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CrowdStrike's 2025 data shows attackers breach AI systems in 51 seconds. Field CISOs reveal how inference security platforms ...

GenAI isn’t magic — it’s transformers using attention to understand context at scale. Knowing how they work will help CIOs ...

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

I created a small benchmark to measure the normalization overhead of converting a constant type-level list into a constant vector. As already indicated in #1977, the complexity of normalization seems ...

The old adage, "familiarity breeds contempt," rings eerily true when considering the dangers of normalizing deviance. Coined by sociologist Diane Vaughan, this phenomenon describes the gradual process ...

Transformers have revolutionized natural language processing as the foundation of large language models (LLMs), excelling in modeling long-range dependencies through self-attention mechanisms. However ...

Large language models have shown improved accuracy in phenotype term normalization tasks when augmented with retrievers that suggest candidate normalizations based on term definitions. In this work, ...

Batching converges tasks in a single go, maximizing productivity and minimizing overhead. Batching converges tasks in a single go, maximizing productivity and minimizing overhead. Batching converges ...

AI training and inference are all about running data through models — typically to make some kind of decision. But the paths that the calculations take aren’t always straightforward, and as a model ...

Contrastive image and text models face significant challenges in optimizing retrieval accuracy despite their crucial role in large-scale text-to-image and image-to-text retrieval systems. While these ...