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The Gradual Public Awareness of the Might of Algorithms
Soylent Mauve writes "The trend toward data- and algorithm-driven tuning of business operations has gotten a lot of attention recently — check out the recent articles in the New York Times and the Economist. It looks like computer scientists, especially those with machine learning training, are getting their day in the sun. From the NYT piece: 'It was the Internet that stripped the word of its innocence. Algorithms, as closely guarded as state secrets, buy and sell stocks and mortgage-backed securities, sometimes with a dispassionate zeal that crashes markets. Algorithms promise to find the news that fits you, and even your perfect mate. You can't visit Amazon without being confronted with a list of books and other products that the Great Algoritmi recommends. Its intuitions, of course, are just calculations -- given enough time they could be carried out with stones. But when so much data is processed so rapidly, the effect is oracular and almost opaque.'"
I just (a few minutes ago) found this free PDF book about algorithms (written for the undergrad-level student). It's pretty good: http://beust.com/algorithms.pdf
Said one computer scientist getting his day in the sun:
"I'm melting, I'm melting!"
Math is a really really powerful tool.
Whereas algorithms are instantly aware of their own prowess.
Is management starting to wonder (again) whether a computer can really do a better job making the important decisions? But can it yet? There is so much data that needs to be acquired in order to return a meaningful answer.
Some of the most powerful organizations are probably making deals to combine as many databases as possible. Interesting to see (if they would let us see) if that will give them the answers they're looking for. As data acquisition becomes more accurate and less expensive, there will be less privacy but more creative computer output, a trade-off in the value of personal information leading to the possible marginalization of humanity.
Know your pads. One time pad: good for cryptography. Two timing pad: where to take your mistress.
But seriously, a food recipe is an algorithm for all general purposes. All these people are saying is that the machine learning algorithms and match peoples' personalities and buy stock are too complicated for the average Joe Programmer Wannabe and look more or less like a black box. (which if they employ neural networks, instead of say SVN, they are actually black boxes even for the author who wrote it...).
Absolutely. I belong to several Yahoo and Google Groups geared at the neopagan crowd, and because the groups are categorized as 'religious' groups, the advertising always contains advertisements for 'End Times' books and appeals to join the United Methodist Church, etc. Then again, maybe this the algorithms are doing just what they're supposed to do ... :)
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This is one of the reason why getting a CS degree is important, despite what the ignorant masses say in the IT industry. Sure writing lame CRUD applications will satisfy your average customer's needs, but sophisticated algorithms are what provide value beyond a simple shopping cart.
If you're still entrenched in the thought that a CS degree "isn't needed for what I do," then let me propose a somewhat common problem. Suppose your client wants the built in reporting in your web application to minimize the amount of noise introduced by users who forget their password and create a new account rather than resetting it. It's up to you to write code to detect these duplicate accounts. How do you begin doing this beyond simple string comparisons?
P: "Heuristics ARE algorithms"
Both of these statements can be true. (Depending on the exact meaning of the GP.) For instance:
Humans are not the same as animals.
Humans are animals.
A more exact statement than either is that heuristics are a subset of algorithms, as humans are a subset of animals.
Have you been touched by his noodly appendage?
Don't get caught up in the hype here. Algorithms are nothing special on their own. These articles are trying to make them look important, like inventions or physical objects, to further pump up the notion of software patents. It's not algorithms that are evil in GWB's great internet filters, it's the machinery that's been built on top of an otherwise dumb network and free internet that's evil.
Without algorithms, there can be no computing but there's nothing really special about any one in particular. Algorithms are just instructions, and there are many ways of achieving the same result. Algorithms can stand alone or be combined into programs that do things users want. The net result is just another set of instructions that can be considered a larger algorithm. Without modern computing equipment, most of these instructions are useless. Like the article say, "try doing this at home." No problem, if you have a computer but a real pain if you only have pen and paper. Medical imaging devices take advantage of mathematics that was little more than a curiosity when it was first published in 1917. The inventors of the device reinvented the math without knowing it some forty years later but it was not until the 1980s that the devices became practical due to the lower cost of computing.
This article is pumping up the value and utility of business methods. Common sense is a valuable thing, but it's not always an invention and business methods never are.
DMCA, Hollings, Palladium. What might have sounded like paranoia is now common sense.
Drums that raise our awareness of global warming.
A post a day keeps productivity at bay.
That's an elegant metaphor, but someone has misled you.
An algorithm is a precise specification of a process whose outcome is defined by the initial conditions. To cite your example, quicksort is an algorithm -- the outcome of the sorting process is well defined, given the inputs.
But typical implementations of quicksort use a heuristic to choose the pivot element -- median of three, media of five, middle element, etc. These are heuristics because their goal is to choose the median value, but they can't make any guarantee that it will find the median. They can't even guarantee that they will find a good value. In fact, they generally don't even consider all of their inputs! They could choose bad values every time... but on average they don't, and quicksort is fast.
Another way of looking at it is that if an algorithm is correct, it will produce a correct answer for all valid inputs. A heuristic might produce incorrect answers for valid inputs, but it's correct often enough so that it might still be worth using -- especially if a correct algorithm is not known.
You may point out that randomized algorithms have a similar property -- but the difference is that with randomized algorithms the probability of error can be made arbitrarily small. With heuristics, there's no telling.
Am I part of the core demographic for Swedish Fish?
My favorite is getting Amazon recommendations for books I've already bought... through Amazon.
I often find myself saying "Ah, yes, I just bought the hardcover version of that book last year, now I should go out and get the paperback, the second edition with a few minor spelling corrections, etc, etc."
Or something.
Have you been touched by his noodly appendage?
Don't apply your intuition concerning human beings to other intelligent systems. A true AI may or may not decide it doesn't need us, depending on how it's programmed.
You ignore the fact that stand-alone sentience has little to do with our evolution-dictated habits (e.g. getting rid of competing group/species/whatever). You assume that all the evolution-dictated behaviour and thinking patterns embedded in human brain will somehow automagically manifest themselves in a true strong-AI machine, a view with which I disagree.