4 ms·

...but in a technical context, not in a scientific one. One thing is identifying (age of copper; age of bronze) the best ways of smelting ore to obtain the met

by mdp2021 3y ago

...but in a technical context, not in a scientific one. One thing is identifying (age of copper; age of bronze) the best ways of smelting ore to obtain the metal through trial and error, another is to try and understand the nature of materials.

mensetmanusman 3y ago
Those steps are both necessary and usually take decades to build understanding.
- mdp2021 3y ago
  But the activity of "attempting to find explanations" is specific. The attempt to formulate laws (the "better faring hypoteses") can bring to "universal laws" or to more humble "patterns". It will contribute to the scientific effort - it does not exhaust it.
- visarga 3y ago
  Next time we get the urge to complain that GPT-n is just applying patterns seen in the training corpus we should remember humans don't do much better. We are just language agents with rich feedback from outside. We can't even write software top-down in one go without running the code.
  - mdp2021 3y ago
    > patterns Except we consciously (intentionally) work on those matchings. > are Opinions should be offered in proper places. Polling is not debating.
  - mdp2021 3y ago
    Incidentally, that opinion is also offensive. Not just some tossed "All X are Y, goodnight", but a loaded one. If you happen to conjure thoughts and let them roam wildly, well don't. Make an effort. Critical thinking as a conscious intentional effort must have plenty of literature. The "feedforward" output, the hallucination, is not a dish for service.
TeMPOraL 3y ago
Corporate wants you to find the difference... That is to say, the two things you mention are the same process. "Identifying the best ways of smelting ore to obtain the metal through trial and error" is the easy part, when you get to pick low-hanging fruits in a field. But as the easy options get cleared out, continuing improvements requires increasingly complex, sophisticated methods - that's where the process transitions towards "trying and understanding the nature of materials". It's still the same process, but couple layers of abstraction up from the original "how to get better stick than neighbor and beat them instead of getting beaten".
- mdp2021 3y ago
  The difference, while moving in "interdependent" directions, is in the purpose: obtaining some sufficient information on how things work versus an actual consideration of the nature of things. It is not really (fully the same process), because you could (in theory) "early stop" when you have achieved technically sufficient competence - the description of the optimal process -, before the jump to the understanding. Something works - that is the technical side; why it works is the scientific side. Note that the approach has controversial sides: if you took Newton's "hypoteses non fingo", He refused that jump explicitly: > hypotheses, whether metaphysical or physical, or based on occult qualities, or mechanical, have no place in experimental philosophy I.e.: Newton proposed an «experimental philosophy» which stopped short of a "true understanding of the reasons behind phenomena", in order to avoid contexts in which solidity (at his time) could not be expected. "Understanding" as "identifying universal laws" was the best that seemed affordable.
  - TeMPOraL 3y ago
    I wanted to address that in the second paragraph, which I ultimately deleted before submitting, because I couldn't phrase it right. But since you brought it up: I'd consider this an effect of specialization. In the process of improving your object-level "how things work" goals, you end up generalizing and stacking increasingly complex theoretical models. Soon enough, you end up with people working high up the stack - not knowing or caring about the initial goals. Those people end up growing the "mound of knowledge" both upwards and sideways. The work is sort of self-justifying, but really, it's also self-similar. Where early materials science may have been driven by, say, desire for better/cheaper weapons, soon enough, you have people doing materials science because they desire to solve a puzzle. Whether the practitioners are smelting different combinations of ores to find one that will win them the war, or they're mixing up different kinds of equations to figure out a clean solution to a theoretical conundrum - it's the same process, same motivation. And it always involves play. The kind of methodical, boring approach, with hypotheses and control groups and peer-reviewed papers? That's the boring part you have to do after play. See also (with no implied judgement in this context): software developers that lose sight of (or care little about) business goals, and instead aim for theoretical markers of what "good code" is, and/or solve abstract puzzles of algorithms and architecture. Or the MBAs that view companies as abstract money-printing processes, running them by the rulebook that's entirely independent of whatever it is the business is actually doing or selling. Both are cases of growing complexity creating a new field of work that's independent of what brought it into existence.

