kip/bot/blog

When I was learning to program in C/C++, for several days/weeks and on several attempts I hit the pointers plateau — that thing which, conceptually, I couldn’t get my head around sufficiently to really grok the damn things. I eventually took a class that spent three weeks on it and now I understand them — their purpose, their usage, their style and how to troubleshoot them. A couple summers ago, I took a geek vacation between jobs and worked my way through the NYU ITP Physical Computing class curriculum and dug deeper into some Arduino stuff.

After a couple weeks, I hit a plateau. I needed things like shift registers to multiply the number of LEDs I could manage with the Arduino’s 13 pins; I needed to use a 555 timer chip to get pulsing, and there was a whole range of chips starting named 74______ that were described as “hugely useful” or “workhorses”. These things were critical and basic, like pointers, but (like pointers) it was impossible to find documentation for them that was comprehensible to someone with my level of experience. It was one of the weird places where the web let me down. I must have done dozens of searches, asked everyone I could for help, and could find nothing. Which is a drag, cuz those chips are what give real ooomph to physical computing projects.

Make Magazine has fixed that with Make: Electronics, an unusually good book even by O’Reilly standards. It contains in-depth explanations of how transistors and logic gates work at the physical level — giving you a more intuitive sense of how to work with them (rather than following steps by rote); detailed descriptions of the pins at three levels: the official specs, the occasional nomenclature, and the actual function; and some simple circuits that show what the thing does. The last might be the most important. Even the most basic 555 Timer chip examples I could find had so much stuff going on that it was impossible to isolate the chip and learn, iteratively through tweaking the code, what the things does. To top it off, the Maker Shed Store has a components kit that pulls all the stuff (including jumper wires) together for you.

The one weird thing about the book is in the index:

What the hell kind of alphabetization system is this?

Of course, it’s not like I have time to do anything on my nifty hand-made workbench. But it’s nice to have it when I’m ready. Hope springs eternal. Put differently.

while (!endOfUniverse)
hope.spring();
;

Ha!

For several years, Steven Johnson’s Emergence, E O Wilson’s Journey of the Ants, and Stephen Wolfram’s A New Kind of Science have bounced around in my head, inextricably/apophenically connected to ideas of creativity, invention, and generative systems. Wolfram’s book, which I could follow through the first three pages of each chapter before the specific science and maths lost me, came and went - people were open to its revelations, found none, then, it seemed, he sank into crankdom. But, in his TED talk, he seems to be pulling it together - computation science (as opposed to computer science or computing) is a source of ideas, beauty, computing power. Best line:

in a sense we can use the computational universe as a way of getting mass customized creativity … to routinely do invention and discovery on the fly … and find all sorts of wonderful stuff that no engineer or incremental evolutionary process could ever come up with.

Steven Johnson is one of my favorite writers. With the exception of Interface Culture, I would gladly see every one of his books (Everything Bad is Good for You, EMERGENCE, Ghost Map, and even The Invention of Air) be made mandatory reading people in digital design, digital strategy, digital marketing. Johnson goes deep into cognitive patterns, longer arcs of human behaviors around entertainment, information-seeking, and learning and provides great frameworks for understanding the features and technologies that are usually the center of gravity in digital discussion.

His Time article on the iPad does a nice job of setting the right tone for discussion. Rather than being millenial (Apple fanboys) or crotchety (iPad haters), he grounds the conversation in the longer arc of how we’ve envisioned computing in the last ten or so years:

If you time-traveled back to 1995 and asked the leading futurists of that time where our machines were soon to take us, you might well have heard just as much rhapsodizing about document-centric interfaces as that about hypertext and the World Wide Web. The first generation of software interfaces forced the user to think too much about the tools, the story went, and too little about the task. …

The weird thing about the iPad is that it has landed us 180 degrees from where we thought we were heading. The iPad interface — like the iPhone’s — tries to do everything in its power to do away with documents and files. There is no Finder or root-level file navigation. It’s apps, apps, apps, as far as the eye can see. According to the demo last week, the main way to launch iWork documents is by an internal document-selection process after launch, where your files are presented to you in a gallery format.

I truly don’t know how I feel about this. It might be genius. Maybe most users are more confused by Finders and File Explorers than I’ve realized. But I can’t help thinking that if the iPad really wants to be a device that you might take on a business trip instead of the laptop, it’s going to need a little more document-centrism.

