How do high-networth families use life insurance as a wealth-building tool? In this episode of Planning Reimagined, we continue the series of the family office and welcome Jay Judas to discuss the intricacies of using life insurance in estate planning for affluent families. This discussion covers the strategic implementation of irrevocable trusts t…

How protected is your wealth? Celeste welcomes Yadira Anzueto to dive into the intricate world of risk management and insurance for affluent families. Yadira, a licensed insurance expert, discusses the vital role of risk management in family planning, revealing how proper insurance can be a family's primary defense against unexpected catastrophic l…

In the latest episode of Planning Reimagined, Celeste and Kris are joined by Charmaine Tang, President of Orca, to explore the evolving landscape of family offices and the pivotal role of technology in enhancing their efficiency and effectiveness. Charmaine brings her expertise to the table, discussing issues such as succession, transitioning withi…

Celeste and Kris are joined in the episode of Planning Reimagined by David Friedman, Partner at Forbes Banister International. David talks about the evolving landscape of family offices, the role of technology in managing family wealth, and the shifting paradigms in investment strategies. He also talks about how technology revolutionizes ownership …

In this episode, Celeste is joined by Courtney Joyner Gage and Michael Mazzone to dive even deeper into the world of family wealth management, estate planning, and business succession. They explore the critical importance of communication and thoughtful planning in ensuring that family legacies are preserved and enhanced through generations. They d…

We know that making sure your family is taken care of is important to building your legacy. However, have you actually thought about true generational wealth building and why it means so much more than making sure your family has assets past your life? In this episode of Planning Reimagined, Kris and Celeste welcome Mark Auten to discuss personal a…

Dr. Vincent Moens is an Applied Machine Learning Research Scientist at Meta, and an author of TorchRL and TensorDict in pytorch. Featured References TorchRL: A data-driven decision-making library for PyTorch Albert Bou, Matteo Bettini, Sebastian Dittert, Vikash Kumar, Shagun Sodhani, Xiaomeng Yang, Gianni De Fabritiis, Vincent Moens Additional Refe…

In this episode of Planning Reimagined, Celeste, Michael, and Kris are joined by Jeff Bermis, Co-Founder of 1031 Specialists, to discuss wealth management through real estate and the intricacies of 1031 exchanges for tax deferment. They unravel the complexities of swapping investment properties, the evolution of Delaware Statutory Trusts, and the p…

Welcome back to another wealth-building episode on the Robin Glen podcast, where your host, Celeste Moya and welcomes Kris Stegall and Michael Mazzone to dive deep into the world of real estate investing. In today’s episode, they discuss the complexities of diversifying your real estate portfolio, understanding the intricate tax implications, and s…

Welcome to the first episode of planning reimagined.By Robin Glen

Arash Ahmadian is a Researcher at Cohere and Cohere For AI focussed on Preference Training of large language models. He’s also a researcher at the Vector Institute of AI. Featured Reference Back to Basics: Revisiting REINFORCE Style Optimization for Learning from Human Feedback in LLMs Arash Ahmadian, Chris Cremer, Matthias Gallé, Marzieh Fadaee, J…

Glen Berseth is an assistant professor at the Université de Montréal, a core academic member of the Mila - Quebec AI Institute, a Canada CIFAR AI chair, member l'Institute Courtios, and co-director of the Robotics and Embodied AI Lab (REAL). Featured Links Reinforcement Learning Conference Closing the Gap between TD Learning and Supervised Learning…

Ian Osband is a Research scientist at OpenAI (ex DeepMind, Stanford) working on decision making under uncertainty. We spoke about: - Information theory and RL - Exploration, epistemic uncertainty and joint predictions - Epistemic Neural Networks and scaling to LLMs Featured References Reinforcement Learning, Bit by Bit Xiuyuan Lu, Benjamin Van Roy,…

Sharath Chandra Raparthy on In-Context Learning for Sequential Decision Tasks, GFlowNets, and more! Sharath Chandra Raparthy is an AI Resident at FAIR at Meta, and did his Master's at Mila. Featured Reference Generalization to New Sequential Decision Making Tasks with In-Context Learning Sharath Chandra Raparthy , Eric Hambro, Robert Kirk , Mikael …

