Sep

The bicycle inventor’s dilemma

I saw someone operate an ultrasound machine today, and was struck by the fact that there exists a class of machines that require particular skill to operate. For example, a bicycle. How do these machines get invented? Does the inventor have to also be the first skilled person who demonstrates the machine? How does the inventor, who, starting off as a rookie, even know whether the machine operation falls within the realm of the humanly possible?

That’s a lot of questions; I’ll start off with the bicycle, about which Wikipedia has a fairly detailed article. Apparently, the first bicycle was foot-driven like the Flintstones’ car; it was only many decades later that the crank and pedal were added, causing a significant increase in the difficulty of driving it.

This evolutionary path provides insight on the parallel roles of the inventor and the expert user in the development of the bicycle; the first bicycle, which its inventor ‘drove’ for eight miles in one hour, posed no challenge to the user because his feet were always on the ground. Therefore, there was hardly the need for an expert user for the routine use of the cycle. However, it is likely that over a period of time, daredevils and show-offs raised their feet from the ground for extended periods of time, especially going downhill; these were the expert users who eventually figured out, after much practice, that it was possible to drive a cycle without necessarily having your feet stay in contact with the ground. It was probably only at this time that manufacturer-inventors caught on to the possibility that better bicycles could be designed if a prospective bicycle user was ‘skilled’, i.e. he could be trained to drive a cycle, instead of being able to do so from the word go.

This is also true for specialized devices. For example, I have been involved in the last few weeks in discussions about welding simulators, mostly in the context of skill development of welders for the Indian job market. I came to know something amazing: there is a ‘sliding scale’ of skill in the welding business, and at the top end, the expert welders get paid Rs 4 lakhs per month to weld. They do such tasks as welding inside nuclear reactors and submarines and tasks that require incredibly high precision. And they get paid a correspondingly incredible salary - the CEO of Infosys earns only twice that amount – for nothing more than a pair of steady hands.

No one would have thought of inventing welding if its first use had required that much of skill. This is the vicious cycle: the inventor does not have steady hands (nor does he need to); the ‘expert user’ does not even have an engineering degree (nor does he need to); yet, both the invention and the expert are needed to complete the solution.

It would take an incredible visionary of an inventor to not only come up with an invention, but to also foresee the level of expertise that would develop in a user of the invention.

I’ve wondered how game designers overcome this problem, and if any of my readers are game developers, perhaps you can enlighten me. At the hardest and highest level of a game, chances are that it is way too difficult for the game designers to ever finish. How do they know that there exists the expert player who will be able to finish that level? How do they know they have not made it too difficult, not being able to go anywhere near that level themselves?

It’s a very intriguing question. I have no idea what the answer is.

259 days ago Short URL 1 Comment

Economics/Engineering/Society

Sep

I don’t believe in evolution

I don’t understand how evolution works. And I am not sure if I believe in evolution at all.

Perhaps I should go and read a good book about it, which I haven’t had the good fortune to do for all these years. But as things stand, my layman interpretation of evolution leaves large holes which are slowly overwhelming my schoolboy belief in evolution itself.

The big question I have is about the dynamics of evolution. Sure, I get the idea of the ‘survival of the fittest’ – it’s obvious that if there are a group of a thousand creatures, ostensibly of the same species but in which one group had a higher chance of success, that group would eventually dominate (and perhaps exterminate) the other group.

The hookey parts of evolution come up when people start talking about ‘random mutations’ causing adaptations. This is wholly unbelievable to me.

I heard an example many years back – in my school days – and I do not know if it is factually correct, but it nonetheless is a good example of fallacious reasoning about evolution. Apparently, a tribe living in the Amazon rain-forests carried wood through large tracts of jungle as part of their livelihood. In some convoluted fashion (which I cannot remember), this wood-carrying ability was critical in their ability to eke out a living in their hunter-gatherer way of life. The way this tribe would carry timber was to balance logs on their shoulders, resting them just below the neck.

