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This discussion is an in-depth exploration of the topic of Generative AI, delving into the latest advancements and trends in the industry. Attendees can expect to gain:
- A deeper understanding of the current state of the field.
- A glimpse into what the future may hold
- Insight into the impact generative AI has on various sectors of society.
The panelists explore the ways in which generative AI is being used to drive innovation and efficiency in these areas and discuss the potential implications of these technologies on the workforce and the economy.
Another important aspect of the discussion is the ethical considerations surrounding generative AI technologies. The panelists dive into the potential risks and challenges of these technologies, such as chatbots like ChatGPT, DALL-E, and deep fakes, and discuss how best to mitigate them. The discussion will provide valuable insight into the potential and challenges of this rapidly evolving field and the ethical concerns that arise with it.
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About the Panelists:
Hamza Farooq has over a decade of experience in leading Data Science/ Machine Learning teams. His tenure spans over three continents and seven countries across APAC, the Middle East and Africa, and North America within multiple industries, namely, Tech.
Batool Haider is a skilled data scientist with expertise in machine learning and NLP. She has a strong track record, having worked as an Applied Scientist at Amazon Web Services, where she conducted research in areas such as deep learning, text generation, and meta-learning.
Raja Iqbal is a data scientist, a passionate educator, and an internationally recognized speaker on data science. Prior to Data Science Dojo, Raja worked at Microsoft in a variety of research and development roles involving machine learning and data mining at a very large scale.
Francesca Lazzeri is a data and machine learning scientist with over 15 years of experience in academic research, the tech industry, and engineering team management. She is the author of a few books on machine learning and applied Data Science: “Machine Learning for Time Series Forecasting with Python.
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Table of Contents:
00:00 - Introduction
04:00 - Use cases in everyday work
12:30 - The impact of ground-breaking generative AI technologies
14:36 - Is generative AI mainstream?
17:26 - Generative AI's impact on creative work
20:40 - Generative AI and traditional methods of data creation and dissemination
23:50 - Societal impact of generative AI
33:44 - Generative AI in education
37:14 - Generative AI in healthcare and energy
41:14 - Generative AI and government regulations
48:20 - QnA
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