AI experts are already looking for a way to improve the speed of so-called machine learning. And recently, Yann LeCun presented a way to bring Intuition And Common Sense To AI.
Ways To Bring Intuition And Common Sense To AI
While the rest of the company is mandated to work towards Mark Zuckerberg’s metaverse dreams, Facebook’s head of AI is quietly building a roadmap toward “autonomous” AI.
For example, the head of Meta AI and famed computer scientist Yann LeCun published a paper earlier this summer, presenting it last week in Berkeley. The writing describes the lack of “common sense” in the current AI effort and lays out a path for future iterations so that machines can “learn as efficiently as humans and animals” as they become increasingly autonomous.
Common sense, as LeCun describes it, is a collection of “world models” that allow humans and animals to predict whether events are likely or unlikely, likely or unlikely, possible or impossible.
“A self-driving system for cars may require thousands of tests to incorporate the fact that going too fast in a corner will have a bad result and learning to slow down to avoid skidding,” wrote the pioneering AI researcher. “In contrast, humans can draw on their intimate knowledge of intuitive physics to predict such outcomes and largely avoid fatal courses of action when learning a new skill.”
To bridge the gap between the many trial-and-error iterations required to train neural networks and the “intuitive” nature of organic knowledge, LeCun proposes to restructure algorithm training methodology to learn more efficiently and thus develop a combination of common sense that we humans take for granted.
Clearly passed, it will likely take something akin to intuition to move AI from its current state—which is no doubt already impressive—to something closer to human intelligence.
“It’s a practical problem because we really want machines with common sense,” LeCun said during his late-September talk in Berkeley. “We want driverless cars, we want home robots, we want intelligent virtual assistants.”
Because he’s a scientist, the Meta AI chief’s next-generation algorithm training architecture involves a bunch of moving parts, like a system that replicates short-term memory, another that teaches self-critical neural networks, and the establishment of a “configurator” module that synthesizes all inputs into useful information. Here is the diagram of it:
Taken together, these components are intended to help artificial intelligence replicate the processes of the human mind, a prospect as fascinating as it is terrifying.
That Meta’s top AI researcher is quietly circulating a paper on turning AIs into autonomous “thinkers” is in itself a very intriguing story, and given what it hopes to accomplish, it may even be a boon to the tech giant. in crisis that has often shown, ironically, a lack of common sense toward its users.
What do you think will happen if we bring Intuition And Common Sense To AI?
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