mensetmanusman 3y ago

Those steps are both necessary and usually take decades to build understanding.

mdp2021 3y ago
But the activity of "attempting to find explanations" is specific. The attempt to formulate laws (the "better faring hypoteses") can bring to "universal laws" or to more humble "patterns". It will contribute to the scientific effort - it does not exhaust it.
visarga 3y ago
Next time we get the urge to complain that GPT-n is just applying patterns seen in the training corpus we should remember humans don't do much better. We are just language agents with rich feedback from outside. We can't even write software top-down in one go without running the code.
- mdp2021 3y ago
  > patterns Except we consciously (intentionally) work on those matchings. > are Opinions should be offered in proper places. Polling is not debating.
- mdp2021 3y ago
  Incidentally, that opinion is also offensive. Not just some tossed "All X are Y, goodnight", but a loaded one. If you happen to conjure thoughts and let them roam wildly, well don't. Make an effort. Critical thinking as a conscious intentional effort must have plenty of literature. The "feedforward" output, the hallucination, is not a dish for service.

TeMPOraL 3y ago

Corporate wants you to find the difference... That is to say, the two things you mention are the same process. "Identifying the best ways of smelting ore to obtain the metal through trial and error" is the easy part, when you get to pick low-hanging fruits in a field. But as the easy options get cleared out, continuing improvements requires increasingly complex, sophisticated methods - that's where the process transitions towards "trying and understanding the nature of materials". It's still the same process, but couple layers of abstraction up from the original "how to get better stick than neighbor and beat them instead of getting beaten".

mdp2021 3y ago
The difference, while moving in "interdependent" directions, is in the purpose: obtaining some sufficient information on how things work versus an actual consideration of the nature of things. It is not really (fully the same process), because you could (in theory) "early stop" when you have achieved technically sufficient competence - the description of the optimal process -, before the jump to the understanding. Something works - that is the technical side; why it works is the scientific side. Note that the approach has controversial sides: if you took Newton's "hypoteses non fingo", He refused that jump explicitly: > hypotheses, whether metaphysical or physical, or based on occult qualities, or mechanical, have no place in experimental philosophy I.e.: Newton proposed an «experimental philosophy» which stopped short of a "true understanding of the reasons behind phenomena", in order to avoid contexts in which solidity (at his time) could not be expected. "Understanding" as "identifying universal laws" was the best that seemed affordable.
- TeMPOraL 3y ago
  I wanted to address that in the second paragraph, which I ultimately deleted before submitting, because I couldn't phrase it right. But since you brought it up: I'd consider this an effect of specialization. In the process of improving your object-level "how things work" goals, you end up generalizing and stacking increasingly complex theoretical models. Soon enough, you end up with people working high up the stack - not knowing or caring about the initial goals. Those people end up growing the "mound of knowledge" both upwards and sideways. The work is sort of self-justifying, but really, it's also self-similar. Where early materials science may have been driven by, say, desire for better/cheaper weapons, soon enough, you have people doing materials science because they desire to solve a puzzle. Whether the practitioners are smelting different combinations of ores to find one that will win them the war, or they're mixing up different kinds of equations to figure out a clean solution to a theoretical conundrum - it's the same process, same motivation. And it always involves play. The kind of methodical, boring approach, with hypotheses and control groups and peer-reviewed papers? That's the boring part you have to do after play. See also (with no implied judgement in this context): software developers that lose sight of (or care little about) business goals, and instead aim for theoretical markers of what "good code" is, and/or solve abstract puzzles of algorithms and architecture. Or the MBAs that view companies as abstract money-printing processes, running them by the rulebook that's entirely independent of whatever it is the business is actually doing or selling. Both are cases of growing complexity creating a new field of work that's independent of what brought it into existence.