Dropping a Dynabook: A comic that turned from Science Fiction to Science Fact

Some time around 1982, I saw an amazing comic on the wall of a Xerox Alto computer room at the MIT AI Lab. Given the subject matter, I assume the comic was originally created at Xerox PARC, possibly as part of the NoteTaker project, but can’t find any trace of it on the web. I have recreated it from memory, below.

The comic is explaining the events that happen when a Dynabook is accidentally dropped off the top of Half Dome in Yosemite National Park. Note that a free-fall calculator claims that it would take over 12 seconds for the Dynabook to hit the Yosemite Valley floor.

Dropped Dynabook Comic

T+00.000 Dynabook accidentally dropped from top of Half Dome.

T+00.016 Dynabook notices that

  • It can’t sense its user.
  • It is in zero gravity.
  • There is a 200 MPH wind from below.

Dynabook concludes that it is falling.

  • Turns off the display to save memory.
  • Opens a radio connection to El Capitan radio tower.
  • Begins backing up the user’s recent changes.

T+05.000 Dynabook hits a glancing blow to the side of Half Dome, breaking 3 of its 6 CPUs. The Dynabook reconfigures itself to continue working with the 3 remaining CPUs.

T+10.000 User data backup finishes.

T+11.000 Dynabook orders the user a replacement Dynabook.

T+12.000 Dynabook turns on an emergency locator beacon.

T+12.816 Dynabook smashes into the rocks at the bottom of Half Dome.

——–=====—–

Pro No Mo - I don't really need a MacBook Pro machine for hobby programming.

I’ve been trying to decide which Apple laptop to buy for hobby programming.

I’m leaning towards the cheapest laptop Apple sells, the 2019 MacBook Air. As far as I can tell, is fine for my current needs.

I specced out a more powerful and future-proof laptop, a 2019 MacBook Pro with 2x the RAM and SSD storage, but it was 60% more expensive.

I think it makes more sense for me to buy the cheaper laptop today, and plan on replacing it sooner. Especially because I have a lot of family members who would be fine with the cheaper laptop as a hand-me-down.

It does feel a little weird to decide that I don’t need a “Pro” machine. When it comes down to it, Xcode, a SSD and a retina display are all the “Pro” I need for hobby programming, and Apple has made those features available in the budget Air line.

Follow-up

In the end I bought the more expensive Macbook Pro. I am a sucker. :-)

The way I solved my daughter's "iMessage Activation" error

Writing these notes in case they help someone.

My daughter recently tried to add her Apple ID to her iPhone’sApple Messages app. (Settings > Messages > Send & Receive > Add Apple ID)

When she tried this, she got a dialog box where she could type in her Apple ID and password. After a 15 second delay she got an error dialog box:

iMessage Activation
  An error occurred during activation.
        Try again

She got a similar error message if she tried to activate FaceTime:

FaceTime Activation
  An error occurred during activation.
        Try again

I searched the Internet, and tried the various remedies that Apple and others suggested:

  • Reboot Phone.
  • Make sure the phone can receive SMS messages.
  • Enable/disable iMessage and FaceTime.
  • Log the iPhone out of iCloud and log back in again.
  • Visit icloud.com and check the iCloud account to see if there’s any warnings or errors.
  • Update the phone OS to the latest release version of iOS.
  • Try to register with WiFi enabled but Cell disabled.
  • Wait 24 hours and try again.

Having exhausted the home remedies, I contacted Apple Support by phone. Apple Support listened sympathetically, and ran me through the same steps, it roughly the same order. They also did a little bit of checking on their own of the Apple ID account to see if there were any issues.

They couldn’t find anything wrong, and they suggested that I contact my carrier.

I contacted my carrier, T-Mobile, and they ran me through the same steps as Apple. They also had me check out my phone’s ability to connect to the Internet for Data and SMS. They had me turn off my phone for a minute, so they could update my phone’s SIM. Unfortunately, nothing they tried helped.

In the end, what worked was to admit defeat. I had my daughter create a new Apple ID. She was able to use the new Apple ID to log into iMessage without any problem.

So far the drawback of this solution seem to be:

  • My daughter lost everything she had stored in iCloud.
    • For many people this would be a serious issue.
    • Luckily my daughter does not use iCloud at all.
    • She uses Google services, like gmail, Google Docs and Google Photos, that do not depend on iCloud.
  • My daughter has to re-add all her Contacts to her new Apple ID.
  • My daughter lost some game progress in some of her Game Center aware video games.

My guess is that the problem was on Apple’s end. The symptoms and cure seem to indicate that my daughter’s old Apple ID account was messed up in some small way, and Apple’s diagnostic systems were not detailed enough to detect or correct the issue.

