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We have all the latest transfer news as Liam Delap From Chelsea to Nottingham Forest is confirmed! Try Oxford Natural, Use Code FFTV For Up to 70% Off! https://oxfordnatural.com/fftv/ The latest Nottingham Forest transfer news has everyone talking after reliable reports, including a major reveal from Percy on X (Twitter), confirmed that a "here we go" deal is in place for Forest to sign Liam Delap from Chelsea. Wolfie breaks down all the details of this massive arrival on Forest Fan TV, diving straight into whether the young striker has what it takes to lead our frontline and make an immediate impact at the City Ground. With the fee reportedly sitting around £45 million, opinions are split across the fanbase on whether this is smart business or if a loan-to-buy arrangement would have been a safer gamble. We want to hear from the Forest faithful on this one—are you happy to see Delap pull on the Garibaldi, or does the £45m price tag make you nervous? Drop your thoughts, debates, and score predictions down in the comments section below, and make sure to hit that subscribe button for more daily Nottingham Forest fan reaction and transfer updates! #nffc #premierleague #chelsea Learn more about your ad choices. Visit podcastchoices.com/adchoices

When we first dicsussed the Summer of Simulative AI in 2024 we knew it would be a brief summer, but it has recently come back with a vengeance with SimGym in April and now Simile AI's $2B Series B, backed by GreenOaks and Index Ventures with prominent backers like Fei-Fei Li and Andrej Karpathy, running tens of millions of simulations for Fortune 100 clients like CVS and 85–99% accuracy vs human focus groups. Time to catch up on why this Second Summer of simulation is working!From creating Smallville, the landmark 2023 paper on Generative Agents that showed AI characters could remember, plan, socialize, and develop emergent behaviors, to now building foundation models of human behavior, Joon Sung Park is trying to answer a much bigger question: what if we could simulate the world before making decisions in it? In this episode, the Simile co-founder and CEO joins us to unpack the path from generative agents to digital twins, why today's frontier models still fail to capture how humans actually behave, and what it would take to eventually simulate all 8 billion people on Earth.We go deep on Simile's approach to modeling human behavior: long-form interviews, observational and transaction data, randomized controlled trials, population-level and individual-level models, and post-training on the causal mechanisms behind why people make decisions. Joon explains how his research created digital twins that reproduced human behavior and attitudes 85% as accurately as people reproduced their own responses, why models optimized to be rational can be bad simulations of irrational humans, and why understanding “social physics” may require changing model weights rather than simply prompting frontier LLMs.We also explore the much larger ambition behind simulation: testing products and policies before deploying them, finding counterintuitive paths toward desired outcomes, modeling emergent behavior across entire societies, and potentially tackling problems like climate change, democratic instability, and UBI. Joon reflects on scaling laws for simulation, the economics of data-center-scale simulated worlds, the connection to Thomas Schelling and psychohistory, why simulation is surprisingly similar to painting, and whether we might already be living in one.We discuss:* How Smallville and Generative Agents led to Simile* Why Joon's team asked: “What if we can just recreate the world that we live in?”* Why useful personal agents require deep models of their users* Memory architectures, Markdown files, and the limits of prompting* “Social physics” and behavioral foundation models* Why web data captures what people say more than what they actually do* Interviews, transactions, observational data, and randomized controlled trials* Why predicting the future matters less than understanding how to shape it* How Simile creates representative simulated populations* Simulation versus prediction and the connection to Foundation's psychohistory* How to evaluate simulations instead of simply stacking LLM hallucinations* Creating digital twins of 1,000 real people and reaching 85% behavioral accuracy* Why frontier models can struggle to reproduce real human behavior* Why good simulations need to reproduce human biases and mistakes* Post-training models on randomized controlled trials* Population-level versus individual-level simulation* Scaling laws for human simulation* The long-term ambition to simulate all 8 billion people on Earth* Whether simulations could help solve climate change or detect collapsing democracy* Thomas Schelling and the history of agent-based modeling* Why future simulations could require an entire data center* Multi-agent simulations and what happens when simulated people interact* Replacing expensive human panels with synthetic populations* Why market research is only the starting point for simulation* Why Joon sees simulation as surprisingly similar to painting* Using simulation to study questions like UBI* Whether we are already living in a simulation* Why AGI and simulation may be the twin technologies of advanced civilizationsJoon Sung Park* LinkedIn: https://www.linkedin.com/in/joonspark* X: https://x.com/joon_s_pk* Website: https://www.joonsungpark.com* Simile: https://www.simile.comTimestamps00:00:00 Introduction and Joon's Path from Art to AI00:01:46 Smallville, Generative Agents, and the Origins of Simulation00:05:03 “Let's Just Create a World” and the Future of Personal Agents00:09:53 Social Physics and Behavioral Foundation Models00:14:08 Prediction vs. Simulation: How Do You Shape the Future?00:16:59 How Simile Models Real People and Populations00:25:35 Evaluating Simulations, Digital Twins, and 85% Accuracy00:30:23 Post-Training Models to Reproduce Human Behavior00:40:04 Scaling Laws and Simulating 8 Billion People00:43:10 From Schelling to Society-Scale Agent Simulations00:46:13 The Cost and Economics of Simulating the World00:52:05 Real-World Use Cases, Synthetic Populations, and the Market00:57:27 The Future of Simulation, Painting, and UBI01:04:23 Are We Already Living in a Simulation?01:06:08 Building Simile and HiringTranscriptIntroduction: Joon Sung Park, Simile, and the Story So FarVibhu [00:00:00]: Today, we have Joon in the podcast. Excited to kick this one off. Very exciting company. I wanna kick off and ask you the question, talk us through the story of your life. How have you gotten here?Joon [00:00:13]: Yeah, for sure. I'm really excited to be here. A story of my life. So I was born in Korea, and I lived there for a good 11 years or so of my life, and then my family moved to Boston. So we moved when I was 11, and my parents were doctors, so they were going through their postdoctoral studies. My dad was a surgeon, so he was doing his sabbatical years at the Boston Children's Hospital. So I grew up there, not too close to tech. I was very much a music and artsy, painting kind of guy.Vibhu [00:00:49]: Painting.Joon [00:00:49]: Exactly. I got into painting a little bit later, in high school, but that's what I used to do. And then I grew up mostly in the East Coast after Korea. So I lived a good number of years in New Hampshire, and then I went to college in Pennsylvania. And I got into more of this tech scene, in college. So I was originally trained to be an artist. I thought that would be my professional career. So it wasn't a hobby. It was like, “Hey, let's make a living out of this.” And then gradually, I got really interested in this idea of, hey, the greatest artist often creates their own medium, and the best medium that we had available today was in computation. So I decided to go deeper into that, and one thing led to another, and we can go deeper into this, but I decided that research was something that I gradually got interested in, and here I am.Smallville, Generative Agents, and the 2023 Breakout PaperSwyx [00:01:46]: So there's a lot that you packed into the research components. You had one of the best papers of 2023, which was the generative agents paper, commonly known as the Smallville paper.Swyx [00:01:58]: Feel free to call back to anything else that you mentioned, but most people would have heard of you from this. Do you have any statistics on how many people have, like, read it? arXiv gives you something, right? Some stats.Joon [00:02:10]: Yeah, it's a good question. How many people have read it, I'm not sure.Joon [00:02:14]: I know we do keep track of citations, and they are going up quite fast.Swyx [00:02:23]: Yeah, Google Scholar has 7,200 citations.Vibhu [00:02:25]: I feel like it made a bigger hit than that, and it was a pretty instrumental paper. It got cited so many times.Swyx [00:02:34]: It is frequently the answer when people ask, “What is the best paper you've read recently?” It's this one.Vibhu [00:02:39]: I thought the memory component was pretty underrated. It was a very good early memory system, and one of the biggest papers.Foundation Models and the Search for Killer ApplicationsJoon [00:02:47]: Yeah, so maybe I can talk a little bit about how this particular paper came together. So when I got into research, it was back in 2020 when I started my PhD program at Stanford, and that was the year, when we were about to get GPT-3 to be available. So we already had GPT-2, and you could sense that there was this new class of models that was just becoming available in the market, and the team got very intrigued. And the general consensus was, “Well, is this model going to be useful for anything?” “It's really strange that these models are not trained to do any particular task.” But we decided to take a bet. So a large group of scholars at Stanford, and it was led by one of my co-founders, Percy Liang, and we came togetherSwyx [00:03:35]: Who coined foundation models.Joon [00:03:36]: Who coined the term foundation models. We wrote this paper, where that term came from called Opportunities and Risks of Foundation Models. And during that process, really the thing that I started to think deeply about was, here is a model that is fundamentally new in our ecosystem. The reason why this was new was it wasn't, again, trained to do anything in particular, but its premise was it could do anything and everything. It was like a stem cell, if you were to take a biology analogy. And I got really interested in this idea that, well, if we were to really think about what are the killer applications that this particular technology would enable, what would that be? Many of my colleagues were using this for simple classification, simple generations. Interesting that these models can do that, but from an interaction perspective, not that interesting. We've known how to do that for many decades. And what we came down to was these models are trained on this very broad data from the web, right? So these are human behavioral data. It's social media, Wikipedia, all these data. So if you poke at the right angle, then you could see human behavior that would just pop out that's quite realistic, and we've never seen that before.The Time Machine Game and Recreating the WorldJoon [00:04:45]: So that got us really interested. The exercise that we decided to do, with this particular group of colleagues, Michael Bernstein, Percy Liang, and myself, who ended up becoming my co-founder at Simile, we sat down and we played this game that we call the time machine game.Joon [00:05:03]: Imagine we were to get on a time machine and fast-forward 10 years and look back. What would have been the single application that will have mattered that would be the most interesting and inspiring? And when we thought, “Well, what if we can just recreate the world that we live in?” it's really hard to get more ambitious than that. Like, let's just create a world.Joon [00:05:24]: And that's where we started. And initially, we had this paper that was a precursor to the generative agents paper called Social Simulacra.Swyx [00:05:32]: Before you go further, were there other candidates for the most ambitious thing in the time machine exercise? What was number two or number three?Personal Agents, User Models, and Why Simulation Came FirstJoon [00:05:44]: There is a close second that we were considering, which ended up becoming more of these automation tools, especially the vision around really personalized agents that would do things for you.Swyx [00:05:59]: That's also happening.Joon [00:06:00]: It's also happening. But it was interesting for us, right, in that the reason why, we decided to go with the idea of simulation, one, I was a huge science fiction nerd, and this idea of creating simulation, I was personally really just fascinated. I loved the idea. It's really cool to see, like, a game town like this and just see these agents live in it. But at the same time, my bet was if you were to create a really amazing personal assistant out of this technology, what you need first is an amazing model of your users. So I told a model, “Hey, can you go buy late dinner for me?” And it orders Hawaiian pizza, and I do not like pineapples on my pizza. Then it totally failed. The way for it to not make that mistake is only by having a deep understanding of who I am. And I gave a very simple and dumb example here, but you can imagine how this core understanding of people is instrumental. This is how, if we have our family and closest friends, they have a good mental model of who we are. That's the basis of our social connection. So our bet also was this technology around simulation, creating accurate representation of people ought to precede the more complex agents that would automate the world that we live in. So that was the bet. But that was a very close second, and I'm still very much fascinated by it. I think there's a lot of interesting work that's going around. My hot take here, though, is I don't think we've seen a true personal assistant that's useful, in ways that meet the ambition of that particular line of work. I think there are early applications that are interesting, and if you talk to even ChatGPT nowadays or Claude, they know a lot about us. So a lot of the generation it's doing, I do think it's much more tailored, but I think the ambition is quite large in that field, and I don't think we quite have all the right ingredients just yet.Swyx [00:08:01]: So OpenClaw and these personal agents, what do you want to see from them that they don't currently have?Memory, Markdown, and the Limits of PromptingJoon [00:08:09]: I do think it's slowly getting there, but I do generally want them to have much deeper understanding of the person. Right now, you look at the models. OpenClaw, what it's leveraging is a Markdown file, and I think it's quite clever, right? So if you look at the generative agents paper, this was the same intuition that we had, where initially when we were creating the memory architecture for the generative agents, and, like, this is, like, back in 2022, so we didn't really quite have the idea of even agentive architecture or the term agent. But the intuition that we shared with some of the work that's coming out today was we initially thought, “Well, do we want to make the memory into, let's say, knowledge graph? Do we want to train a bespoke model?” All of these things. And what we decided to do was, “No. Just forget about all this.” These language models are quite good at modeling text and understanding and reasoning about text. So just put everything in a Markdown file or a text file. You're done. I thought that was quite interesting that we could do that, and there's a lot of strength in doing that. But also, there are limitations. It's the way you retrieve and make sense of data that's extremely large, it takes a lot of work. So I think that technology is getting better. I also do, however, think, there are certain things you just cannot shape just by prompting the model. So to some degree, you do need to touch the parameters of the model itself. So there is this work that I do think does need to happen, and it is happening. The question is, how far can we take it? How do we source data, and how do you also create an ecosystem where people are continuously feeding data to this model so it's learning about you?Vibhu [00:09:50]: What's the intuition between why you need to do it in the model?Social Physics and Behavior Foundation ModelsJoon [00:09:53]: My intuition behind the actual when do you train or even post-train a model versus just prompt a model is if the model has to learn the underlying physics of the world that it's operating in. So it has to learn new social physics. The places where it doesn't have to train are the places where it already has the physics. We trust the physics. It already has the base statistics, but it's just trying to react to an environment. Then I think you can just prompt your way into getting the actions out of it. I don't think the models that are out in the open have yet learned the complete mapping of social physics of humanity. This is one of the core theses of Simile, right? And one of the core reasons why that is the case is if you look at the data that the model was trained on, these models were trained on the web data, like, whatever was available on the web. And these are really interesting data sets, but they are fundamentally the self-exposed attitudinal data with some behavior data that's sprinkled around here and there. And it has yet to learn the really deep behavioral nature of people, not just what people say they do online, but what they do in real life. And this is one of what I would consider to be the dark knowledge of humanity that we haven't quite captured. And it's these data that would also need to get factored into the model creation.Vibhu [00:11:21]: You call it behavior foundation model.Vibhu [00:11:23]: There's a good one-liner here, but outside of that, what type of data do you need? What are you changing on the model level? How do you go about modeling, doing a behavior foundation model?The Three Data Buckets: Interviews, Behavior, and CausalityJoon [00:11:35]: We think about data in three buckets. So one bucket is interview data. It's quite interesting. Rich qualitative data is interesting. It's not behavioral, but we would literally ask people, “Hey, tell me the story of your life.”Vibhu [00:11:53]: It's just what we're doing here exactly.Joon [00:11:54]: The question that you all asked at the beginning of this interview literally is the question we also ask. And we ask our participants to go a little bit deeper, than how far I went. Maybe I can give more of my life story in lieu of this. But the reason why that data is interesting is by learning about this very long-tail information about people, you get a lot of texture around this model, like, this person as a model. So even understanding their childhood memory or even their trauma, their first love, these things, quite informative in ways that's really hard to predict. So that's one. Then there are two tranches of what I would consider to be the behavioral data. One kind of behavioral data is observational. So these might be like transaction data, or these might be data that you can get by scraping the web, right? So you can imagine why these data sets would be interesting, right, because they give you the base statistics of people's behavior.Joon [00:12:55]: But then there is the last category of data, that I personally think is perhaps the most important, which is the data that describes the causal mechanism, the whys of people. Some of this is covered by the interview data, the qualitative, because people talk about why they made certain decisions. But really, where you get to see the most behavioral aspect of this is in randomized controlled trials, like RCTs. Imagine you have the same setup, but you have a few different variables that you are trying to tweak. Can you get realistic human behavior out of it in ways where, imagine you had this particular option. Imagine you're even trying to choose whether you're going to drink coffee or not. The day you drink coffee versus the day you didn't drink coffee, does your behavior change? That's a data set that describes a causal mechanism. This is quite important in modeling people. The reason why this is important is oftentimes when people come to us, or not just to us, but the reason why people are interested in simulation isn't because they want to predict the future. If you're trying to win against the stock market, predicting the future is interesting.Prediction vs. Simulation: Shaping the FutureJoon [00:14:08]: But most people, most decision-makers, what they want to know is, how can we shape the future? It doesn't really help you to hear that your sales are going to tank in two quarters. They're just gonna say, “Wow, that sucks.” What they want to know is, well, what do we need to do now to avoid that future? That's the causal mechanism. And this is also very hard data to come by, right, because the world is our ground truth, but it happens once. So in a very controlled setup where everything is equal except for one variable, this kind of data set rarely happens. So this is a reason why this data set is both hard to come by and quite important if you're trying to model human behavior.Swyx [00:14:50]: So behavior, I think, is the hardest data set to acquire. What is out there? What is even possible? You're not going to know a lot of details about my life. I don't even have data for myself on my own health or habits, and I just don't log everything. So how can you have that data?Joon [00:15:14]: So we run a lot of randomized controlled trials.Swyx [00:15:17]: But you put people in the lab, they watch them sleep, or what?Joon [00:15:20]: We do care a lot about the consent process. People know that we invite them to be a member of this community to both share data and have themselves represented in different forms. But we bring a lot of people to the