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AI could pass any human exam in 5 years, clear medical tests: Nvidia CEO

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The peak of artificial intelligence advancements could be reached in as soon as five years, said AI-chipmaker Nvidia’s chief executive officer Jensen Huang. He added that the possibility of computers that can think and act like humans may arrive in the near future.

Nvidia CEO said that AI could advance rapidly over the next 5 years.(Reuters)
Nvidia CEO said that AI could advance rapidly over the next 5 years.(Reuters)

He was responding to a question at an economic forum held at Stanford University when he talked about how AI could take a massive leap over the next five years.

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While answering this question, the Nvidia CEO said that the measure of AI advancements depend on the goal. If the goal is to pass human tests, then this artificial general intelligence (AGI) could arrive as soon as five years.

“If I gave an AI … every single test that you can possibly imagine, you make that list of tests and put it in front of the computer science industry, and I’m guessing in five years time, we’ll do well on every single one,” he said.

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 should also be able to pass any of them.

However, by other definitions, AGI could still be further away as scientists are still researching how the human brain actually works. “Therefore, it’s hard to achieve as an engineer” because engineers need defined goals, Huang said.

Huang also addressed a question about how many more chip factories, called “fabs” in 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.

The Nvidia CEO said that still many more chip factories are needed, but the AI chips get better and better with time and research, eventually slowing down manufacturing.”We’re going to need more fabs. However, remember 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 is today, and therefore the demand is this much,” he added.

(With inputs from Reuters)

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