This important study provides a mechanistic view of how antibody affinity maturation can reshape encounter-state landscapes and association pathways, with implications for understanding HIV antibody ...

Vector search underpins most retrieval-augmented generation (RAG) pipelines. At scale, it gets expensive. Storing 10 million document embeddings in float32 consumes 31 GB of RAM. For dev teams running ...

Rapid diagnosis of bacterial pneumonia is crucial for clinical diagnosis and treatment, but traditional methods are time-consuming. The wide application of machine learning techniques in medical ...

Add Decrypt as your preferred source to see more of our stories on Google. Social media platform X has open-sourced its Grok-based transformer model, which ranks For You feed posts by predicting user ...

Same-sex sexual behaviour may help monkeys and apes rise up the social ranks and ultimately have more offspring – and it seems to be especially beneficial in harsh environments where there are lots of ...

Individual sensor systems have limitations in the complex task of classifying shredded tobacco. This study aims to overcome these limitations by developing a novel evolutionary algorithm-based feature ...

ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...

A new evolutionary technique from Japan-based AI lab Sakana AI enables developers to augment the capabilities of AI models without costly training and fine-tuning processes. The technique, called ...

See /GLS/README.md for detailed documentation of this innovation. Population size: 200 Maximum generations: 300 Random mating probability (RMP): 0.4 Mutation rate: 0. ...

Abstract: In this paper, an evolutionary algorithm (EA)-based approach for the design of low-power low-drop-out (LDO) voltage regulators is advanced. The optimal performance of LDO regulators usually ...

Evolutionary algorithms form a robust class of metaheuristic methods inspired by natural selection, designed to tackle combinatorial optimisation tasks where the search space grows factorially or ...