Maximizing the Potential of Documents, NLP, and AI - Technical and Non-technical Challenges

Explore the technical and non-technical challenges faced by SEEK, a global employment marketplace, in maximizing the potential of documents, natural language processing (NLP), and artificial intelligence (AI). Dive into a 42-minute keynote presentation from ADCS 2021, delivered by Terrence Szymanski. Learn about SEEK's approach to processing multinational, multilingual job ads and candidate resumes, and discover how they tackle issues such as accuracy, performance, and reliability of services. Gain insights into organizational strategies for large teams, ethical considerations in AI development, and the protection of user data. Examine SEEK's innovative solutions, including structured "bag of tags" representations, unstructured vector space representations, and the use of Elastic ANN for talent search. Understand the iterative development process for new AI services, the implementation of product science, and strategies for cross-squad knowledge and model sharing in Python.

Intro
Four challenges facing Al teams at SEEK
About me
About SEEK's data
About AIPS
How my team helps hirers and candidates
Job data
Candidate data
Structured "bag of tags" representations
Unstructured vector space representations
Many expectations of Al
Delivering innovative Al services
Delivering FAT Al services
Talent Search using using Elastic ANN
Iterative development of a new Al service
Product science at SEEK
Many models, many pipelines?
Market-adapted model training
Cross-squad knowledge sharing
Cross-squad model sharing with Python