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simple. It recognizes
faces. The idea is: you show it a photograph, and it tells you who is in it.
    Simple enough. Tao Software, and its venture capital sugar daddies, have spent over twenty-two million dollars to build P-Scan. Even after this vast amount of money, the product still suffers
from two main problems.
    The first is technical. It doesn’t work. Well, to be more exact, it
kind of
works...
sometimes
. At least, that’s how Darryl describes it. He doesn’t go into
detail about what ‘sometimes’ means, or how software can ‘kind of’ work, but I take the general gist to be that P-Scan’s accuracy depends a lot on the quality of the
photograph fed into it. Give it a good photo, clear and in-focus, and it will return accurate results. But blurry photographs, or photos taken at anything other than a head-on angle, or with a
shaky hand, and poor lighting, will be less accurately identified. In other words, the vast majority of photos taken by actual human beings on planet Earth will not be processed correctly. This,
Darryl concedes, might possibly be a flaw.
    The second problem with P-Scan – and this one is non-technical – is equally serious in my mind, particularly since I’m supposed to be the ‘business person’ in the
room. No one has any idea how to make money with it. The product was born in the burst of enthusiasm that accompanied the rise of social networks like Friendster and Facebook. Everyone in the world
was putting their private photographs online, on the Internet, thereby making them public. Wouldn’t it be interesting (or so the thinking apparently went in the Tao Software boardroom,
perhaps as cannabis smoke wafted under the door) if a computer program could automatically identify everyone in a photograph? That way, you could search for photos of yourself, or for friends, or
for family – no matter whose camera took them, and no matter who put them online. A good idea, and interesting... except for that small, nagging problem that no one is willing to pay for such
a service.
    These are the main points I glean from Darryl’s lengthy description of the product that he and the Tao engineers have built. After Darryl continues for some time about the beauty of
Tao’s latest algorithm, about how it translates photographic pixels into a 1024-bit hash, and not a 128-bit hash; about how Tao’s algorithm can ‘gridify’ a scan at 1/10th of
a millimetre resolution – after he tells me all this, and drones on for what seems like eternity, he finally turns to me and says: ‘So let me show you.’
    Even if the software doesn’t work, at this point I feel an enormous relief, simply that Darryl has stopped talking. Randy must feel it, too, because he nods vigorously, like one of those
bobble head dolls on the dashboard of an old Dodge El Camino.
    Darryl taps his keyboard. Rows of small colour photographs appear on-screen, like a high-school yearbook. I recognize most of the faces as Tao Software employees.
    ‘Choose one,’ Darryl says.
    ‘All right,’ I say, and point to the screen. ‘That one.’
    I have pointed to Rosita, the heavy-set trouble-maker from the lunchroom this morning.
    ‘Good choice,’ Darryl says. ‘Lovely Rosita.’
    He presses a key. A yellow square appears around Rosita’s head. The image is progressively enlarged until her face fills the screen. It’s blurry, not particularly well-photographed.
Blown up to this size, the image is barely recognizable as Rosita at all.
    Darryl clicks another key. The image is transformed into boxy pixels, various shades of grey. As if the P-Scan software is trying to distil the most important aspects of the picture – the
essence of what makes Rosita look like Rosita – it selects some of the blocks, and highlights these in yellow. These yellow blocks mostly come from her cheek and jowl, and from a series of
blocks stretching across her shoulder, as if the P-Scan software has determined that Rosita’s weight and