lab, or virtual lab, where we design experiments that would pose them real behavioral decisions. And often in these experimental setups, what makes the difference between what is attitudinal versus behavioral is whether the stake in your decision is real. That's ultimately what makes it behavioral. So in these setups, we are inspired by our colleagues in social sciences, psychology, and so forth. So when they run studies, the techniques they utilize is imagine there's an online store that you're inviting people to come by. Then whatever they purchase in this experiment, they actually get that item delivered. Like, these are the things that make the stakes real. So we run a lot of these experiments, and we also do partner with firms. Right now, we also have customers who are quite excited to at least give us a glimpse of the behaviors that their users exhibit so that we can get a little bit deeper understanding of how people behave in these different platforms.How Customers Use Simile: Populations, Queries, and ExperimentsVibhu [00:16:39]: I think on the customer side, they have a lot of data about their users, who has bought. They have the action data.Vibhu [00:16:47]: Can you walk us through an example of what someone comes to you for? What questions would they want solved? Do you customize a model for them? Do you have something off the shelf? What does that look like?Joon [00:16:59]: Today, when people leverage our models, it's often to better understand the population of their interest. So usually, the start of the relationship, we come together and hear about what population they want us to model, right? So it might be that if you're a CPG company that's selling to all of the US, then maybe it's fairly straightforward. You want to model the gen pop of the US. But at the same time, if there is a vertical or if there's a market that they're trying to go into, imagine, they want to better understand, let's say, people in their 20s and 30s living in California. That's a much more specific population. So we hear about this population, and we go recruit these people, with consent, and with incentives, and we collect some of their data and create a model of these people. Then what our product allows you to do is query them. So it can take as input a filter that is a description of the population that you want to talk to, just like the one I just mentioned, and an environment. The environment can literally be survey questions, behavioral experiments, It can be A/B testing. Oftentimes, the core use cases are things like concept testing, to start with. But also, people sometimes want to do focus groups or one of the fun use cases that we also serve is even modeling things like earnings calls for public companies.Joon [00:18:21]: So these are the use cases that we often start with.Swyx [00:18:23]: Concept testing, is that an established term? I've never heard of concept testing.Concept Testing, Gallup, and PoliticsJoon [00:18:27]: Yeah. So it has to do with they have, let's say, different messaging, different products, different ideas.Swyx [00:18:32]: It's like a marketing exercise.Swyx [00:18:33]: Okay, got it. Got it. Politics?Joon [00:18:36]: We do, have a strategic partnership with Gallup, and of course, Gallup is deep into policy space and so forth. Right now, we have not worked deeply with politics, like that area just yet, however.Swyx [00:18:49]: I'm curious if there is demand or if they really would have different needs that somehow fundamentally don't mix with your existing, users or people.Joon [00:19:00]: I think there's certainly demand.Joon [00:19:02]: But we are very much mindful of how this technology gets adopted and the societal impact that we'll end up having with this technology. And I do see politics as an area where a company has to be particularly thoughtful about the way they operate and make impact. So this is where we also want to make sure that we form enough of guardrail and perspective on how to leverage this technology before we go on to serve markets like the politics.Swyx [00:19:29]: I'll give people an example. one of my favorite shows is The West Wing. I don't know if people have watched.Swyx [00:19:34]: One of the key storylines is, like, the president has, multiple sclerosis, but they haven't. they need to figure out how to disclose it. So they run a poll with a fake governor and ask people to respond on the poll,Counterfactuals, Polling, and When Simulation Is UsefulSwyx [00:19:47]: They try to make decisions based on the results of that poll on, like, how well they'll be received, like where, how should we play this?Swyx [00:19:54]: And I'm like, well, I think those counterfactual things, I would use a simulation for this if I could trust it.Joon [00:20:01]: For sure.Joon [00:20:02]: In that show, how'd it go?Swyx [00:20:04]: In that show, it was, like a foregone conclusion. They were like, “We know it's bad. We just don't know how bad.” And then the poll came back. It was like, “It's really bad.” And then they just did it anyway.Joon [00:20:14]: Part of it is to show, right? So you're, you're looking at the ideaSwyx [00:20:17]: Maximizing drama.Joon [00:20:18]: How bad could it be? Oh, it's horrible.Swyx [00:20:20]: And to some extent, I think that is part of the trick of the, or the challenge or with being a customer of yours, which is that if I know it's. if I roughly know and can intuitSwyx [00:20:35]: What the effect is going to be, do I need you? What sensitivity of it, of effect do I need in order to make a decision, right? So for example, if I, my approval rating is 50%Swyx [00:20:48]: And I, they have this negative piece, news item comes out, and it drops to 30.Swyx [00:20:52]: If it drops to 20, if it drops to 40, do I care? No. It, I know it drops. It's negative. So when do I care about simulations?Joon [00:21:01]: You do something that's clearly bad, that's not popular, and people don't like you, like, yeah, it's likeSwyx [00:21:05]: You don't need a simulation.Joon [00:21:07]: Yeah. Well, so there are a couple of things. one is, there are use cases where, like every day, developers, designers, policymakers, marketers, every single day, they create assets. They create new products. And turns out, it's many of the decisions in hindsight is obvious. Yes, of course this is bad, but we still run those studies because understanding the magnitude and understanding how acute something is quite difficult, even if, we feel like, of course, like this makes sense. this is the reason why we make so many mistakes. Like, every time somebody goes online and say something that has huge backlash, you look at that and like, “What an idiot.” However, it's tough. That's one. There's also another aspect here, which is, again, this is the reason why simulation is different from prediction. In simulation, in the ideal case scenario. So what simulation is trying to show is it's trying to show each step of the way or each step that we need to take to get to a certain outcome, right? So in the most advanced simulations, sometimes the next step that we're suggesting might be quite counterintuitive. The analogy that I sometimes give, and I ground it in a more realistic example, but, I, as I mentioned, I'm a huge fan of science fiction, and I don't know how, many of the audience members have read, like, things like the Foundation series by Asimov.Simulation as a Path, Not Just a PredictionSwyx [00:22:37]: Oh, yeah. We've mentioned psychohistory a number of times.Joon [00:22:39]: Okay, fantastic. So I might be, talking to the right crew. If you read Foundation series, literally the first act is there's a group of scientists who have found out that, “Oh, our galactic empire is going to collapse, and we're going to have 30,000 years of unrest.” And they run psychohistory, the simulator that tries to teach them, “Okay, how can we keep this unrest to a 1,000 years?” And they plan this out, and the first step of that plan is to get the scientists who say, “Okay, this is coming,” exiled into this random place in this, galax- galaxy.Swyx [00:23:18]: Terminus.Joon [00:23:19]: Exactly. And that's so counterintuitive. Like, what a strange move that you literally sent the group of scientists who was raising voice around this potential collapse of galactic empire into nowhere. How is that the right first move? Well, it turns out in this particular simulation, that was the move.Joon [00:23:40]: It's these things, right? And the reason why these reasoning is possible is because you're showing the step function or each step that results in a particular outcome. So really what simulation allows you to do in its highest form is you give it not a problem or question, like what would people answer to the survey? That's not what we do. What we tell it is, “Here is a goal that we have. In the context of foundation, we want to keep the unrest to a 1,000 years. What is the path that we need to take now to get to that particular future?” And that's what simulation allows you to do. Now, translating that into real market, imagine you're a automobile company and you're about to release a, EV, and you're trying to understand, well, how do we market EV, to make sure that our stock price goes up? But what if the answer comes down that, well, you can market your EV in XYZ way, but that might change people's perception around the cars that's not EV and make your overall sales to go down. Not very intuitive, especially all you're trying to optimize is EV salesss, and that's the only thing that you're tracking, then that might result in a completely wrong solution, or at least different solution than what you would have expected, whether it's right or wrong.Joon [00:24:57]: That's the power of simulation.Swyx [00:24:58]: For listeners, we covered a similar topic with Mikhail Parakhin from Shopify, where they are working on SimGym. I don't know if he ever talked to you about it. it's very similar.Joon [00:25:07]: ISwyx [00:25:07]: The goal is increased conversion, but then the journey is very unusual.Joon [00:25:12]: Journey is unusual.Swyx [00:25:12]: Yeah. The-- He's trying to look for interventions on a shopping trajectory, which is similar to what you're saying. Like, it's not about the attitudinal, is your word for it.Swyx [00:25:24]: It's about behavior.Joon [00:25:25]: It's about behavior.Swyx [00:25:25]: And that's exactly the difference, right? It's, like, not about the near-term direction about-- but it's more about, like, how do you affect multiple turns of interactions.Vibhu [00:25:35]: You had a good quote at the start about this as well. It's not about people wanting to know the outcome. It's about how they can change it, change the way to get there, something like that. But I wanna take it back to how do we know this is grounded? LikeGrounding and Evaluating Digital TwinsVibhu [00:25:47]: How do you run evals? How do you test that simulations come through? if I was to do the same thing that you described with, say, your favorite LLM, Opus, GPT-5.6, have some agent to map out these thingsVibhu [00:26:02]: How different are the answers we would get if I give it the same goal, the same objective, make a decent system? You're saying that you need to change the model weight. You have your own solution to this. But how far off are we, and how do you check if it's grounded? you have some interesting stuff on your site that points to how you run real evals, but if you could take us through that side. I think that's one of the big concerns that people have. They're like, “LLMs hallucinate.”Vibhu [00:26:27]: “You're just hallucinating layer after layer,” right?Joon [00:26:30]: The way we do this, and this is the paper that we worked on after the generative agents paper that really became the, at least for Simile and also the field of simulation and synthetic panels, really became the foundation. Yeah, this is the paper. the paper is called Generative Agent Simulations of 1000 People. Here's what we've done. For this paper, we brought 1,000 people that's representatively sampled from the US to a virtual lab. And what we have done was we spent two hours collecting fairly wide-ranging data. In this particular study, we focused a lot on this interview data, that was, whose script was taken from this project called American Voices Project. And then we would also pair that with a lot of behavior data and so forth, whatever we can collect within two hours. And then we would send these people away for a couple of weeks. And during that time, I would use this data to create their digital twins. And I would bring the humans, participants back after 2 weeks and have them complete a battery of surveys, experiments, behavior studies. So we have the list here, which included things like behavioral economics games. We would run literally, like, Big Five personality test, General Social Survey. We would also go ahead and run the randomized controlled trials that were published on PNAS. And we would have their digital twins predict how the source individuals would have acted in these studies and surveys. And this is where we could replicate people's behaviors and attitudes 85 percent as accurately as people would replicate their own. So that was the first really paper that gave this validated results that we can model individuals in an accurate way. And what we ended up finding now, of course, in AI space, so this paper came out at the end of 2024. AI space, a year and a half, 2 years, that's a lifetime.85% Accuracy and Why Frontier Models Miss Human BehaviorSwyx [00:28:24]: Yeah. Just, for listeners who are not seeing the YouTube, I just wanna say, like, the headline figure is 85 percent accuracy, like, which is a big improvement over all the otherSwyx [00:28:34]: Methods that you showed.Joon [00:28:36]: But the part that was particularly striking to us, especially as we improved this technology even further, was the generative AI models like ChatGPT, Claude that's coming out, it does give you the right foundation. However, what they do not consider is the true attitudinal and behavioral aspect of people, especially in the population that you care about. So what these models are really good at today is they're trying to become the super rational, objective machines, right? So you go get their data from places like Mercor, Scale. You talk to professional programmers, scientists to create model that's amazing at reasoning. That's what they do. Simile doesn't care about any of this. The models that we're talking about here, what we're trying to create are models that are as dumb as I am, right? So if I make some mistakes, the model has to make the same mistake.Swyx [00:29:34]: Oh, that's very hard.Joon [00:29:35]: That's very hard.Swyx [00:29:36]: You're solving Murphy's paradox.Joon [00:29:37]: That's exactly. And this is a completely different data and training objective. This is also where we see quite a bit of discrepancy in the performance in human behavior prediction between the frontier models, Simile's model, and the models being created in this space, where in some cases, the model performance of frontier models go all the way down to 20, 30 percent, especially if you go into that more niche population on topics that our customers would care about. On more gen pop, it might be around 50 to 60 percent. So it's not very robust. Like, you wouldn't want to make your decision off of these and these findings. If you can bring that up to 85 percent, that is ultimately what people end up getting very excited about.Swyx [00:30:20]: Yeah. Do we wanna keep going on the paper, routes?Joon [00:30:23]: Yeah, for sure. So the last one, was an interesting one. So this, paper was the follow-up paper that we had, to the 1000 agents paper, where the idea was now can we augment the models even further and post-train a model based on a lot of randomized controlled trials? So this was an interesting one. The data is always the most interesting part of modeling in many ways. The data that we got here was there's this, there's this platform called Open Science Framework. So some, the audience might be familiar with this. And there has been, especially in the social sciences over the past 5 years or so, there has been this concern around replicability of studies. And so it was a bit of a crisis, the scientists acknowledged, where we rerun the study and we don't see the same finding.Post-Training on RCTs and Replication StudiesVibhu [00:31:12]: Oof.Joon [00:31:12]: It's tough. And the reason why it's there-- that was often the case was there's this survival bias where the papers that get published often need to maintain what we call the value of less than 0.05 in the experiments that we ran. That suggests that only-- there's only 5% chance that the results that we saw is false positive. But the tricky part was all the papers that were not published, and there's still a 5% chance that whatever we publish is totally just randomly generated. Like, there's a 5% chance that, hey, this effect is not real, but it just happened to be real because of the sampling bias. So because of that, what scientists started to do was they started to register their studies. So before running an experiment, they would go to this platform and say, “Here is the data. Here is the population that we're collecting, and here's the hypotheses.” And they would just say, “Here is our hypothesis.” Like, “This is what we believe.” And you cannot retroactively change those hypotheses. This is what gives us more scientific statistical confidence that whatever effect that you ended up seeing is true. So that ended up creating this really interesting platform where there's one platform that has now contains tens of thousands of real-world experiments and hypotheses. And a lot of these are really high-quality, like, professionally designed behavior studies and random- randomized controlled trials. So we got the data and the studies from this platform and used that to make a point. And this particular, model is not, something that we're serving commercially because this was a part of the open science. But this particular data set, helped us make a point that by collecting a lot of these randomized controlled trials, that are really well-designed, we can make significant improvement in model's capability to predict human behaviors. So that's what this paper was about.Vibhu [00:33:10]: Is this stuff done on a individual level? Like, do I need to tune the model per individual, per company? Is there foundation model changes and then some slight post-training? Anything you can share there?Population-Level vs. Individual-Level ModelsJoon [00:33:21]: So this particular model was trained. the data we had at the level of individuals, but this particular model was trained. We experimented with both. And this is what we end up doing at Simile too. We always train 2, distinct model. One is what we call the population-level model. The other is what we call the individual-level model. And both take very similar input, which is the description of a subpopulation or individual and a stimuli. In this particular work, we've done the same. Here, the results that we are reporting are much more geared towards individuals because we do think that is a harder task in many ways, but that's what we have done.Vibhu [00:34:02]: You seen anything on the questions that humans can solve that models can't solve? So likeHuman Biases, Mundane Choices, and What Models MissVibhu [00:34:09]: Currently, it's, I live 5 minutes walk away from a car wash. It's a 10-minute drive. Should I walk or drive?Joon [00:34:16]: Huh.Vibhu [00:34:16]: The model will say, “Oh, walk to the car wash.” And, you don't have your car.Vibhu [00:34:20]: Is anything like this a problem in simulation? You would assume, like, very simple for human to think about, but if the model is saying you should walk to the car wash, anything here?Joon [00:34:32]: It's less, what can we solve, but I think it's more about what biases or mistakes do people make that models miss. Like, imagine that you are, like the. When I was still at Stanford, I lived in Palo Alto. So it's about, I would say, 40-minute walk from the campus. You ask the model, “Okay, let's go home. What can I, what can I do?” It would likely call an Uber or, give me, the bus time. But for the longest time, I really liked walking back. And the reason why I wanted to do that was not for efficiency. It really helped me think. And I like to walk for, half an hour or 40 minutes or so a day, where I just get to, just think about ideas, research, just get lost in my thoughts. That's very human activity. Unless the model has seen that and understands the importance of that activity, it would miss these kinds of features. So that I think, is fundamentally what we're trying to model. Like, what is fundamentally human might not be the most efficient thing to do, might not be the right thing to do, but things that make us who we are.Swyx [00:35:43]: I'm curious if, there are some data sets that you really want that would materially help you. One version of this may be interesting, which is more valuable to you to acquire as a data set, all of LinkedIn, all of Twitter, all of Facebook?What Data Matters: Social Media, Transactions, and FacebookJoon [00:35:57]: It's a little bit hard to rank, in part because, there's, there's this product saying where no feedback is wrong because it teaches you something about your users. Doesn't matter what feedback.Joon [00:36:11]: I think it's a little bit like that.Swyx [00:36:12]: So just whatever is bigger.Vibhu [00:36:13]: What about a different domain? Say it was. What about all of Amazon data?Joon [00:36:17]: Oh, yeah.Vibhu [00:36:18]: Shopping data, right?Joon [00:36:18]: Shopping data. So Amazon data is interesting in that it's very much behavioral, although, like, what people do on social media, you could squint and say that is also behavioral. But the transaction data is always interesting. It is also most commonly available, however.Joon [00:36:33]: If we were to look at purely social media, like if you really, if I were, if I had to really pick, Facebook likely is interesting