This is a pretty straightforward lookup example, statement by statement, once the language parser works. It might look impressive to an uninitiated, but the intelligence level required seems to be minimal.
Famous museum → famous painting → artist → cartoon with artist’s name → cartoon character with the same name → implement in the character’s hand → country of origin.
A more impressive example would be something that requires latent implicit world knowledge and making inferences that a simple lookup would not achieve.
“once the language parser works” is hiding a lot of complexity and sophistication here! Translating from natural language to sequential lookup operations is not a trivial task, else we wouldn’t need a 540 billion parameter model to do it this well. The “uninitiated” are right to be impressed.
I think you’re understating the amount of logical reasoning involved in making that “lookup”, but successes on the winogrande schema challenge fit this bill. If you look at that and explain the tests example by example, going over the implicit world knowledge the AI needs to have, it’s pretty impressive.
This is a pretty straightforward lookup example, statement by statement, once the language parser works. It might look impressive to an uninitiated, but the intelligence level required seems to be minimal.
Famous museum → famous painting → artist → cartoon with artist’s name → cartoon character with the same name → implement in the character’s hand → country of origin.
A more impressive example would be something that requires latent implicit world knowledge and making inferences that a simple lookup would not achieve.
“once the language parser works” is hiding a lot of complexity and sophistication here! Translating from natural language to sequential lookup operations is not a trivial task, else we wouldn’t need a 540 billion parameter model to do it this well. The “uninitiated” are right to be impressed.
I think you’re understating the amount of logical reasoning involved in making that “lookup”, but successes on the winogrande schema challenge fit this bill. If you look at that and explain the tests example by example, going over the implicit world knowledge the AI needs to have, it’s pretty impressive.