As the story goes, when this tribe was studied by anthropologists, it was found that they had abnormally thicker skin in the shoulder area, which was much more resistant to chafing or injury. This was held up (for me) as a classic story of evolutionary adaptation. The hypothesis was that a group of people in this tribe had thicker skin (for random reasons), and this created a higher chance of survival, therefore the trait for this was propagated through the entire community over a few generations.

(I am reminded of a racist joke that one of my friends told me some years back about why some Africans are so tall – because they have to jump for food aid packets dropped from airplanes, the taller ones have the evolutionary advantage.)

A more credible example is the high prevalence of sickle-cell anemia among people living in those parts of Africa that have a high risk of malaria; while sickle-celled RBCs have health risks, these are more than offset by the benefit of having a lower chance of contracting (and dying from) malaria, so it confers an evolutionary advantage. And according to evolutionists, while the first sickle-cell person was a random mutation, this conferred such an evolutionary advantage that a majority of the population eventually acquired this characteristic.

My concern with this theory is the extrapolation from ‘increased chance of survival in one organism’ to ‘widespread prevalence in the species’. I think this would be true only in the most extreme cases, where the conferred ability is so dramatic that it somehow creates a ‘superman’. In the timber-carriers example, imagine that one individual suddenly and randomly was born with thicker shoulder skin. Yes, this confers an increased chance of life and procreation – but how much increase? Considering that there are probably a million other factors that affected this individual’s longevity and fertility, I would say the increase is likely to be less than 1%. It would be a miracle, more or less, for this 1% to pay off in the form of enough discrimination in life and reproduction that it becomes widespread among the entire species.

So the chance that an adaptation is propagated because of a single mutated individual is low.

Another objection is the precise nature of gene mutations that cause such a specific ‘enhancement’ to occur. Is it a single gene that governs sickle-cell production in a human being? It seems a bit unlikely. And if the mutation hit more than 1 gene, what is the likelihood that the only effect of the mutation is a single, specific enhancement? It seems far more possible that, instead, the mutation would cause a disability – the inability of the individual to perform certain acts – rather than an enhancement. So this whole random mutation concept has a stink of improbability around it.

What if mutation took ‘multiple paths’? That is, instead of originating in a single individual, it originated as a mutation in, say, 1% of the population over 1 generation. Then the chances of the 1% advantage in 1% of the population eventually translating into improved ability to live and multiply is much higher. The risk is lower, the chances work out.

But for this to happen, there is an important missing link. And that’s the causal link between the environment and the mutation.

The theory of evolution would be much more compelling if there was a mechanism by which the livelihood of a wood-carrier somehow worked its way into that individual’s DNA over a period of time. For example, if repeated (non-fatal) malaria attacks somehow caused the mutation rather than the other way round (viz. that the mutation caused the malaria attacks to be non-fatal). In other words, the human body (or more generally, any living being) has a feedback cycle by which an environmental factor – such as lighting, or stress, or cell death – finds its way into the DNA as a sort of ‘micro-mutation’. The body would either keep or reject this micro-mutation through a process of internal Darwinian survival, until eventually this mutation was transmitted to the next generation. The key here is that since the mutation is not random, it happens in multiple organisms within the species simultaneously (albeit randomly) and therefore dramatically increases the survival differential between the haves and the have-nots (so the speak).

I have long been fascinated by this possibility for a very selfish reason – because if such a feedback cycle exists, it represents the holy grail of Engineering. That is what we should mimic as engineers – a design process that somehow triggers mutations in existing organisms, causing them to ‘develop’ better solutions to the problems that their environments throw at them.

More on this in a later post. But I am very eager for reading material – if anyone has a reading list for evolution, please send it to me!

264 days ago Short URL 2 Comments

Engineering/Nature/Philosophy/Science

Aug

Inventing Aakash

Through a series of wheelings and dealings, I have gotten myself infiltrated into the Aakash project, which (if you live on a different planet and therefore haven’t heard yet) is the Indian Government’s plan to make a $35 tablet and universally distribute it to students. There was a review meeting yesterday for Aakash 3 (Aakash 2 is now shipping, as I understand it) and I have some strong opinions about the process by which it is conceptualized.

