Generative AI: The Future Is AI Writing Its Own Code – Forbes
Generative AI is in a Cambrian explosion of capability. Dall-E, Stable Diffusion, GPT-3, OpenAI, Hugging Face, and dozens if not hundreds of other projects, startups, and organizations are cultivating AI engines that create art, make music, generate synthetic humans, birth artificial influencers and celebrities, literally generate video from text, and threaten to upend our notions of creativit…….
Generative AI is in a Cambrian explosion of capability. Dall-E, Stable Diffusion, GPT-3, OpenAI, Hugging Face, and dozens if not hundreds of other projects, startups, and organizations are cultivating AI engines that create art, make music, generate synthetic humans, birth artificial influencers and celebrities, literally generate video from text, and threaten to upend our notions of creativity, art, public domain, copyright, and the nature of reality itself.
This is just the beginning, Glimpse AI CEO Alex Cardinell told me in a recent TechFirst podcast.
The ultimate thing for AI to create is more of itself.
God creating Adam, in an image Dall-E created based on a prompt from the writer. Dall-E has major … [+]
John Koetsier
“The most exciting part of it all … is when maybe AI is also at the point where it can start writing the code that will make its own AI even better,” Cardinell says. “And that’s like where the true singularity is … when it can kind of set itself to improve itself, when it can start to improve itself better than what a human can. And the fact that we’re already making great progress in that … it’s impossible to speculate what society could truly look like in such a situation. But I think in most of our lifetimes we’re going to experience that. And for me personally, I can’t think of anything more exciting than that.”
Exciting is one word for that.
Another is terrifying.
The singularity is, of course, that theoretical time when the curved graph of technological progress blasts off like a SpaceX Falcon Heavy rocket and hurtles near-vertical into an incomprehensible future of increasingly accelerating innovation and change. Whether this will happen, and how it will progress if it does is impossible to know, but there’s no guarantee that humanity as we know it would survive such a time, or that the vast AI entities potentially created by such an explosion would be benevolent to life as we know it.
What we do know is that generative AI is exploding now in a new “Silicon Valley gold rush” as, despite the economic downturn, venture capitalists pour hundreds of millions of dollars into 150 (and counting) generative AI startups in the areas from writing code like a software engineer, chatting like a company service representative, generating images like a photographer, creating music like an artist, selling like a sales rep, diagnosing disease like a doctor, and (gulp!) writing text like a human.
And the pace of innovation is accelerating.
“In what was basically like six months, it went from kind of this novelty that you laugh at to something that’s actually generating really high quality content that humans can use, that can even in many cases show [the] same quality as humans,” Cardinell told me. “And it’s really even just the tip of the iceberg in terms of what’s then possible in the future.”
Cardinell’s startup makes a text-creation AI that he’s verticalized into Article Forge, which generates SEO-optimized blog posts on pretty much any topic based on a supplied keyword, and WordAI, which rewrites content uniquely in a customer-defined style.
I tried Article Forge and was reluctantly impressed, although also gratified that while it wrote a fairly decent article about Apple’s new iPhone 14 Pro, it introduced non-obvious errors that human writers wouldn’t.
Example: writing both that Apple has already released the new model, and that the price is expected to be higher than previous models.
Still, the work was strong, and could easily be used as the base superstructure on which a human writer could build, iterate, tweak, edit, enhance. The other use for technology like this is supplying content that no-one will ever write, but could find a useful human audience.
Where, as Cardinell puts it, non-consumption is the alternative.
“I think that really where AI can be empowering is in that long tail when there’s like non-consumption with the alternative, where you could not afford to create that content in the first place. And you can imagine that with like these very obscure topics. You could even imagine that for news where maybe there’s something that happened in your local neighborhood where only 20 people want to read that article and then it doesn’t make sense for a human to write it.”
Yet another alternative: literal on-demand creation of a post or article on an obscure topic. Because, as Cardinell mentions, Google has said that somewhere around 25% of search queries that people enter are things that nobody has ever searched before.
“So, you can imagine that in many ways the next version of that could even be, well, I want something written for me that’s covering a topic that nobody else has ever written about,” Cardinell says.
As always, the key is not necessarily what the technology is doing today. The key is the rate of improvement, which defines how capable it can be tomorrow.
“A couple years ago when you were thinking AI that could create content, you were imagining this kind of machine-written gibberish,” Cardinell says. “It looked like even your four-year-old kid could probably write something better.”
Today it’s already fairly impressive. Tomorrow: who knows?
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