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 an issue at an economic forum held at Stanford University about how long it could take to realize certainly one of Silicon Valley’s long-held goals of making computers that may think like humans.
Huang said that the reply largely will depend on how the goal is defined. If the definition is the power to pass human tests, Huang said, artificial general intelligence (AGI) will arrive soon.
Jensen Huang was responding to an issue at an economic forum held at Stanford University about how long it could take to realize certainly one of Silicon Valley’s long-held goals of making computers that may think like humans. REUTERS
“If I gave an AI … each test that you would be able to 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 similar to legal bar exams, but still struggles on specialized medical tests similar to gastroenterology. But Huang said that in five years it also needs to 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 tips on how to 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 an issue 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.
Artificial generative intelligence could also be much further away, because scientists still disagree on tips on how to describe how human minds work. Getty Images/iStockphoto
Chip maker Nvidia hit $2 trillion in market value on Friday. REUTERS
Huang said that more will probably be needed, but each chip can even recuperate over time, which acts to limit the variety of chips needed.
“We’re going to wish more fabs. Nonetheless, do not forget 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 1,000,000 times over 10 years.”
