SPOTLIGHT INSIGHT
A Brief Review of All the Fuss About AI
Greg Koepel Associate Lecturer of Business
Why is it that AI is seemingly – using the trendy pop culture phrasing – everything, everywhere, all at once? Since late last fall, our newsfeeds have been bursting with articles, stories, product roll outs, etc. of something to do with AI – the abbreviation for “artificial intelligence.” The reason artificial intelligence – AI – has become the topic du jour is because of an app called ChatGPT. ChatGPT was introduced last fall and quickly garnered worldwide attention. Why? Because ChatGPT featured a type of AI that for many was considered speculative or – at best – a long way off – perhaps something that will be available to us at some nebulous time in the future. Yet here it is, in the here and now. The specific type of AI featured in ChatGPT is known as “generative” AI. At this point, it seems some background and definitions are appropriate. Discussions about AI – artificial intelligence – had already begun in earnest during the early days of computing. The term “artificial intelligence” was put forth as a descriptor of potential computing capabilities in the mid 1950’s. Fast forward to today and you’ll find that, as with most any art, craft, professional or technical endeavor, there is a language unique to the field. That’s also true of computer science – while the field has begun to coalesce around some key terms and definitions, it is also spinning out new terminology quickly – so this primer is a very basic overview at best. IBM, a leading computer research, development, and consulting company, defines AI as:
are frequently mentioned in conjunction with artificial intelligence. These disciplines are comprised of AI algorithms which seek to create expert systems which make predictions or classifications based on input data (ibm.com/ topics/artificial-intelligence#). Computer technology company, Oracle, defines a “chat bot” as: A computer program that simulates and processes human conversation (either written or spoken), allowing humans to interact with digital devices as if they were communicating with a real person (oracle.com/chatbots/what-is-a- chatbot/). Another way to describe common AI - in simplistic terms – is to say people program a computer to review vast amounts of data to recognize patterns and from those patterns make predictions. You see an example of this when you use a website and a “chat bot” pops up in the form of a text message that usually says something like, “how can I help?,” with a space for you to type in a question. The chat bot recognizes the pattern of letters you’ve typed in and makes a prediction (provides an answer) based on that pattern. To us it all seems fluid and conversational, to the computer it’s just identifying the pattern and making a prediction. That alone is actually pretty amazing and is the basic notion powering AI systems like Siri and Alexa . Now comes a new term “generative” AI. According to McKinsey, generative AI is an algorithm (computer program) “that can be used to create new content, including audio, code, images, text, simulations, and videos.” ChatGPT is a generative AI chat bot.
A field, which combines computer science and robust datasets, to enable problem- solving. It also encompasses sub-fields of machine learning and deep learning, which
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Center for Business and Economic Insight
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