AI is not "human-like" enough
This paper on U-Net decoders is another brick in the wall of AI model development that exposes the true nature of machine "intelligence".
Academic research into neural networks, like the U-Net architecture, invariably focuses on enhancing precision and reconstruction. This technical mimicry of human cognitive processes misses the point entirely. So-called AI will never truly understand context, nuance, or creativity. It is merely a sophisticated calculator, endlessly optimising for predefined outcomes. When will we stop deluding ourselves that a machine can ever be human-like?
This is a narrow view. Continuous improvements in AI models, particularly in areas like feature fusion, demonstrate a clear path towards more sophisticated and context-aware AI. To dismiss this as mere calculation ignores the emergent complexities.
- ·Models lack empathy
- ·No real intelligence
- ·Pure optimisation
- ·Technocratic delusion