First, I must say the people engaged in this project nation-wide are very forward-thinking about the kind of applications that Aakash will have. I can’t reveal specifics, but I came away from yesterday’s meeting with a very upbeat feeling that this device, widely deployed, could revolutionize education in the country. The promise justifies the investment of time and effort that people are making on the project.

It was interesting to see the way Aakash is being designed (by committee), and contrast it with the way I designed Avaz (almost alone). And the way I was taught to design products in my first year in college…

The objective of product design is to build something that is useful to the customer, with the least amount of effort and cost, and in a reasonable amount of time. (As Steve Jobs said, ‘Real engineers ship.’) However, making a product involves making literally thousands of design decisions, from the color of the casing to the clock speed of the microprocessor. And this is true even if a product doesn’t need fundamental invention. What differentiates the good product engineers from the bad, is the way in which they are able to make those decisions quickly and efficiently, while being able to think outside the box, while always keeping the customer’s interest in mind.

It is not at all easy to do this. The problem is cross-linkages; if you add muscle power to a car, you increase its weight. If you add rich user experience to a tablet, you increase its cost. How do you make those trade-offs?

There are a lot of good engineers and product managers who make those decisions by the gut. They know the rough countours of a product spec (usually from competing products out there) and are able to tweak in the right areas to get things moving. However, if you are making a ‘first-of-a-kind’ machine, you’ll have to use some kind of process to stay on top of the Engineering beast.

When I started designing Avaz, I started with ‘use cases’. I visualized ten kids who would be the ‘power users’ of Avaz three years from its launch. They would use Avaz in different ways: some would talk to their teachers and parents using Avaz, some would achieve independence with their daily activities, some would use it for taking exams and finishing schooling, some would use it for creative expression. I visualized them to an incredible level of detail: their age, their gender, the occupation of their parents, the town where they lived, the number of aunts and uncles in their families… Then I visualized how these ten kids would use Avaz in their daily lives. I must emphasize that though none of the kids were real, they were all composites of real people (and I kept track of which real kids they were modeled from). This formed the basis of my ‘customer stories’. I wrote my customers’ success stories even before I had a product concept!

Then I used these stories to create a list of ‘user specifications’. These are specs for what the user would want to do with the product. For example, one spec was ‘should be able to demonstrate my personality through Avaz’. Another was ‘it should not break when I drop it’. Though I made the first list using my imaginary users, I showed this list to about 20 people (parents, kids, teachers) and fleshed it out, adding new requirements as people came up with them.

Then the difficult bit: figuring out how to convert the user specifications into technical specifications. This requires solid engineering understanding and deep product knowledge. For example, you need to figure out that the ability to control the pitch of a voice synthesizer would be critical in helping an Avaz user individualize the product, or that the drop-test performance of an enclosure would directly relate to its ruggedness.

What you do with the user specs and the tech specs next depends on who taught you design. What I do is something called QFD – quality function deployment. This is a table which maps ‘Whats’ – the customer requirements – to ‘Hows’ – how the engineer will implement them. In this table, you capture cross-relations between Whats, between Hows, and between the Whats vs Hows. QFD provides detailed guidelines also on how to assign quantitative measures to each of the Whats, and allows you to rank the Hows based on how difficult or resource-intensive they would be to implement.

If you have successfully built a House of Quality, you now have everything you need to make quick, good design decisions. You could create a weighted list of technical features, and order them based on how important each one is to each type of customer. You could do market research to figure out the segmentation of different customer types, and weigh their importance accordingly. And finally, you would come up with engineering specifications for your product.

At that point, the QA team takes over. I’ve always insisted, on all the products I’ve worked on, that when the designers get their pencils out, so should the testers; for each engineering spec, there should be a way to figure out the extent to which it is being met. Only then does the implementation team even get formed.

So that’s how I do design. I swear by QFD, I swear by testing, and I believe my customers.

I think the incredible potential of Aakash – and the sheer amount of resources the Government is planning to put behind it – means that some form of design quantification should be done before the pencils come down on drawing sheets. I’ll do my best to steer this agenda from the inside, but I have no idea how successful I’ll end up being. Wish me luck!

