Bug Byte puzzle here - https://bit.ly/4bnlcb9 - and apply to Jane Street programs here - https://bit.ly/3JdtFBZ (episode sponsor). More info in full descript...
They are discussing a very specific approach and a paper that lays out the issues with pursuing this one specific type of generative AI. It’s not about AI in general. The headline is a bit click-baity.
While the paper demonstrated strong diminishing returns in adding more data to modern neural networks in terms of image classifers, the video host is explaining how the same may effect apply to any nureal network based system with modern transformers.
While there are technically methods of generative AI that don’t use a neural network, they haven’t made much progress in recent decades and arn’t what most people mean when they hear or say generative AI, and as such I would say the title is accurate enough for a video meant for a general audience, though “Is there a fundamental limit to modern neural networks” might be more technically correct.
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They are discussing a very specific approach and a paper that lays out the issues with pursuing this one specific type of generative AI. It’s not about AI in general. The headline is a bit click-baity.
While the paper demonstrated strong diminishing returns in adding more data to modern neural networks in terms of image classifers, the video host is explaining how the same may effect apply to any nureal network based system with modern transformers.
While there are technically methods of generative AI that don’t use a neural network, they haven’t made much progress in recent decades and arn’t what most people mean when they hear or say generative AI, and as such I would say the title is accurate enough for a video meant for a general audience, though “Is there a fundamental limit to modern neural networks” might be more technically correct.