Emre Kıcıman, a core developer of DoWhy, delves into open source causal AI with Microsoft and Amazon collaboration. They discuss the core of science in causal AI, the intersection of language models and world models, the usefulness of modeling physics, and the future of generative AI. The conversation explores challenges in causality, the importance of causal inference in decision-making, and the evolution of libraries promoting causal analysis.

Send us a textRecorded on Jan 17, 2024 in London, UK. Video version available hereWhat makes so many predictions about the future of AI wrong?And what's possible with the current paradigm?From medical imaging to song recommendations, the association-based paradigm of learning can be helpful, but is not sufficient to answer our most interesting questions.Meet Athanasios (Thanos) Vlontzos who looks for inspirations everywhere around him to build causal machine learning and causal inference systems at Spotify's Advanced Causal Inference Lab.In the episode we discuss:- Why is causal discovery a better riddle than causal inference?- Will radiologists be replaced by AI in 2024 or 2025?- What are causal AI skeptics missing?- Can causality emerge in Euclidean latent space? Ready to dive in? About The GuestAthanasios (Thanos) Vlontzos, PhD is a Research Scientist at Advanced Causal Inference Lab at Spotify. Previousl;y, he worked at Apple, at SETI Institute with NASA stakeholders and published in some of the best scientific journals, including Nature Machine Learning. He's specialized in causal modeling, causal inferernce, causal discovery and medical imaging. Connect with Athanasios:- Athanasios on Twitter/X- Athanasios on LinkedIn- Athanasios's web pageAbout The HostAleksander (Alex) Molak is an independent machine learning researcher, educator, entrepreneur and a best-selling author in the area of causality. Connect with Alex:- Alex on the InternetLinksThe full list of links can be found here.Support the showCausal Bandits PodcastCausal AI || Causal Machine Learning || Causal Inference & DiscoveryWeb: https://causalbanditspodcast.comConnect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/Join Causal Python Weekly: https://causalpython.io The Causal Book: https://amzn.to/3QhsRz4

Send us a textVideo version available here Are markets efficient, and if not, can causal models help us leverage the inefficiencies?Do we really need to understand what we're modeling?What's the role of symmetry in modeling financial markets?What are the main challenges in applying causal models in finance?Ready to dive in? About The GuestAlexander Denev is the CEO of Turnleaf Analytics. He's an author of multiple books on financial modeling and a former Head of AI (Financial Services) at Deloitte. He lectures at the University of Oxford and has worked for organizations like IHS Markit, The Royal Bank of Scotland (RBS), and the European Investment Bank. He has over 20 years of experience in finance, data science, and modeling. His first book about causal models was published well ahead of its time.Connect with Alexander:- Alexander on LinkedIn- Alexander's web pageAbout The HostAleksander (Alex) Molak is an independent machine learning researcher, educator, entrepreneur and a best-selling author in the area of causality.Connect with Alex:- Alex on the InternetFull list of links can be found here.#machinelearning #causalai #causalinference #causality #finance #CauslBanditsPodcastSupport the showCausal Bandits PodcastCausal AI || Causal Machine Learning || Causal Inference & DiscoveryWeb: https://causalbanditspodcast.comConnect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/Join Causal Python Weekly: https://causalpython.io The Causal Book: https://amzn.to/3QhsRz4

Send us a textLove Causal Bandits Podcast?Help us bring more quality content: Support the showVideo version of this episode is available hereCausal Inference with LLMs and Reinforcement Learning Agents?Do LLMs have a world model?Can they reason causally?What's the connection between LLMs, reinforcement learning, and causality?Andrew Lampinen, PhD (Google DeepMind) shares the insights from his research on LLMs, reinforcement learning, causal inference and generalizable agents.We also discuss the nature of intelligence, rationality and how they play with evolutionary fitness.Join us in the journey! Recorded on Dec 1, 2023 in London, UK. About The GuestAndrew Lampinen, PhD is a Senior Research Scientist at Google DeepMind. He holds a PhD in PhD in Cognitive Psychology from Stanford University. He's interested in cognitive flexibility and generalization, and how these abilities are enabled by factors like language, memory, and embodiment. Connect with Andrew:- Andrew on Twitter/X - Andrew's web page About The HostAleksander (Alex) Molak is an independent machine learning researcher, educator, entrepreneur and a best-selling author in the area of causality (https://amzn.to/3QhsRz4). Connect with Alex:- Alex on the InternetLinksPapers- Lampinen et al. (2023) - "Passive learning of active causal strategies in agents and language models" (https://arxiv.org/pdf/2305.16183.pdf)- Dasgupta, Lampinen, et al. (2022) Language models show human-like content effects on reasoning tasks" (https://arxiv.org/abs/2207.07051)- Santoro, Lampinen, et al. (2021) - "Symbolic behaviour in artificial intelligence" (https://www.researchgate.net/publication/349125191_Symbolic_Behaviour_in_Artificial_Intelligence)- Webb et al. (2022) - “Emergent Analogical Reasoning in Large Language Models” (https://arxiv.org/abs/2212.09196) Books- Tomasello (2019) - “Becoming Human” (htSupport the showCausal Bandits PodcastCausal AI || Causal Machine Learning || Causal Inference & DiscoveryWeb: https://causalbanditspodcast.comConnect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/Join Causal Python Weekly: https://causalpython.io The Causal Book: https://amzn.to/3QhsRz4

