Google DeepMind co-founder and CEO Demis Hassabis made a stunning statement during an internview claiming that artificial intelligence could end all diseases in as early as the next 10 years.
Hassabis predicted that as AI models keep developing in a rapid manner, they could not only help cure diseases, but might even bring an end to all of them.
Being interviewed on CBS' 60 Minutes, the CEO spoke of how human health has been changed by technology in the recent years and how AI could help revolutionise it further.
Take a look at the video here:
"On average, it takes, ten years and billions of dollars to design just one drug. We can maybe reduce that down from years to maybe months or maybe even weeks. Which sounds incredible today, but that's also what people used to think about protein structures. And it would revolutionise human health, and I think one day maybe we can cure all diseases with the help of AI," he said.
{{/usCountry}}"On average, it takes, ten years and billions of dollars to design just one drug. We can maybe reduce that down from years to maybe months or maybe even weeks. Which sounds incredible today, but that's also what people used to think about protein structures. And it would revolutionise human health, and I think one day maybe we can cure all diseases with the help of AI," he said.
{{/usCountry}}His claim shocked even the interviewer so asked him if he was proposing the possibility of coming up with a way to end all diseases, to which Hassabis said: “I think that's within reach. Maybe within the next decade or so, I don't see why not.”
The video gained traction on social media with Perplexity AI's CEO Aravind Srinivas rallying behind the DeepMind boss, “Demis is a genius and he should be given all resources in the world to make this happen," he said.
Recently, Hassabis talked on the advances AI had made in terms of protein structures which are used to design treatments for diseases. He told LinkedIn CEO Reid Hoffman that AI managed to fold 200 million protein structures in just one year, something that would’ve taken humans around a billion years of research time.
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