
The economics of artificial intelligence - caprorso
https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/the-economics-of-artificial-intelligence
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untangle
Management consulting nonsense.

Here's the author's pitch: The value of AI is in "cheaper prediction." So
economic value capture occurs by looking for prediction problems in your
business and unleashing AI on those. The author further prescribes that one
may have to "recast" certain problems (e.g., self-driving cars) as prediction
problems to make it all work.

But the stunner for me was the assertion that the value of the semiconductor
was "cheaper arithmetic."

I find these over-generalizations neither accurate nor helpful.

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ethbro
_> But the stunner for me was the assertion that the value of the
semiconductor was "cheaper arithmetic."_

In what way would you disagree with this?

For purposes of enterprise resource allocation (the article's domain), it
seems an accurate simplification.

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tehsauce
Maybe mentions of all the crucial peripherals would have been relevant. The
enormous storage capacity, the networks, high resolution displays and
sophisticated interfaces.

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ethbro
The original quote was about semiconductors. Not computing systems. From which
the author was drawing a thread to the profound impact a decrease in cost (or
increase in throughput) of an input can have on the economy.

Taking an abstraction out of context and then griping about minutiae with
"Well actually..." quips is intellectually dishonest.

If it's an inaccurate simplification, that's fair, but I thought it was valid
for the domain the author was addressing.

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joe_the_user
This doesn't seem like a perspective offering anything new and possibly
involving a few problems.

Jeff Hawkins' On Intelligence also emphasized the predictive qualities of
intelligence but again, this was a new emphasis, not really a new idea but a
new emphasis in that it's well known time is implicitly an element of nearly
any cognitive process.

Moreover, the current deep learning driven AI renaissance is has been most
effective in predicting patterns in quite static phenomena; image recognition
and competitive video and board games (game involve change over short periods
but their context remain identical over long periods). Similar success hasn't
come in say, the stock market (so far as I know). So it seems increased
prediction at the corporate level will come only as long as larger processes
stay static (when you have cascade of change, you'll have cascades of failing
predictors, which generate further change what could go wrong?).

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UncleEntity
> Similar success hasn't come in say, the stock market

Depends on your metric of success, I suppose.

I couldn't begin to imagine there aren't a bunch of ML tasks hammering away at
something like a mutual fund where a conservative investment strategy could
(probably, dunno?) be learned by an algorithm.

A seat of your pants day trading strategy learned by ML, probably not so much.

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TheOtherHobbes
"There’s some number at which Amazon might think, “We are now sufficiently
good at predicting what you want to buy. Why are we waiting for you to shop at
all? We’ll just ship it.”

This is one of the most politically, economically, and psychologically tone
deaf things I've read this year.

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kristianov
A better way to put it is: “We are now sufficiently good at predicting ...
We’ll just ship it to the warehouse closest to you, so in case you buy it, you
get faster shipping.” To me, that's value of AI.

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JPKab
McKinsey? Well, I guess this cements the fact that AI is now the buzzword of
choice for godawful management consultant bullshit artists.

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Pica_soO
AI is so good at predicting, we predict it will replace consultants buzz-
wording by the end of the year.