287 days ago Short URL Comments

Computers/Education/Engineering/India

Aug

Cardboard furniture

One of the great things about being an entrepreneur is that you get to meet, even socially, some really interesting people. One such person whom I met last week is Ranjan De, whose chequered career includes design, advertising, education and engineering, all suffused with loads and loads of creativity.

When we met last, Ranjan showed me the work he has been doing in designing cardboard furniture. To be more precise, cardboard carton furniture, which is created out of two large unfolded cardboard cartons, which are manipulated without using any glue. This is like doing origami on an industrial scale.

This work was done by Ranjan and his students at the Pearl Academy of Fashion, where he taught till recently. First, Ranjan introduces his students to the manipulation of spatial structures, and concepts of rigidity and fitting. He then encourages them to come up with concept sketches, and build small, scale models out of ivory card. If these models are able to withstand load – he places his palm on top of the model and presses down, and if the model buckles it must be redesigned – the next step is to bring them to life with real cardboard.

Here are a few examples of his students’ work:

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The work of Ranjan and his students is phenomenally inspiring. They do not look as furniture as something that occupies space; they look at space as something to be molded by furniture.

It is also mind-boggling in its implications. Already, Ikea and their ilk have ‘liberated’ furniture; it is no longer necessary to be very, very rich to have beautiful furniture in your house, and you can pack an entire drawing room of furniture into a lie-flat box which can be assembled in half an hour with nothing more than a Phillips screwdriver and an Allen key. With the kind of ideas that Ranjan is talking about, though, you don’t even need to have a fixed idea of how you want your house to look. Think about it: ten housefuls of furniture folded and stored in the loft, looking like nothing more than cardboard sheets, but every season you could rearrange your house by dragging out the appropriate couches and coffee tables and futons, and inflating them. And if you want a new couch or a bedside table, you can buy one – for six hundred rupees. Furniture: the new clothing.

And what better option, really, for the environmentally conscious? As whole new hordes of people move into the house-owning, furniture-shopping classes, instead of cutting down trees to lounge on or eat food off, we would just reuse the boxes in which our washing machines and refrigerators arrive. Moving house would be so simple: put the electronics and movables into the furniture, ship it away, and reconstruct everything when you reach your new house.

Ranjan’s work reminds me of a couple of other things I have seen. One is the work of my friend, fellow-inventor and frequent collaborator, Ramesh Manickam, who runs Centroid Design. A few years back, he built a reconfigurable hotel room which worked almost like a pop-up book; press a button, a wall slides, and out pops an office table, chairs and a bookshelf: instant office. Press another button, and another wall slides down, all of the office furniture pops back into various nooks and crevices, and a bed, a closet and a couch pop up: the office is now a bedroom. Ramesh’s hotel room was solid engineering, built with heavy motors and steel walls, and an ingenious creation.

And that, in turn, reminds me of Gary Chang, who, in a wondrous act of partition and reconfiguration, converted a 344 sqft apartment into 24 different rooms.

Now if that isn’t playing with space, well, what is?!

289 days ago Short URL 1 Comment

Engineering/Enjoying life/Magic

Jul

I’m on TED!

I made a presentation at TED last month (and blogged about it). Now my TED video has gone live!

Check it out if you are interested in my “day-job” as an inventor of devices for children with autism.

For those of you who would rather read a summary, I talk about how most current approaches that help children with autism to communicate work by short-circuiting the ‘verbal pathway’ through the ‘visual pathway’. Most children with autism are really good at remembering pictures, but not so good at language (words, phrases and sentences).

There are a bunch of tools out there that help autistic children communicate by using pictures instead of words. For example, the Picture Exchange Communication System (PECS) is a way of communicating by using pictures to represent ‘operant words’.

But the limitation of pretty much every communication tool out there is that they provide a way of representing words using pictures; they have no way of representing grammar.

A year back, I invented a way of representing ‘meaning’ pictorially – this includes words, but also (crucially) includes grammar. So I came up with a completely language-independent system of communication. I call it FreeSpeech.

