ImageNet Classification with Deep Convolutional Neural Networks
A deep convolutional network demonstrated how data, GPU computation and learned representations could transform visual recognition.
THE RESEARCH ATLAS
Advancing computer use with Ironclad
An official account of progress in computer-use agents. Read the original methods and evaluations separately from deployment claims.
Institution and location sources
Location refers to credited institutions or the listed organization, not author citizenship or an exhaustive collaboration list.
Why read this
Useful for studying the transition from answering questions to acting through interfaces.
Citation
@misc{openai2026advancing,
title = {Advancing computer use with Ironclad},
author = {OpenAI},
year = {2026},
url = {https://openai.com/index/advancing-computer-use-with-ironclad/}
}Rights remain with the original authors. Refer to the original source for citations and licensing.
Related research
Attention Is All You Need
The Transformer replaces recurrent sequence processing with attention, creating a foundation for many later language and multimodal models.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Masked-language pretraining learns bidirectional representations that can be adapted to language-understanding tasks.