because I do think it is most a default version of people. Because you go to LinkedIn, it's very much professional environment. So people put up their, they have their guards up, right? And that still is interesting because that is true human attitude and behavior, but it is not your base state. you go to Twitter- Twitter, people have their own crazy personas, or depending on who you are. Like, my Twitter profile and, persona is very much, initially was I was very much an academic. “Hey, I'm here to share my studies.” Now, I share, things that's related to Simile. But Facebook is one of those more private space where people just connect with their friends. In that way, I do think it shows you a little bit more about who that person is. So if I had to pick, I'd likely pick, Facebook.Swyx [00:37:30]: Yeah. And you're interested in, like, the whole person and their background and philosophy. I, is it too clinical or too machine learning-oriented to just say this is just ways to inject variance and biases? The broad question, is, like, is this any better than a randomized, like, combinatorial explosion version? So we have a link to the TencentBillion Personas, Synthetic Demographics, and Bespoke DataSwyx [00:37:54]: Billion persona paper, where they did not do any of the groundwork that you are doing.Swyx [00:37:59]: They just did like a cross matrix of here's all the professions in the world, here's all the people, possible backgrounds in the world, do a dot product across all of them, and that's it. That's your prompt for a billion people.Swyx [00:38:12]: This will do something. I don't know if it'll do what you do, but it gets you some way, some percent of the way there.Joon [00:38:18]: So this was an interesting paper. Like, what I admired about this paper when it came out was the scale. And you do gradually want to be able to simulate really large societies and interactions. So the scale is definitely admirable. it is relying heavily on the known statistics that went into training the model. So to the extent that you believe that statistics is correct, this is not a bad way to go about this. But the thesis here, and this is something that we also have seen in the market, like if this works, then we have solved simulation.Joon [00:38:54]: It,Swyx [00:38:55]: Because I survey, like, okay, 5% of the US population is in construction.Swyx [00:39:01]: The other 5% is in medicine, whatever, right? And then you just keep going down the list, and then you do the other side. 5% has, like, the big 5 personalitySwyx [00:39:08]: Of, like, neurotic or whatever. That's it.Joon [00:39:11]: That's it. So if you believe that the underlying data set and the platform that we're leveraging has all the right statistics, then this will have solved it. you're at that point merely retrieving the knowledge that is already embedded in the model, in the model parameters. That's not, unfortunately, what we see, where there is such detailed and also niche knowledge about people that if you just take one example, it might feel very mundane, but it's quite rich when you put together, that you do need to do a lot of bespoke data collection to better understand people. And this is also, I think what makes this particular, job fun, which you want to deeply understand people, and the process of deeply understanding them requires a lot of attention to the details. And you do need to pay attention to and pay respect to the daily lives that people lead.Scaling Simulation: From Thousands to SocietiesVibhu [00:40:04]: I wanna talk about scaling simulation.Vibhu [00:40:07]: So what can't we simulate, what can we simulate, and how does scaling affect this? So how big are the models? What if we go from, 8B, like, couple 100 billionVibhu [00:40:18]: Like billion000 parameters, billion000? Do we get scaling? Any interesting emergence? Like, at a certain scale, at a certain amount of training, you uncover anything unusual and any learnings from that?Joon [00:40:31]: What we are seeing is at Simile, so we do post-train our own model. The thing that we're seeing is the early glimpse of scaling law in simulations. The more data about humans and more compute you ingest, you start to get predictive and predictable gains of the model performance in simulating it, simulating people.Vibhu [00:40:51]: Ooh. We need a scaling law curve.Joon [00:40:52]: It's scaling law. Whenever you find it's a beautiful thing. And we're starting to see the glimpse of it, which is quite exciting. But if you talk about the ambition of simulation as a whole, it's not merely about building a model. It's about building a model, then creating the agents that become the individuals in a much larger ecosystem. So they're creating this multi-agent simulation. Down the line, you want these multi-agent simulation to also live in a very rich environment, right? What we are really trying to get to at that point is, hey, can we create. All right, let's do a time machine game again, and 5 years, 10 years into the future, can we create a simulation of 8 billion people living on Earth? I think that's quite interesting. And that really is the vision. And once you get to that state, the questions that you can help answer for the society also start to change from my perspective. The answers are fundamentally about emergence of the emergent behavior of society and large groups of people.Joon [00:41:53]: So the questions that I get excited by, and maybe this is a stodgy- a bit. I have my, academic side of me.Joon [00:42:01]: And for me, it's questions like, can we help solve climate change? If you look at climate change as a problem space, this is what we, like social scientists would often call it the wicked problems, problem where you have many actors with competing incentives for trying to make a very complex decision and coordinating that coordination decision. Very difficult to really solve in real life, which is also the reason why we couldn't solve it. Can simulation help us solve that? Another one is, can we understand the signals for collapsing democracy, or can we understand or can we uncover the origin story of the monetary system? These are societal questions that we never really had a good way of answering. If we can create simulations of our society, you have to believe that these are the problems that we can solve. So that's really the ambition of this field. And, I also think, yes, I think there's a Nobel Prize to be won there, which wouldn't be surprising. And I think there's some amazing societal impact that we can have to help people make better decisions.Climate Change, Democracy, and Societal SimulationSwyx [00:43:04]: Nobel Prize in economics?Joon [00:43:06]: In economics.Swyx [00:43:06]: Oh, I see. I see. Rooting for you to write that paper.Joon [00:43:10]: One of these days. But, one of the scholars that I was deeply inspired by, When I was coming into the space of simulation, is this scholar, named Thomas Schelling.Schelling, Agent-Based Models, and the Nobel PrizeSwyx [00:43:23]: Schelling point?Joon [00:43:24]: So the canonical example of the work that he's done was he was one of the creators of agent-based modeling. So this was, like, in the 1970s and 80s. It's very early days, but this was truly one of the first exemplars of simulations. And one of the canonical model from that time, and of course many of these simulations are trying to tackle the societal problems that's most relevant for their era, it was called the model of segregation. So racial segregation was a big topic, that, we cared about. And what they've done was they created this grid world where they had red dots and blue dots. And these dots were, back in the day, like, they were the agents, and they had a simple rule that governed their behavior. If certain percentage of your neighbors are of different color and if that goes above certain threshold, then you move to a new location at random.Joon [00:44:21]: One of the striking finding of this paper or this agent-based model was for the longest time, people thought the segregation within society was caused by explicit and overt racism.Joon [00:44:34]: But if you look at this model, people's preference towards living with people of the same color, that preference can be very minute.Joon [00:44:42]: But the very small difference causes the society to segregate completely over time. This was very counterintuitive for a lot of people. And this particular work ended up informing housing policies. Mixed income housing, got really inspired by this work. And Thomas Schelling ends up winning the Nobel Prize for having laid the groundwork for very early versions of simulations. The opportunity that I do see here in the more scientific terms, is agent-based models for the longest, had impact in the 1980s, 90s, to some extent, early 2000s, but it has now gotten forgotten by the community a little bit. Because as you can imagine, red dots and blue dots is not really a rich description of people.Joon [00:45:31]: But with the emergence of things like generative AI and, in particular, generative agents, we do have an opportunity to create these agent-based models that are high fidelity enough to help us make really complex decisions. And that's the opportunity that I see. If that truly works, then yes, that is the work that will result in a Nobel Prize.Swyx [00:45:53]: Yeah. For what it's worth, and I grew up in Singapore. 80% of Singapore is in public housing, and public housing has, enforced racial quotas for exactly that reason, which is very interesting. okay, so we talk about scaling, we talk about all these, the agent possible applications.Cost, Reuse, and the Economics of SimulationSwyx [00:46:13]: I'm scared about the cost. if you even-- let's just keep it to the US, about 8 billion people.Swyx [00:46:21]: But, how much does it cost to model so many hundreds of millions of people?Joon [00:46:26]: Oftentimes today, we don't start at that scale, this stage of the, of industry and simulation as technology. But we can get our users extremely rich and meaningful insights even by modeling thousands, tens of thousands of people. And today what we do is every week we are collecting data on the scale of tens of thousands people's data, and we have panel partnerships that gets us to tens of millions of people globally. So that's what we do today.Swyx [00:46:55]: And just as a side note once you've collected one person for one studySwyx [00:46:59]: Can you reuse that same person for all the subsequent studies?Joon [00:47:03]: That's exactly right.Swyx [00:47:03]: Okay.Joon [00:47:04]: The beauty of this model and these agents is the fact that they are domain-agnostic.Joon [00:47:08]: That what you're really trying to understand is what is the fundamental nature of these people? What's their social physics? And there are a lot of, a lot of, people that does change over time. Like, even, like, even things like, how many times have you gone have you been to, like, CVS the past week? that will change. But there's so many traits about people that are also known to never change. Like, your risk tolerance doesn't really change over time. It's very consistent. So it's these things that we're trying to learn. But the scale we are operating is right now hundreds or, tens of thousands to hundreds of thousands. And in many of the core use cases that we are deployed in, and this is more than enough population, to cover those. Really, at that point, what you care about is less the number of people, but more do you have the right subpopulation of interest covered? And this is also the reason why people want a larger sample. It's not because they want, stronger statistical guarantees. It's more that can they filter down to any population of their interest. However, you can also imagine in 10 years, if we truly believe that the compute is going to scale, that we'll have much more availability for compute, and our ambition for simulation is also going to scale accordingly, there's definitely a reason for us to create an entire data center worth of simulations.Joon [00:48:35]: Or in my hunch here is I do think in the next some number of years, we will start creating simulations that will cost as much as training a foundation model. But perhaps it's going to be so valuable to the society that it would be a no-brainer. Right now, even today, like, we are training bunch of new foundation model just so we can say we trained one and we spent tens of millions. But if we can create a simulation at the level of society that would solve climate change, I would run that today. I would raise the money right now just to run that.Multi-Agent Simulation and Social InfluenceSwyx [00:49:10]: Amazing. the follow-up question is, does it also compound if you let the simulations talk to each other?Swyx [00:49:18]: Or do they already do that today? They don't, right, as far as I understand?Joon [00:49:22]: It depends on what simulation you're trying to run.Joon [00:49:24]: In the multi-agent simulation setup, the agents do talk to each other.Swyx [00:49:28]: Right, which is exactly Smallville, right?Joon [00:49:29]: That's right.Swyx [00:49:30]: But a lot of times, for example, in commerce, you're just by yourself, so there's no point talking. which is way cheaper.Vibhu [00:49:37]: But they use all these levels, right? Like, you decide what you will buy based on what other people around you buy and talk about, right?Swyx [00:49:43]: It depends.Vibhu [00:49:44]: It depends.Swyx [00:49:45]: Again, I'm, I'm coming at this from a cost point of view. I'm like, “Oh my God.” LikeVibhu [00:49:48]: I thinkSwyx [00:49:49]: If there is, like, some combinatorial thing of, like, thousands of people talking to thousands of people, then that one million X's might cost.Vibhu [00:49:56]: I have a very different view as the cost point aside. Like, running these studies in reality is a lot more expensive, right? Running any study like this is you gotta have people do it, you gotta sign people up. It's very expensive and sometimes, like, not feasible to run the study.Vibhu [00:50:14]: But the outcome or the decisions you make are very expensive on them, right? So spend X million on something that, the overall process costs 100 million might as well, right? There's, there's a lot of value to be had there. It's a small cost, but I'm excited on the cost side.Joon [00:50:33]: To some extent, and when you deploy technology, you often want to deploy in a way where you can replace existing budget or you can make things more efficient, and that is the best way to deploy. However, the way you capture the long-term value of the technology is making the argument that, no, it's the upside, that by making this better decision using simulation, you have saved yourself or made yourself hundreds of millions or even billions of dollars, and that's a case to be made.Vibhu [00:51:06]: Random tangent question. So if you're doing a lot of inference, a lot of model multi-agent stuff, are you at the point where it makes sense to, train a model that' very sparse? You're expecting to do multi-million dollar runs. Are you thinking about this in model architecture standpoint or inference efficiency, or, you're still at the research phase of it works, we're not super there yet?Joon [00:51:34]: Efficiency, we do think quite a bit about. this is technology that is deployed now in some of the largest enterprise companies in the world, and we do process significant number of queries, that are trying to, simulate the populations in the world. So efficiency is a consistent thing. we don't want to over-optimize too early, so I wouldn't say, like, this is the higher bid Right now, but this is definitely something that we think pretty carefully about.Swyx [00:52:05]: Yeah. Are there other case studies? So we, you talked about CVS, talked about Gallup, Deloitte, Wealthfront.Efficiency, Enterprise Use, and Real-World Case StudiesJoon [00:52:12]: Wealthfront is an interesting one, because one of the things they were trying to do, they were one of the first customers that wanted to do product testing that goes beyond just asking people what they think about, let's say, behavior experiments and so forth. So there, really what we had to do was reason about multimodal input, so images, but also you can also imagine, like, these agents traversing through Figma mockups or websites. So some of the things that our agents can also do is it can be given a domain, like, or, like, a website URL and go use it for a while. It's these things. And Wealthfront was one of the first, customers, that was very excited about this possibility.Vibhu [00:52:53]: What have people been asking? Like, is there any demand that we have not covered? Like, UI testing, right?Vibhu [00:52:59]: I wanna try a new. I wanna ship a new feature, test the UI, simulate how people will do it. Any interesting things that you're seeing demand for?Product Testing, Websites, and Synthetic PanelsJoon [00:53:08]: Today, a lot of the demand does come from like, the places where people have historically used human panels, we can now replace with agents, and these synthetic populations. And this is not replacing human panel. in many ways, the simulation that Simile is building is grounded. So the way that I think about this is we are trying to represent humanity at scale. And in that way, the use cases are what we would expect, but it's the scale of deployment that surprises me.Joon [00:53:44]: Turns out there are so many decisions that people make every day in these organizations, groups, and we want to be able to say, “We listen to people. We have consulted our users.” But in reality, that is rarely the case because getting to people and asking them many questions, it's difficult. It's both costly, time-consuming, but most importantly, people are just not available. If I had to answer 1000 survey questions for this one particular, vendor, even if I wanted to do that, like, I would never do it. And that's very much the case. What simulation can do is ensure that the voices of people are always represented in rooms where the decisions for them is made, right? So all the stakeholders of this particular product launch, ideally they're consulted. That's what this technology really is trying to enable.Market Size, TAM, and Human Decision-MakingSwyx [00:54:39]: In my mind, that means it skews towards more consumer focus, right? Like, anything with a wide enough customer base where you do benefit from the diversity that you represent. What are some rough statistics, just for people who are not familiar with this market in general, what's the market size that. I'm sure you have some, like, rough numbers. market size is, like, a vague questionSwyx [00:55:01]: But, like, how much do people spend?Joon [00:55:03]: So market research is a $100 billion industry.Joon [00:55:06]: But the thing about simulation is not a tool for market research. Simulation is a tool for human decision-making. So the question around what is a TAM here is quite tricky, right? Because it's easy to say, “Well, market research TAM is roughly 100 million or 100 billion.” so is it a TAM? And not really, right? Because in many ways, you're trying to inform all human decision-making. You're trying to inform every decision that are made about humans for humans. What is a TAM for that? It's really unclear. And I'll be honest. Like, I have a scientific background, I have a research background, so I didn't come into the field calculating, oh, what is the TAM for human decision-making? But I just had to assume, well, if we can inform every decision that is made about human for human, that has to be big.Swyx [00:55:58]: Some- something valuable.Joon [00:55:59]: Exactly.Swyx [00:55:59]: To some extent, you are a unicorn founder now, and you have to care as a CEO. But, like, I do think, like, yeah, when you go into these boardrooms with people that you're quoting millions of dollars of contracts for, like, you have to say, “Well, here's what you spend on humans-”Swyx [00:56:15]: “. And here's what we save you, and it's 85% similar.”Joon [00:56:19]: And certainly, the value case, is something that we care deeply about. Like, what is the value that we provide to the users and the decision-makers? But this is also where, like, as a founder, I think valuation only tells one very superficial aspect of the story, and I try not to think too much about valuation, in general, because that's not what also motivates a team or certainly doesn't. I'm, I-- Again, the interesting thing about researchers is we are happy living in academia, getting paid next to. we get paid okay. we don't get paid that much, as a researcher here in academia, but it's the impact and it's the, it's the value that we can provide to the individuals and the society that really drives us. And in that way, ultimately what drives us is the impact. Does the simulation we provide have a real impact in people's decision-making in ways that progresses our society forward? If the answer is yes, then yes. that has to be great business, and we see that in numbers, and we do care deeply about that upside story, but that's the heart of it.Where Simulation Goes NextVibhu [00:57:27]: Do you have any timeline predictions? So we talked about scaling laws of simulations.Vibhu [00:57:33]: You brought up, okay, maybe one day we can simulate how to solve climate change.Vibhu [00:57:38]: Where are we now?Vibhu [00:57:40]: If that's not the end state, what is an end state, and what does progress look like?Joon [00:57:45]: So what I sometimes tell people is simulation as industry, it feels a lot like where GPT-3.5, GPT-4 was, for the AGI saga, which is we have now technology that is powerful enough to do real damage on the verticals that we are tackling. At the same time, there's a lot of progress that is yet to come. And that's, I think, where this is. So the way I see it, I do think there will continue to be breakthroughs both in data, in algorithms, and there will be much more aggressive scaling that will also happen over the next few years. But I think that's roughly where we are.Swyx [00:58:27]: I think that was about the ro

