A wave of A.I. experts left Google, DeepMind, and Meta—and the race is on to build a new, more useful generation of digital assistants
Adept AI and other startups are building digital companions that do more than just talk
Alexa, what’s the future of digital assistants? I don’t how Alexa would answer that question. But looking at the number of top A.I. minds who have recently left big tech companies to create well-funded startups dedicated to building a new-breed of digital assistants aimed at being useful for business, a golden era of digital work companions is likely to be around the corner.
Among this new crop of digital startups is Adept AI Labs. The company, which emerged from “stealth mode” earlier this year with $65 million in initial venture capital funding, stands out for its founding team. They include a group of researchers from Google Brain who in 2017 invented the A.I. architecture known as “The Transformer.” This algorithmic design has underpinned a huge number of A.I. advances, especially in natural language processing, over the past five years. Now, the team that created the Transformer thinks the same basic idea can be used to create more capable, general assistants that will be able to work alongside people to help perform a wide range of business tasks.
“The problem we’ve carved out is how to get machine to collaborate with humans and actually build things for them,” says Ashish Vaswani, Adept’s co-founder and chief scientist. Vaswani was the lead author on the paper that introduced the Transformer. He says what Adept is building is not simply a better chat bot. “We want to figure out how to get machines to perform actions for people, not just have conversations with them.”
Vaswani says the software Adept is building will learn through human feedback, not just by ingesting a lot of pre-existing data from text, which is how most large language A.I. systems are trained today. David Luan, Adept’s co-founder and CEO, says that language understanding is a key capability that Adept’s software will have to possess, since language is a major way humans provide feedback. But the system won’t just stop with language. “You can think of it as a universal teammate,” Luan says. “If you had another person on your team, what would you shamelessly ask them to do? That’s what we want this software to do.”
Adept’s first step has been creating software that can follow natural language instructions to perform tasks using other software. In a demonstration of this that Adept has posted online, its software uses a basic SQL database to perform a variety of tasks. A user types “can you grab the name and population for every country?” and the software goes ahead and pulls that data from the database and assembles it in a simple table. Then a user asks the software to “make a bar plot of that,” and the software does so. But the plot is hard to read because it contains too many countries. So the user asks it to just “to show the countries with the 6 highest populations,” and the software comes right back with a much easier to read chart. This time though the labels for the six countries are overlapping, which still isn’t great. So the user types, “Good. But the x axis is still a bit hard to read, can you fix that?” And remarkably, the software does so—by writing the labels on an angle—even though the feedback from the user was not that specific. Later in the demo, the software grabs publicly-available U.S. unemployment figures from the Internet and charts those.
This is what Luan calls teaching the software to “climb the ladder of abstraction.” Eventually, Vaswani says, he wants the software to be able to take an instruction as abstract and complex as, “tell me how my customers are churning?” and have the software analyze the data and produce a report, all without having to receive additional instructions.
Why didn’t Vaswani and his group just stay at Google and build this general assistant for the tech giant? Well, Niki Parmar, another member of the Google team who left to co-found Adept as its chief technology officer, says that at Google, A.I. research is set up to enhance existing products, not create entirely new product categories. “This is what excites us about Adept,” she says. “Here we can have both research and product together.” She says Adept plans to have a minimally viable product out with customers within months. “We are a small team that is very aligned to the mission, and we can move fast,” she says.
In addition to Adept, there are also startups such as Cohere AI, also founded by veterans of Google Brain, including researchers who worked alongside Vaswani on the Transformer, as well as alumni from Meta’s AI Research division and DeepMind. And there’s Inflection, which was co-founded by former DeepMind co-founder Mustafa Suleyman and LinkedIn co-founder Reid Hoffman. All of these companies are looking to create A.I. to assist humans at a wide variety of tasks.
It will be interesting to watch and see how capable these new digital assistants will really be, which will gain traction and for what uses, and how the major tech companies, such as Google and Microsoft, will respond to what could turn out to be a formidable threat to parts of their business.