"A rose by any other name would smell as sweet" -- Romeo and
Juliet, by William Shakespeare
I don’t know if algorithms smell sweet, but I do know that they have other
names.
According to one definition, an algorithm is a set of instructions on performing
a specific task. Applied to computers, that means that an algorithm is the same thing as computer code. Different name. Does it smell as sweet?
Having said that, when algorithms are combined with machine learning, a
different creature emerges. This combination enables an algorithm, a simple set
of static instructions, to evolve into ever more interesting sets of
instructions, adapted to changing circumstances.
What’s
the Deal With Algorithms? offers an excellent overview of the way in which
algorithms and machine learning interact to achieve remarkable results.
WHY IS THIS
IMPORTANT?
Because desulfurization technology depends on advances in catalysis. And
catalyst development depends on algorithmic machine learning.
We’ll explore this in more detail in the next post.
Meanwhile, here are excerpts from the article highlighted above.
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What’s the Deal With Algorithms?
Your 101 guide to the
computer codes that are shaping the ways we live.
By Jacob Brogan
Feb 02, 2016
[ EXCERPT ]
Can I level with you? I’m not always sure I know what people are talking about
when they say algorithm?
You’re not alone: Honestly, I haven’t always been sure what I meant when I said
it either. But here’s the absolute simplest definition: An algorithm is a set
of guidelines that describe how to perform a task.
Come on. That’s it?
Yup. As UCLA’s John Villasenor has pointed out, this means that even something
as innocuous as a recipe or a list of directions to a friend’s house can be
understood as an algorithm. Things are a bit more complicated in the computer
science context where the term most often comes up, but only ever so slightly.
In his book The Master Algorithm, Pedro Domingos offers a masterfully simple
definition: “An algorithm is,” Domingos writes, “a sequence of instructions
telling a computer what to do.” As Domingos goes on to explain, algorithms are
reducible to three logical operations: AND, OR, and NOT. While these operations
can chain together in extraordinarily complex ways, at core algorithms are
built out of simple rational associations.
It’s starting to sound like we’re just talking about computer code here.
You’re not wrong. Silicon Valley marketers love the term algorithm, since it
makes the features they’re selling seem a little more mysterious, and hence,
perhaps, a little more enticing. The fact of the matter is that most of us
don’t have a strong grasp of how our computers (or our phones, or our watches)
work, but we tend to have at least a general sense of what code is. Because
it’s less familiar, algorithm tends to emphasize our uncertainty.
Then what makes algorithms special?
Generally speaking, when people talk about algorithms these days, they’re
talking about something more specific, like the operations that power our
social media news feeds. In one way or another, most of these systems are
examples of a technology called machine learning. Instead of repeatedly
processing a stable set of instructions, systems based on machine learning
rewrite themselves as they work. It’s this that frightens some people, since it
makes algorithms sound like they’re alive, possibly even sentient.
Free full text source: https://slate.com/technology/2016/02/whats-the-deal-with-algorithms.html
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Google® Better!
Jean Steinhardt served as Librarian,
Aramco Services, Engineering Division, for 13 years. He now heads Jean
Steinhardt Consulting LLC, producing the same high quality research that he
performed for Aramco.
Follow Jean’s blog at: http://desulf.blogspot.com/ for continuing tips on effective online
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Email Jean at research@jeansteinhardtconsulting.com with questions on research, training, or
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provide
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