Cheng Soon Ong: Resources and Innovation in AI (Ep. 3) | The Universal AI impact

Cheng Soon Ong: Resources and Innovation in AI (Ep. 3) | The Universal AI impact

LEMMiNO - Cipher https://www.youtube.com/watch?v=b0q5PR1xpA0 CC BY-SA 4.0 In this insightful podcast episode, we delve deep into the fascinating intersection of machine learning and education, discussing how high school students can bridge the gap between complex mathematical theories and practical machine learning code. We address challenges faced by educators trying to present these intricate concepts, and explore the importance of ethics in machine learning research, especially during the model development stages. The conversation also touches upon the role of governmental bodies in crafting regulations that both oversee and nurture innovations in the machine learning space, emphasizing the delicate equilibrium between risk and long-term technological benefits. To help us answer these questions is industry expert and renowned Machine Learning scientist Cheng Soon Ong. With a wealth of experience in the research field and director of a major research organization: Machine Learning and AI at CSIRO, he can give us industry level insights on these topics.

Annette Iversen: AI In Education (Ep. 2) | The Universal AI Impact

LEMMiNO - Cipher https://www.youtube.com/watch?v=b0q5PR1xpA0 CC BY-SA 4.0 Education is an integral part of society. With such rapid changes in the field of AI, the very notion of education is being challenged. To help us answer these questions is Annette Iversen, a veteran in the Educational and Financial fields. Her experience will give us some useful insights into how we should approach remodeling current education practice for the benefit of society.

AI for the Masses (Ep. 1)

LEMMiNO - Cipher https://www.youtube.com/watch?v=b0q5PR1xpA0 CC BY-SA 4.0 Everyone has heard of "AI" as a buzzword. Recent advancements like GPT and Tesla's self driving have exploded in popularity. While learning to code and develop a machine learning model is relatively easy given the resources, there is a severe lack of back-end knowledge which in turn, leads to a severe misunderstanding in the potential of this technology. What does the future really hold? Throughout this podcast, I aim to bridge the gap between Technical reports and newspaper headlines.