This was late last year. I attended an event hosted by Google to celebrate its AI advances. The company’s domain in New York’s Chelsea neighborhood now extends literally onto the Hudson River, and about a hundred of us gathered in a pierside exhibition space to watch scripted presentations from executives and demos of the latest advances. Speaking remotely from the West Coast, the company’s high priest of computation, Jeff Dean, promised “a hopeful vision for the future.”
The theme of the day was “exploring the (im)possible.” We learned how Google’s AI was being put to use fighting wildfires, forecasting floods, and assessing retinal disease. But the stars of this show were what Google called “generative AI models.” These are the content machines, schooled on massive training sets of data, designed to churn out writings, images, and even computer code that once only humans could hope to produce.
AI has a strange world. In the early part of this century, the field burst out of a lethargy—known as an AI winter—by the innovation of “deep learning” led by three academics. This approach to AI transformed the field and made many of our applications more useful, powering language translations, search, Uber routing, and just about everything that has “smart” as part of its name. We’ve spent a dozen years in this AI springtime. In the past year, however, there’s been an unexpected aftershock to this earthquake. A sudden profusion mind-bending generative model has appeared.
Google displayed a wide range of toys at the New York Pier. Most were generative models, including its flagship LaMDA model. It can answer questions and work with creative writers to make stories. Other projects can produce 3D images from text prompts or even help to produce videos by cranking out storyboard-like suggestions on a scene-by-scene basis. A large portion of the program addressed ethical concerns and the potential dangers associated with unleashing robot content creators onto the world. The company made it clear how they were cautious when using their powerful creations. Douglas Eck, principal scientist at Google Research, made the most striking statement. “Generative AI models are powerful—there’s no doubt about that,” he said. “But we also have to acknowledge the real risks that this technology can pose if we don’t take care, which is why we’ve been slow to release them. And I’m proud we’ve been slow to release them.”
But Google’s competitors don’t seem to have “slow” in their vocabularies. Google only allowed limited access to LaMDA through a private Test Kitchen app. Other companies offer a smorgasbord of chatbots, image generators, and all you can eat food. Only a few weeks after the Google event came the most consequential release yet: OpenAI’s latest version of its own powerful text generation technology, ChatGPT, a lightning-fast, logorrheic gadfly that spits out coherent essays, poems, plays, songs, and even obituaries at the merest hint of a prompt. Taking advantage of the chatbot’s wide availability, millions of people have tinkered with it and shared its amazing responses, to the point where it’s become an international obsession, as well as a source of wonder and fear. Will ChatGPT kill the college essay? Destroy traditional internet search? Put millions of copywriters, journalists, artists, songwriters, and legal assistants out of a job?
Answers to those questions aren’t clear right now. However, one thing is clear. Granting open access to these models has kicked off a wet hot AI summer that’s energizing the tech sector, even as the current giants are laying off chunks of their workforces. Contrary to Mark Zuckerberg’s belief, the next big paradigm isn’t the metaverse—it’s this new wave of AI content engines, and it’s here now. The 1980s saw a boom in products that could move tasks from paper onto a PC. You could easily make quick money by moving desktop products online in the 1990s. The shift to mobile was made a decade later. Building with generative AI will be the major trend in the 2020s. A lot of startup companies will create business plans that are based on these systems’ APIs this year. Generating generic copy will become virtually free. AI-generated video will likely dominate TikTok by the end of this decade. While they won’t be as innovative as those created by talented humans, robots will still dominate quantitatively.
