We are proud to have launched our first competition on Kaggle!
The primary challenge of this competition is to develop an AI tool or method that can accurately extract questionnaire questions from documents, primarily PDFs.
This competition offers a unique opportunity for participants to contribute to the field of natural language processing and document analysis as well as open source for social science while developing solutions that have real-world applications. We encourage participants to think creatively, leverage available resources, and push the boundaries of current technologies.
Requirements: Python 3.10 or greater
Create an account on Kaggle.
Install Kaggle on your computer:
pip install kaggle
On the Kaggle website, download your kaggle.json file and put it in your home folder under .kaggle/kaggle.json.
Download and unzip the competition data:
kaggle competitions download -c harmony-pdf-and-word-questionnaires-extract
unzip harmony-pdf-and-word-questionnaires-extract.zip
To generate predictions for the training data and write to train_predictions.csv:
python create_sample_submission.py train
To evaluate the train predictions:
python evaluate_train_results.py
To modify the prediction logic or inject your own model, you can edit the function dummy_extract_questions.
To generate predictions for the test data and write to submission.csv:
python create_sample_submission.py test
kaggle competitions submit -c harmony-pdf-and-word-questionnaires-extract -f submission.csv -m "Message"
How are research funders reacting to the AI governance vacuum? A recent article by Sense about Science, a leading independent charity that promotes the public interest in sound science and evidence, highlights the growing need for responsible AI governance in research. The article, titled Research funders tackle AI governance vacuum with pragmatic guidance, discusses the alarming gap between the rapid development and adoption of AI tools, and the lack of clear frameworks for their safe and ethical use.
Tech Talk at the AI|DL AI Meetup (London) Artificial Intelligence and Deep Learning for Enterprise Thomas Wood presents the Harmony project at the 19th AI and Deep Learning for Enterprise meetup on 8 October 2024. In case you missed the talk about Harmony on Tuesday at Civo Tech Junction with AI and Deep Learning for Enterprise sponsored by Daemon, you can now watch the recording of the live stream on AI|DL’s channel.