"89 is such a hoax, dude." Chris Cote is mad at gas stations, and it's not for the reason you think. He also once put green gas in his car because he was distracted. Amin is mad at dogs again and especially mad at Ethan's dog, who is named Percy, NOT Malachi. Plus, Hall of Fame quarterback Drew Brees joins the show to discuss the emotions of his enshrinement, how close he came to signing with the Miami Dolphins, and when the last time he went to the movies was. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Wij praten in deze aflevering met Ingeborg en Percy, het echtpaar achter de Online Viltschool en EcoPrint. Ingeborg was ooit docente, maar samen met haar partner bouwde ze een bloeiend bedrijf rond een hobby waar de meeste mensen nog nooit van gehoord hebben: vilten, oftewel wol met je handen tot stof maken. Met meer dan 800 betalende leden en een mailinglijst van 10.000 mensen bewijzen ze dat een kleine niche geen kleine business hoeft te zijn. Ze vertellen ✅ Hoe ze 90 cursussen verkochten zonder funnel, mailinglijst of betaalpagina ✅ Hoe zij 10.000 euro omzet deden voordat hun product bestond ✅ Wanneer je beter voor Facebook kunt kiezen dan voor Instagram ✅ De webinar-truc waarmee Ingeborg live lesgeeft zonder iets live voor te doen ✅ De strategie om overladen te worden met social proof van je klanten ✅ Hoe ze als businesspartners hun huwelijk niet laten verstoffen ✅ Hoe je een doelgroep van 60-plussers online aan het werk krijgt

