Category Archives: Technology

Primitive car safety testing

Another story from the Robert McNamara archives.

Before becoming Secretary of State, he worked at Ford on car safety. He described their testing programme in The Fog Of War.

I said, “What about accidents? I hear a lot about accidents.”

“Oh yes, we’ll get you some data on that.” There were about forty odd thousand deaths per year from automobile accidents, and about a million, or a million two injuries.

I said, “Well, what causes it?”

“Well,” he said, “it’s obvious. It’s human error and mechanical failure.”

I said, “Hell, if it’s mechanical failure, we might be involved. Let’s dig into this.” I want to know, if it’s mechanical error, I want to stop it.

“Well”, they said, “There’s really very few statistics available.”

I said, “Dammit, find out what can we learn.”

They said, “Well, the only place we can find that knows anything about it is Cornell Aeronautical Labs.”

[Cornell] said, “The major problem is packaging.” They said, “You buy eggs and you know how eggs come in a carton?”

I said, “No, I don’t buy eggs. I never have — my wife does it.”

Well, they said, “You talk to her and ask her: when she puts that carton down on the drain board when she gets home, do the eggs break?”

And so I asked Marg and she said “No.”

So Cornell said, “They don’t break because they’re packaged properly. Now if we packaged people in cars the same way, we could reduce the breakage.”

We lacked lab facilities, so we dropped the human skulls in different packages down the stairwells of the dormitories at Cornell. Well, that sounds absurd, but that guy was absolutely right. It was packaging which could make the difference.

Testing and iteration by dropping skulls down stairs. Smashing!

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More McNamara here (my post on the terrible odds for WWII US pilots). Full interview transcript here (I made a few edits for clarity’s sake). Image by pegasus22 on Etsy.

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The Strangeness of Silicon Valley

From a conversation between John Naughton and Judy Wajcman:

The technology industry is actually rather small. And dysfunctional. And solves its own problems. But Silicon Valley has convinced us that the problems of a small set of socially-unusual people (who sleep at their desks and have no social life) are actually our own problems too, and that we need products and services that help to solve them.

In case proof of this were needed – here’s Elon Musk (PayPal, SpaceX, and Tesla founder) on relationships:

I would like to allocate more time to dating. I need to find a girlfriend. That’s why I need to carve out just a little more time. I think maybe even another five to ten — how much time does a woman want a week? Maybe 10 hours? That’s kind of the minimum? I don’t know.

Clearly a genius, but a rather strange one. The other side of the Valley.

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Links: Naughton/Wajcman, Musk.

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The Robots Already Won

You can relax! Our robot overlords already took control.

Three examples of their successful infiltration:

1. Ipswich Town’s PR teambots

Ipswich defender Tyrone Mings paid off all his mum’s debts. Wonderful news! A footballer with a conscience!

An Ipswich spokesman said it was:

A private matter between Tyrone and his mum.

THESE GUYS ARE ROBOTS

2. Verizon CEObot

Verizon spent $4,400,000,000 (that’s $4.4bn) on buying AOL. Blockbuster deal!

Lowell McAdam, Verizon chairman and CEO, said:

Verizon’s vision is to provide customers with a premium digital experience based on a global multiscreen network platform. This acquisition supports our strategy to provide a cross-screen connection for consumers, creators and advertisers to deliver that premium customer experience.

THIS GUY IS A ROBOT

3. Local councilbots

Water fountain dating back to 1853, adorned by Biblical quote. Historically interesting! And possibly significant!

ROBOTS ROBOTS ROBOTS

Game over, see you later. MAYBE.

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Links: Mings, Verizon, Water.

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BYE!

 

 

Homescreen’s where the Art is

Yay, I finally found some data on what people have on their homescreens!

Here’s what I found on Homescreen, a site/app that helps you share a screenshot of your iPhone homescreen.

I like all this because, as co-founder Matt Hartman puts it:

The App Store is a black box.

The site shows the most popular apps, and gives the % of users’ homescreens on which each app appears. 500,000 different apps from 13,000 screens indexed so far.

The data comes from Homescreen users, so obviously there’s a heavy selection bias going on here. The Homescreen app itself appears on 9.82% of homescreens indexed this week… which I doubt is true of the full iPhone userbase.

So, what can we learn?