Pierluca D'Oro and Martin Klissarov on Motif and RLAIF, Noisy Neighborhoods and Return Landscapes, and more! Pierluca D'Oro is PhD student at Mila and visiting researcher at Meta. Martin Klissarov is a PhD student at Mila and McGill and research scientist intern at Meta. Featured References Motif: Intrinsic Motivation from Artificial Intelligence F…

Martin Riedmiller of Google DeepMind on controlling nuclear fusion plasma in a tokamak with RL, the original Deep Q-Network, Neural Fitted Q-Iteration, Collect and Infer, AGI for control systems, and tons more! Martin Riedmiller is a research scientist and team lead at DeepMind. Featured References Magnetic control of tokamak plasmas through deep r…

Max Schwarzer is a PhD student at Mila, with Aaron Courville and Marc Bellemare, interested in RL scaling, representation learning for RL, and RL for science. Max spent the last 1.5 years at Google Brain/DeepMind, and is now at Apple Machine Learning Research. Featured References Bigger, Better, Faster: Human-level Atari with human-level efficiency…

Julian Togelius is an Associate Professor of Computer Science and Engineering at NYU, and Cofounder and research director at modl.ai Featured References Choose Your Weapon: Survival Strategies for Depressed AI Academics Julian Togelius, Georgios N. Yannakakis Learning Controllable 3D Level Generators Zehua Jiang, Sam Earle, Michael Cerny Green, Jul…

Jakob Foerster on Multi-Agent learning, Cooperation vs Competition, Emergent Communication, Zero-shot coordination, Opponent Shaping, agents for Hanabi and Prisoner's Dilemma, and more. Jakob Foerster is an Associate Professor at University of Oxford. Featured References Learning with Opponent-Learning Awareness Jakob N. Foerster, Richard Y. Chen, …

Danijar Hafner on the DreamerV3 agent and world models, the Director agent and heirarchical RL, realtime RL on robots with DayDreamer, and his framework for unsupervised agent design! Danijar Hafner is a PhD candidate at the University of Toronto with Jimmy Ba, a visiting student at UC Berkeley with Pieter Abbeel, and an intern at DeepMind. He has …

AI Generating Algos, Learning to play Minecraft with Video PreTraining (VPT), Go-Explore for hard exploration, POET and Open Endedness, AI-GAs and ChatGPT, AGI predictions, and lots more! Professor Jeff Clune is Associate Professor of Computer Science at University of British Columbia, a Canada CIFAR AI Chair and Faculty Member at Vector Institute,…

We are moving! The "Arise, Shine" Podcast will not be "Immanuel Lutheran Loveland Podcast featuring Pastor Glen Schlecht." Please click on the link below and subscribe to this new podcast. If you have any questions, email Pastor Robin at rdugall@immanuelloveland.org. Link to the NEW Immanuel Lutheran Loveland Podcast - Subscribe TODAY! https://podc…

Honest Repentance: Purification. Our topic this week in our Honest Repentance series isn’t one that is talked about much – purification. A few weeks ago we explored the theme of water throughout the Bible. This week, we thought about fire and how it’s used by God – and specifically how He uses it to purify us. We looked at "fire" from two different…

Hear about why OpenAI cites her work in RLHF and dialog models, approaches to rewards in RLHF, ChatGPT, Industry vs Academia, PsiPhi-Learning, AGI and more! Dr Natasha Jaques is a Senior Research Scientist at Google Brain. Featured References Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog Natasha Jaques, As…

Honest Repentance: Repentance. This is a core Sunday in this series because we talked very directly about “Repentance” – Honest Repentance! To get there, we took a look at the account of the prophet Jonah when God commanded him to go to the city of Ninevah, a city of great wickedness, darkness, and evil, and call them to repentance. Jonah wasn’t th…

Jacob Beck and Risto Vuorio on their recent Survey of Meta-Reinforcement Learning. Jacob and Risto are Ph.D. students at Whiteson Research Lab at University of Oxford. Featured Reference A Survey of Meta-Reinforcement Learning Jacob Beck, Risto Vuorio, Evan Zheran Liu, Zheng Xiong, Luisa Zintgraf, Chelsea Finn, Shimon Whiteson Additional References…