This week we return from our summer holidays (having avoided the wildfires in France) with Pam narrating the life of Captain John Smith. A man from Lancashire who became both a key part of the British settling of the East Coast of America, and a Disney Character.From humble orphan origins, John embarked on the life of an adventurer which encompassed pretty much everything you could imagine. So strap in for a tale of Crusades, duels, slavery, disasters, double-dealing, slanders, pirates, exploration, life or death struggles and cartography!With special guest appearances from Pocahontas and (potentially) a pug called Percy.Guest Host: Pamela Loetterle Hosted on Acast. See acast.com/privacy for more information.

This episode is a recording of our book club. The book we discuss is Why Die? The Extraordinary Percy Cerutty, 'Maker of Champions' by Graem Sims (Author).Percy Cerutty was an Australian athletics coach who transformed distance running in the 1950s and 1960s. Based at his rugged Portsea training camp, he developed the Stotan philosophy, blending Stoic discipline, Spartan toughness, natural diets, sand-hill running, weight training and intellectual growth. Best known for coaching Herb Elliott to world records and Olympic gold, Cerutty inspired athletes to pursue physical excellence and personal mastery. Our discussion is led by Dr David Turner, a Senior Lecturer in Sports Coaching at Anglia Ruskin University in the United Kingdom, and we are also joined by Andrew Gunn the author of Percy Cerutty: Life Lessons From A Remarkable Coach by Andrew Gunn.I scribbled down these 3 self-reflective questions:· Where in my life could I benefit from choosing growth over comfort?· What is one challenge I have already overcome that shows I am capable of reinvention?· How do I personally measure success: by outward achievement, or by how far I have come from where I started? If you would like to send us any feedback or if you know a great coach, who has a unique story to share, then we would love to hear from you, please contact us at paul@thegreatcoachespodcast.com and if you would like to receive our newsletter with 5 ideas to help you improve your leadership, then sign up at: https://thegreatcoaches.beehiiv.com/subscribe Hosted on Acast. See acast.com/privacy for more information.

Episode 156 - Every Tool's A Hammer (Fallout RPG)    After returning home to Vault Theta, our explorers take the opportunity to rest and consider what they've just been through. The Overseer is deep in discussion with the Ghoul family that the explorers found along the coast, attended by Shuttlecock; Victor looks to personalise the Laser weapon he "borrowed" from Harry, and Percy & Sally set to building a set of armour, to protect from future dangers...Dangers which may be closer than they think!   Find Us on Bluesky @PretendWithDice, @MonkeyMagicEden, @Ajheretic666, @MarkusMalice87 & @unklchop You can also find us on Facebook, Instagram & Twitter/X @PretendWithDice Links to all of our online presences can be found at www.pretendingwithdice.com, including our Ko-fi page, Merch Store, Discord server and much much more!

Bishop Tony Percy says the 1st reading (1 Kings 19) and the Gospel (Matthew 14) are linked by the revelation of God's effortless mastery. Both readings reveal God's supernatural power entering quietly yet authoritatively into human fear and chaos

Existe um caminho certo para chegar à liderança? E como uma instituição financeira se prepara para atender clientes com uma visão cada vez mais global?No novo episódio do Mind Asset, recebemos Percy Moreira, CEO do Itaú USA e Head do Itaú Private Bank Internacional, para uma conversa sobre carreira, liderança, gestão de equipes globais e expansão internacional do Itaú.Ao longo da conversa, Percy compartilha aprendizados da sua trajetória, apresenta sua visão sobre a expansão das operações do Itaú nos Estados Unidos e mostra por que investir internacionalmente pode contribuir para a diversificação do patrimônio e para a construção de portfólios mais resilientes.

