The Evolving Role of Artificial Intelligence in Business

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The Evolving Role of Artificial Intelligence in Business

We discussed the potential impact of artificial intelligence and automation on jobs last month, and we’ve explored the future of driverless cars and trucks in several previous issues. Now, let’s explore how artificial intelligence will impact businesses.

Artificial intelligence (AI) is typically defined as “a field of computer science dedicated to the study of computer software making intelligent decisions, reasoning, and problem solving.”

However, that definition leans toward what experts consider “strong AI,” which focuses on artificial intelligence systems that are able to perform as flexibly as the human brain. That version of AI is still likely to be at least three decades from becoming a reality.

Instead, what is emerging in countless everyday applications today is what is known as “Weak” AI. Weak AI functions within a tightly focused area of ability, performing either one or a few simple tasks more efficiently than humans can perform them. Examples include:

  • Air-traffic control systems that determine flight plans and choose the optimal landing gates for airplanes.
  • Logistics apps that help companies like UPS route their trucks to save time and fuel.
  • Loan-processing systems that assess the creditworthiness of mortgage applicants.
  • Speech-recognition tools that handle incoming calls and provide automated customer service.
  • Digital personal assistants that search multiple data sources and provide answers in plain English, like Apple’s Siri.

In both cases, AI is based on a series of algorithms—a formula or set of rules—that neural networks use to process information and arrive at an answer. While scientists have been working on artificial intelligence for decades, it is only now emerging as an important business tool because of two key developments:

  1. Processing power continues to accelerate. As predicted by Moore’s Law, named for Intel cofounder Gordon Moore, the number of transistors per chip has been roughly doubling every year for the past four decades. To keep improving the performance, companies like Nvidia are supplementing the central processing unit (CPU) cores in their chips with graphics processing unit (GPU) cores.1 A CPU consists of a few cores that use serial processing to perform one task at a time, while a GPU consists of thousands of cores that use parallel processing to handle several tasks simultaneously...

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