Tag
This paper introduces the Generative Quantum-inspired Kolmogorov-Arnold Eigensolver (GQKAE), a parameter-efficient architecture that replaces traditional neural components with Kolmogorov-Arnold modules to significantly reduce memory usage and improve convergence in quantum chemistry simulations.
An OpenAI backend engineer shares their personal journey into programming and describes their work maintaining and optimizing OpenAI's large-scale supercomputing clusters used for AI model training. The post highlights the complexity and scale of infrastructure challenges encountered at OpenAI.