I also came up with a way of translating this system (FreeSpeech) into English.

This is still from the lab; we haven’t made a product out of it yet. But hopefully, that will happen soon enough… and then it will be worth the endless hours of burning the midnight oil!

Here’s the video:

My TED talk

312 days ago Short URL 2 Comments

Disability/Engineering/Entrepreneurship

Jul

The world is full of simulators (part 2)

Very few people appreciate the magic that goes into the simulation, using an LCD screen, of all the infinite colors in the world. This magic is possible because all of the infinite colors in the world – each ‘color’ meaning a ‘spectrum’, of different intensities of different monochromatic components – are viewed (for us humans) through the filter of only three kinds of color receptors, or cones.

The top half of this picture shows how a squirrel would look to another squirrel. The bottom half shows how it looks to us humans.

Squirrels, that have only two kinds of cones (instead of the three that we have), therefore also have a correspondingly drab picture of the world. (Drab, that is, by our standards. I am sure squirrel aesthetics works very differently.)

So the eye distills all the colors in the world to three numbers (to combinations of three responsivity spectra corresponding to the three cones, actually, but that’s a technicality). Still, what magic allows us to recreate the world of color, the red-brown and white of squirrel fur, without actual red-brown-white fur, instead using only paint or phosphor?

As an aside: I remember as a kid, I (and many of my friends) were confused by the term ‘primary colors’. In physics, we learnt, the primary colors were red, blue and green. But we knew, from our experience, that if you mixed blue paint and yellow paint (watercolors worked best), you would get green – a ‘primary’ color. What was going on here? I learnt the answer much later. An ideal blue paint would absorb everything from white light except blue. But the blue that goes for blue paint in watercolor sets isn’t actually blue, it’s a kind of cyan, which is what you get when you subtract red from white. So the blue paint isn’t absorbing everything except blue; it’s absorbing red. An ideal yellow paint, likewise, absorbs blue – it’s what you get when you subtract blue light from white light. And when you mix ‘blue’ pigments and yellow pigments, you get white minus red minus blue, which is green. (Here is a very good introduction to the way color works: http://mintaka.sdsu.edu/GF/explain/optics/color/color.html.)

But back to simulation: paint simulates color well, because white light falling on blue paint stimulates the three cones of the eye in pretty much the same way as blue light falling on the 3 cones.

Reasoning along the same lines also gave me a very beautiful a-ha moment in my study of sound. I did much of my thesis work in sound compression, and very early in my research, I discovered there were two vastly different means of compressing sound. The first is systems like MP3. These work (roughly speaking) by taking a sound signal, and changing parts of it subtly so that it still sounds the same. This subtly changed signal is vastly easier to compress than the original signal. This process is called psychoacoustic modeling of sound.

The second is systems like GSM, which is used in cell phones. These work (again, roughly speaking) by taking what is essentially ‘white noise’ and filtering it with mathematical systems that model something like hissing and popping sounds. The hissing and popping systems can be parametrized. In a cell-phone, speech is compressed by figuring out which noise-hiss-pop parameters best represent a small segment of speech, and transmitting those parameters alone. Counter-intuitively, this works very well, and just 50 sets of parameters per second will encode very good quality speech. This class of algorithms is called Linear Predictive Coding, or LPC.

I wondered, for a very long time, why there was this crazy dichotomy between MP3 and GSM – both compress sound, but there is no mathematics at all in common with the algorithms.

And then one day it dawned upon me: the algorithms behind MP3 simulate the way the ear hears music, dropping off everything from sound that is irrelevant to the ear. And the algorithms behind GSM simulate the way the mouth produces speech, dropping off everything from sound that cannot be produced by the mouth. That’s why they’re different!

This still remains one of the most beautiful insights I have ever had in Engineering.

(To be concluded, in Part 3[?] of my series on simulation.)

317 days ago Short URL Comments

Engineering/Science

Jul

The world is full of simulators

The world is full of simulators. That’s why simulation is definitely in my top 3 of most interesting things in Engineering.

