Nvidia's Jensen Huang Says AGI Is 5 Years Away

Haje Jan Kamps writes via TechCrunch: Artificial General Intelligence (AGI) -- often referred to as 'strong AI,' 'full AI,' 'human-level AI' or 'general intelligent action' -- represents a significant future leap in the field of artificial intelligence. Unlike narrow AI, which is tailored for specific tasks (such as detecting product flaws, summarize the news, or build you a website), AGI will be able to perform a broad spectrum of cognitive tasks at or above human levels. Addressing the press this week at Nvidia's annual GTC developer conference, CEO Jensen Huang appeared to be getting really bored of discussing the subject -- not least because he finds himself misquoted a lot, he says. The frequency of the question makes sense: The concept raises existential questions about humanity's role in and control of a future where machines can outthink, outlearn and outperform humans in virtually every domain. The core of this concern lies in the unpredictability of AGI's decision-making processes and objectives, which might not align with human values or priorities (a concept explored in depth in science fiction since at least the 1940s). There's concern that once AGI reaches a certain level of autonomy and capability, it might become impossible to contain or control, leading to scenarios where its actions cannot be predicted or reversed.

When sensationalist press asks for a timeframe, it is often baiting AI professionals into putting a timeline on the end of humanity -- or at least the current status quo. Needless to say, AI CEOs aren't always eager to tackle the subject. Predicting when we will see a passable AGI depends on how you define AGI, Huang argues, and draws a couple of parallels: Even with the complications of time-zones, you know when new year happens and 2025 rolls around. If you're driving to the San Jose Convention Center (where this year's GTC conference is being held), you generally know you've arrived when you can see the enormous GTC banners. The crucial point is that we can agree on how to measure that you've arrived, whether temporally or geospatially, where you were hoping to go. 'If we specified AGI to be something very specific, a set of tests where a software program can do very well -- or maybe 8% better than most people -- I believe we will get there within 5 years,' Huang explains. He suggests that the tests could be a legal bar exam, logic tests, economic tests or perhaps the ability to pass a pre-med exam. Unless the questioner is able to be very specific about what AGI means in the context of the question, he's not willing to make a prediction. Fair enough.

Read more of this story at Slashdot.