AI is consuming staggering amounts of energy—already over 10% of U.S. electricity—and the demand is only accelerating. Now, researchers have unveiled a radically more efficient approach that could slash AI energy use by up to 100× while actually improving accuracy. By combining neural networks with human-like symbolic reasoning, their system helps robots think more logically instead of relying on brute-force trial and error.
Exactly, it’s like people got a hammer and everything looks like a nail. Like, yes, LLMs can be contorted to do a lot of different tasks, but that doesn’t mean they’re the optimal tool for accomplishing these tasks. It seems that as we’re starting to hit limits of what you can squeeze out of LLMs, the hype is starting to die down and people are rediscovering other well known techniques that can be combined with them.
Exactly, it’s like people got a hammer and everything looks like a nail. Like, yes, LLMs can be contorted to do a lot of different tasks, but that doesn’t mean they’re the optimal tool for accomplishing these tasks. It seems that as we’re starting to hit limits of what you can squeeze out of LLMs, the hype is starting to die down and people are rediscovering other well known techniques that can be combined with them.