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You are comparing a species going from developing language to building spaceships on the order of hundreds of thousands of years, to a technology that was inven

You are comparing a species going from developing language to building spaceships on the order of hundreds of thousands of years, to a technology that was invented 7 years ago and only started to really be taken seriously 4 years ago. Working memory systems required for learning and iteratively developing ideas are in their infancy (on the scale of recent developments), but the recall technology (vector databases a la RAG) is quite well proven. I see no reason that a language model couldn't do iterative science in the same way humans have been with the resources available to it (APIs) using the composition of current technologies.

somenameforme 2y ago
The current technology for LLMs is still a rather complex guess the next word algorithm. But this leaves the software with no real room to ever move beyond its training, regardless of how much time or training you give it. You could give them literally infinite processing power and they would not suddenly start developing new meaningful knowledge - it would still be little more than simple recombinations of its training dataset, until somebody gave it something new to train upon.
xracy 2y ago
> I see no reason that a language model couldn't do iterative science in the same way humans have been with the resources available to it (APIs) using the composition of current technologies. I think this belies a common refrain from people in non-tech feeling like people in tech tend to oversimplify their fields and claim they can "fix any problem" without any actual specific knowledge in that field. This just feels like the next iteration of that.
- Zambyte 2y ago
  This seems like a lot of words to just say "you are wrong". Can you explain why? What features of the scientific method cannot be achieved through the composition of existing technologies? Feel free to be specific and use technical terms.
  - xracy 2y ago
    I think you're misreading this. I'm not saying "you are wrong". I'm saying there's a common trap that a lot of people in tech (and therefore a lot of people on HN fall into), where they believe that they can solve any problem from what they know of basic tech problems. > What features of the scientific method cannot be achieved through the composition of existing technologies? ^This statement, sums up the above trap perfectly. "I know how to create a workflow, therefore, I know how to create a workflow of the scientific method, therefore I can replace a scientist with an AI robot." But okay, how do we know what quantitatively, is a significant result? R=0.05 is the most common cut-off for this, but like, that's a number we picked, and isn't even agreed on.

somenameforme 2y ago

The current technology for LLMs is still a rather complex guess the next word algorithm. But this leaves the software with no real room to ever move beyond its training, regardless of how much time or training you give it. You could give them literally infinite processing power and they would not suddenly start developing new meaningful knowledge - it would still be little more than simple recombinations of its training dataset, until somebody gave it something new to train upon.

xracy 2y ago

> I see no reason that a language model couldn't do iterative science in the same way humans have been with the resources available to it (APIs) using the composition of current technologies. I think this belies a common refrain from people in non-tech feeling like people in tech tend to oversimplify their fields and claim they can "fix any problem" without any actual specific knowledge in that field. This just feels like the next iteration of that.

Zambyte 2y ago
This seems like a lot of words to just say "you are wrong". Can you explain why? What features of the scientific method cannot be achieved through the composition of existing technologies? Feel free to be specific and use technical terms.
- xracy 2y ago
  I think you're misreading this. I'm not saying "you are wrong". I'm saying there's a common trap that a lot of people in tech (and therefore a lot of people on HN fall into), where they believe that they can solve any problem from what they know of basic tech problems. > What features of the scientific method cannot be achieved through the composition of existing technologies? ^This statement, sums up the above trap perfectly. "I know how to create a workflow, therefore, I know how to create a workflow of the scientific method, therefore I can replace a scientist with an AI robot." But okay, how do we know what quantitatively, is a significant result? R=0.05 is the most common cut-off for this, but like, that's a number we picked, and isn't even agreed on.