Step into a new era! NVIDIA (NVDA.US) CEO Jensen Huang: AI may be able to pass human tests within 5 years.

NVIDIA (NVDA.US) CEO Jensen Huang said on Friday that, according to some definitions, artificial intelligence may be able to pass human tests in just five years. Huang is the head of a leading global artificial intelligence chip manufacturer, whose chips are used to create systems like OpenAI's ChatGPT. He answered a question at an economic forum at Stanford University about how long it will take to achieve one of Silicon Valley's long-standing goals - creating a computer that can think like a human. Huang said that the answer largely depends on how this goal is defined. If defined as the ability to pass human tests, he said, artificial general intelligence (AGI) is on the horizon. He stated: "If I give artificial intelligence...every test that you could think of, put the test list in front of the computer science industry, I guess within five years, we will do well on every test." His company NVIDIA reached a market value of $2 trillion on Friday. Currently, artificial intelligence can pass tests such as legal qualification exams, but still faces difficulties in specialized medical tests (such as gastroenterology). However, Huang said that within five years, it should also be able to pass any of these tests. However, Huang also said that, according to other definitions, AGI may still be far off, as scientists are still debating how to describe the workings of human thinking. He said: "So, as an engineer, it's hard to achieve because engineers need clear goals." In addition, Huang also addressed a question about the need for more chip factories (known as "fabs") to support the expansion of the artificial intelligence industry. OpenAI CEO Sam Altman has previously stated that more fabs are needed. Huang agreed that more fabs are indeed needed, but each chip will also improve over time, which limits the number needed. He said: "We will need more fabs. However, remember, as time goes by, we are also making significant improvements in algorithms and processing (artificial intelligence). This is not to say that the efficiency of computing is the same as today, and therefore demand is this high. In 10 years, I will have improved computing efficiency by millions of times."