Is the point he is trying to make then about verification of results…
If a “cancer cure” was well verified through the standard FDA approval process then it would be okay,
but if there was a lack of verification or the verification is via some assumption based verification method (maths proof, modeling, …) and has no real world experimentation to back it then ofc it would always be questionable to take.
Then the issue becomes generating better verification layers - could be through automate lab work or some other interface with the real world - to validate efficacy.
You wouldn’t give credit to Python or rust for the execution of your code that led to published results or a discovery…
The Hubble telescope was a tool that led to downstream innovation…
are these LLM/xyz models not the same?
Solo iOS app that I have been working on since January: https://bhol.app - crossed 500 MRR in June. Seeing the traction and feedback from users is the best form of motivation to keep going.
Now working on scaling it via UGC/social media, landing deals with local language schools, and upping the design with more Rive assets.
If a “cancer cure” was well verified through the standard FDA approval process then it would be okay,
but if there was a lack of verification or the verification is via some assumption based verification method (maths proof, modeling, …) and has no real world experimentation to back it then ofc it would always be questionable to take.
Then the issue becomes generating better verification layers - could be through automate lab work or some other interface with the real world - to validate efficacy.