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b"Dr. Rosanne Liu, Research Scientist at Google DeepMind and co-founder of the ML Collective, shares her journey and the mission to democratize AI research. She explains her pioneering work on intrinsic dimensions in deep learning and the advantages of curiosity-driven research. Jon and Dr. Liu also explore the complexities of understanding powerful AI models, the specifics of character-aware text encoding, and the significant impact of diversity, equity, and inclusion in the ML community. With publications in NeurIPS, ICLR, ICML, and Science, Dr. Liu offers her expertise and vision for the future of machine learning.\\n\\nInterested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.\\n\\nIn this episode you will learn:\\n\\u2022 How the ML Collective came about [03:31]\\n\\u2022 The concept of a failure CV [16:12]\\n\\u2022 ML Collective research topics [19:03]\\n\\u2022 How Dr. Liu's work on the \\u201cintrinsic dimension\\u201d of deep learning models inspired the now-standard LoRA approach to fine-tuning LLMs [21:28]\\n\\u2022 The pros and cons of curiosity-driven vs. goal-driven ML research [29:08]\\n\\u2022 Discussion on Dr. Liu's research and papers [33:17]\\n\\u2022 Character-aware vs. character-blind text encoding [54:59]\\n\\u2022 The positive impacts of diversity, equity, and inclusion in the ML community [57:51]\\n\\nAdditional materials: www.superdatascience.com/797"