Guest Stephen Senn, an expert in causal inference and clinical trials, delves into the myths of randomization and the limitations of randomized trials in answering causal questions. He discusses the importance of understanding mechanisms of change, considering covariates, and the ethical challenges in clinical trials. Senn also explores innovative trial designs in asthma and chronic diseases, the impact of covariates in statistical analyses, and critiques the Bayesian method while engaging in philosophical discussions on determinism and free will.

Robert Ness discusses the broad perspective on causal inference encompassing graphical models, Bayesian inference, reinforcement learning, generative AI, and cognitive science. The conversation explores the challenges and importance of causal inference in AI models for understanding complex scenarios and human decision-making processes, with a focus on bridging computational models with human reasoning for Artificial General Intelligence (AGI). Delve into the integration of causality in identifying latent representations in generative AI for image manipulation, emphasizing the importance of understanding causal relationships in creating realistic images.

Send us a textSupport the showVideo version available on YouTubeRecorded on Sep 27, 2023 in München, GermanyFrom supply chain to large language models and backIshansh realized the potential of data when he was just 10 years old, during his time as a junior cricket player. His journey led him to ask questions about the mechanisms behind the observed events. Can large language models (LLMs) help in building an industrial causal graph? What inspires stakeholders to share their knowledge and which causal discovery algorithms have been most effective for Ishansh's supply chain use case? Hear the insights from one of the BMW Group's fastest-rising young data science talents. Ready? About The GuestIshansh Gupta is a Lead Data Scientist at BMW Group. Previously, he worked for several companies, including a legendary German sports club SV Werder Bremen. He studied Computer Science, and co-founded an educational startup during his study years. He has supervised or supported students in various universities, including the Munich-based TUM and MIT. Connect with Ishansh: - Ishansh on Twitter/X - Ishansh on LinkedInAbout The HostAleksander (Alex) Molak is an independent machine learning researcher, educator, entrepreneur and a best-selling author in the area of causalityConnect with Alex: - Alex on the InternetLinksPapers Full list of papers hereBooks- Molak (2023) - Causal Inference and Discovery in Python - Pearl & Mackenzie (2019) - The Book of WhyOther- causaLensCausal Bandits TeamProject Coordinator: Taiba MalikVideo and Audio Editing: Navneet Sharma, AleksanderSupport the showCausal Bandits PodcastCausal AI || Causal Machine Learning || Causal Inference & DiscoveryWeb: https://causalbanditspodcast.comConnect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/Join Causal Python Weekly: https://causalpython.io The Causal Book: https://amzn.to/3QhsRz4

