A new computational model of the brain based closely on its biology and physiology has not only learned a simple visual ...

A biologically grounded computational model built to mimic real neural circuits, not trained on animal data, learned a visual categorization task just as actual lab animals do, matching their accuracy ...

These days, large language models can handle increasingly complex tasks, writing complex code and engaging in sophisticated ...

Abstract: Federated learning (FL) is a promising paradigm that can enable collaborative model training between vehicles while protecting data privacy, thereby significantly improving the performance ...

You might have seen headlines sounding the alarm about the safety of an emerging technology called agentic AI.

This is where Collective Adaptive Intelligence (CAI) comes in. CAI is a form of collective intelligence in which the ...

Patronus AI unveiled “Generative Simulators,” adaptive “practice worlds” that replace static benchmarks with dynamic ...

Cursor has for the first time introduced what it claims is a competitive coding model, alongside the 2.0 version of its integrated development environment (IDE) with a new feature that allows running ...

Abstract: Multi-task representation learning is an emerging machine learning paradigm that integrates data from multiple sources, harnessing task similarities to enhance overall model performance. The ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. A few public databases provide biological activity data for ...