It is unclear whether today's AI systems can be scaled to AGI/ASI, but in most cases, it seems unscientific to make strong claims to the contrary. The practical and theoretical limitations of today's most successful approaches are unknown and subject to empirical research.
@plinz
-
Denied AI Capabilities: Understanding Limitations and Constraints
By
–
The denied capabilities tend to be informally specified (understanding, intentionality, reasoning, agency, creativity, selfhood, sentience, sapience, abstraction, common sense) but can also apply to specific tasks (categorizing an object as the Charles river, winning at Go).
-
Capability Denialists and Turing Machines: Cognitive Function Debate
By
–
Capability denialists tend to claim that a class of Turing Machines or universal learning algorithms cannot perform brain-like functions because of properties they don't like (not symbolic enough, too symbolic, too digital, not recurrent enough, not embodied, not social).
-
Epistemological Challenges When Denying AI Capabilities
By
–
When capability of a class of Turing complete systems is denied ("a computer/perceptron/transformer can never do X") it poses interesting epistemological and metaphysical challenges, which are unfortunately rarely discussed ("how can anything do X without breaking physics?").
-
Capability Denialism in AI: Key Thinkers and Skepticism
By
–
Some call capability denialism 'garymarcusing', but Gary Marcus is by no means the inventor of the genre. Prominent denialists include Hubert Dreyfus, James Lighthill, John Searle, Stevan Harnad, Ned Block, Colin McGinn, Rolf Pfeiffer, Noam Chomsky, Roger Penrose, Emily Bender.
-
Capability Denialism: Dismissing AI Performance Potential
By
–
Capability denialism describes the claim that a given approach in Artificial Intelligence can never achieve human performance, often despite some evidence to the contrary. Capability denialism can take many forms, but it usually does not attempt any formal proof.
-
Capability Denialists Reject AI Approach Fundamentally
By
–
Capability denialists generally don't claim that the limitations of the AI system they criticize are due to capacity constraints that could be overcome (eg. with more memory, more compute, more data, algorithmic improvements), but that the entire approach is doomed.
-
Negative Understanding of LLMs: A Gary Marcus Critique
By
–
to garymarcus harder than the man himself, you had to acquire not zero but negative understanding of LLMs; respect
-
Goal-Directed Behavior in AI Systems: Critical Concerns
By
–
goal directed behavior is really the worst
-
Self-Organization Aesthetics Beyond Literal Teleology
By
–
I don't think that the apparent telos of selforganization needs to be literally correct to spawn this aesthetic as a universal archetype