Amazon Has Drastically Changed the Way I Read

Since I got my first Kindle my reading habits started to change. That was a few years ago, so the change has been very gradual. Here are some differences:

– A few years ago I might finish a book and not have another one in the pipeline. I would start watching a TV series, which would occupy my spare time for a while. The Wire was the last one, I downloaded all seasons and watched them in a couple of months. Now my Kindle is filled with unread books, so when I finish one I naturally start another one. As a result I haven’t watched TV in a couple of years. I don’t think there’s anything wrong with watching TV, it just turns out that I find reading more relaxing.

– The Kindle is not a device; it’s a platform. Besides the device itself, I use Kindle for Android, for the Mac, and even for the iPad sometimes. A great feature of the platform is that it synchronizes to the last page you’ve read on any connected device. Of course I prefer to read on the Kindle, and on a rainy day like today I may spend several hours with it in bed or the couch. If I’m at work and a meeting finishes early, I may stay in the room and continue reading a book on my laptop. When my wife goes to the bathroom at a restaurant, I can either check Twitter or read a couple of pages on the phone. As a result, I go through books much faster than I used to.

– I’m starting to buy books based on their availability on the Kindle store. Last week I was trying to choose my next book. The one I wanted the most only had a hardcover version, so I “postponed” reading it. I can’t wait for all books to have electronic versions. Obviously for some the printed medium matters, but for the vast majority (in my opinion) it doesn’t.

– I’ve begun to see printed books as deadweight, a burden to carry. I do not have a bookcase anymore, and during my last move I gave away all but a few of my printed books. It used to be very rare for me to re-read a book. It’s happening more often now that I see them on the home page of my Kindle!

– I don’t pirate books unless there’s absolutely no alternative. An ebook typically costs $5 to $15. I’m going to spend hours reading it, and I value my time highly. I also value the enjoyment I expect to get out of the book. With Amazon’s one-click delivery to my Kindle, paying for it is a no-brainer. The only reason to pirate a book is when I want to read it NOW and nobody sells an e-version. I’ll spend a couple of minutes searching for an “unofficial” e-copy. If the quality is acceptable, I’ll read it. Publishers please take note: printed books are going the way of CDs. I have bought mp3 albums a few times in the past year; I have no idea when I bought music in a physical container for the last time.

– The Kindle is so cheap that I see it as a “physical app”, just like the iPod Shuffle. I couldn’t care less about the object itself. I don’t have a case for it, and when it breaks I’ll order a new one overnight without thinking twice about it.

This “future” that we live in is a mixed bag, and this is one of the good things about it.

My New Year’s Resolutions

I never do this, but I thought I’d give it a try. Here are my New Year’s Resolutions for 2012. Because it’s my first time I’ll go easy and see how it turns out. I’m shooting for at least five.

  • Tweet once a week or more.
  • Wait at least a week before buying the new Apple gadget.
  • Solve one interesting differential equation (interesting to me, of course).
  • Memorize the NATO phonetic alphabet, and use it when I spell words on the phone.
  • Not let the milk in the fridge go bad.
  • Turn off all electronic devices before takeoff. No airplane mode, no cheating.
  • Resist the constant impulse to buy a Boeing 767.
  • Take a picture of a tourist taking a picture of other tourists. The more meta, the merrier.
  • Wait until the last beep of the microwave before opening it.
  • Stay the course. Keep flossing.
  • Read one random book from the Gutenberg project. If possible, enjoy it.
  • Stay hungry, stay foolish until lunchtime.
  • Learn a new programming language, write “Hello World!” in it, and promptly forget about it.
  • Honk at a stranger for no reason on the 4th of July.
  • Avoid climbing Mount Everest. It’s dangerous, and I already have plenty of conversation topics for cocktail parties.
  • Wash the car once, and celebrate it with a shot of the best wheatgrass money can buy.
  • Live every day to the fullest extent of the law.

VCs Also Succumb to Cognitive Biases

I was just reading Fred Wilson’s post Mocked And Misunderstood

When people ask me, “how do you know which companies and services are going to be the biggest successes?”, I usually tell them to look for the companies and services that are mocked and misunderstood. For some reason, that correlates highly with the biggest breakout successes.

