with sales manager
2. Search problems - focus on exclusively on solving search problem
3. Web browser, search results - fraction of a second
4. 
   

We first wrote these “10 things” when Google was just a few years old. From time to time we revisit this list to see if it still holds true. We hope it does—and you can hold us to that.

1. Focus on the user and all else will follow.

Since the beginning, we’ve focused on providing the best user experience possible. Whether we’re designing a new Internet browser or a new tweak to the look of the homepage, we take great care to ensure that they will ultimately serve you, rather than our own internal goal or bottom line. Our homepage interface is clear and simple, and pages load instantly. Placement in search results is never sold to anyone, and advertising is not only clearly marked as such, it offers relevant content and is not distracting. And when we build new tools and applications, we believe they should work so well you don’t have to consider how they might have been designed differently.

2. It’s best to do one thing really, really well.

We do search. With one of the world’s largest research groups focused exclusively on solving search problems, we know what we do well, and how we could do it better. Through continued iteration on difficult problems, we’ve been able to solve complex issues and provide continuous improvements to a service that already makes finding information a fast and seamless experience for millions of people. Our dedication to improving search helps us apply what we’ve learned to new products, like Gmail and Google Maps. Our hope is to bring the power of search to previously unexplored areas, and to help people access and use even more of the ever-expanding information in their lives.

3. Fast is better than slow.

We know your time is valuable, so when you’re seeking an answer on the web you want it right away–and we aim to please. We may be the only people in the world who can say our goal is to have people leave our website as quickly as possible. By shaving excess bits and bytes from our pages and increasing the efficiency of our serving environment, we’ve broken our own speed records many times over, so that the average response time on a search result is a fraction of a second. We keep speed in mind with each new product we release, whether it’s a mobile application or Google Chrome, a browser designed to be fast enough for the modern web. And we continue to work on making it all go even faster.

4. Democracy on the web works.

Google search works because it relies on the millions of individuals posting links on websites to help determine which other sites offer content of value. We assess the importance of every web page using more than 200 signals and a variety of techniques, including our patented PageRank™ algorithm, which analyzes which sites have been “voted” to be the best sources of information by other pages across the web. As the web gets bigger, this approach actually improves, as each new site is another point of information and another vote to be counted. In the same vein, we are active in open source software development, where innovation takes place through the collective effort of many programmers.

5. You don’t need to be at your desk to need an answer.

The world is increasingly mobile: people want access to information wherever they are, whenever they need it. We’re pioneering new technologies and offering new solutions for mobile services that help people all over the globe to do any number of tasks on their phone, from checking email and calendar events to watching videos, not to mention the several different ways to access Google search on a phone. In addition, we’re hoping to fuel greater innovation for mobile users everywhere with Android, a free, open source mobile platform. Android brings the openness that shaped the Internet to the mobile world. Not only does Android benefit consumers, who have more choice and innovative new mobile experiences, but it opens up revenue opportunities for carriers, manufacturers and developers.

6. You can make money without doing evil.

Google is a business. The revenue we generate is derived from offering search technology to companies and from the sale of advertising displayed on our site and on other sites across the web. Hundreds of thousands of advertisers worldwide use AdWords to promote their products; hundreds of thousands of publishers take advantage of our AdSense program to deliver ads relevant to their site content. To ensure that we’re ultimately serving all our users (whether they are advertisers or not), we have a set of guiding principles for our advertising programs and practices:

• We don’t allow ads to be displayed on our results pages unless they are relevant where they are shown. And we firmly believe that ads can provide useful information if, and only if, they are relevant to what you wish to find–so it’s possible that certain searches won’t lead to any ads at all.

• We believe that advertising can be effective without being flashy. We don’t accept pop–up advertising, which interferes with your ability to see the content you’ve requested. We’ve found that text ads that are relevant to the person reading them draw much higher clickthrough rates than ads appearing randomly. Any advertiser, whether small or large, can take advantage of this highly targeted medium.

• Advertising on Google is always clearly identified as a “Sponsored Link,” so it does not compromise the integrity of our search results. We never manipulate rankings to put our partners higher in our search results and no one can buy better PageRank. Our users trust our objectivity and no short-term gain could ever justify breaching that trust.

