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Does The Shortage Of Human Inputs Limit AI Development?
One of the stories that has been making the rounds recently is the idea that there is a limit or a plateau to how smart AI can get, particularly LLM (large language model) artificial intelligence.
That's right - humans have been writing and speaking and driving seemingly without limits, but it's just not enough.
"There is a serious bottleneck here," AI researcher Tamay Besiroglu, lead author of a new paper to be presented at a conference this summer, told the Associated Press. "If you start hitting those constraints about how much data you have, then you can’t really scale up your models efficiently anymore."
"And scaling up models has been probably the most important way of expanding their capabilities and improving the quality of their output," he added.
(Via Futurism)
Perhaps artificial intelligence developers should take a hint from science fiction writer Anthony Boucher. In his 1943 short story Q.U.R., Boucher describes how royalties should be paid to the subjects of machine learning:
...without new training data, it's likely the models won't be able to get any smarter, a point of reckoning for the burgeoning AI industry.
"I got one of those new electronic cameras - you know, one thousand exposures per second... So we took pictures of Guzub making a Three Planets, and I could construct this one to do it exactly right down to the thousandth of a second. The proper proportion of vuzd, in case you're interested, works out to three-point-six-five-four-seven eight-two-three drops. It's done with a flip of the third joint of the tentacle on the down beat. It didn't seem right to use Guzub to make a robot that would compete with him and probably drive him out of business, so we've promised him a generous pension from the royalties on usuform barkeeps."
(Read more about Royalties For Machine Learning Subjects)
Scroll down for more stories in the same category. (Story submitted 6/2/2024)
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