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DTSTART;TZID=Australia/Sydney:20260430T080000
DTEND;TZID=Australia/Sydney:20260430T170000
DTSTAMP:20260430T131515Z
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UID:3699-1777536000-1777568400@aquanetica.com
SUMMARY:Cohere Labs - Yulu Gan\, Second-year CS PhD at MIT
DESCRIPTION:Motion understanding is fundamental to physical reasoning\, enabling models to infer dynamics and predict future states. However\, state-of-the-art models still struggle on recent motion benchmarks\, primarily due to the scarcity of large-scale\, fine-grained motion datasets. Existing motion datasets are often constructed from costly manual annotation\, severely limiting scalability. To address this challenge\, we introduce FoundationMotion\, a fully automated data curation pipeline that constructs large-scale motion datasets. Our approach first detects and tracks objects in videos to extract their trajectories\, then leverages these trajectories and video frames with Large Language Models (LLMs) to generate fine-grained captions and diverse question-answer pairs about motion and spatial reasoning. Using datasets produced by this pipeline\, we fine-tune open-source models including NVILA-Video-15B and Qwen2.5-7B\, achieving substantial improvements in motion understanding without compromising performance on other tasks. Notably\, our models outperform strong closed-source baselines like Gemini-2.5 Flash and large open-source models such as Qwen2.5-VL-72B across diverse motion understanding datasets and benchmarks. FoundationMotion thus provides a scalable solution for curating fine-grained motion datasets that enable effective fine-tuning of diverse models to enhance motion understanding and spatial reasoning capabilities. \nYulu Gan is a second-year CS PhD at MIT\, studying AI and Science. Advised by Tomaso Poggio and Phillip Isola. His research focuses on reasoning in VLMs and LLMs\, and neuroevolution.Boyi is a Research Scientist at NVIDIA Autonomous Vehicle Research Group and a Postdoctoral Scholar at UC Berkeley\, advised by Profs. Jitendra Malik and Trevor Darrell. She earned her Ph.D. at Cornell University. Her research focuses on embodied intelligence\, leveraging multimodal data to develop algorithms and systems\, with key areas including reasoning\, large language models\, generative models\, and robotics. She emphasizes aligning representations across 2D\, 3D\, language\, and audio data. \nAdd event to calendar \nApple Google Office 365 Outlook Outlook.com Yahoo
URL:https://aquanetica.com/event/cohere-labs-yulu-gan-second-year-cs-phd-at-mit/
CATEGORIES:Others
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DTSTART;TZID=Australia/Sydney:20260430T080000
DTEND;TZID=Australia/Sydney:20260430T170000
DTSTAMP:20260430T131254Z
CREATED:20260430T131254Z
LAST-MODIFIED:20260430T131254Z
UID:3696-1777536000-1777568400@aquanetica.com
SUMMARY:SAP Sapphire 2026
DESCRIPTION:Join us at SAP Sapphire\, to learn more about our partnership with SAP and our sovereign AI solutions.
URL:https://aquanetica.com/event/sap-sapphire-2026/
CATEGORIES:Conference
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DTSTART;TZID=Australia/Sydney:20260430T080000
DTEND;TZID=Australia/Sydney:20260430T170000
DTSTAMP:20260430T130420Z
CREATED:20260430T125905Z
LAST-MODIFIED:20260430T130420Z
UID:3687-1777536000-1777568400@aquanetica.com
SUMMARY:Cohere Labs - Dr. James Bedford\, Education Specialist in AI at UNSW
DESCRIPTION:There has ironically never been a worse time for EdTech to be this easy to build. While recent studies suggest that simply installing air conditioning has a greater impact on student outcomes than giving every child a laptop\, the EdTech industry has come under fire as it continues to push generic\, profit-driven\, “one-size-fits-all” software that may be benefiting no one. But what happens when the barrier between natural language and functional code completely dissolves? What happens when teachers can make their own software to meet the needs of their students?\nEnter “Vibe coding”.\nIn this session\, Dr. James Bedford explores the dawn of University 3.0—a paradigm shift moving away from “Consumer AI” and toward the “Teacher-as-Creator.” With the rise of advanced LLMs\, educators with zero technical background can quickly develop their skills to start engineering their own hyper-local\, pedagogically aligned technological solutions. Drawing on real-world examples—like building a multilingual Socratic math bot complete with digital canvas integration—this talk will explore how we may be able to finally reject generic platforms in favour of an ‘Entangled Pedagogy (Fawns 2022) empowering us to create tech solutions that meet the specific\, localised needs of our students.\nJoin us as we discuss the superpowers (and the pitfalls) of vibe coding\, how to navigate institutional red tape\, and why the future of impactful\, inclusive EdTech might be built by the teachers themselves.\nWhat You Will Learn:\n• The Shift to University 3.0: How the dissolution of the coding barrier is empowering educators to become software creators rather than software consumers.\n• Entangled Pedagogy in Action: Why technology\, pedagogy\, and local classroom context cannot be separated\, and how vibe coding solves the “generic software” problem.\n• Surviving the “Vibe Trap”: Practical insights on the novelty effect\, technical debt\, and why building apps with AI requires more than just “prompt and pray.”\n• Real-World Application: A look at custom\, privacy-centric AI tools currently being built and deployed in Higher Education using natural language. \nJames Bedford is an award-winning writer and educator with over 12 years’ experience working in higher education. He holds a PhD in Creative Writing from UNSW and is a Senior Fellow of the Higher Education Academy. He currently serves as an Education Specialist in Artificial Intelligence at UNSW College.
URL:https://aquanetica.com/event/cohere-labs-dr-james-bedford-education-specialist-in-ai-at-unsw/
CATEGORIES:Others
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