If I Understood You, Would I Have This Look on My Face?: My Adventures in the Art and Science of Relating and Communicating

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How to Download Just Copy Paste the Link Into Your Browser https://cdn.bkc1a.club/r/BR6sY6 If I Understood You, Would I Have This Look on My Face?: My Adventures in the Art and Science of Relating and Communicating

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If I Understood You, Would I Have This Look on My Face?: My Adventures in the Art and Science of Relating and Communicating

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I had the honour of presenting my reflections on the autobiography of Professor Isaac Folorunso Adewole, titled "Uncommon Grace." As someone deeply invested in documentation and history, I found Professor Adewole's decision to narrate his journey from humble beginnings to occupying one of the highest offices in the land both inspiring and invaluable. In this eloquently written memoir, Professor Adewole provides a comprehensive account of his life, from his ancestral roots to his time as Minister of Health in Nigeria. The unique aspect of this autobiography is that he portrayed himself authentically without taking the help of third-party narratives, which is often seen in accounts of high-ranking officials. His upbringing was greatly influenced by his father's commitment to education. He became a prominent figure in advocating for the rights of the underprivileged through trade unionism. His story is one of unwavering determination, resilience, and faith. His experiences, including both successes and struggles, provide priceless lessons on leadership, perseverance, and the alignment of personal values with public service. While reading "Uncommon Grace," I was struck by the deep leadership lessons that are embedded within its chapters. Professor Adewole stresses the importance of inclusivity, servant leadership, and planning, which are all highly relevant in today's complex world. His commitment to accountability, as well as his primary responsibility as a researcher, serves as a guiding light for aspiring leaders across various disciplines. During his tenure as the Vice Chancellor of the University of Ibadan, he led with visionary leadership and transformative impact. His accomplishments have been meticulously documented in the book, which can serve as a blueprint for rejuvenating institutions and promoting academic excellence. In the latter part of his autobiography, Professor Adewole shares his experiences as a Minister, detailing the challenges he faced while serving the public with integrity and courage. His reflections on the complexities of public service, coupled with his commitment to the well-being of the nation, offer practical insights for policymakers and citizens alike. I have carefully read "Uncommon Grace" and it is more than just a memoir. It is a timeless book that is hard to put down once you start reading. While intellectuals may continue to debate whether uncommon grace was made possible by uncommon preparation or the other way around, I applaud Professor Adewole for sharing his ideas, knowledge, and experience with the public. I highly recommend this book to everyone.

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Despite remarkable successes in various domains such as robotics and games, Reinforcement Learning (RL) still struggles with exploration inefficiency. For example, in hard Atari games, state-of-the-art agents often require billions of trial actions, equivalent to years of practice, while a moderately skilled human player can achieve the same score in just a few hours of play. This contrast emerges from the difference in exploration strategies between humans, leveraging memory, intuition and experience, and current RL agents, primarily relying on random trials and errors. This tutorial reviews recent advances in enhancing RL exploration efficiency through intrinsic motivation or curiosity, allowing agents to navigate environments without external rewards. Unlike previous surveys, we analyze intrinsic motivation through a memory-centric perspective, drawing parallels between human and agent curiosity, and providing a memory-driven taxonomy of intrinsic motivation approaches. The talk consists of three main parts. Part A provides a brief introduction to RL basics, delves into the historical context of the explore-exploit dilemma, and raises the challenge of exploration inefficiency. In Part B, we present a taxonomy of self-motivated agents leveraging deliberate, RAM-like, and replay memory models to compute surprise, novelty, and goal, respectively. Part C explores advanced topics, presenting recent methods using language models and causality for exploration. Whenever possible, case studies and hands-on coding demonstrations. will be presented.

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