TODAY ON THE ROBERT SCOTT BELL SHOW: Polypharmacy Death Risk, Dr. Shonna Calica, Annalisa Percy RN, Global Natural Health Solutions, Hormonal Homeopathic Care, Cyclospora Skinny Trend, Medical Reform Failure, Jennifer Margulis, Anna Bazarnaya, Writing Under The Tuscan Sun, Lepidium Bonariense, and MORE! https://robertscottbell.com/polypharmacy-death-risk-dr-shonna-calica-annalisa-percy-rn-hormonal-homeopathic-care-cyclospora-skinny-trend-medical-reform-failure-jennifer-margulis-anna-bazarnaya-lepidium-bonariense-and-m/ Purpose and Character The use of copyrighted material on the website is for non-commercial, educational purposes, and is intended to provide benefit to the public through information, critique, teaching, scholarship, or research. Nature of Copyrighted Material Weensure that the copyrighted material used is for supplementary and illustrative purposes and that it contributes significantly to the user's understanding of the content in a non-detrimental way to the commercial value of the original content. Amount and Substantiality Our website uses only the necessary amount of copyrighted material to achieve the intended purpose and does not substitute for the original market of the copyrighted works. Effect on Market Value The use of copyrighted material on our website does not in any way diminish or affect the market value of the original work. We believe that our use constitutes a 'fair use' of any such copyrighted material as provided for in section 107 of the U.S. Copyright Law. If you believe that any content on the website violates your copyright, please contact us providing the necessary information, and we will take appropriate action to address your concern.

Mary and Doug blether about Dr Percy Calder and his work on Tuberculin milk. Learn more about your ad choices. Visit megaphone.fm/adchoices

Wrath of the Triple Goddess, ch. 26 to 30 This week on Unwise Girls, we discuss Deltarune, the tragedy of our GOAT, a fix to some of our previous problems, Percy's journey to learn that women are people, more overt magical school allusions, the sad state of being a woman who is a mother, and the superpower of neurodivergence. Come back next week for Wrath of the Triple Goddess, ch. 31 to 35! Check out our Patreon! (https://www.patreon.com/unwisegirls) Follow the show (bsky.app/profile/unwisegirls.bsky.social) Join our Discord! (https://discord.gg/XnhhwzKQ8d) Hosted by Jacqueline (https://twitter.com/swampduchess) and Jane (https://twitter.com/janeyshivers). Edited by Jacqueline. Cover art by Vera (https://twitter.com/Innsmouth_Inn). Intro/outro: "Super Mariocean" by spacepony (https://ocremix.org/remix/OCR01147) This podcast is powered by Pinecast.

Episode 149. The boys are back! In this episode Corwin waits for Supergirl to come straight to demand, then becomes astonished at No Way Home's box office numbers. Meanwhile, Scott talks about his trip to Alaska, then admits after 149 episodes he still does not know who Slayback is. They then play catch up and are up to date on Percy's run of Deadpool. In Past-O-Vision they continue reading The Last Ronin. For Merc File, Corwin takes the wheel for once and breaks down Guy Garner. And as always Robot Chicken Hulk wraps the show up with a PSA. Note: This episode was recorded before Brand New Day and the SDCC MUC Panel. Second note, episode 150 the boys will be covering the anime series Steins;gate and Steins;gate 0 and the movie.   0:22:56 Movie Talk 0:32:07 Anime Talk 0:34:29 Corwin's One Piece Progress 0:39:11 Jeff Meets Daredevil (2026) #1 0:44:10 Wade Wilson: Deadpool (2026) #3 0:47:34 Wade Wilson: Deadpool (2026) #4 0:55:20 Wade Wilson: Deadpool (2026) #5 1:01:17 Wade Wilson: Deadpool (2026) #6 Past-O-Vision 1:07:38 TMNT: The Last Ronin (2020) #2 1:17:57 Merc File: Guy Gardner   [MwaP RSS] Subscribe [RSS All] Subscribe [Google Podcasts] Subscribe [Apple Podcasts] Subscribe   Music by Jenki Girls of Los Angeles Email: HipsterDaken@gmail.com Website: http://www.EarthsMightiestPodcast.comFacebook Group: https://www.facebook.com/MercWithaPodcast/ Episodes #1-26 can be found @ Cultural Wormhole.com The Merc Report has now joined the EMP family of podcasts and has now become The Merc With a Podcast! -EXPLICIT CONTENT

With Sarah on foreign shores, Alex heads to the Old Vic rehearsal room to chat to stage and screen legend Roger Allam. Known for his TV and stage appearances in the likes of The Thick of It, Les Misérables and Frank and Percy, Allam is back on stage this summer in How The Other Half Loves at the Old Vic. And, apparently, he played a certain body part in an Ayckbourn radio play. Allam also touches on the topic of amplification and seeing his greats at the Old Vic when he was young. Hosted on Acast. See acast.com/privacy for more information.

Mandy Wiener speaks to Co-Author of My Boss, Mrs Mandela by Zodwa Zwane about her book for the book of the week feature. The Midday Report with Mandy Wiener is 702 and CapeTalk’s flagship news show, your hour of essential news radio. The show is podcasted every weekday, allowing you to catch up with a 60-minute weekday wrap of the day's main news. It's packed with fast-paced interviews with the day’s newsmakers, as well as those who can make sense of the news and explain what's happening in your world. All the interviews are podcasted for you to catch up and listen to. Thank you for listening to this podcast of The Midday Report Listen live on weekdays between 12:00 and 13:00 (SA Time) to The Midday Report broadcast on 702 https://buff.ly/gk3y0Kj and on CapeTalk https://buff.ly/NnFM3Nk For more from The Midday Report go to https://buff.ly/BTGmL9H and find all the catch-up podcasts here https://buff.ly/LcbDdFI Subscribe to the 702 and CapeTalk daily and weekly newsletters https://buff.ly/v5mfetc Follow us on social media: 702 on Facebook: https://www.facebook.com/TalkRadio702 702 on TikTok: https://www.tiktok.com/@talkradio702 702 on Instagram: https://www.instagram.com/talkradio702/ 702 on X: https://x.com/Radio702 702 on YouTube: https://www.youtube.com/@radio702 CapeTalk on Facebook: https://www.facebook.com/CapeTalk CapeTalk on TikTok: https://www.tiktok.com/@capetalk CapeTalk on Instagram: https://www.instagram.com/ CapeTalk on X: https://x.com/CapeTalk CapeTalk on YouTube: https://www.youtube.com/@CapeTalk567 See omnystudio.com/listener for privacy information.

Bishop Tony Percy links Isaiah's invitation, "Come to the water, all you who are thirsty," foreshadows the multiplication of the loaves and is completed at the Last Supper. Jesus gives himself to us because we need his life within us, so that, nourished and transformed by this free gift, we may become his Body in the world and carry on his mission

Hello, this one goes out to Preston, Kaden, and all the farmers out there, but specifically those two, cause theyre the coolest farmers.   This week started where all weeks start, talking about porridge, and Percy, mainly Percy. We attempted to talk about The World Cup, which went terribly. Played Hypothetical Trivia(which, if you didn't know, was created by Carrington), and laughed way too hard about David murdering Goliath; it was for a good cause, right? RIGHT?!?!?! After that, we got a special guest, and you'll never guess who it was. That's right!! ANOTHER FRICKEN ASTRAL TRAVELER!! I swear the lore in this world is getting more convoluted than the MCU. Thank you all for listening; this thing does take a decent amount of energy(shocking, I know), so seeing everyone still listening is actually a huge deal for us, or at least for me; the boys don't love you as I do. Muah!!! See you next time!!   Email: hotcrossbunspod@gmail.com Instagram/TikTok: @hotcrossbunspod

Have you heard the story of Henry Hugh Manvers Percy? This 19th century member of the Percy family won a Victoria Cross for his actions in the Battle of Inkerman, one of the crucial fights during the Crimean War, and his story is told in the book 'A Bearskin's Crimea' by Algernon Percy, newly re-released in an expanded an illustrated edition.We are joined by the author on this episode of the Alnwick Castle Podcast, where he explains who Henry Percy was, some of his actions in the Crimea, and the origins of the Victoria Cross, among many other things. If you are interested in this period of history, this episode and the book are definitely for you; and if you have not heard anything about the Crimean War beyond names like Florence Nightingale, Mary Seacole or the Charge of the Light Bridge, well, we hope this episode and the book are for you too!You can get a copy of 'A Bearskin's Crimea' now. Buy directly from Alnwick Castle at alnwickcastle.com/shop , or you can also order it online through Waterstones.And don't forget to look out for Henry Percy's sword on display in the State Rooms next time you visit Alnwick Castle!

Everything has changed this summer and Every Year After is officially going for it. Jillian is joined by Claire to break down Episode 4, “Anatomy of a Romance,” as the series reaches one of the book's most anticipated scenes and takes the story into completely unexpected territory.They discuss Percy's mission to swim across the lake, the anatomy textbook moment that finally pushes Percy and Sam across the friendship line, and Sam immediately getting in his own way. Plus, Charlie reveals the heartbreaking truth about what happened after his father died, Percy confronts Sam about years of mixed signals, and Sue causes chaos from beyond the grave by leaving The Tavern to Percy.Jillian and Claire also rank their Top 5 “Everything Has Changed This Summer” moments, unpack Percy's struggle to reconnect with the fearless girl she used to be, and celebrate the wine-fueled Barry's Bay girls' night that ends with breaking and entering, shocking confessions, and a trip to jail. With kisses, breakups, family resentment, and one truly unhinged will reading, this episode brings the drama in every possible timeline.00:00 Intro to pod02:08 Ep 4 "Anatomy of a Romance"03:03 Recap of Ep 407:33 Top 5 Everything Has Changed Moments09:02 Percy swims lake16:40 Truth after dad's death21:56 Anatomy textbook scene26:05 Sam ends it34:37 Percy's Tavern41:36 McMansions43:16 ChantalThank you to Matt Buechele (@mattbooshell) for creating our new theme song. You can listen to "Sunscreen" on Spotify: https://open.spotify.com/artist/1gFHHF3QyQxjbbKXV3qLu9Buy our merch: ⁠https://www.etsy.com/shop/PreviouslyOnTeenTV⁠Follow Previously On Teen TV on Instagram: ⁠⁠https://www.instagram.com/previouslyon_teentv/Follow Previously On Teen TV on TikTok: ⁠⁠https://www.tiktok.com/@previouslyon_teentv⁠⁠Subscribe to our YouTube: ⁠⁠https://www.youtube.com/channel/UCe2lgvvZGKMrQ8v24FmDdWQ?sub_confirmation=1⁠

Send us Fan MailAnimated fantasy gets thrown into a lot of different categories, but The Legend of Vox Machina stands out from the crowd. We break down Season 1, talking about its over-the-top action, surprisingly brutal violence, crude humor, and the emotional moments that make it all work. We also discuss how well the series captures the feeling of a real D&D campaign, from the established party dynamic to the moments where you can almost see the dice rolls behind the action. And yes, Scanlan absolutely steals the show.We also dive into the Critical Role roots of the series, Percy's revenge story in Whitestone, the Briarwoods, cursed weapons, vampire lore, and big moments like Pike's return. Whether you're a longtime fan or watching for the first time, there's plenty here to enjoy if you love fantasy, tabletop games, or character-driven adventures.If you enjoyed the conversation, subscribe, share the episode with a fellow fantasy fan, and leave us a five star review to help more people discover the show.Twitter handles:Project Geekology: https://twitter.com/pgeekologyAnthony's Twitter: https://twitter.com/odysseyswowDakota's Twitter: https://twitter.com/geekritique_dakInstagram:https://instagram.com/projectgeekology?igshid=1v0sits7ipq9yYouTube:https://www.youtube.com/@projectgeekologyGeekritique (Dakota):https://www.youtube.com/channel/UCBwciIqOoHwIx_uXtYTSEbASupport the show

