Yann LeCun, chief AI scientist at Meta, speaks at the Viva Tech conference in Paris on June 13, 2023.
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Yann LeCun, chief scientist at Meta and a deep learning pioneer, believes that today’s AI systems have the common sense to push their abilities beyond simply summarizing piles of text in creative ways. He said he believed it would take decades to reach awareness.
His perspective is in contrast to that of Nvidia CEO Jensen Huang recently said that within five years, AI will be “fairly competitive” with humans and will outperform them at many mentally intensive tasks.
“I know Jensen,” LeCun said at a recent event marking the 10th anniversary of Facebook’s parent company’s Fundamental AI Research Team.Mr. Lucan said: Nvidia CEOs have a lot to gain from the AI trend. “There’s an AI war going on and he’s supplying the weapons.”
”[If] The more AGI you think you have, the more GPUs you need to buy,” LeCun said of engineers trying to develop artificial general intelligence, an AI equivalent to human-level intelligence. The pursuit of AGI will require more Nvidia computer chips.
LeCun said society is likely to adopt “cat-level” or “dog-level” AI years before human-level AI. And the technology industry’s current focus on language models and text data alone will not be enough to create the advanced human-like AI systems that researchers have been dreaming of for decades.
“Text is a very poor source of information,” LeCun said, explaining that it would probably take humans 20,000 years to read the amount of text used to train modern language models. “Even if you train a system with the equivalent of 20,000 years of reading material, it still won’t understand that if A is the same as B, then B is the same as A.”
“There are a lot of really basic things in the world that you can’t get with this kind of training,” LeCun says.
That’s why LeCun and other Meta AI executives are hard at work exploring how the so-called transformer models used to create apps like ChatGPT can be tailored to handle a variety of data, including audio, image, and video information. I’ve been doing it. The idea is that the more these AI systems can discover perhaps billions of hidden correlations between these different types of data, the more likely they will be able to perform greater feats.
Part of Mehta’s research includes software that can help teach people how to play tennis better while wearing the company’s Project Aria augmented reality glasses, which blend digital graphics into the real world. . Executives showed off a demo in which a tennis player wearing AR glasses can see visual cues that teach them how to hold a tennis racket correctly and swing their arms with perfect form. This type of digital tennis The AI model required to power his assistant requires that in addition to text and voice he combines three-dimensional visual data, in case the digital assistant needs to speak. .
These so-called multimodal AI systems represent the next frontier, but their development won’t be cheap. And with more parent companies like Meta and Google; alphabet Exploring more advanced AI models could give Nvidia an additional advantage, especially if no other competitors emerge.