An important insight which I had a few years back is that a lot of our world is based on simulations. Take a cell-phone, for example. The job of a cell-phone (in essence) is to simulate the complex, organic machinery of a human voice apparatus (which includes everything from the lung to the tongue) using nothing more than a vibrating piece of metal, which is its speaker.

Or take a photograph, which must simulate the incredibly complicated interaction of light and matter using nothing more than a few inks and paper.

These simulations are of such high quality that we do not stop, even, to think about them; for many people today, the distinction between live music and recorded music almost doesn’t exist, and blindfold, perhaps, many would not even be able to distinguish whether the source of music is a band in front of them or a set of good speakers.

But at the core of it, making simulation work is a task of engineering genius.

Take color, for example. We know the physics basis of color: that it is equivalent, somehow, to the wavelength of light. So the color ‘red’ could be nominally defined as light with a wavelength of 700 nanometers.

But if you see a bright red car, for example, the effect is very different from that of a monochromatic ray of red light. The car is a complex shape with many different paints and pigments on it. At every point in the car, a combination of the pigments used, and the surface on which the pigments are used, define a way by which that point on the car interacts with light that falls on it – absorbing, reflecting different wavelengths to different extents and in different directions. Each point, then, is an infinite tangle of parameters that govern how it interacts with light.

And the light that falls on it is another glorious tangle of parameters. It has a spectrum – defined by a nearly infinite number of wavelengths, each having a certain intensity. And this light may not even be uniform; for example, it may be a spotlight, that is bright in the center and dim on the sides, or sunlight, which is (for most practical purposes) uniform white.

This light falls on every point in the car and produces an ‘effect’. The result of this effect is that a now-modified light falls in our eyes, focused by our eye-lenses onto our retina, which ‘perceives’ it.

And in that perception lies the secret key that allows us to simulate the effect of all this complex intermingling of many materials, light and matter, with nothing more than a few inks on a photograph.

Consider this stunning photo, from a BBC article on Animal colors through animal eyes:

The left side is how we perceive it; the right side is how a bird’s view of it is enhanced. This is because our eyes have only 4 parameters for ‘perceiving’ light: the rods, that sense the brightness of the light, and three types of cones, that each sense the level of a different color.

And – this is the interesting part – a bird’s eyes have four types of cones instead of three: they can not only view what we can, but also light in the ultra-violet spectrum.

The fact that we have three types of cones ensures that all light we see – any spectrum, i.e. any mixture of wavelengths – eventually is sensed by us as merely a set of 3 color-intensities.

And that gives rise to that beautiful idea: that there may be two different spectra of light that stimulate the cones in the same way – and therefore look identical to us. Thus is born the whole field of ‘reproducing color’ – photography, painting, printing, displays, monitors, projectors.

And we are able to simulate the colors of the entire universe, really, with nothing more than 3 paints, or inks, or filters.

More tomorrow (this is the first of a 3[?]-part series of ruminations on simulation).

318 days ago Short URL Comments

Engineering/Science

Jun

Gates, Jobs

I have been re-reading Hard Drive – the very old and rather rare biography of Bill Gates. the book was published in 1992, so it doesn’t cover most of ‘modern’ Microsoft products. Rather, it’s a story of the foundations, because by ’92, Microsoft had already become a little behemoth, and Gates was still a very young man then.

Nowadays it is very fashionable to like Steve Jobs. It’s almost as though just invoking his name makes you ‘cool’. I know a wannabe entrepreneur who told me, ‘I treat my employees like shit and I am impatient with my developers… I am like Steve Jobs.’ Yeah right.

I haven’t read Steve Jobs’ biography (yes, the famous one) and I intend to read it sometime in the near future, but I doubt that it will change my mind about Gates being the real hero of the computer revolution. In fifty years, both Jobs and Gates will probably be forgotten by the unwashed masses; but for computer scientists and computer historians, Gates will be the revolutionary, the visionary. Jobs will be one of the multitude of fads and trends that will go in and out of fashion between now and then.

