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What’s “Generative,” Anyway?
Getting to an era of generative AI hasn’t been a short journey—and plenty of experts say we’re just at the beginning, including McIndoe Risk Management founder and CEO Bruce McIndoe, whose background includes a master’s degree in computer science from Johns Hopkins University as well as work on the fundamentals of AI with a number of government agencies prior to entering the risk management world.
In its simplest form, McIndoe said, ChatGPT and its AI foundations are “just math,” performed by systems that tokenize words (in English and other Western languages) or characters (in languages like Chinese), which machines can recognize, associate with commonly corresponding words and information and, when prompted to engage on a topic, will communicate back with humanized linguistic patterns. While it sounds simple, the scale at which machines can perform this work makes it seem “magical,” to use Twigg’s word, but it doesn’t work without humans. At least not yet, said McIndoe.
Humans train machines to weigh associations, bake in variables and return information in what seems like spontaneous combinations. In its current form, McIndoe said, ChatGPT is still reliant on human prompts, searching a vast universe of tokenized words on a network and returning responses based on the number and weight of associated vectors. Without continuous prompts, however, he said the technology as it functions today would “collapse on itself,” pulling information that it generated and reformulating it over and over.
“We’re literally just stepping off very simple machine learning using neural networks,” he said, referring to those technologies that give weight to strong and weak information associations.
Even so, industries have seen generative AI use the foundation of those inputs with multiple machine learning algorithms and a layer of creative synthesis to analyze texts, write novels, produce digital images, compose music and code more spontaneous action into video games.
There are serious concerns within systems, however, with issues of factuality, bias, quality, plagiarism and intellectual property. ChatGPT, Bard and OpenAI produce much of its content “in the style of” and clearly based on the inputs of human artists and content owned by companies or individual creators. Questions of intellectual property, privacy and data ownership in the face of generative AI are real for every industry. Yet, so are the possibilities.
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