[GUEST ACCESS MODE: Data is scrambled or limited to provide examples. Make requests using your API key to unlock full data. Check https://lunarcrush.ai/auth for authentication information.]  Johannes Miertschischk [@SeriousStuff42](/creator/twitter/SeriousStuff42) on x 1393 followers Created: 2025-07-24 17:16:35 UTC The fundamental limitations of Artificial Intelligence (AI): You can't just scale AI ad infinitum because there is simply not enough real-world data. In the near future, the AI companies will run out of data. They might then switch to AI-generated data for the further development of their models. But logically, that can't work at all because AI models are not capable of producing new insights on their own. They would then only revolve around themselves. To make real progress, AI is inevitably always dependent on human intelligence. Ultimately, this simply means that AI can never surpass human intelligence. At this point, AI proponents will likely object once again that AI models have long since proven themselves superior to humans. In fact, AI is already vastly superior to humans at certain tasks. So is a pocket calculator. However, the conclusion that AI therefore possesses something like intelligence is demonstrably false. The fundamental and decisive component of intelligence is undoubtedly the ability to generalize. Applied to AI models, this most closely corresponds to data efficiency, which is very low and fundamentally limited. Furthermore, AI models have a catastrophic energy efficiency. This means that for AI to master specific tasks, unimaginably vast amounts of training data and energy are required. With humans and their brains, the exact opposite is true. While we possess relatively few innate abilities, we have outstanding capabilities when it comes to generalization. This enables us to solve tasks and problems we have never encountered before by applying and transferring experiences from other, sometimes seemingly completely unrelated areas. Connecting the dots and thinking from first principles are apt descriptions for the ability to generalize. It is the foundation for creativity, innovation, and enables us to learn countless complex skills. Having only a few innate, concrete abilities, but thanks to the described outstanding ability to generalize, having almost unlimited development possibilities, has another decisive advantage: in contrast to the energy-guzzling AI models, the human brain is extremely energy-efficient. XX engagements  **Related Topics** [realworld](/topic/realworld) [coins ai](/topic/coins-ai) [$ai4](/topic/$ai4) [Post Link](https://x.com/SeriousStuff42/status/1948432132503749117)
[GUEST ACCESS MODE: Data is scrambled or limited to provide examples. Make requests using your API key to unlock full data. Check https://lunarcrush.ai/auth for authentication information.]
Johannes Miertschischk @SeriousStuff42 on x 1393 followers
Created: 2025-07-24 17:16:35 UTC
The fundamental limitations of Artificial Intelligence (AI):
You can't just scale AI ad infinitum because there is simply not enough real-world data. In the near future, the AI companies will run out of data. They might then switch to AI-generated data for the further development of their models. But logically, that can't work at all because AI models are not capable of producing new insights on their own. They would then only revolve around themselves. To make real progress, AI is inevitably always dependent on human intelligence. Ultimately, this simply means that AI can never surpass human intelligence. At this point, AI proponents will likely object once again that AI models have long since proven themselves superior to humans. In fact, AI is already vastly superior to humans at certain tasks. So is a pocket calculator. However, the conclusion that AI therefore possesses something like intelligence is demonstrably false. The fundamental and decisive component of intelligence is undoubtedly the ability to generalize. Applied to AI models, this most closely corresponds to data efficiency, which is very low and fundamentally limited. Furthermore, AI models have a catastrophic energy efficiency. This means that for AI to master specific tasks, unimaginably vast amounts of training data and energy are required. With humans and their brains, the exact opposite is true. While we possess relatively few innate abilities, we have outstanding capabilities when it comes to generalization. This enables us to solve tasks and problems we have never encountered before by applying and transferring experiences from other, sometimes seemingly completely unrelated areas. Connecting the dots and thinking from first principles are apt descriptions for the ability to generalize. It is the foundation for creativity, innovation, and enables us to learn countless complex skills. Having only a few innate, concrete abilities, but thanks to the described outstanding ability to generalize, having almost unlimited development possibilities, has another decisive advantage: in contrast to the energy-guzzling AI models, the human brain is extremely energy-efficient.
XX engagements