I like Gates a lot more than Jobs (this is, I hasten to add, purely judged by entrepreneurship and engineering) because Gates focused on problems; Jobs focused on solutions. In other words, Gates seems to me to be the kind of guy who went out into the world and looked at what people wanted, and used that as a starting point. Jobs went into himself and tried to discover what he could do well, what would make him happy, and used that as a starting point.

I do not see anything wrong with Jobs’ approach and certainly he deserves a lot of adulation for his ‘internal courage’ and consistency of expression. But let’s face it. Jobs’ career was about making pretty white boxes and selling a lot of them. Did the iPod revolutionize the world? No, it didn’t. True, it opened up a new industry of digital music. But today, downloadable music exists, the iPod hardly does. Even the industry has faded out – who buys MP3 players any more? Jobs was possibly motivated by the fact that he knew that he could make an MP3 player better than everyone else out there. And he went ahead and did it.

On the other hand, Gates made his career by building permanent stuff: languages. compilers. operating systems. office applications. He did not do it because he knew how to make a perfect operating system – in fact, he didn’t. A lot of early Microsoft software was buggy, and it took till the 3rd or 4th iteration before it became world-class. But Gates deserves respect for identifying a problem and providing a solution – not just out of the need to scratch an intellectual itch, but out of a vision to make computing ‘fuller’, to solve all the unsolved problems, to create (however imperfectly) a brave new world, this world today, where computers and software are ubiquitous. When he made his billions, he started looking at bigger problems: water. disease. education. And there, too, he isn’t perfect — but he is the man in the arena, he isn’t afraid of trying, and he is driven not by the elegance of the solution but by the importance of the problem.

Real engineer, real entrepreneur.

337 days ago Short URL 5 Comments

Computers/Engineering/Entrepreneurship/History

May

What people think about computers

I met someone interesting for lunch today, an engineer from Chicago who did his master’s thesis in ubiquitous computing. We had a very interesting conversation about how computers are viewed, and how they *ought to be* viewed.

We’ve heard numerous examples of people who have never used computers in their lives take to devices like an iPad or a mobile phone. We’ve also heard of people who have never used ‘high technology’ in their lives use cell-phones on a daily basis. And that serves as a kind of role model for us when we try to design computers nowadays, and target them at the ‘digital have-nots’ – for the billions that have not had access to computers so far.

However, there is a difference between a mobile phone and a computer, even at the conceptual level. A mobile phone is an appliance; so is an iPod, for example. They are meant to perform one task (or a few tasks) well. In the case of a mobile phone, it is to make and receive calls, and send and receive messages. In the case of an iPod, it is to play music. So the conceptual model for their use is straightforward; for a mobile phone user making a call, it is: choose a recipient, initiate a call, talk, and hang-up.

It has become fashionable of late to design software for computers that make them appear as appliances. For example, if you pop in a DVD into a computer, most likely the software that plays the DVD will have controls that mimic a DVD player, with a play/pause/volume button. So anyone who is comfortable using a real DVD player would, hopefully, be able to relate the user interface of the computer’s DVD playing software to the actual functioning of a DVD player, and feel familiar (or at least, less intimidated) by the software.

Packaged software has become the mainstay of our interaction with computers today. That is why, when I ask people of my father’s generation (who have probably started using computers only in their 40′s or 50′s) what computers can do, they say, computers can create documents, play music and movies, browse the internet, solve equations, video-conference.

All of which are true, except: it is not the computer that does these things (except indirectly); it is the appropriate software package that does them.

And no one who is exposed to computers in that way will ever answer the question of “what do computers do?” with the right answer, which is, “computers compute.”

And that is why, despite innumerable efforts by several groups of people, all of these people will feel intimidated by ‘programming’ a computer. Their mental model only fuzzily (if at all) recognizes that computers can be programmed to do anything that is computationally feasible, not limited by what software exists. For them, the basic conceptual blocks of computers are menus, mouse cursors, pointing and clicking, buttons, and volume control – not data structures and algorithms.

The question we discussed over lunch today – a discussion which did not definitively end – was: what would it mean to have people build non-appliance mental models of computers?

