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A Beginner’s Guide To… Algorithms

Published Jul 18, 2017 by Neil Cumins

Algorithms are an essential part of computing. But what are they, and how can they benefit people who don’t know a byte from a Boolean?

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When you were at school, you probably found math class rather dull. Quadratics, algebra, algorithms…who needs them?

When it comes to algorithms however, we all do. They’re an essential aspect of computing, since an algorithm is a sequence of instructions that can be followed to complete a task. You could break many human activities down in the same way, like driving a car. Indeed, Tesla and Google’s autonomous vehicle trials are powered by algorithms that replicate human decision-making according to available intelligence. Green light, go. Red light, stop.

 

Computing Power

Of course, computing algorithms are rather more complex than knowing when to give way or change lanes. Computers are simple creatures, and they can’t problem-solve unless we give them the tools to do so. That’s where an algorithm comes in. It lets the computer follow a path to a conclusion, which can simplify processes humans might struggle with. It can also complete them in a tiny fraction of the time it would take us to reach the same outcome.

 

Personalization

Take on-demand streaming services. Those recommended programs or “you might also like” suggestions provided by YouTube and Netflix are the product of algorithmic analysis of your viewing history. If you like Homeland and 24, you’ll probably enjoy Prison Break as well. These curated suggestions are nothing more than a computer crunching data, looking for links and generating a logical conclusion. They’re not always right, but algorithms are generally more reliable than the decisions we make every day based on our own experiences.

 

Data Management and Analysis

Algorithms really come into their own when the volumes of data are being processed are far beyond human capacity. Google and Bing use vast algorithms to populate search results pages, ranking each website on a variety of criteria. Positive and negative attributes are gauged to produce a likely order of importance for each search result. These web crawlers are among the most sophisticated algorithms ever created, yet they operate along the same principles as a simple program that finds the largest number in an unsorted list.

You’ll probably never need to know how to build an algorithm, but you’ll end up relying on them. For instance, if you’re not a natural writer, the Jetpack plugin for WordPress can intelligently identify grammatical errors and recommend better ways to write web copy. It doesn’t just check spelling – it can consider context and identify clichés, as a person might. It does this through algorithmic analysis of past results, learning as it goes.

 

Machine Learning

This represents the ultimate extension of algorithms – artificial intelligence, where software makes decisions based on the knowledge it’s acquired from prior experience. Many people are tipping AI to be as revolutionary as the internet itself, powering everything from smart devices and automation to Siri and Alexa. Next time your phone recommends ways to optimize its performance, or your antivirus package identifies a possible threat to your computer, it’s harnessing the power of algorithms. Turns out math really is useful, after all.

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