Fred Wilson is obviously a very smart guy, but that doesn’t make him impervious to cognitive biases. The above article shows a few of them. Let’s start.

1) Survivor bias. Gandhi Nicholas Klein said: “First they ignore you, then they laugh at you, then they fight you, then you win.” Wilson is skipping the companies that are ignored. Twitter was mocked because it was already standing out. Nobody mocked Twttr back when it started. That’s when you wanted to invest in it. Mocked and misunderstood implies that a company has a ton of media attention.

2) Hindsight bias. Think about companies that are mocked and misunderstood. Misunderstood is a loaded word. Do Webvan or make that list? They were mocked, but were they misunderstood? Misunderstood implies a time sequence. At first you mocked the company, but then you thought “oh, maybe I misunderstood something.” Or it means that those who mock the company are not the same as those who misunderstanding. In any case, you can only realize that something *was* misunderstood at the time, not that it is misunderstood right now.

3) Availability bias. Can you think of successful companies that were not mocked or misunderstood? Of course, but it takes more effort. Why? Because the vast majority of companies are not mocked or misunderstood. On the other hand, unsuccessful companies that were mocked and misunderstood are no more, and you have forgotten them.

You can try this experiment: list all the startups that launched in 2007. Pick a sufficiently large random set (say 100). Find all relevant press articles for that year. How many “mocked and misunderstood” companies went on to be successful compared to companies with an equal amount of coverage that were not mocked or misunderstood?

Fred Wilson, I strongly recommend that you read Daniel Kahneman’s Thinking, Fast and Slow. Every investor should read this.

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Killer phone app: taking pictures FAST

I just did the following experiment:

I have a clock in front of me. I imagined that the start of a new minute was an unforeseen event that I wanted to capture. I had my Samsung Galaxy S2 in my pocket. At the start of the minute I pulled it out, unlocked it, navigated to the camera icon, opened it and took a picture of the clock. The whole thing took ten seconds.

Ten seconds is a lot of time. Someone’s purse gets snatched, a car hits someone and drives away, etc. in much less. Why couldn’t phones have a mechanism to take a picture in the time it takes to point it to the object? In my case, it’s two seconds. It shouldn’t be that hard, all you need is two or more buttons that are hard to press by accident, but that you could press quickly in an emergency. Perhaps that combined with an accelerometer. It’s definitely possible to have a phone recognize the gesture “pulled it out of my pocket and pointed the camera at something, holding still now.”

Of course it doesn’t need to be an emergency. It could be your baby’s first step, a stranger proposing to another, a spontaneous smile. How many of those images are lost every day?

Apple, Samsung, anyone? Bueller?

Think Like a VC

The intent of this post is to save you time. Pitching to VCs takes a lot of energy, and it’s easier if you prepare correctly. More importantly, you must know whether it makes sense to do it given what you have to offer.

Suppose you’re a VC. Your job is to maximize the return of an investment fund over a period of time. The whole premise of a VC fund is that as an asset class it’s riskier than diversified funds, and it should outperform them in the long run. Let’s not argue whether that actually happens, let’s assume the premise make sense and keep going.

A typical VC fund is in the hundreds of millions. That means that over the course of the investment horizon (say, ten years) it must generate a return in that order of magnitude. A VC fund will invest in tens or even hundreds of companies, usually amounts in the order of millions to tens of millions. Some (probably most) of these companies will produce a negative return, some will generate modest returns and a few will be “home runs.” These home runs are the head of the distribution, and they make or break the fund. 

Why is it important to know this? Because VCs need home runs, they care deeply about whether an investment has the potential to be one.

This has several implications. The first one should be obvious but I found out that it isn’t to many entrepreneurs.

– When you first meet a VC, he/she will be trying to assess whether you are looking for a home run, or would be content with an early exit. If you are a first-time entrepreneur for whom a few million dollars would be life-changing, VCs would want you to be slightly irrational and overly ambitious. They would want you to be in it to change the world. When they ask you questions such as “how does your company get to make tens of millions a year” they want to know that you are seriously considering building something big. They don’t care so much about the response. They are interested in your reaction, your body language, and the fact that you’ve spent brain cycles on this.

