A new paper from Apple's artificial intelligence scientists has found that engines based on large language models, such as those from Meta and OpenAI, still lack basic reasoning skills.
The current AI discussion I’m reading online has eerie similarities to the debate about legalizing cannabis 15 years ago. One side praises it as a solution to all of society’s problems, while the other sees it as the devil’s lettuce. Unsurprisingly, both sides were wrong, and the same will probably apply to AI. It’ll likely turn out that the more dispassionate people in the middle, who are neither strongly for nor against it, will be the ones who had the most accurate view on it.
It’ll likely turn out that the more dispassionate people in the middle, who are neither strongly for nor against it, will be the ones who had the most accurate view on it.
I believe that some of the people in the middle will have more accurate views on the subject, indeed. However, note that there are multiple ways to be in the “middle ground”, and some are sillier than the extremes.
For example, consider the following views:
That LLMs are genuinely intelligent, but useless.
That LLMs are dumb, but useful.
Both positions are middle grounds - and yet they can’t be accurate at the same time.
The current AI discussion I’m reading online has eerie similarities to the debate about legalizing cannabis 15 years ago. One side praises it as a solution to all of society’s problems, while the other sees it as the devil’s lettuce. Unsurprisingly, both sides were wrong, and the same will probably apply to AI. It’ll likely turn out that the more dispassionate people in the middle, who are neither strongly for nor against it, will be the ones who had the most accurate view on it.
I believe that some of the people in the middle will have more accurate views on the subject, indeed. However, note that there are multiple ways to be in the “middle ground”, and some are sillier than the extremes.
For example, consider the following views:
Both positions are middle grounds - and yet they can’t be accurate at the same time.