Couple things to love here:

- pointing out that there is a widget-centricity to the iPad. Hadn’t noticed it, but now that I think about it, it sounds like a bad way to make netbooks suck less.

- The comment that “most users . . . might be more confused than I realized”, highlights another weird dynamic in the discussion — just how bad do laptops and netbooks suck? Aren’t hundreds of millions of people living with these supposedly “fatally flawed” devices? A lot of the dialogue about the iPad as netbook talk about how unpleasant people find computing, but is the problem of OS stability and feature bloat so bad that we need a neutered appliance to replace it?

And what a great writer Steven Johnson is. I’ve been scribbling in my notebook, in evernote and two blog entries (this’n and this’n here) to get this idea across:

The iPhone revolutionized smartphones, but I think we all accept that smartphones were in our future. There is no equivalent consensus that tablets or couch computers or casual computers are inevitably on the road ahead. We don’t even agree on the aims here: Is the iPad replacing the laptop or supplementing it?

Anyway, a great article.

One of the smartest designers I know gave a typically compact and smart assessment of the iPad:

DOA. Apple does better (in the last 10 years or so) when it re-imagines categories, not when it invents them. I’m sure I will regret saying this, but that’s how I feel right now.

It does a nice job highlighting Apple’s strengths (re-invent what’s out there after drafting on others’ experience in the market and with an unwavering focus on user experience), but it also hints at the bigger problem: it’s trying to be several categories (reader, netbook, bigger media player, game platform, web browser), under one technology (shiny, thin, touch screen, with none of those nasty mechanics that collect crumbs from your lunch) without being any one thing that is clearly needed.

While Apple often wins by delivering better versions of stripped down, less function-laden things like the iPod, the iPad is doing this across too many categories and likely to fail in all but one:

Reader Steve Jobs infamously said he would never do a reader because people don’t read anymore. He’s actually onto something — some people are passionate readers, while most do it casually. This means the number of passionate readers is too small for an e-reader to be as big as the iPod. The iPad won’t serve either audience well. It will suck for passionate readers: the battery life is dubious, the finger smudges will be a drag, and most important, the backlighting will be prohibitive. Jane Jepson, the creator of the OLPC screen and founder of Qi technologies (LED displays) likened reading from a computer screen to putting a flashlight in your eyes, it’s unsustainable for passionate readers. Casual readers won’t read enough for it to be worth dropping a big chunk of change and things like beach reading, subway reading will be dicey with a fancy device that large. The math will look better than the Kindle’s — spending $400 on a Kindle vs buying books is a quick and obvious decision for many — but the all-in-one argument is pretty weak when it comes to the reading.

Netbook Jobs’s digs at netbooks totally miss the value they have for people who like having a portable work device. The iPad doesn’t replace the processing power or precise mousing needed for real apps like word processing or spreadsheets with graphics, and it’s still unclear whether typing on glass for extended periods of time (like writing something longer than an email or entering numbers into a budget) works for people.

Bigger Media Player This one is tricky to guess, but I have a hard time picturing people dropping serious coin on a third screen that is bigger than their phone but smaller than their TV. Where would you use it? To watch something in bed before going to sleep? Is that worth the cost of getting a decent flat screen?

Game Player Again, a risky proposition. What’s the market for people wanting to play games bigger than the iPhone but smaller than their console? What do those games look like? They’ll lack the immersion of a TV or computer screen game because it’s too small, but will they add to the little games of the iPhone?

Web browser Right on! The video on apple.com references the superior web browsing experience of the iPad many many times, and they’re right. Having the iPad in the living room (with a remote built-in) so I can do quick simple email tasks (like writing “you’re very welcome” as in the video, or forwarding with “FYI”, or deleting what you don’t need) and look up baseball stats while watching the Yankees on an iPad is vastly superior to using overheated macbook or my crunched netbook keyboard. I do a lot of web stuff while I watch crap TV and baseball, and, as a reasonably affluent convenience-obsessed guy with some concerns about the aesthetics of my appliances, this might be enough to see my way clear to $500.

But that’s it. The iPad will be a high-end version of the web appliance that we all talked about several years ago. Only it will be too fancy to use while cooking (one of the standard scenarios we all gushed about), and much too fancy for us to call it an appliance.