Honest Repentance: Faith. Pastor Glen's message this week is about Abraham and the unthinkable command that God gave to him to sacrifice his only son, Isaac. As Abraham, by faith, trusted God and obeyed what He commanded him, God stopped Abraham from actually killing his son, this act of faith became the foundation from which faith is talked about …

Honest Repentance: Chaos. Throughout the season of Lent, we are thinking about Honest Repentance. On this Sunday, we considered the chaos that life so often brings – chaos all around us as well as chaos within us. As part of our consideration, we looked at all the metaphors connected to water that we find throughout the Bible. God uses this to conv…

Epiphanization at its Best! As we wrapped up the Epiphany season with Transfiguration Sunday, we’re reminded in no uncertain terms that it’s always about Jesus. The Transfiguration event in Matthew 17 was all about Jesus – pointing to Him, the presence of Moses and Elijah giving clarity about Jesus and who He truly is, the glowing/shining and then …

Epiphanized to Live. The Scriptures we explored this Sunday are beautiful and powerful expressions of LIFE and what the Lord very clearly puts in front of us. He gives us choices and His ultimate desire is that we listen to Him, obey Him, and follow Him. As we continue our Epiphany series, Epiphanized!, these choices are significant when it comes t…

Epiphanized with Foolishness. We continue our Epiphany series, Epiphanized!, thinking about how we as God’s people are being looked upon as being more foolish every day. This is good because it’s a testimony that we represent the Light of Christ. We hold dear the message of the cross, the Gospel of Jesus Christ, which is life-giving and life-sustai…

Darkness, Light, and the Kingdom. We continue our Epiphany series, Epiphanized!, continuing to talk about darkness and light. Today, we looked at these realities in the context of living in the Kingdom of God. Jesus had some things to say about Kingdom-living and they relate pretty directly to what we hear throughout God’s Word and some of the chal…

John Schulman is a cofounder of OpenAI, and currently a researcher and engineer at OpenAI. Featured References WebGPT: Browser-assisted question-answering with human feedback Reiichiro Nakano, Jacob Hilton, Suchir Balaji, Jeff Wu, Long Ouyang, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, Xu Jiang, Karl Cobbe, …

Sven Mika is the Reinforcement Learning Team Lead at Anyscale, and lead committer of RLlib. He holds a PhD in biomathematics, bioinformatics, and computational biology from Witten/Herdecke University. Featured References RLlib Documentation: RLlib: Industry-Grade Reinforcement Learning Ray: Documentation RLlib: Abstractions for Distributed Reinforc…

Karol Hausman is a Senior Research Scientist at Google Brain and an Adjunct Professor at Stanford working on robotics and machine learning. Karol is interested in enabling robots to acquire general-purpose skills with minimal supervision in real-world environments. Fei Xia is a Research Scientist with Google Research. Fei Xia is mostly interested i…

Saikrishna Gottipati is an RL Researcher at AI Redefined, working on RL, MARL, human in the loop learning. Featured References Cogment: Open Source Framework For Distributed Multi-actor Training, Deployment & Operations AI Redefined, Sai Krishna Gottipati, Sagar Kurandwad, Clodéric Mars, Gregory Szriftgiser, François Chabot Do As You Teach: A Multi…

Aravind Srinivas is back! He is now a research Scientist at OpenAI. Featured References Decision Transformer: Reinforcement Learning via Sequence Modeling Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch VideoGPT: Video Generation using VQ-VAE and Transformers Wilson Y…

Dr. Rohin Shah is a Research Scientist at DeepMind, and the editor and main contributor of the Alignment Newsletter. Featured References The MineRL BASALT Competition on Learning from Human Feedback Rohin Shah, Cody Wild, Steven H. Wang, Neel Alex, Brandon Houghton, William Guss, Sharada Mohanty, Anssi Kanervisto, Stephanie Milani, Nicholay Topin, …

