Digital Themes


Algorithms are a series of instructions that inform a task. They impact elements of daily life in significant ways, from the laptops we work on to the personal electronics we use to track our physical activity. Algorithms within these devices are essentially “step-by-step” lists of instructions that “tell” a device how to use data or complete a task.

In the world of computer science, algorithms are considered the building blocks of programming. Large digital networks draw on the power of algorithms to search, sort, categorize and streamline data. An efficient computer algorithm, for example, can quickly interpret and sort large amounts of data to scale business operations and maximize profits. Similarly, dynamic algorithms work behind the scenes to anticipate, isolate and address critical network failures in real time.

Beyond the simple mathematical function of an algorithm lies the potential for a computer to engage in “machine learning.” Algorithms are used to facilitate artificial intelligence, allowing a computer to move beyond simple executive function to engage in automated reasoning. Using pattern recognition and data mining, computers can independently analyze online behavior to make judgements about what a user sees, then deliver targeted content designed to influence user activity online.

Algorithms have many practical business applications, allowing the user to

  • Efficiently organize data. Sorting algorithms form the basis for other algorithms to work, ordering data in such a way that is more readable and understandable for the user. They fine-tune data searches with a high level of detail, such as those related to glossaries or dictionaries.
  • Identify information quickly. A binary search can quickly and accurately pinpoint specific data and is extremely useful for scanning big lists. Rather than scan each individual term, this algorithm continuously divides a data set until a search term is identified.
  • Solve logistical challenges. Using shortest path algorithms, businesses can find cost paths that optimize overall operations, from networking to transportation and logistics. Practical applications include mapping delivery routes, or building infrastructure, such as roads or bridges.
  • Optimize complex networks. Dynamic programming relies on algorithms to break apart challenges into smaller, more identifiable issues that are easier to resolve. The result is a sustainable network design that can work through unexpected failures without interruption.
  • Find new customers. Search algorithms organize and prioritize content for consumers based on their online habits. Known as “machine learning,” search algorithms are used by internet search engines and voice recognition apps based on historical data or user experience.
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