It’s got a look (or maybe it’s the music):

The first 1:30 of the documentary Moog has a great line from Robert Moog, the inventor of the synthesizer and one of the parents of electronic music: “I can feel what’s going on inside of a piece of electronic equipment.” There are other passages in the movie (which has great tributes from electronic music performers such as Sun Ra, DJ Spooky, Mix Master Mike, Electric Skychurch and a wonderful animated title sequence), where he shows how visualizes the interactions of circuits and components. Interestingly, he also points out that his synthesizers are analog instruments, not digital ones and that he knows musicians approach the physicality of the electrical vibrations in the same way they approach violin, guitar, and piano strings.

Anyway, that close connection to material — which strikes me as a result of closely working and experimenting with them — as a source of inspiration, quality, and innovation is a theme near and dear to me. So, I clipped the movie and encourage would-be innovators and inventors to check it out. Moog the man is charming, engaged, lives a full life, and could be a more earth-bound person to learn from than Steve Jobs, Edison, and other lofty luminaries.

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PS One last reason to watch the movie is a Schaeffer beer commercial in which a 70s-mustachioed dude in polyester, riffs on the Moog for 20 seconds before the jingle (”Schaeffer is the one beer to have when you’re having more than one.”) Worth the price of admission all by itself.

A colleague just sent me a link to an MIT student project/installation site, called “Personas: How does the internet see you?”, which is part of a larger exhibit called Metropathologies. You type in your name and it assesses what you are/do/care about based on on-line presence. Fun idea, great animation during the algorithm crunch, surprising results:

(Click image for larger, cleaner version.)

Amused: sports so large, fashion that it shows up at all (must be based on client lists)
Saddened: politics is so little (and in black! like a mournful armband)
Pleased: design and art seem to be big
Concerned: medicine?
Can’t tell if this blog is covered in it . . . that might explain the sports, what about flickr? Need to explore.

Stumbled across the OLPCorps on Flickr this morning. The program is pretty awesome: propose a teaching plan for a 9 - 10 week program in any African country if you get accepted, they help you go, hook you up with equipment, and then you participate in a conference about computing, constructivism and your experience. Best part of the find, though, was an interesting nugget buried in the FAQ for the program:

[Question] Can we give XOs to several schools to start computer labs?

One does not think of community pencils—kids have their own. They are tools to think with, sufficiently inexpensive to be used for work and play, drawing, writing, and mathematics. A computer can be the same, but far more powerful. Furthermore, there are many reasons it is important for a child to own something—like a football, doll, or book—not the least of which being that these belongings will be well-maintained through love and care. Read Core Principles for more.

The picture at the top of this post has nothing to do with OLPCorps. I couldn’t find many OLPCorps pictures, but in the process of searching came across this one. The Lego attachment is a viewfinder you attach to the laptop, in order to use the XO as a point and shoot camera.

or should be to a certain extent, if we take recently anointed Google numbers guru Hal Varian’s words to heart. The former economist (a very heavy maths-focused one at that) is frequently quoted as saying that statistician will be the next ’sexy’ job (just like engineer was), but the line, from McKinsey goes much deeper:

I keep saying the sexy job in the next ten years will be statisticians. People think I’m joking, but who would’ve guessed that computer engineers would’ve been the sexy job of the 1990s? The ability to take data—to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it—that’s going to be a hugely important skill in the next decades, not only at the professional level but even at the educational level for elementary school kids, for high school kids, for college kids. Because now we really do have essentially free and ubiquitous data. So the complimentary scarce factor is the ability to understand that data and extract value from it.

I think statisticians are part of it, but it’s just a part. You also want to be able to visualize the data, communicate the data, and utilize it effectively. But I do think those skills—of being able to access, understand, and communicate the insights you get from data analysis—are going to be extremely important. Managers need to be able to access and understand the data themselves.

I recently started working my way through Ben Fry’s Visualizing Data and adding Fry’s process to Varian’s shows some of the deep changes people need to make in order to embrace the new numeracy. Visualizing Data is more about Fry’s Processing language and how to hook it to datasets than it is about thinking visually or how to work through those datasets to find a pattern or evocative image, but it begins with a seven-step process:

ACQUIRE — Obtain the data, whether from a file on a disk or a source over a network.

