Andrew Gibbons
Andrew is an artist, born and raised in Melbourne, Victoria.
Break dancing from the age of 13, and doodling his way through exercise books during his school years; homogenized societal expectations have only ever been able to pacify Andrew's creative streak temporarily.
In 2013, the film Major, made a new commitment to the pursuit of skills within visual arts.
The appeal of uncapped growth and development has remained a motivation ever since, and his experimentation with his craft has continued to reveal how important art is to him as a person.
Andrew works primarily in the digital form, painting using a tablet screen and stylus.
He has a fondness for many artistic disciplines and has added sprayed mural work to the list of skills which, although requiring great attention and practice, allows him to connect with himself and others differently.
Andrew will be painting a sprayed mural work at TEDxBlighStreet, using the theme of Interconnection to symbolise the responsibility that we have to our planet and the natural world - and to safeguard it for future generations.
Andrew's recent work, a mural of a koala with a note of thanks for Australia's rural fire services painted in Melbourne's Hosier Lane, caught the attention of BBC World News and has helped raise awareness of the recent catastrophe on a global scale. More than 10 million hectares of land is estimated to have been decimated in the Australian bushfires since 1 July 2019, killing more than 1 billion animals and pushing countless native species to extinction.
Josh Dykgraaf
Josh Dykgraaf is a photographic manipulation artist and illustrator based in Melbourne, Victoria. His work centres around transforming his photography into other forms, exploring a sense of place by deconstructing our natural and built environments.
Josh's most recent project, Terraform, is a series that takes landscape photography and images of flora, and transforms them into various animal forms native to that landscape. Each piece is intricately detailed, taking 35-60 hours to complete each piece.
In progress for 12 months now and featuring some 24 pieces, the current stage of the project looks at the recent bushfires ravaging our country using photography of the aftermath of the East Gippsland fires.
Terraform is currently on show at the East Hotel in Manuka, Canberra from 12 February - 11 March.
Website: joshdykgraaf.com
Socials: My Instagram @joshdykgraaf
UBTECH Sydney AI centre
The UBTECH Sydney Artificial Intelligence Centre at The University of Sydney is committed to advancing AI to endow machines with the capabilities of perceiving, learning, reasoning and behaviour. Researchers in the centre design shallow or deep models to extract, represent and understand information encoded in data and develop algorithms and theories.
The centre aims to establish, analyse and evaluate models that can: learn and make predictions on data; create prototypes or applications to investigate autonomous agent actions; and identify patterns and apply logic. Ultimately the centre’s vision is to lead AI research in Australia and become one of the most prestigious AI research hubs in the world.
AI is a transformative technology that promises tremendous societal and economic benefit. It has the potential to revolutionise how we live, work, learn, discover and communicate. Research into AI can advance Australia's national priorities, including greater economic prosperity, improved educational opportunities and quality of life, and enhanced national and homeland security.
Recently, the centre has placed enormous effort towards understanding deep learning which despite leading the technical revolution, still lacks a comprehensive theoretical guarantee. This phenomenon considerably undermines the confidence of industrialising deep learning in security-critical domains. The centre attempts to explain the muse of deep learning and has obtained a number of promising results which shed light on (1) the properties of the extremely non-convex and non-smooth loss surface of deep learning, (2) the roles of data noise, optimisation, network depth, and residual connections in the generalisability of deep learning, and (3) the fundamental laws of adversarial robustness, optimal transport, algorithmic stability, and Bayes optimality, which govern the performance of deep learning.
Theoretical developments inspire researchers in the centre to devise efficient algorithms and models which help the centre achieve top level performance in computer vision challenges, such as object detection and tracking in the 2017 ImageNet challenge (known as the world cup in computer vision and machine learning); the 2017 CVPR Visual Question Answering Challenge; the 2018 visual dialog challenge; matching and ranking in the 2017 TRECVID; detection and classification in the 2016 Large Scale Activity Recognition Challenge (ActivityNet); single image depth prediction in the Robust Vision Challenge 2018; the Finnish-English (FI-EN) track in the 2019 WMT (Machine Translation); and the 2019 MICCAI Multimodal Brain Tumor Segmentation Challenge (BraTS).