So, anyway, I wrote this up to offer one more home remedy for people suffering from the “An error occurred during activation” message when trying to log in to iMessage. That message could have one of a number of different causes. If you are seeing it, please try the simpler remedies first, and please contact Apple Support (and your phone carrier’s support) for help. But if everything else fails, be aware that for some users such as my daughter, one solution was to switch to a new Apple ID.

2018 iPad Pro 12.9" Report

After weeks of research and thought, I bought a iPad Pro 12.9” 3rd Generation.

My impressions, based on a week’s use:

  • It’s too expensive, especially once you include the pencil and keyboard case.
  • It’s a significant improvement over the 1st generation iPad Pro 12.9”.
    • It’s physically much smaller.
    • The new keyboard is nicer.
    • The new pencil’s magnetic charger makes it much more useful than before, because now it’s always charged when I want to use it.
  • Flaws
    • The magnets holding the pencil to the iPad are too weak. It’s easy to knock the pencil off the edge of the iPad when picking it up or carrying it.
    • When the keyboard case is folded back, your hands touch the keys. This feels weird at first.
    • The hardware is held back by iOS 12 and Apple App Store limitations.

FWIW I think for most people the ordinary 2018 iPad, with a Logitech Crayon, would be a better purchase.

But I do enjoy using it!

Solving the anemone puzzle in Botanicula

Botanicula is a whimsical graphical adventure game for the iPad and other computers. One of the puzzles near the end of the game requires a bit of thinking to solve. When I came upon it, after a couple of hours of play, I was too tired to think. So I wrote some code to brute-force the solution. I’m unreasonably pleased that it worked the first time. Here’s the code, cleaned up and commented:

// Solve the anemone Botanicula puzzle.
// Number the anenome 1 to 7, left-to-right.
// Encode a list of anemones into a single integer, where bit 0 is anemone 1, etc.
func encode(_ d:[Int])->Int {
	return d.reduce(0, {x, y in x | (1 << (y-1)) })
}

// A list of which anemones are pulled down when a given anemone is tapped.
let moves = [
	encode([5,7]), // Tap anemone 1
	encode([3,6]),
	encode([2,4]),
	encode([3,5]),
	encode([4,1]),
	encode([2]),
	encode([1]), // Tap anemone 7
]

// Calculate the effect of tapping a given anemone |m|.
func move(state: Int, tap m: Int)->Int {
	return (state | // original state
		encode([m])) & // raise the item that was tapped
		~moves[m-1] // lower the items that need to be lowered
}

// Brute force solver. Try all moves to depth |depth|.
func solve(state: Int, goal: Int, depth:Int) -> [Int]? {
	if state == goal {
		return [] // We've reached our goal, don't have to make any moves.
	}
	if depth <= 0 {
		return nil // Ran out of depth, give up.
	}
	for m in 1...7 {
		let newState = move(state:state, tap:m)
		if let soln = solve(state:newState, goal:goal, depth:depth-1) {
			// If we could solve the newState, prepend our move to that solution.
			return [m] + soln
		}
	}
	// Couldn't find a solution.
	return nil
}

// Produce the shortest solution, if one exists.
func tryToSolve(state:Int, goal:Int, depth:Int)-> [Int]? {
	// Do a breadth first search by searching successively deeper.
	for d in 0...depth {
		if let soln = solve(state:state, goal:goal, depth:d) {
			return soln
		}
	}
	return nil
}

let start = encode([1,6]) // This will vary depending upon the state of the puzzle.
let goal = encode([7]) // This is the desired state (just anenome 7 raised.)
let solution = tryToSolve(state:start, goal:goal, depth:12)

print(solution ?? "no solution found")

Computer History Museum Oral Histories

The Computer History Museum Oral Histories are a wonderful project. They are deep, long, interviews with many different programmers. Lots of never-before-made-public details about important projects.

For example, this oral history by Oral History of Kenneth Kocienda and Richard Williamson goes into details of how iOS was designed:

Oral History Video Part 1

Oral History Video Part 2

Or if you prefer PDFs:

Oral History Part 1

Oral History Part 2

One of the interesting things I found out was that there was an attempt to use HTML/Web APIs to write iPhone apps, and that for the first two or three iOS releases some of the apps, including the Stocks and Weather apps were implemented as HTML/Web apps.

Trying to decide what personal computer to buy in 2018

I’m thinking of buying a new personal computer. I’m writing this essay to crystalize my thoughts on what to buy.

Why I don’t currently have a personal computer:

I must have bought twenty personal computers over the years, starting from an Exidy Sorcerer in 1978 and ending with a 13” Macbook Pro in 2013.

But since 2014 I’ve been without a personal computer of my own. The Macbook Pro’s been taken over by my son. I’ve got accounts on all my family’s computers, but when they’re all in use I’m reduced to using my work laptop.