Jordan Terry is a PhD candidate at University of Maryland, the maintainer of Gym, the maintainer and creator of PettingZoo and the founder of Swarm Labs. Featured References PettingZoo: Gym for Multi-Agent Reinforcement Learning J. K. Terry, Benjamin Black, Nathaniel Grammel, Mario Jayakumar, Ananth Hari, Ryan Sullivan, Luis Santos, Rodrigo Perez, …

Robert Tjarko Lange is a PhD student working at the Technical University Berlin. Featured References Learning not to learn: Nature versus nurture in silico Lange, R. T., & Sprekeler, H. (2020) On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning Vischer, M. A., Lange, R. T., & Sprekeler, H. (2021). Semantic RL with Act…

We hear about the idea of PERLS and why its important to talk about. Political Economy of Reinforcement Learning (PERLS) Workshop at NeurIPS 2021 on Tues Dec 14th NeurIPS 2021By Robin Ranjit Singh Chauhan

Amy Zhang is a postdoctoral scholar at UC Berkeley and a research scientist at Facebook AI Research. She will be starting as an assistant professor at UT Austin in Spring 2023. Featured References Invariant Causal Prediction for Block MDPs Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precu…

Xianyuan Zhan is currently a research assistant professor at the Institute for AI Industry Research (AIR), Tsinghua University. He received his Ph.D. degree at Purdue University. Before joining Tsinghua University, Dr. Zhan worked as a researcher at Microsoft Research Asia (MSRA) and a data scientist at JD Technology. At JD Technology, he led the r…

Eugene Vinitsky is a PhD student at UC Berkeley advised by Alexandre Bayen. He has interned at Tesla and Deepmind. Featured References A learning agent that acquires social norms from public sanctions in decentralized multi-agent settings Eugene Vinitsky, Raphael Köster, John P. Agapiou, Edgar Duéñez-Guzmán, Alexander Sasha Vezhnevets, Joel Z. Leib…

Dr. Jess Whittlestone is a Senior Research Fellow at the Centre for the Study of Existential Risk and the Leverhulme Centre for the Future of Intelligence, both at the University of Cambridge. Featured References The Societal Implications of Deep Reinforcement Learning Jess Whittlestone, Kai Arulkumaran, Matthew Crosby Artificial Canaries: Early Wa…

Dr Aleksandra Faust is a Staff Research Scientist and Reinforcement Learning research team co-founder at Google Brain Research. Featured References Reinforcement Learning and Planning for Preference Balancing Tasks Faust 2014 Learning Navigation Behaviors End-to-End with AutoRL Hao-Tien Lewis Chiang, Aleksandra Faust, Marek Fiser, Anthony Francis E…

Sam Ritter is a Research Scientist on the neuroscience team at DeepMind. Featured References Unsupervised Predictive Memory in a Goal-Directed Agent (MERLIN) Greg Wayne, Chia-Chun Hung, David Amos, Mehdi Mirza, Arun Ahuja, Agnieszka Grabska-Barwinska, Jack Rae, Piotr Mirowski, Joel Z. Leibo, Adam Santoro, Mevlana Gemici, Malcolm Reynolds, Tim Harle…

Thomas Krendl Gilbert is a PhD student at UC Berkeley’s Center for Human-Compatible AI, specializing in Machine Ethics and Epistemology. Featured References Hard Choices in Artificial Intelligence: Addressing Normative Uncertainty through Sociotechnical Commitments Roel Dobbe, Thomas Krendl Gilbert, Yonatan Mintz Mapping the Political Economy of Re…

Professor Marc G. Bellemare is a Research Scientist at Google Research (Brain team), An Adjunct Professor at McGill University, and a Canada CIFAR AI Chair. Featured References The Arcade Learning Environment: An Evaluation Platform for General Agents Marc G. Bellemare, Yavar Naddaf, Joel Veness, Michael Bowling Human-level control through deep rei…

Robert Osazuwa Ness is an adjunct professor of computer science at Northeastern University, an ML Research Engineer at Gamalon, and the founder of AltDeep School of AI. He holds a PhD in statistics. He studied at Johns Hopkins SAIS and then Purdue University. References Altdeep School of AI, Altdeep on Twitch, Substack, Robert Ness Altdeep Causal G…