Nvidia Chief Executive Jensen Huang on Friday said that artificial general intelligence could – by some definitions – arrive in as little as five years.
Huang, who heads the world’s leading maker of artificial intelligence chips used to create systems like OpenAI’s ChatGPT, was responding to a matter at an economic forum held at Stanford University about how long it will take to realize one in every of Silicon Valley’s long-held goals of making computers that may think like humans.
Huang said that the reply largely is determined by how the goal is defined. If the definition is the flexibility to pass human tests, Huang said, artificial general intelligence (AGI) will arrive soon.
“If I gave an AI … each test that you may possibly imagine, you make that list of tests and put it in front of the pc science industry, and I’m guessing in five years time, we’ll do well on each one,” said Huang, whose firm closed above $2 trillion in market value on Friday for the primary time.
As of now, AI can pass tests such as legal bar exams, but still struggles on specialized medical tests such as gastroenterology. But Huang said that in five years it must also have the opportunity to pass any of them.
But by other definitions, Huang said, AGI could also be much further away, because scientists still disagree on describe how human minds work.
“Due to this fact, it’s hard to realize as an engineer” because engineers need defined goals, Huang said.
Huang also addressed a matter about what number of more chip factories, called “fabs” within the industry, are needed to support the expansion of the AI industry. Media reports have said OpenAI Chief Executive Sam Altman thinks many more fabs are needed.
Huang said that more can be needed, but each chip may also recover over time, which acts to limit the variety of chips needed.
“We’re going to wish more fabs. Nevertheless, keep in mind that we’re also improving the algorithms and the processing of (AI) tremendously over time,” Huang said. “It’s not as if the efficiency of computing is what it’s today, and subsequently the demand is that this much. I’m improving computing by one million times over 10 years.”