Template:M intro technology rumours of our demise: Difference between revisions

Template:M intro technology rumours of our demise (view source)

Revision as of 09:02, 20 November 2023

2,218 bytes added , 20 November 2023

no edit summary

Amwelladmin

Bureaucrats, Interface administrators, Administrators

83,194

edits

@@ Line 185: / Line 185: @@
 Now if artificial intelligence is so spectacular, shouldn’t we be a bit more ambitious about what ''it'' could do for ''us''? Isn’t “giving you the bare minimum you’ll take to keep stringing you along” a bit ''underwhelming''?
+===Digression: the profligacy of Darwin’s Dangerous Idea===
+By now most accept the magic of evolution by natural selection. This really is magic: a comprehensive explanation of the origin of reflexive general intelligence — indeed, the sum of all organic “creation”, as it were — can [[reduction|reduce]] to the operation of a simple algorithm that can be stated in a short plain English sentence.
+There is a real cost to that magic, though: cost. Evolution by natural selection is incomprehensibly inefficient. The chain of adaptations that led from amino acid to Lennon and McCartney may have billions of links in it, but the number of adaptations that didn’t — that arced off into one of design space ’s gazillion dead ends and forlornly fizzled out — is orders and orders of magnitude greater. Evolution isn’t directed — that is it's very super power, so it fumbles blindly around, fizzing and sparking, and a vanishingly small proportion of mutations go anywhere. Evolution is a random, [[stochastic]] process.
+Even though it came about through that exact process, mammalian intelligence — call it “natural general intelligence” (NGI) — isn’t like that. It is directed. Because we can hypothesise, we can rule out experiments which plainly won’t work. This is human’s great superpower: it took 5 billion years to get from amino acid to the wheel, but 5000 years to get from the wheel to the Nvidia graphics chip.
+Large learning models are undirected. They work by a stochastic algorithm not dissimilar to evolution by natural. They get better by running that algorithm faster.
 ====LibraryThing as a model====
-A sensible use for this technology would create [[system effect]]<nowiki/>s to ''extend'' the long tail.
+A better use for this technology — if it is as good as claimed<ref>We would do well to remember Arthur C. Clarke’s law here. The parallel processing power an LLM requires is lready massive. It may be that the cost of expanding it in the way envisioned would be unfeasibly huge — in which case the original “business case” for [[technological redundancy]] falls away. See also the [[simulation hypothesis]]: it may be that the most efficient way of simulating the universe with sufficient granularity to support the simulation hypothesis is ''to actually build and run a universe'' in which case, the hypothesis fails.</ref> — would create [[system effect]]s to ''extend'' the long tail.
 It isn’t hard to imagine how this might work. A rudimentary version exists in {{Plainlink|https://www.librarything.com/|LibraryThing}}’s recommendation engine. It isn’t even wildly clever '''—''' {{Plainlink|https://www.librarything.com/|LibraryThing}} has been around for nearly twenty years and doesn’t, as far as I know, even use AI: each user lists, by ASIN, the books in her personal library. She can rate them, review them, and the LibraryThing algorithm will compare each users’s virtual “library” with all the other user libraries on the site and list the users with the most similar library. The non-matched books from libraries of similar users are often a revelation.