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A conformal PINN framework bypasses model dependence and deep learning pitfalls to extract fundamental hadronic physics, yielding a $a_渭^{蟺蟺}$ contribution with unprecedented precision.
TPUs aren't just for Google anymore: Gemma 4 fine-tuning is 1.6x faster and 2x cheaper than on GPUs, with faster time-to-first-token for inference.
VLMs that ace RGB images completely fail at thermal imagery, revealing a critical gap in their ability to reason about temperature and physical properties.
