HIGHLIGHTS
Shane Legg had made this prediction back in 2011.
By 2028, artificial intelligence (AI) had a 50% chance of being as smart as humans are.
There’s a twostep process that can help achieve his goal.
AI has taken the world by storm. From ChatGPT to Siri and AlexaBack, everyone is engaging and dependent on AI in some way or the other. But back in the early 2000s, if you would’ve asked someone if they believed in the power of AI, then you would’ve become a laughing stock. Let alone the early 2000s, even if you had asked someone this five years back, they would have disagreed. However, this guy from Google had predicted that by 2028, which is just five years from now, AI will become as good as human intelligence. Is it true? Let’s find out.
What Google AI Boss has predicted?
Shane Legg, the co-founder of Google’s DeepMind AI lab, had made a prediction back in 2011 that by the year 2028, artificial intelligence (AI) will accomplish Artificial General Intelligence (AGI). This means that AI will be as intelligent as humans. However, he also added that it has a 50-50 chance of being as smart as humans are. He predicted that AI evolution would match up with human intelligence. Bold prediction for the time, wasn’t it?
Let’s come to the present-day scenario now. It’s 2023, AI has developed a lot in recent years. A report by Firstpost stated that during a podcast with tech podcaster Dwarkesh Patel, Legg said that he still believes that his prediction will come true.
Considering the current scenario, Legg suggests that there’s a two-step process that can help achieve his goal. I’ll take you through them.
Firstly, he says that the achievement of Artificial General Intelligence (AGI), which is as smart as humans, will be compared to Human Intelligence. Now, human intelligence is neither quantifiable nor is it easy to define. It is very complex. He says that if researchers develop a series of tests for human intelligence and if AI succeeds in them, then it can be considered AGI.
Secondly, he suggests that AI training programs need to be scaled up significantly. AI companies are presently consuming a lot of energy. It is now time that algorithms are created that can handle the computational requirements of AGI.
He further added that we’ve reached the level where we can actually achieve the goal. Will it happen? Only time will tell.