Search Results for author: David Paradice

Found 3 papers, 0 papers with code

Deep Transfer Learning & Beyond: Transformer Language Models in Information Systems Research

no code implementations18 Oct 2021 Ross Gruetzemacher, David Paradice

Recent progress in natural language processing involving transformer language models (TLMs) offers a potential avenue for AI-driven business and societal transformation that is beyond the scope of what most currently foresee.

Transfer Learning

Alternative Techniques for Mapping Paths to HLAI

no code implementations2 May 2019 Ross Gruetzemacher, David Paradice

To address these limitations we propose the use of alternative techniques for an updated systematic mapping of the paths to HLAI.

Forecasting Transformative AI: An Expert Survey

no code implementations24 Jan 2019 Ross Gruetzemacher, David Paradice, Kang Bok Lee

Respondents indicated a median of 21. 5% of human tasks (i. e., all tasks that humans are currently paid to do) can be feasibly automated now, and that this figure would rise to 40% in 5 years and 60% in 10 years.

Cannot find the paper you are looking for? You can Submit a new open access paper.