Meta’s AI Chief Publishes Paper on Creating ‘Autonomous’ Artificial Intelligence

In the nearly 70 years since AI was first introduced to the public, machine learning has exploded in popularity, and has since grown to reach dizzying heights. Yet despite how quickly we’ve come to rely on the power of computing, one question has haunted the field for almost as long as its inception: Could these superintelligent systems one day gain enough sentience to match, or even surpass humanity?

Despite some dubious recent claims—for example, the ex-Google engineer who claimed a chatbot had gained sentience before being fired—we’re pretty far off from that reality. Instead, one of the biggest barriers to a robot overlord situation is the simple fact that compared to animals and humans, current AI and machine learning systems are lacking in reason, a concept essential to the development of “autonomous” machine intelligence systems—that is, AI that can learn on the fly, directly from observations of the real world, rather than lengthy training sessions to perform a specific task. 

Now new research published earlier this month in Open Review.net by LeCun, proposes a way to fix this issue by training learning algorithms to learn more efficiently, as AI has proven that it isn’t very good at predicting and planning for changes in the real world. On the flip side, humans and our animal counterparts are able to gain enormous amounts of knowledge about how the world works through observation and with remarkably little physical interaction. 

LeCun, besides leading AI efforts at Meta, is also a professor at New York University has spent his storied career developing learning systems that many modern AI applications rely on today. In trying to give these machines better insight into how the world operates, he could arguably be hailed as the father of the next generation of AI. In 2013, he went on to found the Facebook AI Research (FAIR) group, Meta’s first foray in experimenting with AI research, before stepping down to become the company’s chief AI scientist a few years later. 

Since then, Meta has had varying levels of success in trying to dominate the ever-growing field. In 2018, their researchers trained an AI to replicate eyeballs in hopes of making it easier for users to edit their digital photos. Earlier this year, the Meta chatbot BlenderBot3 (which proved to be surprisingly malicious towards its creator), stirred up debate on AI ethics and biased data. Most recently, Meta’s Make-a-Video tool is able to animate both text as well as single and paired images into videos, spelling even more bad news for the once-promising rise of AI-generated art.