My company has a “don’t use company resources for personal projects” policy. Since 2014 I’ve complied with this mostly by being too busy/lazy/distracted to do any personal projects. :-) But now that I’m helping my kids with their programming projects, it’s time to once again consider a personal computer.

Why not an iPad Pro?

I bought the original 12.9” iPad Pro and tried using it as a personal computer. It didn’t work out, because I like to program apps, and the iPad Pro doesn’t let you do much programming. And even if it did, the iPad Pro keyboard is not very good for typing.

The 2018 model iPad Pros have great hardware, including an improved keyboard, but they still don’t allow programming apps.

What’s my budget?

To put things in perspective, my first PC cost over $3,500 in current dollars, my first Mac was $7,000 in current dollars and my most expensive personal computer ever was a Macintosh IIfx at $20,000 in current dollars. I didn’t actually pay $20,000. I was an Apple employee at the time, and they had a “Loan to Own” program with extremely generous employee discounts. My most recent personal computer cost $1,650 in current dollars.

So, all things being equal, I’d say my budget is in the $500-$2,500 range. Perhaps more if there’s a really big benefit.

What do I want to do with it?

  • iOS programming
  • Unix programming
  • Web surfing
  • Content creation

I don’t need a high end GPU. I’m not planning on using it for PC gaming or local machine learning.

Laptop or Desktop?

Over the past few years I’ve been living the laptop lifestyle at both work and home. I like being able to take my laptop on trips. Recently it’s been useful to take my laptop around the house to my different kids as I help them with their programming projects.

So for me I think the laptop portability outweighs the bigger screen and better price/performance of a desktop.

One use case: iPhone development. This typically requires the ability to charge, and debug a USB-attached device at the same time.

The case for an iMac Retina.

Recently I’ve been using an iMac Pro at work. I really enjoy:

  • Speed of compilation.
  • Beautiful 5G screen.
  • Large number of ports.
  • Clean industrial design.

That makes me think that maybe a iMac 5G might be a reasonable choice.

Hardware specs:

  • 16 GB RAM
  • 512 GB SSD

New or used?

I don’t mind used, but it needs to be new enough to run the current version of Xcode.

Upcoming changes:

  • New macbook and iPad Pro TBA October 30th.
  • iMac 5G spec bump October/Nov?
  • New mac mini “pro” some time this year.
  • New mac pro some time 2019

Some possible configs

Hardware Price $
iMac 5K 32GB/512GB (includes third party RAM upgrade) 2400
Macbook Pro 15 32/512 3000
Macbook Pro 13 16/512 2200
Macbook Air 13 8/512 (not retina) 1400  
Hackintosh AMD 16/500 (reuse old monitor.) 900
Hackintosh laptop 600-900
Nothing, keep using current hardware. This is a good option during the school year. 0

Conclusion

In the end I bought a 2019 Macbook Pro 13”. I sometimes regret the small screen, compared to an iMac, but I like the price and porability.

Girls Who Code iPhone App Development Course Review

One of my daughters recently took the Girls Who Code iPhone App Development course.

This was a two-week summer course, taught 9 am to 4 pm in a high school computer science classroom. The first week the girls were taught the basics of the Swift programming language and iPhone App development. The second week the girls formed into 4-person teams and wrote their own iPhone apps.

The girls learned how to use modern software development tools like Stack Overflow, GitHub, and Trello.

Much of the instruction during the first week was by way of working through examples from a private Girls Who Code website.

What worked well:

  • The girls learned the basics of iOS app development, especially the Interface Builder.
  • The girls learned how to work in small teams, how to design apps, how to meet deadlines, etc.
  • The girls were motivated by the assignment of writing an app to improve society/the world.
  • The girls learned how to present their final project to a group.

What could have been better:

  • From watching to the final presentations, it seems like all the teams had trouble merging their changes. Every team reported that they had “lost” files and changes.
    • I think an hour spent explaining how to deal with git merges and conflicts, and more tutor hand-holding during merging would be helpful.
  • The course instructors were not familiar with advanced iOS programming, and could not help teams that wanted to explore more advanced iOS techniques.

Overall I think this was a well run course, with good value for money. It would be appropriate for a high school girl who was already comfortable programming in Python or Java, and was looking to learn the basics of iOS programming.

On-the-cheap Machine Learning, revisited

A short update on my On the Cheap Machine Learning blog post. After almost a year of use, I’m still pretty happy with the setup. The hardware has worked well. I haven’t done as much independent ML research as I had hoped, but I have contributed many hours of night-time GPU cycles to the Leela Zero open-source Go-game-AI project. I don’t think I would change anything about the build, and there’s nothing about it I want to upgrade yet.

