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Exactly three weeks ago, OpenAI released ChatGPT.
Since then, it has been nearly impossible to keep up with both the hyped-up excitement and brow-furrowing concerns around use cases for the text-generating chatbot, ranging from the fun (writing limericks and rap lyrics) and the clever (writing prompts for text-to-image generators like DALL-E and Stable Diffusion) to the dangerous (threat actors using it for generating phishing emails) and the game-changing (could Google’s entire search model [subscription required] be upended?).
Is it possible to compare this moment in the evolution of generative AI to any other technology development? According to Forrester Research AI/ML analyst Rowan Curran, it is.
“The only thing that I’ve been able to compare it to is the release of the iPhone,” he told VentureBeat. Apple’s iPhone was not the first smartphone, but it buried the competition with its touchscreen, ease of use and introduction of apps that put an entire computing experience in our pockets. The release of the original iPhone in January 2007, followed by the launch of the App Store in July 2008, ushered in a period of historic technological change, Curran explained — when the mass public learned there was an entire universe of creativity and applications they could work with.
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It made people aware “that you could have this handheld computer that is basically like [having] a Star Trek tricorder in our hand — this thing with tons of sensors and capability,” he said.
ChatGPT, like the iPhone, is changing public consciousness
ChatGPT, too, is changing the public consciousness around what’s possible. But what’s happening now goes even beyond that, Curran pointed out.
“I think what is really unique here is we have a technology that is useful today, that is advancing very quickly, and that we are all learning about in real time — in terms of both how to use it and how to prevent it being used in negative ways,” he said.
ChatGPT’s release and adoption cycle has also been unique, he added. “There were a million users in the first few days or so — even if we assume a quarter of those are doubles, that is still hundreds of thousands of human brains who are all of a sudden playing with this technology, which is very much unlike any other way that we’ve had technology released and adopted,” he said.
Was this a responsible way to release ChatGPT?
While some have criticized the way OpenAI released ChatGPT — for example, venture capitalist, economist and MIT fellow Paul Kedrosky recently tweeted “[S]hame on OpenAI for launching this pocket nuclear bomb without restrictions into an unprepared society” — Curran insists it was “probably one of the most responsible ways that they could have introduced the public to this.”
OpenAI’s approach to iterating on ChatGPT and showing it to people stage-by-stage is “a really good way to get people acclimatized to this, because otherwise this would all be done behind closed doors at a large enterprise,” he said, pointing out that even for those paying attention and weren’t shocked by ChatGPT’s capabilities, advancements are coming at a remarkable pace.
“For the public to have gone right to whatever comes after ChatGPT, people would lose their minds when it came out,” he said. “I think OpenAI is trying to avoid culture shock with what they’re creating.”
Potential for seismic change in the enterprise
Just as the iPhone and apps ultimately led to a revolution across all areas of the business — from software development and social media to customer service and marketing — Curran said he thinks ChatGPT and other generative AI tools could have a “seismic change” in the enterprise in 2023, if enterprises and vendors are deliberate about how they adopt the technology.
“If we can avoid any immediate short-term, major, negative press events around this, I think the adoption will be quite deep, because the appetite is really strong right now,” he said. “You see the ease with which people are already integrating [generative AI] into existing systems of work, with a bottom-up approach — you can see this with Shutterstock, for example, which two months ago integrated DALL-E, and now Microsoft has a beta-access product called Designer, which is basically a text-to-image generator integrated with PowerPoint.”
Implementing best practices is still essential
And no matter whether it is ChatGPT or any other generative AI capabilities, implementing best practices is still essential, Curran said.
“I think we’re still all collectively figuring that out what the exact best practices are, but there is no reason to not continue to implement best practices around understanding your vendor solutions,” he said. “If you’re getting a large language model through a vendor, what model are they using? What was the base training data? What is the fine-tuning of the training data? How are they auditing this model?”
In the past, he added, enterprises have been burned by new technologies. “We never seem to really learn that when new technology comes along, we should be deliberate about its adoption,” he said. “But this time around, because there’s so much possibility for people to get involved at a grassroots level, we can actually have people step in and say, okay, I want to participate in this governance process.”
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