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From CUDA to MLX: How K-Search Brings Decades of Kernel Expertise to Apple Silicon

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Figure 1: CUDA-to-MLX optimization translation map. CUDA optimization knowledge can be translated into architecture-native MLX strategies rather than copied instruction-for-instruction. We face a new epoch in computing. Hardware is changing rapidly — not just faster GPUs, but a growing range of chips from different vendors,…

Source: The Berkeley Artificial Intelligence Research Blog

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The AI Hype Index: Unsexy AI

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It feels bad enough when an open letter signed by leading economists warns that AI might steal your job. The fact it may soon be better than you at making dinner? Insult to injury. But that’s exactly what the company 1X promised when it showed…

Source: MIT Technology Review

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OmniPhys: Knowledge-Graph-Driven Benchmarking and Collective Optimization for Physical Commonsense in Text-to-Image Generation

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arXiv:2607.25641v1 Announce Type: cross Abstract: While text-to-image models exhibit remarkable visual fidelity, they frequently violate fundamental physical commonsense. Existing benchmarks often rely on coarse-grained descriptions, failing to diagnose the mastery of specific physical principles. Moreover, the high stochasticity of generative processes causes current prompt optimization…

Source: cs.AI updates on arXiv.org

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At-the-Roofline Sparse Tensor Contractions on Vector Processors for Transformer Inference

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arXiv:2607.25504v1 Announce Type: cross Abstract: Fine-grained weight pruning and activation sparsification have emerged as effective approaches for reducing the compute and memory cost of inference for Transformer models. In the moderate-sparsity regime, Gustavson's dataflow provides a natural execution model for exploiting both activation and weight…

Source: cs.AI updates on arXiv.org

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A Machine-Learning-Based Gas Lift Optimization Workflow for Unconventional Fields

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arXiv:2607.25885v1 Announce Type: cross Abstract: In this paper, we present an automated data-driven workflow using Machine Learning (ML) for gas lift optimization in unconventional fields. This workflow integrates a ML model that accurately forecasts the Gas Lift Performance Curve, and a Bayesian Optimization Framework to…

Source: cs.AI updates on arXiv.org

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