However, in the past year a new option has appeared for on-the-cheap machine learning: Google’s Colaboratory project. Colaboratory is a free web-based IDE for writing machine learning applications. What’s especially cool about it is that comes with access to a cloud-based GPU. The GPU they provide is the NVIDIA K80, which is not the fastest GPU, but it’s still plenty fast for experimenting with machine learning. [Disclosure: I work for Google, but not in any groups related to Google Colaboratory.]

Colaboratory puts machine learning within the reach of anyone with a modern web browser, even if that browser is on a device (like a laptop, tablet, or even phone) that doesn’t have a high-end GPU.

I find myself using Colaboratory instead of my own desktop computer simply because my son’s often using my desktop computer for schoolwork, YouTube and playing games.

What I learned in 2017

Shipping an Audio Pipeline

In 2017 I shipped a new audio rendering pipeline for the iOS version of Google Play Music. I use it to render a particular flavor of fragmented MP4 that we use in the Google Play Music streaming music service. It was quite a learning experience to write and ship real-time audio code on iOS.

If you are looking to write an audio pipeline for iOS, I highly recommend basing it on The Amazing Audio Engine 2. Core Audio is a powerful library with an peculiar API. TAAE2 provides a much nicer API on top of Core Audio, without adding much overhead.

I had designed and implemented much of my new audio pipeline in 2016, but 2017 was the year that I deployed the pipeline to production.

I learned that shipping an audio rendering pipeline comes with a long tail of bugs, most of which have the same symptom: “I was listening to a song when it stopped”. I was able to find and fix most of my bugs by using a combination of:

  • Great base libraries. (TAAE2 and Core Audio)
  • A clean, well-thought-out design.
  • Unit tests.
  • Assertions.
  • Playback error logging that is aggregated on the server side.
  • A/B testing. (Between different versions of my audio renderer code.)
  • Excellent bug reports from alpha users.
    • My boss and my boss’s boss’s boss were the two most prolific bug reporters.
    • Several other alpha users went out of their way to help me diagnose bugs that affected them.

The error logging and A/B testing together gave me the confidence to roll out the feature, by showing how well it performed compared to the previous renderer stack.

Learning a new code base

In 2017 I joined the YouTube Music team to work on the iOS version of YouTube Music, which meant that I had to get up to speed on the YouTube Music code base. It’s a large complicated app. I found it difficult to get traction.

What finally worked for me was giving up my quest for general understanding. I just rolled up my sleeves and got to work fixing small bugs and adding small features. This allowed me to concentrate on small portions of the program at a time, and also provided a welcome sense of progress. My understanding of the overall architecture has grown over time.

Learning Swift and UIKit

In 2017 I audited both the iOS 10 and iOS 11 versions of the Stanford iOS programming class. In past years I’ve just watched the lectures. This year I actually did the programming assignments. These classes gave me a thorough understanding of Swift and UIKit. I felt they were well worth my time.

The reason I audited both the iOS 10 and iOS 11 versions of the course is that changes to the Swift language meant that the final programming assignment of the iOS 10 version of the class can’t be completed using Xcode 9. I was only able to finish the first half of the iOS 10 version of the course. When the iOS 11 version came out in December, I was able to resume my studies. I’ve done the first 3 problem sets, and hope to complete more before the end of my Christmas / New Years’ Day holiday.

Learning Machine Learning

I am fascinated by the recent advances in machine learning, especially the DeepMind AlphaGo and Alpha Zero programs.

In 2016 I built a modest home PC capable of doing machine learning, but it sat idle for most of 2017. I haven’t been able to do much with machine learning other than read papers and run toy applications. I am contributing computer cycles to the Leela Zero crowd-sourced Go player inspired by AlphaGo.

As a long-time client-side developer, it’s frustrating that there’s no “UI” to machine learning, and the feedback loop is so long. I’m used to waiting a few minutes at most to see the results of a code change. With machine learning it can take hours or days.

It is also frustrating that there are so many different toolkits and approaches to machine learning. Even if I concentrate on libraries that are built on top of Google’s TensorFlow toolkit, there are so many different APIs and libraries to consider.

Learning to let go of personal computing

In 2017 I continued to adapt to the decline of the personal computer. I am gradually retiring my local, personal computer based infrastructure, and adopting a cloud-based mobile phone infrastructure.

I’m surprised how smoothly the transition has gone. I still have laptops and PCs around my house, but the center-of-gravity for computer use in my family is continuing to shift to phones.

I’m happy that I’m spending less time on computer maintenance.

Looking forward to 2018

My engineering learning goals for 2018 are:

  • Finish the Stanford iOS 11 programming course.
  • Write a small machine learning app.
  • Help my kids improve their programming skills.

Hat tip to Patrick McKenzie for the writing prompt.