RE-WORK Community Selects Top AI Research Papers of 2021
Industry experts speaking at the Deep Learning Hybrid Summit highlight thirteen of the most important AI papers published this year. The selected research covers diverse topics ranging from foundation models to genomic data privacy.
The RE-WORK community highlights thirteen essential AI papers of 2021 as chosen by experts scheduled to speak at the upcoming Deep Learning Hybrid Summit. This curated list spans a wide array of topics, from computer vision advancements to deep learning applications that help uncover the mysteries of space. All selected papers remain free to access for anyone interested in the cutting edge of artificial intelligence research.
Vera Serdiukova, Senior AI Product Manager for NLP at Salesforce, points to the significant paradigm shift occurring in AI with the rise of foundation models. Her top pick, "On the Opportunities and Risks of Foundation Models" by Rishi Bommasani et al., explores models trained on broad data at scale that adapt easily to various downstream tasks. The paper provides a comprehensive look at the technical principles, capabilities, applications, and societal impacts of these increasingly central AI systems.
Alexandra Ross, Senior Data Protection and Ethics Counsel at Autodesk, highlights the critical intersection of artificial intelligence and legal compliance. She recommends research analyzing the requirements of the CCPA and GDPR in relation to genomic data and smart contracts like non-fungible tokens. This paper details the strict restrictions these major privacy laws impose on the storing, accessing, processing, and transferring of personal data in emerging technological contexts.