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Welcome to episode 148 of the ‘Eye on AI’ podcast. In this episode, host Craig Smith sits down with Ahmed Imtiaz, a PhD student from Rice University working on deep learning theory and generative modeling. Ahmed is currently spearheading his research at Google, exploring the dynamics of text-to-image generative models.
In this episode, Ahmed sheds light on the concept of synthetic data, emphasizing the delicate equilibrium between real and algorithmically generated data. We navigate the complexities of model autophagy disorder (MAD) in generative AI,highlighting the potential pitfalls that models can fall into when overly reliant on their own generated data.
We also go through AI capabilities in lesser-explored languages, with Ahmed passionately sharing about his initiative "Bengali AI" aimed at advancing AI proficiency in the Bengali language. Ahmed introduces pioneering strategies to differentiate and manage synthetic data.
As we wrap up, Ahmed and I deliberate on the merits and challenges of open-sourcing formidable AI models. We grapple with the age-old debate of transparency versus performance, juxtaposed against the backdrop of potential risks.
Dive into the world of AI, synthetic data, and deep learning and join the discussion with Ahmed Imtiaz, as we tackle some of the most pressing issues the AI community is facing today.
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview and Oracle ad
(02:56) Ahmed's Academic Journey
(04:14) The Challenge of Non-English AI
(06:34) Model Autophagy Disorder Explained
(14:40) Internet Content: AI's Growing Involvement
(21:08) The New Age of Data Collection
(26:28) AI’s Role in Protecting Digital Assets
(38:51) Open-Source vs Proprietary Model Debate