Send us a textSupport the showVideo version of this episode is available on YouTubeRecorded on Oct 15, 2023 in São Paulo, BrazilCausal Inference in Fintech? For Brave and True OnlyFrom rural Brazil to one of the country’s largest banks, Matheus’ journey could inspire many. Similarly to our previous guest, Iyar Lin, Matheus was interested in politics, but switched to economics, where he fell in love with math. Observing the state of the industry, he quickly realized that without causality, we cannot answer some of the most interesting business questions. His popular online book 'Causal Inference for The Brave and True' was a side effect of his strong drive to learn causal inference and causal machine learning, while collecting as much feedback as possible along the way. Did he succeed? ------------------------------------------------------------------------------------------------------ About The GuestMatheus Facure is a Staff Data Scientist at Nubank and the author of "Causal Inference for The Brave and True" and "Causal Inference in Python".Connect with Matheus: - Matheus on Twitter/X- Matheus on LinkedIn - Matheus's web pageAbout The HostAleksander (Alex) Molak is an independent machine learning researcher, educator, entrepreneur and a best-selling author in the area of causalityConnect with Alex: - Alex on the InternetLinksBooks - Facure (2023) – Causal Inference in Python- Molak (2023) – Causal Inference and Discovery in PythonWebcasts - AMA WebcastsCausal Bandits TeamProject Coordinator: Taiba Malik Video and Audio Editing: Navneet Sharma, AleksaSupport the showCausal Bandits PodcastCausal AI || Causal Machine Learning || Causal Inference & DiscoveryWeb: https://causalbanditspodcast.comConnect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/Join Causal Python Weekly: https://causalpython.io The Causal Book: https://amzn.to/3QhsRz4

Send us a textSupport the showVideo version available on YouTube Recorded on Sep 13, 2023 in Beit El'Azari, Israel The eternal dance between the data and the modelEarly in his career, Iyar realized that purely associative models cannot provide him with the answers to the questions he found most interesting. This realization laid the groundwork for his search for methods that go beyond statistical summaries of the data. What started as a lonely journey, led him to become a data science lead at his current company, where he fosters causal culture daily. Iyar developed a framework that helps digital product companies make better decisions regarding their products at scale and at budget. Here, causality is not just a concept, but a tool for change. Ready to dive in?------------------------------------------------------------------------------------------------------ About The GuestIyar Lin is a Data Science Lead at Loops, where he helps customers make better decisions leveraging causal inference and machine learning methods. He holds master's degree in statistics from The Hebrew University of Jerusalem. Before Loops, he worked at ViaSat and SimilarWeb. Connect with Iyar: - Iyar on LinkedIn- Iyar's web page About The HostAleksander (Alex) Molak is an independent machine learning researcher, educator, entrepreneur and a best-selling author in the area of causality (https://amzn.to/3QhsRz4). Connect with Alex: - Alex on the InternetLinksPapers - Breiman (2001) - Statistical Modeling: The Two CulturesBooks - Molak (2023) - Causal Inference and Discovery in Python- Pearl et al. (2016) - Causal Inference in Statistics - A PriSupport the showCausal Bandits PodcastCausal AI || Causal Machine Learning || Causal Inference & DiscoveryWeb: https://causalbanditspodcast.comConnect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/Join Causal Python Weekly: https://causalpython.io The Causal Book: https://amzn.to/3QhsRz4

Send us a textSupport the showVideo version available on YouTubeRecorded on Sep 4, 2023 in London, UKA causal betDarko's story begins in Eastern Europe, where his early attempts in building a business and the influence of early-stage role models shaped his attitudes and helped him move through challenging and lonely moments in his career. See how mosquitos, Pascal programming language, and problems with generalization in vision models inspired Darko to build a company that helps some of the world's top companies streamline and deploy causal inference workflows today. Learn how his hedge fund experience shaped his thinking about business. Causal Bandits Extra is a series of conversations with non-technically-focused people involved in or interested in causality from business, social and other perspectives. ------------------------------------------------------------------------------------------------------ About The GuestDarko Matovski, PhD is the co-founder and CEO of causaLens, a $50M venture-backed scaleup. He holds a PhD in Computer Science and an MBA from the University of Southampton. Connect with Darko: - Darko Matovski on LinkedIn: https://www.linkedin.com/in/matovski/ - causaLens web pageAbout The HostAleksander (Alex) Molak is an independent machine learning researcher, educator, entrepreneur and a best-selling author in the area of causal machine learning. Connect with Alex: - Alex on the Internet Causal Bandits TeamProject Coordinator: Taiba Malik (https://www.instagram.com/taibasplay/) Video and Audio Editing: Navneet Sharma, Aleksander Molak *Action* Connect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/ Join Causal Python Weekly: https://causalpython.io Causal Bandits: https://causalbanditspodcast.com The Causal Book: https://amzn.to/3QhsRz4 *Sponsorship Disclaimer* This episode has been made possible with the support of causaLens. We appreciate their contribution to makingSupport the showCausal Bandits PodcastCausal AI || Causal Machine Learning || Causal Inference & DiscoveryWeb: https://causalbanditspodcast.comConnect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/Join Causal Python Weekly: https://causalpython.io The Causal Book: https://amzn.to/3QhsRz4