What is the strongest mechanistic argument that next token prediction plus reinforcement learning can produce open-ended general intelligence? [D]
Mirrored from r/MachineLearning for archival readability. Support the source by reading on the original site.
Most conversations I see on various AI subreddits start from the assumption that AGI/RSI/ASI is possible, we're on the way right now, and that things will be incredibly different afterward. The only question is what the post-AGI world looks like.
I'd like to start one logical step earlier: What is the strongest argument that the learning mechanisms underlying today's AI systems can actually produce AGI?
I'm particularly interested in arguments grounded in causal mechanisms, computational learning theory, information theory, and first principles, rather than trend extrapolations or appeals to future discoveries.
I'm not arguing that technological progress will stop, or that future breakthroughs are impossible. I'm asking what we understand about current systems that gives us reason to expect general intelligence to emerge from continued development of those systems.
What is the strongest mechanistic case?
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