Index for AI research blogs / Geoff Davis London
I am doing research into computer text generation, specifically machine learning and text generation, in a field generally known as AI or artificial intelligence, at University of London CCI Camberwell London. My research supervisor is Professor Mick Grierson (see credits at bottom). I’m also doing other practice-based artworks for an exhibition in 2021.
I previously programmed ‘story generators’ in the days of home micros. The first computer poems were generated in 1953. So literature and computing has a long history.
2020 research: what happens when writers use a computer text generator to help write various types of articles? What are their experiences when doing this hybrid activity? This is open-ended (no hypothesis, grounded research) and multi-modal.
Apart from the practicalities of using a text generator, I also addressed plagiarism and ‘fake news’ (see below), and examined how the writer’s occupation (poet, copywriter) affected response.
Study 1 – August 2020
Google GPT-2 was used for research into how professional writers use text generation.
I am now working with OpenAI’s latest GPT-3.
A Poetry Generator will be released this summer.
The study had three text generation and editing experiments, and included many feedback questions.
Nine out of ten of these writers (89%) had never used a text generator before. It is easy when working in the computer domain to assume everyone knows about advances, but they do not.
Research topics are now archived. The report will be published soon.
For more information on ‘fake news’ research
These are the most recent papers on fake news:
This study was devised and the study site programmed by Geoff Davis for post-graduate research at University of London UAL CCI 2019-2020. Research supervisor is Professor Mick Grierson.
A publicly available text generator was used in the study experiments, as this is the sort of system people might use outside of the study.
It was also not practical to recreate (program, train, fine-tune, host) a large scale text generation system for this usability pre-study.
Fabrice Bellard, coder of Text Synth:
Text Synth is build using the GPT-2 language model released by Google OpenAI. It is a neural network of 1.5 billion parameters based on the Transformer architecture.
GPT-2 was trained to predict the next word on a large database of 40 GB of internet texts. Thanks to myriad web writers for the training data and OpenAI for providing their GPT-2 model.
Permission was granted to use Text Synth in the study by Fabrice Bellard July 7 2020.
Visit OpenAI’s blog for more information on Google’s OpenAI text generation.
Image prompt man and dog photo
The image is from public sources under free license, it is an old image. See Man and Dog blog.
All material on this website is copyright Geoff Davis London 2021.