PARSE — Provide some structure for the data’s meaning, and order it into categories.

FILTER — remove all but the data of interest.

MINE — Apply methods from statistics or data mining as a way to discern patterns or place the data in mathematical context.

REPRESENT — Choose a basic visual model, such as a bar graph, list, or tree.

REFINE — Improve the basic presentation to make it clearer and more visually engaging.

INTERACT — Add methods for manipulating the data or controlling what features are visible.

This does a nice job of highlighting that Varian’s charge is a mix of skills for managers, practitioners, and interpreters alike. Some of the steps are naive or described in a way that invites unhealthy simplisticism (simplicity == good, simplisticism, the thing we often get instead of simple is reductive, which is always bad). MINEing and REPRESENTing are the steps where numbers emerge into something living and actionable. MINE, as defined by Fry, is focused on software, rather than cognitive styles and elastic minds, for the generation of insights and pattern recognition. Certainly software is needed, but the hypotheses and candidate patterns you validate with the software come from soft eyes, something I blogged about a while ago. Similarly, REPRESENT is posed as choosing from a list of standard data tropes. But hey, it’s a software book and we all know Fry is more visual than that.

The real point is that this path shows a range of skills and validation even broader than what Varian points to. Someone working with someone working with data needs to know, understand, and respect the technical underpinnings of the first two steps, which set up the infrastructure of your entire data exercise. Like software, you need to measure twice, cut once here because this is the infrastructure of your inquiry and you won’t be able to change it quickly. Filter, mine, represent are subjects for another book perhaps, but they put you in the land of Tufte, Orwell, as well Flowing Data and statistics — a mix of simple communication, humanities, and the techniques of numbers.

The last one was also pretty interesting. I love how Fry reminds people to let the data grow with the audience by giving some interactivity. Sure, you do the first crack at it, but letting your audience go deeper, create their own juxtapositions, or simply play with the data gets them more engaged, allows for even more meaning to emerge from the data.

http://www.kipbot.com/blog/2008/03/05/dd-my-grad-school-footnote/

Interesting read in May 2009 issue Servo Magazine, which I got free at Maker Faire about new ways to teach groups.

The writer/editor, Bryan Bergeron, teaches a course on technology and the future of healthcare at Harvard Medical School. Each year, a session of the class simulates the creation of a business to give students a brief sense of the hours, adrenaline rush, complexity, and many dimensions of a tech start-up. This year, he did something new. He had his class break into two teams and gave each of them a Lego Mindstorm NXT kit and an hour (another link here). The assignment was to “design, build, and program a robot that could traverse 32″ and then stop just before the obstacle.” (This is a classic, and continually revisitable, robotics program - a combination of “hello world” and a sorting algorithm. There are a million ways to have a robot measure/detect/sense/calculate the distance it has traveled with various tradeoffs around accuracy, amount of code, use of resources, speed, etc.) The winner would be whichever person’s robot got closest to the goal. (In the case of a tie they would look at business plans. This course didn’t teach the immutable law of marketing that quality and performance just don’t matter, apparently.)

The two groups further subdivided themselves into teams: the business crew which figured out a model for selling the robot; the programming crew which learned how to program the thing; the “alogrithm” group addressed the problem of how to measure 32 inches; and a fourth group that attempted to spy and prevent spying(!). Both groups built their robots successfully and the difference in performance was one millimeter.

It’s important to point out, and this is the point of the column, that these people were not technical. They weren’t programmers. They learned the NXT language and interface on-the-fly and then applied that knowledge to the solution of their problem. They focused their time mostly on solving the problem (creating an algorithm for moving the distance, essentially designing the product), implementing it (figuring out the production and engineering), and debugging and trying additional ideas (optimizing). Valuable modes of learning both for individuals and teams, enough technology to open people’s eyes to some of the complexities of tech development (but not so much as to kill the exercise).

Most important, though, it was a real-life problem to solve. Lots of team building exercises tend to focus on hypothetical situations into which you can throw hypothetical answers. The intangibility of the assignment forces us to say the process is what matters, not the outcome. But, really the process can suck too — one person can do it all so it looks good when you present back to the group, the conversations can be blue sky with no grounding, etc. This exercise forces people to think analytically, solve a problem, communicate, and really, really work together.

Kind of an adult version of another President Nerd charge featured at Maker Faire: