Prof.Dacheng Tao

Speech Title:

More Is Different: Beyond Wittgenstein’s Philosophy

Abstract:

Delving into the hidden wisdom within vast data is an enticing pursuit. The key: foundation models. These powerful transformers unlock the enigmatic knowledge concealed in data’s depths. They combine parameters, computations, and data in a symphony of potential, reigniting our quest for Artificial General Intelligence. In this presentation, we embark on a thrilling journey into the realm of foundation models. Starting with the ground-breaking LLMs, such as ChatGPT, we explore the innovation, trend, and opportunity they’ve ignited. Along the way, we grapple with concerns surrounding singularity while offering unique insights into this burgeoning trend. We delve into the theoretical bedrock, explore ingenious decentralized optimization algorithms, and unearth the fertile ground where applications flourish under the influence of these models. This adventure doesn’t shy away from the challenges and opportunities that await in the era of these titans. Our optimism remains steadfast: foundation models are poised to be the architects of the of AI within the next five years. Let’s rock on this remarkable expedition where data, computational prowess, and algorithms converge to reveal unparalleled possibilities.

Bio of lecturer:

Dacheng Tao is currently a Professor of Computer Science, Peter Nicol Russell Chair and an Australian Laureate Fellow in the Sydney AI Centre and the School of Computer Science in the Faculty of Engineering at The University of Sydney. He was the founding director of the Sydney AI Centre. He mainly applies statistics and mathematics to artificial intelligence and data science, and his research is detailed in one monograph and over 200 publications in prestigious journals and proceedings at leading conferences. He received the 2015 and 2020 Australian Eureka Prize, the 2018 IEEE ICDM Research Contributions Award, and the 2021 IEEE Computer Society McCluskey Technical Achievement Award. He is a Fellow of the Australian Academy of Science, AAAS, ACM and IEEE.

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