Data.conversations is a new series by the UWA Data Institute aimed at people at manager level and above that are not data science or IT practitioners whose teams are using AI.
The target attendee is someone involved in assessing potential opportunities for the introduction of AI to improve business process. In this fast moving space you want to understand more about potential pipelines, capabilities, data, and time required, and hear what others' experiences have been. You are curious (but cautious) and value the opportunity to ask questions.
A data.conversations 1/2 day workshop is about having these conversations.
The format will be based on a series of short talks, panels and small group discussions with participants able to interact with the speakers and each other. Each data.conversations workshop will have a theme. The first one is on Natural language processing, Chat GPT, and language models.
The first data.conversations workshop will be on using 'Language-based pipelines to deliver value'. Some have estimated that as much of 80% of corporate data is stored as unstructured text. How do you get value from this?
The event will be hosted by Professor Melinda Hodkiewicz and the team from the UWA NLP-TLP group https://nlp-tlp.org/ and include NLP-TLP members and industry speakers.
The NLP-TLP team is at the forefront internationally of technical language processing. Members of the NLP-TLP team have practical experience in NLP, building annotated data sets for fine-tuning language models, knowledge graphs, ChatGPT, constructing ontologies on organisational data for addressing business questions. Much of their work is available as open-source code, tools and models and is being used by users across the world. See more about their work at https://nlp-tlp.org/ and https://github.com/nlp-tlp/
Professor Meinda Hodkiewicz came to UWA from industry having held roles similar to the target audience for this field. With the support of expertise in the NLP-TLP team she has been able to transform how she accesses and uses data in maintenance, reliability and safety to ask and answer questions with improved confidence in the result (reduce the human error element) and in a fraction of time over manual approaches. Melinda's past roles have included NOPSEMA Advisory Board (2017-2022), BHP Fellow for Engineering for Remote Operations (2016-2022), METS Ignited Advisory committee, Chair Standards Australia MB19 committee ISO 55000-2 Asset Management (2012-215), and visiting Fellow at the Alan Turing Institute in the UK. She is currently active representing Australia in ISO TC 184 SC4 Industrial Data committee and in the development and publication of the ISO CD 23726 Industrial Data Ontology. More about her background is https://research-repository.uwa.edu.au/en/persons/melinda-hodkiewicz