Archive for the 'Apple' Category


The reason to upgrade to iOS 4.0.1

There’s a great reason for iPhone users to upgrade to the new iOS 4.0.1, and it’s not the changes to the signal strength indicators: it’s the reversion of the behavior of the wake/sleep button.

There are two principal complaints users are making about the iPhone 4: the loss of signal when you bridge the antenna with your salt-water hands, and the oversensitivity of the proximity sensor (aka the “I keep hanging up on you with my cheek” problem). I’ve found the antenna issue to match the conventional wisdom, and have had far fewer dropped calls on the iPhone 4 than on any previous model. The proximity sensor, though, has been a real problem, as I’ve been hanging up, accidentally muting calls, and starting FaceTime calls – no matter how much I think I’m holding the handset away from my cheek at a weird angle.

Of course, I used to press buttons accidentally on previous versions, especially when I would put the phone in my pocket and wear my handset. In every version of the iPhone and iOS before 4, this was easy to avoid: pressing the wake/sleep button during a call would lock the phone. So I’d press the button as I put the phone in my pocket.

In iOS 4.0, that behavior changed: pressing the wake/sleep button during a call would hang up the call. So for the first week, I’d try to avoid the accidental hangup problem by pressing the wake/sleep button, and so then I’d hang up on them anyway. This was a clear change in behavior that I haven’t seen documented anywhere. (I don’t know if it behaved the same way on the 3G or 3GS.)

In iOS 4.0.1, the behavior is reverted – pressing wake/sleep locks the phone again. So now, if you make “always lock when you start the call” part of your muscle memory, you won’t hang up on people quite as often. And if that isn’t what you want from your phone, what is?

UPDATE: It turns out that I was entirely wrong – Elan Lee had a larger array of phones to test than I did, and he determined that the behavior didn’t actually change – it’s just that the wake/sleep button only locks the phone when your headset is in. Since I’d never had the cheek problem before, I wasn’t locking the phone when I held it to my ear – that hangs up in earlier models as well.

I did hear from a few other folks thanking me for telling them about the locking-with-headset trick, though, so my doofusness wasn’t entirely useless.


Your iPhone flies (to you) for 46 cents

It also bends time and space

It also bends time and space

On Friday, June 19, the iPhone 3G S launches, and for the first time, Apple has made launch day home delivery available. This has made some things clear – for example, we know that phones are shipping from China to Alaska all on the same day. I was curious about the magnitude of this delivery – size, cost, etc. Here are some estimates:

Total Sales

Apple sold at least 1 million 3G’s in the first weekend. It’s reasonable to assume that the number will be about the same – ease of home delivery counterbalancing the extra few days. So we assume 1,000,000 phones shipping from China.

Getting to the US

We know that the phones are shipping from Hong Kong to Anchorage via UPS. Unless UPS has some undiscovered stealth supertechnology, it’s by plane. Let’s assume they’re all shipping at the same time (though that doesn’t matter, it’s more interesting).

I don’t know the whole UPS fleet, but they bought 27 Boeing 767-300ER’s in 2007, so we’ll use those for our size analysis.

How many planes?

The limiting factor could be volume or could be weight.


The 767-300ER holds 30 LD2s. Now, the phones could be shipping in of three forms:

  • raw phones in trays to be Apple-packaged and ship-boxed in Alaska or another port.
  • Already-assembled Apple boxes, still not packaged for ship.
  • Fully shippable boxes (for home delivery)

Obviously the tradeoff in each case is volume you can ship v. assembly time on landing. The first seems really unlikely – there’s no way accessory boxing is happening across the country in ports in such a tight timespan. I would assume the second case, because ship boxing is a partly-automatable process and because the volume savings are so significant.

We don’t know the size of the new 3G S box, but the 3G box was 2.25″ x 3.5″ x 5.75″, so let’s assume the same dimensions. Each LD2 is 61.5″ x 60.4″ x 64″ (in their more generous size).

As I haven’t yet solved the packing problem, let’s just assume 80% utilization of the full volume. (That’s probably generous with pallets and such.)

181683 in2(LD2 volume) / 45.25 in2 (3G volume) * .8 = 4200 boxes

So 30 DL2s = 126,000 boxes: thus it takes 8 fully-loaded cargo planes to bring 1,000,000 iPhones to the US.


Weight’s not a limiting factor. UPS says my package is 0.5kg, and the 767-300ER can carry 96,870 kgs – at 80% utilization that’s 155,000 boxes/plane.

Estimate, then, is 8 cargo planes to get the phones to the US. I like to think of them in Top Gun formation.


The 767-300ER uses 3.47gal/mi: the air distance is ~5100 miles, so each plane uses 17,700 gallons: the estimated price today for jet fuel is $1.80/gallon (nice price if you can get it – assumes bulk discounts), so that’s $32,000 for gas – add another 20% for overhead and you have ~$38,000/flight to Anchorage. Anchorage to Miami is another 4000 miles: assume an average of 2000 miles for in-US travel (and higher overhead) and you add another $20,000/flight’s worth of travel (obviously spread across many other planes, many with smaller cargo holds). That’s $464,000 in flight costs, or $0.46/phone. (I haven’t factored in packaging and local delivery costs – either from Shenzhen to Hong Kong [23 miles] or from the airport to your home or store – which aren’t insignificant.)

It’s also ~57,000 lbs of CO2, but, y’know, whatever.

Final Words

Only $500K to get the phones to local ports in the US? Really? I’m surprised it’s so low, but math is math (though my packing assumption could be flawed).

