Demis Hassabis, founder and CEO of DeepMind recently was one of the three joint recipients of this year’s Nobel Prize in chemistry. DeepMind was founded with the mission of “solving” intelligence — designing artificial intelligence systems that could mimic and even supersede human cognitive capabilities. DeepMind is now focused on applying its algorithms to areas that can benefit humanity, including healthcare and climate change.
Hassabis is one of the world’s top AI pioneers and was able to unlock a 50-year-old problem: predicting the structure of every known protein using AI software known as AlphaFold.
In a recent interview with Axios, Demis says the technology’s coming power has been clear for so long that he’s amazed the rest of the world took so long to catch on.
“I’ve been thinking about this for decades. It was so obvious to me this was the biggest thing,” says in the virtual interview. “Obviously I didn’t know it could be done in my lifetime. … Even 15 years ago when we started DeepMind, still nobody was working on it, really.”
He further added, “Maybe it’s a watershed moment for AI that it’s now mature enough, and it’s advanced enough, that it can really help with scientific discovery.” “We don’t have to wait,” he said, for artificial general intelligence (AGI) systems that can outsmart humans, the holy grail for AI developers. AI can already “revolutionize drug discovery,” he pointed out.
DeepMind’s new positioning at the center of Google’s AI development was prompted by OpenAI’s ChatGPT, the Microsoft-backed group’s chatbot that provides plausible and nuanced text responses to questions. Hassabis said AI may be “overhyped in the near term” because of the success of OpenAI’s ChatGPT, which has fueled a frenzy among investors.
He shared a concern that researchers have spent years working slowly and deeply to make the present era what it is now. “I’d rather it would have stayed more of a scientific level,” he said for ChatGPT. “But it’s become too popular for that.”
However, Google DeepMind has remained primarily centered on complex and fundamental problems in science and engineering, making it one of the most influential projects in AI globally.
Hassabis thinks AI is “still massively underrated in the long term”. “People still don’t really understand what I’ve lived with and sat with for 30 years.”