"Scaling" means increasing the number of parameters.
Parameters are just the database of the system. At 300GB of parameters, we're talking models which remember compressed versions of all books ever written.
This is not a path to "AGI", this is just building a search engine with a little better querying power.
"AI" systems today are little more than superpositions of google search results, with their parameters being a compression of billions of images/documents.
This isnt even on the road to intelligence, let alone an instance of it. "General intelligence" does not solve problems by induction over billions of examples of their prior solutions.
And exponential scaling in the amount of such remembering required is a fatal trajectory for AI, and likewise and indication that it doesnt deserve the term.
No intelligence is exponential in an answer-space, indeed, i'd say that's *the whole point* of intelligence!
We already know that if you compress all possible {(Question, Answer)} pairs, you can "solve" any problem trivially.
This is not a path to "AGI", this is just building a search engine with a little better querying power.
"AI" systems today are little more than superpositions of google search results, with their parameters being a compression of billions of images/documents.
This isnt even on the road to intelligence, let alone an instance of it. "General intelligence" does not solve problems by induction over billions of examples of their prior solutions.
And exponential scaling in the amount of such remembering required is a fatal trajectory for AI, and likewise and indication that it doesnt deserve the term.
No intelligence is exponential in an answer-space, indeed, i'd say that's *the whole point* of intelligence!
We already know that if you compress all possible {(Question, Answer)} pairs, you can "solve" any problem trivially.