“I tried to warn you the last few years.” (Elon Musk)
e4 c5
Twenty six years ago, on February 10, 1996, the opening
moves above launched the monumental chess match marking the ultimate battle of
man vs. machine -- the reigning world chess champion Gary Kasparov vs. IBM supercomputer
Deep Blue – warping, since then, the history of the game of chess.
Playing defense against Deep Blue’s Alapin Sicilian, Kasparov,
as if carrying the weight of humanity on his shoulder, was forced to resign after
37 moves. Game over it was for a man in the world of chess – a startling upset that
grabbed the headlines as millions watched around the globe.
Looking like a classic plot line of a sci-fi movie, in the 1997 rematch, Deep
Blue with its power to explore up to 200 million possible chess positions per
second with its AI program (5 decades in the making), beat Kasparov after a
six-game match: 2 wins for the machine, 1 for the champion, and 3 draws, with
the final score of 3 ½ to 2 ½.
Roughly fifteen years later, in 2011, another machine
beat man: Supercomputer IBM Watson vs. not one, but two greatest champions in
Jeopardy -- a quiz competition named by TV Guide magazine as the best game show
of the 70s.
While chess engages our creative right brain to
recognize patterns coupled with our analytical left brain to choose a logical
move, Jeopardy pushes all the more for our brain not only to wield encyclopedic
recall but also to untangle complex questions, not to mention the quick, almost
knee-jerk, pressing of the button.
Named after IBM’s founder Thomas J. Watson, the
supercomputer took about 20 researchers and 3 years to develop into a machine
much smarter than its Jeopardy human opponents. Processing 200 million pages of
stored information from a variety of sources, Watson was 100 times faster than
Deep Blue.
Watson faced two formidable Jeopardy-winning
brainiacs: Ken Jennings and Brad Rutter – the two best players the show had
produced over its decades-long lifetime. The former had the longest unbeaten
run at 74 winning appearances, the latter had earned so far the biggest prize
pot in the show.
The Year 2022. After a little over a decade, more than
two weeks ago, a machine beat man – this time in the realm of the art
competition. The Washington Post reported:
“When Jason Allen submitted his ‘Theatre D’opera
Spatial’ into the Colorado State Fair’s fine arts competition last week, the
sumptuous print was an immediate hit, beating 20 other artists in the
‘digitally manipulated photography’ category to win the first-place blue ribbon
and a $300 prize.
“What Allen had only hinted at, however, was that the
artwork had been created in large part by an artificial intelligence [supercomputer],
MidJourney, that can generate
realistic images at a user’s command. The portrait of three figures, dressed in
flowing robes, staring out to a bright beyond, was so finely detailed the
judges couldn’t tell.”
Artists have been on the warpath after Allen’s win
went viral on Twitter where it had backfired as the following tweeted messages
have spelled out:
“We’re watching the death of artistry unfold right
before our eyes.”
“This sucks for the exact same reason we don’t let robots
participate in the Olympics.”
“What makes this AI different is that it’s explicitly trained on current working artists. This thing wants our jobs, it’s actively anti-artist.
We’ve just gotten acquainted with Deep Blue, Watson,
and Midjourney. Now, let’s meet GPT-3, the third generation Generative
Pre-trained Transformer. This neural network machine has learned the nuts and
bolts of natural language by “analyzing thousands of digital books, the length
and breadth of Wikipedia, and nearly a trillion words posted to blogs, social
media and the rest of the internet” Cade Metz wrote in The New York Times. This means GPT-3 can tweet, write poetry,
summarize emails, answer trivia questions (remember Watson?), translate
languages, write computer programs, and even blog and argue. As a blogger
myself, to that last one: Tsk tsk.
In one test, Metz wrote that GPT-3 showed it could
imitate the writings of public figures. Topic: “How do we become more creative?” Imitated writer: Scott Barry
Kaufman, pop psychologist. The opening lines of the GPT-3 piece I am excerpting
below:
“I think
creative expression is a natural byproduct of growing up in a diverse world.
The more diverse the world is, the more you get exposed to different people, to
different opportunities, to different places, and different challenges…”
As a writer myself, what has caught my eye in GPT-3
piece above is its use of a rhetorical device -- repetition. One book on
writing stressed: “Good writers may repeat keywords or phrases to reinforce
ideas and emotions, to establish a rhythm.”
When the real Kaufman read the whole GPT-3 piece, it stunned him. “It definitely sounds like something I would say,” he tweeted. “Crazy accurate AI.”
I wrote in my past ATABAY article “Scam Can Happen
Anytime Anyplace to Anyone” about the scammer who used my FB identity. My niece
engaged the scammer in a brief chat which I am excerpting below:
Scammer: I
couldn’t believe it until I got the grant delivered to my doorstep too. I got
$75,000 after I applied and it doesn’t need to be paid back and everyone is eligible
to apply for this opportunity.
My niece: Where
do you live now?
Scammer: Should
I share with you the link to the attorney in charge so that you can apply as
well?
My niece: Wla
baya ko kasabot unsa na sya. Asa man ka nagpuyo karon Uncle?
[I don’t know what it is. Where do you live now, Uncle?]
Scammer: I’m
enjoying my vacation trip at Singapore. [Holy smokes! The scammer could
understand Cebuano.] I’m just trying to
share the blessings that God has done for me.
[Pronto, my niece blocked the scammer.]
Just as the GPT-3 piece stunned the real Kaufman, so
too did the scammer’s closing line to my niece astonish me. It seemed to be
like spiritually-inspired final words I would say. Could such a scammer be a
machine? With the recent emergence of GPT-3 AI technology, the answer is a
no-brainer. Here’s a more thought-provoking question: What will the future look
like?
Metz saw the handwriting on the wall of the near
future: AI is not a myth. It is the future. And it is happening right now.
The good news: lots of new jobs will be created that
require a high degree of creativity and emotional intelligence. The bad news:
AI will replace millions of jobs. World Economic Forum reported that 75 million
jobs are expected to be lost by 2022. Half of all jobs today will be lost by
2030. For any working couple now, one will lose his or her job.
The one-million-dollar man-vs-machine question: Will you lose your job to a machine?
Head still photo courtesy of pixabaydotcom
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