9/27/2023 0 Comments Hexagon tech![]() ![]() At last count, more than 25 million people were using ChatGPT each day, and millions are testing a variety of other new products. That’s still the case, except now, instead of testing a product’s viability by circulating it among a small number of experts, companies are releasing new AI tools to larger and larger audiences. ![]() “It was a way to create hype,” says Cantarella. This made a minimum viable product better than no product at all. ![]() As Cantarella notes, tech companies at the turn of the millennium risked losing funding by waiting to release products because of how fast the development process was. In the late 90s, tech companies started to popularize the idea that when it comes to software, good is better than perfect, and that products can be released-and problems corrected-later. “The tool is just so powerful.” Across many industries, firms are already relying on its less-than-perfect output to make key hiring, marketing, and operational decisions.įor years, companies have trialed products before releasing them, usually behind closed doors, in focus groups or beta testing. “There is a risk in this case,” says Chris Cantarella, global sector leader of the Software practice at Korn Ferry. ![]() They contend that the potential risks-of a new AI tool that can create content almost as well as a human being can-are too great to be left to users to figure out. The approach is known as the “minimum viable product” model, and it has at least some experts worried. Welcome to a longstanding practice in the tech field: the release of flawed products designed to improve as consumers use them. Since then, various tech firms, large and small, have come out with other intriguing AI products that are similarly imperfect In a matter of months, millions of people have come to rely on ChatGPT, even though the technology, by its own makers’ admission, was released while still in beta. ![]()
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