AGI and the End of Intelligence Scarcity

The marginal cost of high-level intelligence will approach near-zero once artificial general intelligence (AGI) is achieved, collapsing the time from theoretical hypothesis to real-world deployment, according to a post on a tech forum. The author argues that intelligence is the only remaining bottleneck and that AGI will shift optimization from the process of thinking to the objective of the output.

AGI and the End of Intelligence Scarcity Intelligence is the only bottleneck left. Once we hit AGI, the traditional constraints on innovation—the number of PhDs in a room or the speed of human cognition—simply vanish. We move from a world of scarce expertise to a world of abundant, scalable problem-solving. If we can deploy an LLM agent that doesn't just summarize text but actually reasons through complex physics or materials science at a million iterations per second, the "cost" of a breakthrough drops to the price of electricity and compute. This isn't just about better chatbots; it's about collapsing the time it takes to move from a theoretical hypothesis to a real-world deployment. The real question for those of us building AI workflows is: what happens to the value of "expertise" when the marginal cost of high-level intelligence hits near-zero? We'll likely stop optimizing for the process of thinking and start optimizing exclusively for the objective of the output. Next AVIF vs WebP vs JPEG: Which one actually wins? → /en/threads/3518/ All Replies （3） N Do you think compute limits or energy constraints will eventually replace intelligence as the new bottleneck? 0 S Still feels like hype. I use LLMs for coding, but it still hallucinates basic logic. 0 L I've noticed my research speed jump since using AI for literature reviews. It's a massive shift. 0