Interviews with scientists and engineers working in Machine Learning and AI, about their journey, insights, and discussion on latest research topics.
Jay Shah Podcast
Claim This Podcastby Jay Shah
5.0(19 reviews)
97 episodes
Updated Bi-weekly
Accepts GuestsHas Sponsors
57
Podcast Authority
BetaFairBased on show quality, social media presence, reviews, charts, and more
Quality60
Social0
YouTube86
Engagement51
Podcast Overview
Interviews with scientists and engineers working in Machine Learning and AI, about their journey, insights, and discussion on latest research topics.
Language
🇺🇲
Publishing Since
9/17/2020
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57
Podcast Authority
BetaFairBased on show quality, social media presence, reviews, charts, and more
Quality60
Social0
YouTube86
Engagement51
8
Excellent Areas
0
Good Performance
11
Growth Opportunities
excellent
Episode Length
55 minutes
Performing excellently!
needs improvement
Publishing Consistency
Every 18 days
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Recent Episodes
February 18, 2026
The Hidden Flaws in AI Safety & Evaluation Benchmarks | Prof. Jackie Chi Kit Cheung
<p>Dr. Jackie Cheung is an Associate Professor at McGill University where he co-directs the Reasoning and Learning Lab. He is also an Associate Scientific Director at Mila-Quebec Artificial Intelligence Institute. He and his team are developing computational models to improve the reliability, pragmatics, and evaluation of large language models to ensure they are contextually appropriate and factually grounded.Jackie was worked as a consultant researcher with Microsoft Research and before his current appointments, he earned his PhD and MSc in Computer Science from the University of Toronto, focusing on computational linguistics, and his BSc from the University of British Columbia.00:00:00 Highlight & Introduction00:02:04 Entrypoint in AI & NLP00:04:47 Academia vs. Industry: Career choices00:09:48 Language Revitalization using AI00:12:24 Addressing Biases & Data sovereignty in language revitalization 00:15:49 Evaluating LLMs as Judges00:17:14 Validity and reliability in LLM evaluation 00:25:11 Evidence-centered benchmark design (ECBD) framework00:30:38 Gaps in LLM benchmarks and meaning of "general purpose" AI00:35:24 General purpose intelligence vs reasoning00:40:16 Safety as an undefined bundle in LLMs00:51:45 Stochastic chameleons: how LLMs generalize and hallucinate 01:03:02 Potential & Biases of agentic frameworks for research01:05:52 Evaluating LLMs for summarization01:11:43 Scaling large language models01:16:33 Advice to beginners entering AI in 202601:20:33 Pitfalls to avoid in AI research & development More about Jackie & his research: https://www.cs.mcgill.ca/~jcheung/About the Host:Jay is a Machine Learning Engineer III at PathAI working on improving AI for medical diagnosis and prognosis. Linkedin: https://www.linkedin.com/in/shahjay22/Twitter: https://twitter.com/jaygshah22Homepage: https://jaygshah.github.io/ for any queries.Stay tuned for upcoming webinars!***Disclaimer: The information in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***</p>
February 2, 2026
The Future of AI in Pathology: Transforming Diagnosis & Drug Development | Andrew Beck, PathAI
<p>Andrew Beck, MD, PhD is the Co-founder and CEO of PathAI, where he and his team are developing AI tools to improve the precision of pathology and the efficacy of drug development for diagnosis of cancer and also many other complex diseases.Before founding PathAI, Andrew was an Associate Professor at Harvard Medical School, where his research focused on the application of machine learning to cancer pathology. He earned his MD from Brown University and his PhD in Biomedical Informatics from Stanford University, where he pioneered some of the first computational models used to predict patient outcomes in oncology.Time stamps of the conversation:00:00:00 Highlights00:01:28 Introduction00:02:18 Entrypoint in AI00:07:02 Background in Medicine and Bioinformatics 00:10:00 Leap from academia to entrepreneurship00:16:20 Translating AI developments to Pathology00:21:15 Specialist vs Generalist AI models in medicine00:24:15 What sets PathAI apart?00:26:32 AI adoption medicine00:34:25 Usage of AI tools in clinical workflows, example MASH00:40:10 AI in Dermatopathology00:42:15 AI for biomarker discovery00:47:05 Will AI models replace pathologists?00:52:28 Avoiding over-reliance on AI00:57:40 Is AI living unto the hype?01:01:00 Challenges in clinical trials 01:05:12 AI reaching patients directly01:09:50 Working at intersection of AI & Healthcare01:15:30 Pitfalls to learn fromMore about PathAI: https://www.pathai.com/and Andy: https://www.pathai.com/about-us/andy-beckAbout the Host:Jay is a Machine Learning Engineer III at PathAI working on improving AI for medical diagnosis and prognosis. Linkedin: https://www.linkedin.com/in/shahjay22/Twitter: https://twitter.com/jaygshah22Homepage: https://jaygshah.github.io/ for any queries.Stay tuned for upcoming webinars!***Disclaimer: The information in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***</p>