If you add the UPS packaging in China or HK, you probably add 3-4X the planes and the cost, so there’s no way that’s happening. Anchorage was probably quite busy today.


Amazon’s iPhone mobile app and privacy

The new Amazon mobile app for the iPhone is excellent – well-designed, a great mix of iPhone and Amazon visuals, and easy to use. Despite the lack of Gold Box integration, I’ll use it all the time.

And the idea of Amazon Remembers – a place for you to take photos and have them stored online – that’s neat, though obviously overlapping with dozens of other photo storage services. It also offers product identification – take a picture of something and have people tell you what it is.

Remembers, though, breaks the social contract: it makes pictures that reasonable users might assume will be private, and makes them public.

As has been documented online, when you take a picture and upload it to Amazon Remembers, it’s sent out to Mechanical Turk users for product identification. That makes sense – product identification is hard and mturk is great for these kinds of problems – except that

  1. People might use Amazon Remembers for non-product images. The marketing materials talk about how you _can_ use it for product images, but not that it’s the only use of the service. Here’s the first page of the Remembers tab in the app:

    Amazon Remembers iPhone image, first screen 

    And here’s the pre-picture screen:

    Amazon Remembers, Screen 2

    No content on either screen assumes that it must be a product, or that other people besides you will see it.

    For the user who does click “What happens to my photos?”, you get partial information:

    Amazon Remembers, Screen 3
    This does say that people look at it, but it’s not clear who those people are.

  2. Every picture is then visible to strangers via Mechanical Turk. There’s no obvious pre-screening of images to make sure they’re acceptable. Keep in mind that Mechanical Turk respondents are not Amazon employees – they simply can’t be expected to keep private images private and not to violate people’s privacy. To test this, I took an image of a young-looking, non-recognizable Dakota Fanning and added a fake name and address to it: I then took a photo of that image and added it to Amazon Remembers. Here’s the image:

    And here’s the Mechanical Turk hit that appeared <15 seconds after the image was sent up:
    Amazon Mechanical Turk for Amazon Remembers
    So to review: I posted a picture of a minor with a name and an address, and that picture showed up on Mechanical Turk, in front of strangers, immediately. (To their credit, the Turkers who saw this image did recognize it as Dakota Fanning, and sent me to this head shot.)

The violation is that people will assume that memories are private. This isn’t the same thing as Amazon’s Customer Images, for example, where customers know when they’re using the feature that the images show up on the product page. 

The principle is pretty simple: if you’re going to take something that people might assume to be private and make it public, you have to be explicit about it. This approach is either poorly-thought-through or sneaky, but either way, it’s a violation of customer’s trust in Amazon. This problem could be seriously reduced with much clearer messaging, or eliminated with employee human review (which almost certainly won’t happen). 

I don’t know how large this problem is – I’ve looked at ~30 submitted images, and only one was an obviously personal image, and had no (obvious) identifying info (though there could be data encoded in the image). But the people picking up the app now are likely early adopters, and are perhaps more likely to be well-informed or to read the fine print. 

(Disclosure: I worked at Amazon for four years, working on customer-facing features that dealt with similar issues.)


On Apple, Amazon, Reviewing, and Large Companies

Two interesting stories going around in the last week, which I find to be similar (even if their impact is different): Apple’s being raked over the coals for rejecting an iPhone app that duplicates Apple functionality, and Amazon’s been dealing with the customer review attack on Spore, including purging and then restoring all of the reviews.

As I’ve mentioned before, I used to manage the Amazon customer reviews business, and so I know very well what the current team is going through. My assumption is that the Apple app store review business has some similar processes and problems. Here are some things I learned while dealing with this:

You start with some philosophical rules, and you try to make them stick. Providing guidelines is the only way to start. Example philosophies for Amazon (made-up, these aren’t real, don’t quote them anywhere else) could include “our customer is the Amazon buyer” (so no, Ms. Vendor, we won’t take down the negative reviews of your book, even though you spend a lot of money on advertising with us), “we eliminate reviews with demonstrably false information”, and “fairness is more important than justice” (so if you generally write good reviews and then get caught plagiarizing once, you can be given more chances). 

All sensible on face and all make sense to folks who think in these kinds of abstractions all day – there may still be debate but these are good places to start. 

There’s a clear chain of command for decisions. The escalation path from “customer service rep in her fourth week receives a review complaint in the mail queue” to “Jeff decides the review stays” should be very clear. (In my ~2 years dealing with customer reviews, btw, Jeff only engaged once on actual content, and the issue was much larger than just reviews (and he was getting hundreds of mails on this topic) – he generally trusted the heads of these teams to do the right thing as long as they could articulate the philosophy.)

All of this sounds good, of course, but then people get involved. And customer service reps are trying to interpret the philosophies (if they can find them among hundreds of pages of other rules), and some of them are judgment calls (what is “demonstrably false?” If I say “the defibrillator didn’t work and my dad died,” is someone going to check? are comments on voting records trustworthy? etc.) that different people will make, and of course you don’t want Jeff or Steve Jobs or anyone making every decision.

So it’s messy, and when it’s messy, strange things happen – reviews appear and disappear, apps go away and come back (like Netshare), etc. 

This is a long way of saying that it’s entirely likely that the banning of Podcaster is a problem of human judgment in a theoretically well-structured system – not least because the decision seems inconsistent – and that could easily come back, not because of a correction of a philosophy, but because of a correction of a human error.

Now, it’s Apple’s responsibility to make that correction, and then to treat the errant employee with respect and look at how the company can do a better job. 


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