The "Intelligence Optimum" - How smart can AI really become? As AI benchmarks continue getting saturated, I've been thinking about a fascinating parallel to graphics in the '90s and 2000s. Back then, once you hit tens of thousands of triangles in 3D models, your eye couldn't really tell the... difference between 60,000 and 6 million triangles. The improvements became imperceptible despite orders of magnitude more computational power. I suspect we're heading toward the same phenomenon with large language models. Here's why: Intelligence fundamentally comes down to two things - the ability to represent information and manipulate that information effectively. Research suggests that around 130-140 IQ, human brains can generate any cognitive primitive needed - meaning with enough time and effort, they can learn virtually anything. Once AI systems cross this "intelligence optimum" threshold - where they can represent all necessary cognitive primitives and perform all required manipulations - additional parameters become essentially vanity metrics. Beyond that point, the real competition shifts to speed, efficiency, and energy consumption, not raw capability. This doesn't mean intelligence has a hard ceiling, but rather that practical general intelligence might have a sweet spot where adding more compute stops yielding meaningful improvements. What do you think - are we chasing diminishing returns, or will AI continue surprising us with qualitative leaps?show more

David Shapiro ⏩

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