Turns out that even geeky homescreen curators will often keep the default Apple apps front and centre:

So what happens when we cut out the default Apple apps?

Things look a bit different. By this view, mobile is all about social. And as Quartz points out: no games, no newsreaders.

I’d love to see the data in more detail – for different devices, demographics, locations, etc. But the company just added profile pages as a feature (see e.g. Pocket), and on every profile page there’s cool stuff like which other apps it shares a folder with, and which other apps it most often appears alongside on the homescreen.

Here’s my current homescreen, with the %s of Homescreen users who have each app on their own homescreen. Man, they are missing out on Trello!

 

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Thanks for reading! ~ Todd

How to get a bargain on a new iPhone (and a free cost calculator)

Which of these costs more?

  1. iPhone 5C, 8GB
  2. iPhone 6, 16GB

Trick question: they cost the same amount (£1107 over 2 years) if you choose the right purchase option.

That’s one of the surprises I discovered when I compared the costs of all models, storage sizes, and purchase types (direct / 12m contract / 24m contract).

No shady stuff, no gimmicks or trade-ins – below I set out what I found just by building a little tool to compare all the usual options.

My trusty 4S borked last night after 2.5 years’ service, so I’m wondering (1) whether to stick with an iPhone and (2) if so, which to buy.

Assuming that I want to get another iPhone, there are three main variables:

  1. Model (5C, 5S, 6, 6+)
  2. Storage (8GB, 16GB, 32GB, 64GB, 128GB)
  3. Purchase option (direct purchase, 12-month contract, 24-month contract)

I built a basic cost calculator to help me decide which to buy. You can use it too – link below.

Remarkably, there are some relative bargains available.

Example bargains:

  • iPhone 6, 16GB for the same price as 5C, 8GB (the example given at the top)
  • iPhone 5S, 16GB cheaper than 5C, 8GB
  • iPhone 6, 64GB cheaper than iPhone 5S with 16/32GB
  • iPhone 6 Plus, 128GB cheaper than iPhone 5S, 64GB

Also – in all cases, buying direct from Apple is cheaper than spreading the cost across a contract – so if you have the cash, buy direct.

Here’s the key part of the spreadsheet, and here’s the link to download the calculator (.xlsx file): iPhone comparison calculator – 04-10-14

I haven’t made my mind up yet – but this will stop me overpaying if I do decide on an iPhone.

Enjoy!

~ Todd

What is B? What The Data Can Never Tell You: Games and The Flash Crash

The 2010 Flash Crash was a United States stock market crash on Thursday May 6, 2010 in which the Dow Jones Industrial Average plunged about 1000 points (about 9%) only to recover those losses within minutes. It was the second largest point swing, 1,010.14 points, and the biggest one-day point decline, 998.5 points, on an intraday basis in Dow Jones Industrial Average history.

The Flash Crash was caused by human error.

The [official] report said that this was an unusually large position and that the computer algorithm the trader used to trade the position was set to “target an execution rate set to 9% of the trading volume calculated over the previous minute, but without regard to price or time”.

And that original error was magnified by a sequence of automated knock-on effects:

The New York Times [wrote]: “Automatic computerized traders on the stock market shut down as they detected the sharp rise in buying and selling.” As computerized high-frequency traders exited the stock market, the resulting lack of liquidity “…caused shares of some prominent companies like Procter & Gamble and Accenture to trade down as low as a penny or as high as $100,000.”

Remarkably, the problem self-corrected after a few minutes. But it was not an isolated incident:

The growth of computerized and high-frequency trading in commodities and currencies has coincided with a series of ‘flash crashes’ in those markets. The role of human market makers, who can match buyers and sellers and provide liquidity to the market, is now more and more played by computer programs. If those program traders pull back from the market, then big “buy” or “sell” orders can lead to sudden, big swings. It increases the probability of surprise distortions… In February 2011, the sugar market took a dive of 6% in just one second. On March 1, Cocoa-futures prices dropped 13% in less than a minute on the IntercontinentalExchange. Cocoa plunged $450 to a low of $3,217 a metric ton before rebounding quickly. The U.S. dollar tumbled against the yen on March 16, falling 5% in minutes, one of its biggest moves ever. According to a former cocoa trader: “The electronic platform is too fast; it doesn’t slow things down” like humans would.