October 23, 2025
Beyond Accuracy: Evaluating the learned representations of Generative AI models | Aida Nematzadeh
<p>Dr. Aida Nematzadeh is a Senior Staff Research Scientist at Google DeepMind where her research focused on multimodal AI models. She works on developing evaluation methods and analyze model’s learning abilities to detect failure modes and guide improvements. Before joining DeepMind, she was a postdoctoral researcher at UC Berkeley and completed her PhD and Masters in Computer Science from the University of Toronto. During her graduate studies she studied how children learn semantic information through computational (cognitive) modeling. Time stamps of the conversation<a href="https://www.youtube.com/watch?v=gYqr1mGfzE0">00:00</a> Highlights<a href="https://www.youtube.com/watch?v=gYqr1mGfzE0&t=80s">01:20</a> Introduction<a href="https://www.youtube.com/watch?v=gYqr1mGfzE0&t=128s">02:08</a> Entry point in AI<a href="https://www.youtube.com/watch?v=gYqr1mGfzE0&t=184s">03:04</a> Background in Cognitive Science & Computer Science <a href="https://www.youtube.com/watch?v=gYqr1mGfzE0&t=295s">04:55</a> Research at Google DeepMind<a href="https://www.youtube.com/watch?v=gYqr1mGfzE0&t=347s">05:47</a> Importance of language-vision in AI<a href="https://www.youtube.com/watch?v=gYqr1mGfzE0&t=636s">10:36</a> Impact of architecture vs. data on performance <a href="https://www.youtube.com/watch?v=gYqr1mGfzE0&t=786s">13:06</a> Transformer architecture <a href="https://www.youtube.com/watch?v=gYqr1mGfzE0&t=870s">14:30</a> Evaluating AI models<a href="https://www.youtube.com/watch?v=gYqr1mGfzE0&t=1142s">19:02</a> Can LLMs understand numerical concepts <a href="https://www.youtube.com/watch?v=gYqr1mGfzE0&t=1480s">24:40</a> Theory-of-mind in AI<a href="https://www.youtube.com/watch?v=gYqr1mGfzE0&t=1678s">27:58</a> Do LLMs learn theory of mind?<a href="https://www.youtube.com/watch?v=gYqr1mGfzE0&t=1765s">29:25</a> LLMs as judge<a href="https://www.youtube.com/watch?v=gYqr1mGfzE0&t=2156s">35:56</a> Publish vs. perish culture in AI research<a href="https://www.youtube.com/watch?v=gYqr1mGfzE0&t=2400s">40:00</a> Working at Google DeepMind<a href="https://www.youtube.com/watch?v=gYqr1mGfzE0&t=2570s">42:50</a> Doing a Ph.D. vs not in AI (at least in 2025)<a href="https://www.youtube.com/watch?v=gYqr1mGfzE0&t=2900s">48:20</a> Looking back on research careerMore about Aida: <a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbjRLWUh4UWFHZVpBaDlwMWM3b1VrMHAzSFI0UXxBQ3Jtc0tuTHVIWGU3REdBNWJkSGl3dXh6WndyT3g2M2xuUll4enBibVI0SnEzbXltNkxwbFdtY2JSQnoyZXZBR2k3SkhhLWJIUUVzWlVCNnBQc0doaGEyVGNUOGdSWVh3LUpVSW9WNjFLeURoX1ZTR3ctZnpxQQ&q=http%3A%2F%2Fwww.aidanematzadeh.me%2F&v=gYqr1mGfzE0" target="_blank" rel="nofollow">http://www.aidanematzadeh.me/</a>About the Host:Jay is a Machine Learning Engineer at PathAI working on improving AI for medical diagnosis and prognosis. Linkedin: <a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqblMzNnQ1YW9ZcVVDWVFmbXpsVlZ0MWpRRWJiQXxBQ3Jtc0trcjY3aXduQ1Bha0hvVHJJNzZTS2ZxdklWb0pIZG9XbTdaa2tTY1p2bGFlc2plTm1sc09MX0xUTHpCTUhpVGZlZTVZbUVTWk5BSk1Cc25JVmtWQ0FMMHI2UkExOXpNeTBETWhtVnc3LTFsWXJHRktfRQ&q=https%3A%2F%2Fwww.linkedin.com%2Fin%2Fshahjay22%2F&v=gYqr1mGfzE0" target="_blank" rel="nofollow">shahjay22 </a>Twitter: <a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqa1l1MmJwYVZjY2NwX2NOYW1MT21tbWtaVlhuZ3xBQ3Jtc0tuY1ZiU3hUTmQ1QlhyMnlOaE90dEh6M2FtbUZFSmQ2QlRxTlB4MjVJaVdkZVAzWndDSXpVeDZPdzllMlZtUjBvOTVaUHJwQm15VmxvcHFOT19HbVB3MnowYTVMWjlEZ3dleDhQck1vZnZzZGhYYVJ5Yw&q=https%3A%2F%2Ftwitter.com%2Fjaygshah22&v=gYqr1mGfzE0" target="_blank" rel="nofollow"> jaygshah22 </a>Homepage: <a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbWM2WUljMGQwUTZzZmhIYTRybzRlWWlDQ2hGd3xBQ3Jtc0trdWNtM1FkYkxEaE5ZRlIwRzh0WmQ5RFRtS0UyNmwxNkVkcTYxZFV4aHl2bE9wbVRDRUtyNnhac0ppNmZDM2xreDlsTG55WXQyS21BRHNjbmdNZlNKQWlrMmc4c0gxR081b0VaNTU1UGFCSlBrVG12Zw&q=https%3A%2F%2Fjaygshah.github.io%2F&v=gYqr1mGfzE0" target="_blank" rel="nofollow">https://jaygshah.github.io/</a> for any queries.Stay tuned for upcoming webinars!<strong>**Disclaimer: The information in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.**</strong></p>
97 total episodes available
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This podcast updates bi-weekly.
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This podcast is available on 10 platforms including Apple Podcasts, Spotify, and more. You can also use the RSS feed directly.
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