Nature

Transfer learning with graph neural networks for improved molecular property prediction in the multi-fidelity setting

We investigate the potential of graph neural networks (GNNs) for transfer learning and improved molecular property prediction in the context of funnels or screening cascades characteristic of drug ...
Nature

Transfer learning on protein language models improves antimicrobial peptide classification

Antimicrobial peptides (AMPs) are essential components of the innate immune system in humans and other organisms, exhibiting potent activity against a broad spectrum of pathogens. Their potential ...
techtimes

Transfer Learning Slashes Cosmology AI Costs: Neutrino Mass Degeneracy Triggers Negative Transfer

A strategy borrowed from generative AI — train cheaply on the familiar, then fine-tune on the hard problem — can cut the number of expensive physics simulations needed by nearly a factor of ten. But a ...
VentureBeat

Fine-tuning vs. in-context learning: New research guides better LLM customization for real-world tasks

Two popular approaches for customizing large language models (LLMs) for downstream tasks are fine-tuning and in-context learning (ICL). In a recent study, researchers at Google DeepMind and Stanford ...
Geeky Gadgets

15+ AI model fine tuning tips and tricks

Fine-tuning AI models can be a complex and resource-intensive process, but with the right strategies and techniques, you can optimize it effectively to achieve superior results. This comprehensive ...