"Percy...all beans with a little frank but he gets the job done."Hey Little Paulsters! Your hosts, Jeff Macanovich and Jaime Cavazos, welcome Beast back to drink some beers and watch the first half of WWF Survivor Series 1997. Notwithstanding that, the old men kick off the show by (once again) yelling at the cloud that is modern professional wrestling, Beast airs some fantasy football grievances and the guys add a radio morning show to the canon.The guys enjoyed beers from Miller Brewing Company, Lagunitas Brewing Company, Grupo Modelo, Buffalo Creek Brewing, New Holland Brewing and Garage Beer.New episodes drop every other Tuesday morning and follow the show @WorkTheArmPod, on Twitter, Instagram, Blue Sky and (I guess) Threads.Check out our merch from the mind of Starman here: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠T-Shirts by Starman's Podcasting Buddies | TeePublic⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Grab something with the Work The Arm logo here: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠T-Shirts by WorkTheArm | TeePublic⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Wind and Water, Hearth and Home, All beneath the blue sky dome,When the crying gulls have flown, Wind and Water, bring me homeCW: ThalassophobiaDeath/dyingViolenceShipwreckFireThunder/lightningMentions/Discussions of: Harm to animals, Drowning, Poison, AlcoholSFX: Knives being sharpened, Cannon fire, Created by Lou Sutcliffe and Daisy McNamaraTranscript is available HERE: https://cytochromehear.wordpress.com/home/eelers-choice/eelers-choice-episode-12/Daisy's book: https://daisymcnamara.com#gospelofhavennovelWriter, composer and sound designer - Lou SutcliffeProducer and dialogue editor - Daisy McNamara.Directed by Lou Sutcliffe and Daisy McNamara.Script editing was by Ken Cumberlidge.Our executive producer was Pongo.Nama Fishercliff - Lindsey C. Prin Whitchanter - Caroline Orejuela. Merry Whitechanter - Tanja Milojevic. Blethin Stormsinger - David Ault. Pugill Flenserly - B. Narr. Aderyn Tanner - Leon Egan. Spartina Sawbones - Interiority. Acaster Selvage - Rhys Lawton. Moryana Whitechanter - Erika Sanderson. Beyin Ossificer - Kale Brown. Ned Sharktackle - Meg Molloy-Tuten.Opochtli Pulpodore - Diego HerreraMeredith Redeland - J.E. Haywood. Selachia - Hera Alexander Elasmo - Jamie Petronis.Lir Fishercliff - William WellmanSistra - Jessica Law. Bone Creature - Fay Roberts. Ran Stormsinger - Rae LundbergWith additional voices by Lauren Oakley and Jessica LawOur theme for this episode, “When I Am Gone” was written by Lou Sutcliffe and sung by Diego Herrera, Elijah Harper, Derrick Valen, Jessica Law and Lou Sutcliffe.We would like to thank the following crowdfund backers for their support: Sarah Vincent, Susan Hance, Aimleo17, MerelyMatt, Aarlone, Mike Fielding, Michael Hudson, KyokoNyan, Siobhan Thomas, Audrey Martin, Ella Watts, Robin Johnson, Nepenthe Wang, Francesca Mylod-Ford, Alexandra Pal, Pine Gonzalez, Rowan Ash, Rowan van Grinsven, Jon Ware, Kale Brown, Sue R, Reuben Eadon, Ruth Beebe, Percy, Kim Khavelund, Hannah Brown, Nicole Hislop, Jack McDonald, Josh Burgess, Rowan Blue, Felix Cosm, Just Jenah, Bee Allen, Naem D. Chouinard, Anja Myers, Niamh Lynn-Devere, Devin from the Dead West, Ben Hamlin, Mark Nixon, Leon Egan, Tom Borowski, Pen Toll, Liz Lynch, Helen Sears, Annette McArdle, Scott Paladin, Jack Fulmin, Elizabeth Bonnell, Candace Brednow, Sera Darland, Libby Thomas, Corrie P, Aliyah Ingman, Amy Crossway, Jem Hawes, Doodles v. de Castro, Katherine Nickerson, Nishka Corey and Reag Coster.A production of Cytochrome Hear and Eelsong StudiosOur Social Media: The Website Formerly Known As Twitter: https://twitter.com/eelerschoiceTumblr: https://www.tumblr.com/eelerschoice Bluesky: https://bsky.app/profile/eelerschoice.bsky.socialWebsite: https://cytochromehear.wordpress.com/home/eelers-choice/ Hosted on Acast. See acast.com/privacy for more information.

Send us Fan MailEpisode 271 – The Beast of Brotonne Forest | William Marshal Hunts a Medieval WerewolfFreshly knighted, William Marshal, Gervais, and the flamboyant Percy of Northumberland travel into the ancient Brotonne Forest after reports of a terrifying beast killing villagers in medieval Normandy.What begins as a simple hunt soon becomes something far darker.As the villagers clear centuries-old woodland in the name of progress, Fenrir senses something ancient awakening beneath the forest. A mysterious child carries an impossible acorn from a tree that should never bear fruit again, while strange tracks reveal that whatever stalks Brotonne Forest is no ordinary wolf.Then Fenrir discovers something he believed impossible.A member of his own ancient wolf family still survives.This dark fantasy episode blends medieval history, supernatural horror, werewolf mythology, Norman France, folklore, and humour as William Marshal faces his first mission as a newly made knight.If you enjoy medieval fantasy, werewolves, historical fiction, supernatural mysteries, ancient forests, folklore, and long-form audio drama, this episode is for you.Written by Fenrir Thorvaldsen and Gregory Alexander-Sharp. New episodes weekly—join the pack!Support the show • Books in the universe available on Amazon • Private Facebook group for Lunatics.Books by Fenrir ThorvaldsenAuthors' page on Amazon.https://amzn.to/3OJkzD0The Werewolf's Story by Fenrir Thorvaldsenhttps://amzn.to/4aX18xP Books by Gregory Alexander-SharpAuthors' page on Amazonhttps://amzn.to/4cTtf3CIl Lupo by Gregory Alexander-Sharphttps://amzn.to/4aZyCvABuy us a coffee at this link right here:https://www.buymeacoffee.com/WerewolfwilGrendel Press, our horror genre partnerThe best indie house publishers of horror in the blooming worldhttps://grendelpress.com/Grendel's very own cool Podcast.https://grendelpress.com/sinister-soup. Join the Lunatics at the Private Facebook Group.Facebook Grouphttps://www.facebook.com/groups/werewolfthepodcast/Greg's X profile: @SempaiGregFenrir's X profile: @FenThorvaldsenWerewolf the Podcast X profile: @AWerewolfsStoryWilShop at Dead_End_Society on Vinted.https://www.vinted.co.uk/member/3159606835Intro partnership with Grendel Press.Intro partnership with Grendel Press.https://grendelpress.com/ Outro partnership with Grendel Press.https://grendelpress.com/Support the show

Things are heating up in Barry's Bay and someone's gonna get burned! In this episode of Previously On, Jillian and Claire break down Every Year After Episode 3, “Playing With Fire,” as the past and present begin mirroring each other in increasingly complicated ways.In honor of the episode title, we're counting down the Top 5 “We're Playing With Fire” moments including Percy and Sam sharing a bed, the jealousy-fueled bonfire kiss, and Percy getting dressed up for a totally casual 6 p.m. pierogi-making date.We also discuss Charlie and Chantal's roadside detour where we discover these two have more in common than they think. And we break down the surprise ending where Percy learns she's been named in Sue's will, and she'll have to stick around for the reading...THE DRAMA!00:00 Reenactment "Sam got hot"00:53 Ice cream lick03:41 Intro to pod04:59 Ep 3 Recap06:15 Top 5 Playing with Fire Moments06:33 Sam and Percy09:32 Sharing bed18:38 Charlie and Delilah23:07 Percy bonfire kiss31:33 Almost kiss39:14 Will reading42:01 Passport probsThank you to Matt Buechele (@mattbooshell) for creating our new theme song. You can listen to "Sunscreen" on Spotify: https://open.spotify.com/artist/1gFHHF3QyQxjbbKXV3qLu9Buy our merch: ⁠https://www.etsy.com/shop/PreviouslyOnTeenTV⁠Follow Previously On Teen TV on Instagram: ⁠⁠https://www.instagram.com/previouslyon_teentv/Follow Previously On Teen TV on TikTok: ⁠⁠https://www.tiktok.com/@previouslyon_teentv⁠⁠Subscribe to our YouTube: ⁠⁠https://www.youtube.com/channel/UCe2lgvvZGKMrQ8v24FmDdWQ?sub_confirmation=1⁠

durée : 00:59:23 - par : Nathalie Piolé - La playlist jazz de Nathalie Piolé. - équipe : Emmanuelle Lacaze, Fabien Fleurat Vous aimez ce podcast ? Pour écouter tous les épisodes sans limite, rendez-vous sur Radio France

Percy es un pingüino alegre, divertido y lleno de ocurrencias. Pero mientras él disfruta haciendo reír a todos. Sus compañeros lo consideran demasiado inquieto y deciden dejarlo de lado. Un hermoso cuento que nos recuerda que cada persona tiene cualidades únicas y que nuestras diferencias también enriquecen a quienes nos rodean.

Bishop Tony Percy says in the 1st reading Solomon responds to God's offer asking not for wealth or power, but for a discerning heart to distinguish good from evil, modelling true prudence, humility and wisdom. Christians are encouraged to imitate Solomon by praying for wisdom, cultivating prudence, and allowing God to guide our decisions

Send us Fan MailWilliam Marshal finally earns the honour he has spent his entire life fighting for.After surviving brutal medieval warfare, captivity, and impossible horrors, William Marshal returns to Château de Tancarville alongside Sir Gervais and the flamboyant Percy of Northumberland.Before Guillaume de Tancarville, William's courage is recognised, and he is formally knighted, becoming Sir William Marshal.But there is little time to celebrate.Reports emerge from the ancient Forest of Brotonne of villagers disappearing and armed men being slaughtered by what locals believe is a werewolf.William, Gervais and Percy receive their first mission together as knights: hunt the beast and bring back its head.Yet Fenrir, William's ancient wolf companion, recognises the forest immediately—and for the first time in centuries, he is genuinely afraid.This episode blends real medieval history, Norman France, historical fiction, Arthurian atmosphere, dark fantasy, werewolf mythology, humour and emotional character development into one of the most important chapters of the series.Perfect for fans of Bernard Cornwell, The Last Kingdom, Game of Thrones, medieval history, historical fantasy, dark fantasy and supernatural audio dramas.Written by Fenrir Thorvaldsen and Gregory Alexander-Sharp. New episodes weekly—join the pack!Support the show • Books in the universe available on Amazon • Private Facebook group for Lunatics.Books by Fenrir ThorvaldsenAuthors' page on Amazon.https://amzn.to/3OJkzD0The Werewolf's Story by Fenrir Thorvaldsenhttps://amzn.to/4aX18xP Books by Gregory Alexander-SharpAuthors' page on Amazonhttps://amzn.to/4cTtf3CIl Lupo by Gregory Alexander-Sharphttps://amzn.to/4aZyCvABuy us a coffee at this link right here:https://www.buymeacoffee.com/WerewolfwilGrendel Press, our horror genre partnerThe best indie house publishers of horror in the blooming worldhttps://grendelpress.com/Grendel's very own cool Podcast.https://grendelpress.com/sinister-soup. Join the Lunatics at the Private Facebook Group.Facebook Grouphttps://www.facebook.com/groups/werewolfthepodcast/Greg's X profile: @SempaiGregFenrir's X profile: @FenThorvaldsenWerewolf the Podcast X profile: @AWerewolfsStoryWilIntro partnership with Grendel Press.https://grendelpress.com/ Outro partnership with Grendel Press.https://grendelpress.com/Support the show

Dan Bardell is live to react to Jacob Tanswell's reports on "The Athletic" that Chelsea's Alejandro Garnacho and Nicolas Jackson are of interest to Aston Villa.Dan also reacts to John Percy's report in "The Telegraph" that there may be further sales. Sponsored by Luke 1977.com. Use code 'TVV20' at checkout for 20% off.