We have so much data, and so many smart tools for managing and manipulating it. These are tools so smart that they work automatically, without human direction or intervention. It’s like when your hand touches the cooker: you pull it away before the pain message even reaches your brain, because your nerves respond automatically, much faster than your thoughts.

But with all this data, and all these smart tools – are we cutting ourselves out of the loop too fast?

An analogy from games: dozens of companies are running thousands of A/B tests on millions of data points to try to figure out how to optimise their products.

But even though examining the data might tell you what you’re doing wrong, it cannot tell you how to put it right.

An A/B test divides players into two groups: A is the control, the normal version. B is the test, the new version. For example – you could run an A/B test which changes the way a new type of archer in Age Of Empires is introduced to the player in a tutorial (is that game still going? classic!). The games guys run versions A and B alongside each other and compare the results – checking which group used the new archer type more, were more likely to return to the game the following day, or were more likely to do more of whatever else they were looking to improve.

But if A is what you have now – the current version – then what is B?

B must be defined, built, designed by humans.

It can’t be automated. So you have to invent it yourself.

Using big data and smart tools is an art as well as a science.

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P.S.s…

Age of Empires is still going! Info on the series can be found here.

All the quotes above are from the Wikipedia article on the 2010 Flash Crash. The best stories are the true ones.

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VC School

Best ways to learn about something new, in order:

  1. Start doing it
  2. Help someone do it
  3. Listen to someone who knows about it

For #3 I have recently built myself a VC School.

I downloaded Digg (now an excellent RSS reader) and connected it to my ten favourite VC blogs. Now, online and offline (important in London since half my commute is on the tube), I have a constant stream of high-quality posts available on my phone.

Posts I read today:

  • Web vs. native apps for consumer startups
  • Sticking with struggling investments
  • Dealing with recruiting mistakes
  • Bitcoin prospects
  • Snapchat/no revenues debate

Why VCs in particular? Three reasons:

  1. Connections: they know lots of entrepreneurs with new ideas
  2. Incentivised to be open: their aim in blogging is partly to attract interesting new cos, so they have good reason to share what they know
  3. Long-term perspective: unlike tech news (mostly ephemeral and therefore dull), VCs want to invest in ideas that have long-term relevance

So I’m finding Digg + VCs’ RSS feeds a great way to learn. It’s also an efficient way to discover new products, since they’re always plugging their portfolio companies. Combo bonus.

Sounds interesting? Here are the blog feeds, in alphabetical order:

Bill Gurley, Above The Crowd – blogRSS
Paul Graham, Essays – blogRSS
Chris Dixon – blogRSS
Mark Suster, Both Sides of the Table – blogRSS
Fred Destin – blogRSS
Fred Wilson, A VC – blogRSS
Andreessen-Horowitz – blogRSS
Semil Shah – blogRSS
Tom Tunguz, ex post facto – blogRSS
Dave McClure, 500 Hats – blogRSS 

Enjoy.

Slides: How Data Can Make You More Creative

Slides from a talk I gave to the 3rd-year media students at Regent’s University in London a few days ago. Lots of examples from TV and from my own experience.

Aim is to offer advice to anyone who is working in / wants to work in a creative industry.

In short, data is important.

Roll the dice

(Russell Westbrook slams it)

 

My girlfriend Emma told me that sports photographers use cameras that take 11 photos per second.

 

(Carmen Basilio beats Tony DeMarco 1955)

 

That’s because everything happens in a split-second, and they don’t know exactly which will be right shot.

 

(Wladimir Klitschko – BOSH!)

 

So instead of taking one shot and hoping it works, they press the button and spread their bets. It’s a focused scattergun approach – you’re taking many shots, but you still need to be in the right place, press the button at the right time, and nail a really great shot.

 

(Bob Beamon breaks the long jump world record in 1968)

 

It’s hard to make something great. But if you roll the dice over and over again, you are loading them in your favour.

 

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The best way to predict the future

The best way to predict the future is to invent it

— Alan Kay, Wired 06.12

I think this applies both the grand, world-changing things, and personally too.

Also – Alan Kay has the greatest tech CV of all time. He worked for Xerox PARC, Stanford, Atari, Apple, Disney, UCLA, MIT and HP.

 

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