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width are the singular aspects of what makes her who she is. I think silently to
myself that we must be very careful about how we demonstrate this product in public, particularly to women.
    The remainder of the photograph fades, leaving behind only the series of yellow blocks, like a photographic signature.
    The word, ‘Scanning... ’ appears on the screen, and then, below it, come quick bursts of text: ‘DMV:Alabama... DMV:Alaska... DMV:American Samoa... DMV:Arizona... ’ and so
on – through the US states and territories.
    It’s probably at this point that I should mention what makes Tao’s software unique. Facial recognition is, in itself, an old art. Programmers have been doing it for years. You can
generally match any two photographs of the same person, assuming that you first tell the computer who is who. But Tao’s P-Scan does not require any sort of ‘who-is-who’ directory.
Instead, P-Scan uses the entire Internet as its directory.
    So, when you ask P-Scan to identify a person in a photo, it sifts through millions of images on the Internet – from both formal sources (government driver’s licences and passport
photos), and informal sources (wedding announcements in the
New York Times
, magazine photos, or even private personal Web sites).
    The idea behind P-Scan – and it is audacious, I have to give them that – is that any person, in any photograph, should be identifiable. Point to a photo, and say, ‘Who is
this?’ and let the software search the Internet to figure out the answer.
    On-screen, the cursor flickers as the various databases are scanned. During the search of ‘DMV:Maryland’, the computer pauses, and dings a soft musical chime, and displays:
‘Possible Match’: along with a photograph. It’s a driver’s licence photo of a Maryland woman, with the same wide face and Hispanic complexion as Rosita. But it’s
clearly not the customer service person who works at Tao, and the computer seems to realize this, because it immediately appends: ‘Match probability: 48%’ and resumes scanning.
    This process continues through the various state Department of Motor Vehicles databases. Simultaneously, I notice, P-Scan sifts through other databases, in parallel: ‘Flickr.com photos...
NBC network news... Facebook.com... Poughkeepsie Register... ’
    It’s an amazing demonstration, really – hundreds of image sources, possibly millions of images – zipping through the computer’s memory, being compared to a mathematical
representation of Rosita.
    I’m about to comment on this, and ask Darryl something like, ‘How many images can it process per hour? How many per day?’ – because those are the units of time I think
are applicable here – hours or days – and I am sure that it will take at least an entire day to process Rosita’s image and to find her needle in the haystack of the world
Internet.
    But before the words can form on my lips, the screen goes black, and then two images appear, side by side. On the left, the grainy image from Tao’s employee photo of Rosita; and on the
right, an enlarged colour photograph from a high-school yearbook. It says: ‘Rosita Morales, St. Cloud High School, Class of 2003’. It’s a picture of Rosita – much younger
and thinner than I know her – with neatly coiffed hair, sitting primly with clasped hands, in front of a fake sky-blue background.
    ‘Ta da!’ Darryl says triumphantly. ‘It worked!’ He sounds quite surprised that it did.
    ‘Holy shit,’ I say, softly. I’m not much of a technologist – can barely use a spreadsheet, I admit – but this is one of the most amazing software demonstrations
I’ve ever seen. ‘How did it—’ I start.
    Darryl launches into yet another description of his software, beaming like a proud father. ‘Brilliant, right? Well, that was pretty lucky, to be honest, because we happen to have a lot of
Florida high-school yearbooks in the database. But if you chose an employee from Oregon