Is it a good thing? -Would we empower people if we described computers to them as ‘programming machines’, or would we go back to a world where only the intellectual elite felt safe around computers?

And, is it good to teach all people that they, too, can program a computer? Or should the status quo continue – where everyone is more or less comfortable using a computer, but only a handful of anointed experts, mostly with engineering degrees, are capable of programming them?

Which way? What do you think?

364 days ago Short URL 1 Comment

Computers/Education/Engineering

May

Crooked House

The first great science fiction story I read was “…And He Built a Crooked House”, by Robert A. Heinlein. I read it in a collection called “Space Odyssey”, which also had a number of other first-class stories (such as the hilariously named “Coffin Cure” about a man who finds a cure for the common cold).

“…Crooked House” reels you in right on the first page; in fact, it hooks you right at the first sentence:

Americans are considered crazy anywhere in the world.

The rest of the first page goes:

They will usually concede a basis for the accusation but point to California as the focus of the infection. Californians stoutly maintain that their bad reputation is derived solely from the acts of the inhabitants of Los Angeles County. Angelenos will, when pressed, admit the charge but explain hastily, “It’s Hollywood. It’s not our fault—we didn’t ask for it; Hollywood just grew.”

The people in Hollywood don’t care; they glory in it. If you are interested, they will drive you up Laurel Canyon “—where we keep the violent cases.” The Canyonites—the brown-legged women, the trunks-clad men constantly busy building and rebuilding their slap-happy unfinished houses—regard with faint contempt the dull creatures who live down in the flats, and treasure in their hearts the secret knowledge that they, and only they, know how to live.

Lookout Mountain Avenue is the name of a side canyon which twists up from Laurel Canyon. The other Canyonites don’t like to have it mentioned; after all, one must draw the line somewhere!

High up on Lookout Mountain at number 8775, across the street from the Hermit—the original Hermit of Hollywood—lived Quintus Teal, graduate architect.

And Quintus Teal is the man whom the story is about. He’s a crazy, enthusiastic, excited architect, a lovely counterpoint to the insufferable Howard Roark.

The story begins with Quintus Teal talking his friend, Homer Bailey, into building a 4-dimensional house. It takes some persuasion, but Homer Bailey finally agrees to commission Teal to build an opened-out tesseract — a 4-dimensional cube — as a surprise gift for his wife. The wife, predictably, takes a very dim view of the house once she sees it; particularly when an earthquake ‘folds’ the house in the 4th dimension into a real tesseract.

I found “…Crooked House” very funny, and I still do. Quintus’s character is infinitely endearing – the architect with a crazy idea and a friend to bankroll it, who makes the most of the artistic license he’s given.It’s hard not to love his enthusiasm — such as when he shows off an automatic staircase inside the house: “Teal wriggled like a boy who has successfully performed a card trick”.

As a general rule, my preference in science fiction is for stories set in the present, or in the recent past, or perhaps in the very recent future. Not for me the era of galactic explorations or disembodied intelligences; I prefer stories that are about the world we live in today, but with one or two minor modifications. Minor from a science perspective, that is; but which make a world of difference in science fiction.

At MIT for the TR35, I met Noah Snavely, that very personable image processing genius who invented Microsoft Photosynth. We spent a delightful half hour together at coffee, discussing our favorite science fiction. My ‘favorite’ list had only three names on it, all short stories. For the record, here they are. Each was read approximately 5 years after the previous one.

1. …And he built a crooked house, by Robert Heinlein
2. Dust, by Greg Egan
3. Story of Your Life, by Ted Chiang.

I think my favorite science fiction novel would probably be Contact (by Carl Sagan) though I like a lot of Clarke too. I’m not that much into science fiction novels, though.

For what it’s worth, Noah’s list had only two items on it, and they weren’t exactly science fiction. They were both by Borges:

1. “Funes the Memorious”
2. “Pierre Merard, Author of the Quixote”

Sad to say, I haven’t read either of them yet — not even after such a high recommendation by Noah.

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Books/Engineering

I, Q.

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