Facebook's artificial intelligence chief is quietly building a road map towards "autonomous" machine intelligence as the rest of the company is mandated to work towards Mark Zuckerberg's metaverse dreams.
A case in point is a paper that was published earlier this summer by Meta Artificial Intelligence Chief and renowned computer scientist, Yann LeCun, that describes a lack of common sense in current artificial intelligence efforts and lays out a path to future iteration that learns as efficiently as humans.
According to LeCun, common sense is a collection of models of the world that allow humans and animals to predict whether an event is likely or not.
A self-driving system for cars may need thousands of trials of reinforcement learning to learn that driving too fast in a turn will result in a bad outcome, and to learn to slow down to avoid skidding. Humans can use their knowledge of intuitive physics to predict outcomes and avoid fatal courses of action when learning a new skill.
LeCun wants to bridge the gap between the many iteration of trial and error required to train neural networks and the "intuitive" nature of organic knowledge.
While it doesn't sound sexy, something akin to intuition will likely be required to move Artificial Intelligence closer to human intelligence.
LeCun said during his talk at Berkeley that he wanted machines with common sense. Self-driving cars, domestic robots, and intelligent virtual assistants are some of the things we want.
A system that replicates short-term memory is one of the moving parts of the Meta AI chief's next generation architecture.
The components are meant to help machine intelligence mimic the processes of the human mind.
It's a fascinating story, and it may even be a huge boon for the ailing tech giant because of the paper that Meta's top artificial intelligence researcher is circulating.
A woman is horrified to discover that her private medical photos are being used to train artificial intelligence.
All Rights Reserved © 2024
