Randommaggy
Randommaggy t1_j8ohpv5 wrote
Reply to comment by ThirdEncounter in NASA's "evolved structures" radically reduce weight – and waiting by Maxcactus
Where is the intelligence in the glorified inverted indexes with result blending bolted to them that are paraded about these days?
Inventing authors and papers that sound plausible when asked for citations is a strong indication that the smoke and mirrors make people ascribe a lot of intelligence that is simply not there.
Randommaggy t1_j8njz0p wrote
Reply to comment by TrumpetSC2 in NASA's "evolved structures" radically reduce weight – and waiting by Maxcactus
Genetic algorithm is more accurately described as AI than most "AI" Tools out there.
Randommaggy t1_j18dsog wrote
Reply to comment by Canaduckfart5 in After Arrest of 7 Cops, LAPD Reminds Its Own Officers Not to Drink and Drive by Exastiken
Once proven guilty such offenses should come with automatic loss of employment for police (and judges).
Power should come with consequences when not properly wielded.
Randommaggy t1_j17pb60 wrote
How is this not an automatic firing?
Randommaggy t1_j0liml3 wrote
Reply to comment by decrementsf in What Plato Would Say About ChatGPT: Zeynep Tufekci argues that A.I. can be a learning tool for schools with enough teachers and resources to use it well. (The New York Times) by darrenjyc
Its not even a practical nailgun its an impractical one with a heavy V12 engine that needs specialized skills to wield without taking of a leg or killing your neighbors.
Its also tempting for people that does not understand the subject they are applying it to.
Randommaggy t1_j8oi1yp wrote
Reply to comment by TrumpetSC2 in NASA's "evolved structures" radically reduce weight – and waiting by Maxcactus
How is a genetic algorithm that optimizes for a set of constraints fundamentally different from a GAN or reinforcement learning model except in implementation details and resource-efficiency?
The discriminative network in a GAN is the provider of constraints aka part of the training dataset or the measurer of fitness.
The generative network proposes solutions and refines it's weights based on the fitness of the output.
There are differences but the premise is more similar than dissimilar.
Your funding would also likely be better if you could convince people that it is a form of AI maybe branded as a subcategory of supervised reinforcement learning.