Nobody saw ChatGPT coming. Not even OpenAI comes close. Before it became the fastest-growing consumer app in history, before it popularised the phrase "generative pre-trained transformers," and before every company you can think of was racing to adopt its underlying model, ChatGPT debuted in November as a "research preview."
In this article, we have explained how ChatGPT sparked a new AI race and revived the popularity of text boxes. Read to know more about ChatGPT sparked a new AI race.
The blog post that announced ChatGPT has since become a hilarious case study in underselling. "ChatGPT is a sibling model to InstructGPT, which is trained to respond to a prompt with a detailed response." We are excited to launch ChatGPT to gather user feedback and learn about its strengths and weaknesses." That's all! That's the entire pitch! There will be no waxing lyrical about fundamentally altering the nature of our interactions with technology, not even a line about how cool it is. It was just a sneak peek at the research.
But now, only four months later, it appears that ChatGPT will truly change the way we think about technology. Or, more precisely, change it back. Because, if things continue as they are, the future of technology will not be whiz-bang interfaces or the metaverse. It's "typing commands into a computer text box." The command line is back, but it's a lot smarter now.
In reality, generative AI is moving in two directions at the same time. The first is much more infrastructure-oriented, adding new tools and capabilities to what you already have. Large language models, such as GPT-4 and Google's LaMDA, will assist you in writing emails and memos; they will automatically spruce up your slide decks and correct any errors in your spreadsheets; they will edit your photos better than you can; and, in many cases, they will write code for you.
Isn't this roughly the path AI has taken for years? Over the last few years, Google has been incorporating various types of AI into its products, and companies such as Salesforce have established strong AI research projects. These models are costly to develop, train, and query, but they have the potential to revolutionize corporate productivity. AI enhancements in products you already use are a big business-or are being treated as such-and will be for a long time.
The other AI trend, in which interacting with the AI turns into a consumer good, was much less obvious. It makes sense now, of course: who doesn't want to talk to a robot that knows all about movies and recipes and what to do in Tokyo, if I say just the right things might go totally off the rails and try to make out with you? But before ChatGPT took the world by storm, and before Bing and Bard both took the idea and tried to build their products out of it, I certainly wouldn't have bet that typing into a chat window would be the next big thing in user interfaces.
In some ways, this is a return to an old idea. For many years, most users only interacted with computers by typing on a blank screen-the command line was how you told the machine what to do.
But then, a funny thing happened: we invented better interfaces! The problem with the command line was that you had to know exactly what to type and where to type it for the computer to behave. It was much easier to teach people what the computer could do by pointing and clicking on large icons, and it was much easier to teach people what the computer could do by using pictures and icons. The command line gave way to the graphical user interface, and the GUI still reigns supreme.
However, developers never gave up trying to make chat UI work. WhatsApp is a good example: the company has spent years trying to figure out how users can use chat to interact with businesses. Also, one of Google's numerous failed messaging apps, hoped you'd interact with an AI assistant while chatting with your friends. The first round of chatbot hype, circa about 2016, had a lot of very smart people thinking that messaging apps were the future of everything.
There's just something alluring about the messaging interface, the "conversational AI." It starts with the fact that we all know how to use it; messaging apps are how we communicate with the people we care about the most, so they're a place where we spend a lot of time and energy. You might not know how to use the Uber app or find your frequent flier number in the Southwest app, but "text these words to this number" is a behavior that almost everyone understands. In a market where people don't want to download apps and mobile websites mostly still suck, messaging can simplify experiences in a big way.
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