| ▲ | mrandish 2 hours ago | |||||||
> For the benefit of a layman, can you explain why this is so much different than a human doing it? More broadly than the existing answers (which are correct), For a layman, I'd also add that LLMs are essentially 'brains in a vat'. They can't confirm ground truth about physical reality. They only know what's in their training data and prompt, which is incomplete and can be incorrect. Even with real-time external sensors they are limited to the sensor's margin of error, range and trusting it's working correctly. When properly trained, fine-tuned and prompted, LLMs can be very effective in well-defined, non-physical domains like logic, writing, math and code but making things function in the real-world quickly spirals into combinatorial complexity. | ||||||||
| ▲ | interstice 2 hours ago | parent | next [-] | |||||||
> They are limited to the sensor's margin of error, range and trusting it's working correctly So are we and our sensors can be pretty vague in comparison, I can only imagine human error correction is pretty next level. | ||||||||
| ▲ | hackyhacky 2 hours ago | parent | prev | next [-] | |||||||
> They can't confirm ground truth about physical reality. That's true. Of course we can hook an llm up to Motors and sensors. That's a robot. Or a self-driving car. So would you say that those devices can confirm the ground truth about physical reality, and therefore are capable of creativity? | ||||||||
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| ▲ | satvikpendem 2 hours ago | parent | prev [-] | |||||||
What is ground truth? If I see a digital painting by a human is that ground truth? | ||||||||