Other implications:

– An already successul entrepreneur is more aligned with a VC’s goals. If you have millions of dollars in the bank, making a few more won’t change your life just like it won’t make a huge difference to the investment fund. If Evan Williams goes to raise money, you can be sure he’s trying to build a world-changing company that would generate billions of dollars in value.

– The flipside of this: if you are a first-time entrepreneur and you’d be happy with an “early exit” that would give you enough money to not worry about bills, you must seriously consider whether you want VCs involved in your company. A VC will accept an early exit if the company looks very unlikely to become a home run. If you are close to running out of cash and not making revenue, they will take the “base hit” and move on. But if your company looks like it has a chance to become huge, a VC will be very reluctant to sell. A 10% chance of 100M in two years is better than a 100% chance of 5M now to a VC. This lack of alignment between entrepreneurs and VCs is not uncommon, and it shouldn’t be a surprise.

– Single founders are also slightly less attractive to VCs because they have more equity than each of two or more co-founders. I would expect a team of three first-time cofounders to be happy with an exit that’s 3x what a single founder would take.

Here’s an interesting exercise: spend an hour pretending to be a VC. You have 1B dollars and you need to turn it into 3B over 10 years. Would you consider your own company? What companies would you invest in? What do they have in common? Would you want your company to be more like one of those? If so, can you do it?

Isn’t this a fun game.

Search Engines Cannot Be Objective

Over the years I’ve heard people repeat the idea that Google is an “objective search engine” because they allow their algorithms to reflect “the voice of the web.” This sounds great in theory, but in practice it implies two things:

  • There is such a thing as “the voice of the web.”
  • Google can be a perfect mirror of such voice.

Here’s a video in which a few Google insiders talk about how Google Search works. At one point the moderator (Danny Sullivan) asks if Google ever manually tweaks results. He brings up one time when the top result for the query “Jew” was an antisemitic site. Amit Singhal (head of Google’s ranking algorithm) responds: (jump to minute 41)



Singhal refers to a principle that Google holds dear: they would not manually (emphasis mine) promote, demote or remove results even if their judgment is saying that their algorithms are doing the wrong thing. However, he proceeds to explain how in that case the algorithm was clearly wrong, so they fixed it.


Think about this for a second. What does it mean for the algorithm to be wrong? In this case, Google was in the spotlight because of a controversial query. It so happens that they agreed with those who complained about the result. Are those people the voice of the web? He then moves on to other cases in which the judgement is not so “black and white.” In those cases, they just let the algorithm do its thing and not privilege one point of view over the other.


Here’s the catch: what’s described above could be done manually. Putting the algorithms in charge is a cop-out. What this accomplishes is removing responsibility from any single human being. As we all know though, human beings are behind the algorithms, and they (we) are able to steer them. We can justify our algorithm’s settings by announcing to the world that they were automatically optimized to maximize the satisfaction of human judges. Well then, who are those human judges and how were they chosen? How do you choose a set of human judges who perfectly represent the “voice of the web”? Moreover, could you (even inadvertently) prime those humans to choose the parameters you agree with?


Even if you could have a perfectly fair process to maximize the satisfaction of a representative set of individuals of all ethnicities, languages, geographies and beliefs, it all goes out the window when you decide that your algorithm is “wrong” because it doesn’t agree with your core values. It raises the question: is the algorithm wrong for a huge number of queries that nobody at Google feels strongly enough about?


Google knows that their search results reflect their opinion, and they publicly admit it. It’s interesting to see someone like Amit Singhal being disingenuous about it many months after that admission. He’s trying to play up the fact that nobody does anything manually as a dearly held principle. The implication is that if you have an algorithm to “decide what’s right”, then it’s all good. Even if you have to “fix it” once in a while when its “obviously wrong.” I believe that Singhal has no intention to mislead the public, and that this is just a blind spot in the engineering mind.


Those of us who work in search must be honest with ourselves about issues like this one. Whether we like it or not search results influence public opinion enormously, perhaps more than any other source of information in the world. This is the great responsibility that comes with great power.