Nvidia CEO Jensen Huang said Wednesday that artificial intelligence is overtaking humans.
Speaking at the New York Times’ annual Dealbook Summit, Huang said that if artificial general intelligence (AGI) is defined as a computer that can complete tests in a way that is “fairly competitive” to human intelligence. , “Within the next five years, of course, there will be AI that can accomplish those tests.”
Nvidia’s business is rapidly growing in high-performance graphics processing units needed to train AI models and run high-volume workloads across industries such as automotive, architecture, electronics, engineering, and scientific research. (GPU) and OpenAI’s ChatGPT are rapidly increasing in demand. .
Nvidia’s fiscal third quarter revenue tripled and net income rose to $9.24 billion from $680 million a year earlier.
In an interview on Wednesday, Hwang said that before he left the AI Project in 2018, AI Project co-founder Elon Musk told OpenAI he wanted to “worldwide” after hearing Hwang speak about the device at a conference. He recalled delivering the first AI supercomputer.
“Elon looked at it and said, ‘I want that.’ He told me about OpenAI,” Huang said. “That day, I delivered the world’s first AI supercomputer to OpenAI.”
Regarding the recent turmoil surrounding OpenAI, its board structure, and the firing and subsequent reinstatement of CEO Sam Altman, Huang said he hopes things calm down.
“I’m glad they reconciled and I hope they reconcile. They really are a great team,” said Hwang. “It also reminds us of the importance of corporate governance. NVIDIA is here 30 years after its founding, and we have overcome a lot of adversity. No one knows what happened.”
Huang predicts that competition in the AI field will lead to the emergence of off-the-shelf AI tools that companies across industries, from chip design and software creation to drug discovery and radiology, can tailor to their needs. did.
On stage, Hwang was asked to rank the success of various companies in the AI market.
“I’m not going to rank my friends,” he said. “I admit it, and I’d like to, but I’m not going to do it.”
One reason the high-tech industry is still years away from realizing AGI is that while machine learning is currently proficient at tasks such as recognition and recognition, That’s because step-by-step inference can’t be done yet, Huang said.
“Everyone is working on it,” Huang said.
And technology is advancing very rapidly.
“There’s no question that the rate of progress is high,” Huang said. “What we realized today is, of course, what we can do today with these models and intelligence is related, but not the same.”
clock: Nvidia CEO says it will take at least 10 years for U.S. chipmaker’s Chinese supply chain to become independent
