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AIML Special Presentation: How tough is your data? Applying structural graph theory to robust fitting and clustering

David Suter

Structural graph theory is making great advances in understanding what characteristics of graphs act to make those graphs difficult or easy for algorithms for a range of common problem types (maximum clique, graph cuts, etc.). Modern machine learning is largely driven by the success (or otherwise) of a proposed model/algorithm on standard test datasets. This involves a plethora of different measures and sometimes one might suspect that a dataset has “easy examples” and “hard examples” and that a statistic might be affected by the proportion of hard or easy samples. So a structural graph theory based understanding of AI problems should help both understand benchmark results and also to design algorithms according to the range of complexities of data a problem setting can “throw up”.

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AIML Special Presentation: Introducing the Responsible AI Research (RAIR) Centre

Kate Klimeš

We're pleased to welcome Kate Klimeš, Program Manager for the newly established Responsible AI Research (RAIR) Centre, who will be presenting on the vision and goals of the new centre. The Centre is based at AIML in the Lot Fourteen business and technology precinct in Adelaide. RAIR represents a powerful collaboration between AIML’s world-class researchers in artificial intelligence and machine learning, scientific experts from CSIRO, and is supported by the South Australian Government.

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AIML Special Presentation: Accelerating Science with NVIDIA

Dr Johan Barthélemy

NVIDIA's advanced GPU technologies and AI platforms are revolutionising scientific computing across multiple domains. This talk will explore how NVIDIA's solutions are enabling unprecedented acceleration of research and discovery in fields like generative AI, digital twins, data science, climate modelling, robotics and drug discovery. Dr Johan Barthélemy will introduce the latest AI-powered tools such as RAPIDS, Modulus, (Bio)NeMo, Omniverse, Cosmos, and Groot, pushing the boundaries of what's possible. Real-world examples will demonstrate how researchers are leveraging those technologies to tackle complex problems orders of magnitude faster and more efficiently than traditional methods.

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AIML Special Presentation: Continuum Robots for Minimally Invasive Surgery: Smaller, Softer, and Smarter

Liao Wu

Surgical robots have achieved commercial success and are experiencing rapid global growth. The robotics community continues to push the boundaries of safety, ease of use, and minimally invasive techniques in surgical robots. Continuum robots, with their intrinsic flexibility and miniature sizes, are emerging as ideal candidates for the next generation of minimally invasive surgical systems. Their development, however, presents three major challenges: design and manufacturing, human-robot interaction, and intelligent perception. In this talk, Dr Liao Wu will share his efforts to overcome these challenges, focusing on advancements that make surgical continuum robots smaller, softer, and smarter.

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AI on the Ground: The Great Chatbot Debate Watch Party

The Great Chatbot Debate

Chatbots based on large language models (LLMs), like ChatGPT, answer sophisticated questions, pass professional exams, analyze texts, generate everything from poems to computer programs, and more. But is there genuine understanding behind what LLMs can do? Do they really understand our world? Or, are they a triumph of mathematics and masses of data and calculations simulating true understanding?

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AIML Research Seminar: The Search for LLM-Based Disinformation

Dr Jason Pittman

Disinformation is one of the biggest threats to social progress and stability. Lies and post-truths radicalize decision-making and pervert knowledge. Accordingly, there has been an explosion of research seeking to detect disinformation in online content. Here, the frontier of disinformation detection research leverages a variety of ML techniques. Yet, a recent meta-analysis discovered existing techniques are only 79% accurate. More problematic is existing techniques only work against generated artifacts. Meaning, articles, tweets, and Reddit posts are in the wild before detection occurs. We need a technique to detect potential disinformation in the ML models before content gets loose. Fortunately, work is underway attempting to construct such a technique. This presentation will bring you up to speed on misinformation concepts. We will cover existing machine learning detection methods. The feature will be a progress snapshot of working at the model level. Keep in mind this is not only about fake news. No. Detecting misinformation is about preserving all human knowledge.

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AIML Special Presentation: ARC Discovery Project on Hyperspectral Video Tracking

Jun Zhou

Video tracking is a fundamental AI technology with more than 100 billion dollars market values. Traditional tracking models based on colour or grayscale videos have inherent limitations in detecting and tracking objects. Focused on challenging scenarios faced by conventional camera systems, this research in the past five years harnesses the capability of hyperspectral video cameras in material identification within and beyond the visible spectrum to capture and model the spectral, spatial, and temporal information for object tracking. This talk gives an overview of hyperspectral imaging technology and how it is used to develop hyperspectral tracking methods, which form the foundation of a recently funded ARC Discovery Project.

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CAR CATALYST Information Session

CAR Catalyst participants at the AIML building

AIML has joined forces with deep tech, venture capitalist firm Main Sequence as its preferred partner to co-lead the Centre for Augmented Reasoning’s (CAR) Catalyst Program. This innovative initiative aims to significantly boost participants by nurturing their entrepreneurial goals and accelerating their path from product development to market entry.

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AIML Special Presentation: HARNESS: Hierarchical Abstractions and Reasoning for Neuro-Symbolic Robotic Systems—From Perception to Autonomy

Hamid Rezatofighi

In this talk, Dr Rezatofighi will present HARNESS: Hierarchical Abstractions and Reasoning for Neuro-Symbolic Robotic Systems—From Perception to Autonomy, showcasing our work under the DARPA Assured Neuro-symbolic Reasoning (ANSR) program. This project focuses on building fully autonomous systems that unite perception, reasoning, and planning through neuro-symbolic frameworks, emphasising explainability, performance robustness and assurance.

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AIML Research Seminar: Gaëlic Bechu

Gaelic Bechu

Gaëlic Bechu is a PhD student at the Centre for Augmented Reasoning, focusing on the role of AI in embodied systems, including robotics. In this seminar, he will share the latest developments in his PhD research, providing insights into his ongoing work and its applications.

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