7. There’s always more information out there.

Once we’d indexed more of the HTML pages on the Internet than any other search service, our engineers turned their attention to information that was not as readily accessible. Sometimes it was just a matter of integrating new databases into search, such as adding a phone number and address lookup and a business directory. Other efforts required a bit more creativity, like adding the ability to search news archives, patents, academic journals, billions of images and millions of books. And our researchers continue looking into ways to bring all the world’s information to people seeking answers.

8. The need for information crosses all borders.

Our company was founded in California, but our mission is to facilitate access to information for the entire world, and in every language. To that end, we have offices in more than 60 countries, maintain more than 180 Internet domains, and serve more than half of our results to people living outside the United States. We offer Google’s search interface in more than 130 languages, offer people the ability to restrict results to content written in their own language, and aim to provide the rest of our applications and products in as many languages and accessible formats as possible. Using our translation tools, people can discover content written on the other side of the world in languages they don’t speak. With these tools and the help of volunteer translators, we have been able to greatly improve both the variety and quality of services we can offer in even the most far–flung corners of the globe.

9. You can be serious without a suit.

Our founders built Google around the idea that work should be challenging, and the challenge should be fun. We believe that great, creative things are more likely to happen with the right company culture–and that doesn’t just mean lava lamps and rubber balls. There is an emphasis on team achievements and pride in individual accomplishments that contribute to our overall success. We put great stock in our employees–energetic, passionate people from diverse backgrounds with creative approaches to work, play and life. Our atmosphere may be casual, but as new ideas emerge in a café line, at a team meeting or at the gym, they are traded, tested and put into practice with dizzying speed–and they may be the launch pad for a new project destined for worldwide use.

10. Great just isn’t good enough.

We see being great at something as a starting point, not an endpoint. We set ourselves goals we know we can’t reach yet, because we know that by stretching to meet them we can get further than we expected. Through innovation and iteration, we aim to take things that work well and improve upon them in unexpected ways. For example, when one of our engineers saw that search worked well for properly spelled words, he wondered about how it handled typos. That led him to create an intuitive and more helpful spell checker.

Even if you don’t know exactly what you’re looking for, finding an answer on the web is our problem, not yours. We try to anticipate needs not yet articulated by our global audience, and meet them with products and services that set new standards. When we launched Gmail, it had more storage space than any email service available. In retrospect offering that seems obvious–but that’s because now we have new standards for email storage. Those are the kinds of changes we seek to make, and we’re always looking for new places where we can make a difference. Ultimately, our constant dissatisfaction with the way things are becomes the driving force behind everything we do.

How Google Thinks About Hiring, Management and Culture

 Here is the link. 

Assess people - training interviewer 

15 minutes - same quality results - train people thinner and thinner

Reason:

confidence, conscientious, 

Snap judgement - look for data - Separate committee - maintain the quality 

Hiring committee - maintain the quality 

Objective, structure interviews - do not predict performance 

screen hard level - drill down - do not make decision on one person's opinion

Build a website - 2013 - start to work on website - 

Get work done - set goal - manager - we want to make sure that people get work done 

Manage them very well - Forget everything you know - Behavior 

Employee - peer feedback - manager - take away power away from managers 

People can see them customers and feedbacks 

500 engineers - report to one director 

Training people - story in the book - tell them the story how to play golf like Tiger Woods 

HR - consultant - Share group entrepreneurs 

Manage - day one - 50,000 people - how to manage them? 

close the deal and make things happen

Partner, KPCB - beth 

Compensation - pay unfairly 

politics, performance above average - average MBA - system is not fair - performance is observable

different research - software engineers - best people are way better than average 

Difference too big - salary - 20% to 30% 

Best people are way more than that - not 10 times more - absolute - exponential

justify - pay transparent - problems - no one is happy 

procedure justified - change the outcome - appreciated - second thing 

79 cents a dollar - 

Based on your job - not prior pay 

Do not create new one - really wide distributed - market will pay them very well 

Influence - get them in the market - absolute best people and generate most value