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Machine learning

Alternative labels
Neural network modelling
Artificial neural networks
Deep learning
Large language model (LLM)
Subject Hierarchy
Current term
Machine learning
Permalinks
APO URI

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Report

Cyber information sharing: building collective security


Over the past 10 years, significant strides have been made in facilitating better cyber information cooperation and sharing, including the emergence of a number of different operating models. This report examines barriers to the progress of greater information that will support the security and resilience of the global economy.
Report

The future of agricultural technologies


The adoption of emerging agricultural technology could help to respond to future trends and catalyse the transformational change needed in the agricultural sector, in terms of profitability, sustainability and productivity. The report examines the impacts of nine technologies on the agriculture sector.
Journal article

Deep learning in the construction industry: a review of present status and future innovations

The construction industry is known to be overwhelmed with resource planning, risk management and logistic challenges which often result in design defects, project delivery delays, cost overruns and contractual disputes. The overall aim of this article was to review existing studies that have applied deep learning to prevalent construction challenges like structural health monitoring, construction...
Guide

Poverty lawgorithms


Automated decision-making systems make decisions about our lives, and those with low-socioeconomic status often bear the brunt of the harms these decisions cause. This guide explains automated decision-making systems so lawyers can better identify the source of their clients' problems and advocate on their behalf.
Report

The robots are NOT coming (and why that’s a bad thing …)


This research shows that Australia’s economy is now regressing in its use of new technology, with negative implications for productivity, incomes, and job quality. The report's findings contrast sharply with the common concern that robots and other forms of automation will threaten future job security for Australian workers.