Bishop Tony Percy says that when we do not know how to pray, the Holy Spirit prays within us, interceding for us in our weakness when we lack words. Offering our hurt to the Holy Spirit enables Him to transform injury into compassion and pain into intercessory prayer

Send us Fan MailWilliam Marshal's darkest secret survives another day.After a night of bloodshed and revelation, William and Sir Gervais ride toward Normandy carrying a truth neither man dares speak aloud. Gervais has seen something impossible — a gigantic black werewolf tearing through armed soldiers — but refuses to force his friend to confess what he truly is.Before they can reach the Château de Tancarville, a flamboyant young noble arrives with trumpets, banners, flower petals and enough titles to exhaust a monastery: Percy of Northumberland.What begins as a ridiculous medieval reunion becomes deadly when a supposedly dead crossbowman rises from the battlefield and fires at William Marshal. In a single heartbeat, Percy throws himself from his horse and tackles William clear of the bolt, saving his life.This episode of Werewolf the Podcast: A Serial (Killer) Drama combines medieval history, Norman knights, supernatural horror, dark fantasy and the growing brotherhood between William Marshal, Gervais and Percy.Featuring: William Marshal • Percy of Northumberland • Sir Gervais • Fenrir the wolf soul • Medieval warfare • Crossbow ambush • Werewolf mythology • Norman England • Historical fantasy • Horror audio drama.Written by Fenrir Thorvaldsen and Gregory Alexander-Sharp. New episodes weekly—join the pack!Support the show • Books in the universe available on Amazon • Private Facebook group for Lunatics.Books by Fenrir ThorvaldsenAuthors' page on Amazon.https://amzn.to/3OJkzD0The Werewolf's Story by Fenrir Thorvaldsenhttps://amzn.to/4aX18xP Books by Gregory Alexander-SharpAuthors' page on Amazonhttps://amzn.to/4cTtf3CIl Lupo by Gregory Alexander-Sharphttps://amzn.to/4aZyCvABuy us a coffee at this link right here:https://www.buymeacoffee.com/WerewolfwilGrendel Press, our horror genre partnerThe best indie house publishers of horror in the blooming worldhttps://grendelpress.com/Grendel's very own cool Podcast.https://grendelpress.com/sinister-soup. Join the Lunatics at the Private Facebook Group.Facebook Grouphttps://www.facebook.com/groups/werewolfthepodcast/Greg's X profile: @SempaiGregFenrir's X profile: @FenThorvaldsenWerewolf the Podcast X profile: @AWerewolfsStoryWilIntro partnership with Grendel Press.https://grendelpress.com/ Outro partnership with Grendel Press.https://grendelpress.com/Support the show

Tasting Notes Include: Forcing Tiny Tony to Grow Up Fast, Percival being Immortal, but not Invulnerable, Archie being a General in the War for Good and Evil, Percival can teleport, but his clothes can't, Powers get turned on their users, Percy gets got by the Devil, A Comet is coming to crash into Riverdale and also the World.   So Sorry about how long it took to get these episodes out. Life is dark and full of terrors. Say hi on Social Media because we love to hear from you!   Our Socials: @Riverdale Runs on Bluesky and riverdale_runs on Insta Our Email: arrtipod@gmail.com

The verdict is in!  Check out if this was good spice or bad writing.  Both?  Neither? Title: For Whom the Belle TollsAuthor: Jaysea LynnReviewed by: Percy, Daisy, Aris Created by the Podcast Team at the Harris County Public Library.www.hcpl.netPodcast Team Members include: Beth Krippel, John Harbaugh, Mary Mink, Dylan Smith, Sadina Shawver, Alinda Mac, John Schaffer, Jennifer Finch, Katelyn Helberg, Darcy Casavant, Darla Pruitt and Nancy Hu 

Guess who's baaaaack??? It's us (hiiiii). We've returned from our hiatus and what better way to celebrate than to turn our focus to that ol' party animal Percival (middle name redacted) Weasley? Did that textbook middle child really get a fair representation in the series? What is the narrative purpose of the series of events surrounding Percy's return in Book 7? And which Wilson is headed to an ashram? Support the showSupport FFH on Patreon: patreon.com/thefoxandthefoxhoundFollow us!IG: @thefoxandthefoxhoundTikTok: @thefoxandthefoxhound

Booktalks Podcast Episode 107 reviews Every Summer After by Carley Fortune before watching the TV adaptation.This is Part 1 of our Every Summer After series! We discuss Percy and Sam's relationship, Charlie, the alternating timelines, our favorite moments, what worked, what didn't, and whether the TV show has a chance of living up to the book.⚠️ Full spoilers for the novel.Next week we'll be back with Part 2 after we've watched the TV adaptation to compare the show with the book.Follow us:Instagram: @booktalkspodcastTikTok: @booktalkspodcastYouTube: @book_talks_podcastIf you enjoyed this episode, please follow the podcast and leave us a rating—it really helps other readers discover Booktalks Podcast!

Wrath of the Triple Goddess, ch. 16 to 20 This week on Unwise Girls, we discuss abusive doggy dynamics, a confusing pandemic timeline, Percy's lack of grasp on his own personal history, Grover's double life, tragic yaoi meters exploding, more Rick Old Man moments, and epic business fails. Come back next week for Wrath of the Triple Goddess, ch. 21 to 25! Check out our Patreon! (https://www.patreon.com/unwisegirls) Follow the show (bsky.app/profile/unwisegirls.bsky.social) Join our Discord! (https://discord.gg/XnhhwzKQ8d) Hosted by Jacqueline (https://twitter.com/swampduchess) and Jane (https://twitter.com/janeyshivers). Edited by Jacqueline. Cover art by Vera (https://twitter.com/Innsmouth_Inn). Intro/outro: "Super Mariocean" by spacepony (https://ocremix.org/remix/OCR01147) This podcast is powered by Pinecast.

So has the book delivered the spice?  Find out in this next installment. Title: For Whom the Belle TollsAuthor: Jaysea LynnReviewed by: Percy, Daisy, Aris Created by the Podcast Team at the Harris County Public Library.www.hcpl.netPodcast Team Members include: Beth Krippel, John Harbaugh, Mary Mink, Dylan Smith, Sadina Shawver, Alinda Mac, John Schaffer, Jennifer Finch, Katelyn Helberg, Darcy Casavant, Darla Pruitt and Nancy Hu 

Presented by Everett 3 on 3 Seattle basketball reporter Percy Allen joins the Iconic Sonics Podcast for a conversation that spans the past, present and future of hoops in the Pacific Northwest. We look back at the 2008 NBA Draft, the final draft in SuperSonics history, and revisit the selection of Russell Westbrook with the fourth overall pick. Percy also shares his perspective on the Sonics leaving Seattle 18 years ago, what that moment was like to cover and how the city has continued to rally around basketball ever since. We also dive into the latest around the Seattle Storm, the local basketball scene and where Seattle hoops stands today. This episode is presented by Everett 3 on 3, one of the Northwest's premier basketball tournaments. Grab your friends, build your squad and sign up to compete! Follow us on social: Instagram: @iconic_sonics X: @iconic_sonics TikTok: @iconic_sonics  

TODAY ON THE ROBERT SCOTT BELL SHOW: The Case Against Scientific Retraction, Annalisa Percy, Global Natural Health Solutions, Eating disorders, Natural Medicine is Powerful, From Healing to Harm, Morley Robbins, Cu-re, Root Cause Protocol, Guarea Trichiloides, and MORE! https://robertscottbell.com/the-case-against-scientific-retraction-annalisa-percy-jama-natural-medicine-is-powerful-from-healing-to-harm-morley-robbins-cu-re-root-cause-protocol-guarea-trichiloides-and-more/ Purpose and Character The use of copyrighted material on the website is for non-commercial, educational purposes, and is intended to provide benefit to the public through information, critique, teaching, scholarship, or research. Nature of Copyrighted Material Weensure that the copyrighted material used is for supplementary and illustrative purposes and that it contributes significantly to the user's understanding of the content in a non-detrimental way to the commercial value of the original content. Amount and Substantiality Our website uses only the necessary amount of copyrighted material to achieve the intended purpose and does not substitute for the original market of the copyrighted works. Effect on Market Value The use of copyrighted material on our website does not in any way diminish or affect the market value of the original work. We believe that our use constitutes a 'fair use' of any such copyrighted material as provided for in section 107 of the U.S. Copyright Law. If you believe that any content on the website violates your copyright, please contact us providing the necessary information, and we will take appropriate action to address your concern.

Reading Room Radio hosts the team of Good Spice, Bad Writing starting this mini series.Title: For Whom the Belle TollsAuthor: Jaysea LynnReviewed by: Percy, Daisy, Aris  Created by the Podcast Team at the Harris County Public Library.www.hcpl.netPodcast Team Members include: Beth Krippel, John Harbaugh, Mary Mink, Dylan Smith, Sadina Shawver, Alinda Mac, John Schaffer, Jennifer Finch, Katelyn Helberg, Darcy Casavant, Darla Pruitt and Nancy Hu 

Content note: This episode includes discussion of gun violence, homicide, and the loss of loved ones, including children, which may be distressing for some listeners. Listener discretion is advised. In this episode of Philanthropy Speaks, we mark Gun Violence Awareness Month with a candid conversation about community safety in Flint and Genesee County. Host Moses Bingham, Director of Strategic Initiatives at the Community Foundation of Greater Flint, sits down with Dr. Kenyetta Dotson and Percy Glover, co-chairs of the Community Safety Collaborative (CSC).Dotson, founder of WOW Outreach and community engagement lead at Michigan State University's C.S. Mott Department of Public Health, and Glover, a Flint native, national speaker on jail and judicial reform, and founder of Fair Voting Alliance, bring lived experience and real solutions to the table.Tune in to learn why gun violence is a public health crisis, how community violence intervention (CVI) saves both lives and dollars, and why no act of care is ever too small. From mentoring young people to the CSC's community safety calendar and resource dashboard, discover how Flint residents are working together to prevent gun violence and build a safer community.Learn more about the Community Foundation of Greater Flint and the Community Safety Collaborative at https://www.cfgf.org/impact/community-safety-collaborative.Support the show

This episode, concept illustrator Fernando Acosta is here to talk all things Disney+ Percy Jackson and the Olympians! Discussion topics may include: finding the right look for Thalia's tree, the process behind concept art, illustrating Polyphemus' island, the brilliance of Production Designer Dan Hennah, and taking inspiration from the books as you go.Check out Fernando's work on Percy & more here: https://www.facosta.com/#/percy-jackson/Check us out on Patreon to submit questions for future interviews and to get exclusive episodes, cut material, art previews, and more! https://www.patreon.com/MonsterDonutPodcastHave a question? Want to contribute your own analysis? Feel like arguing? Email monsterdonutpodcast@gmail.com.Come say hi and check out the sketches Phoebe made this episode on Twitter, Instagram, or TikTok! @PJOPod on all platforms.Find our new Monster Donut merch here!: https://www.redbubble.com/people/monsterdonut/explore.More information on the show can be found at https://www.monsterdonutpodcast.com/THEME SONG:"The Mask of Sorokin," music and arrangement by Dan CordeGuitars - Dan CordeBass - Quinten MetkeDrums - Todd CummingsRecorded, mixed, & mastered by Todd CummingsOUTRO MUSIC:"Shadow Run," music and arrangement by Dan CordeGuitars - Dan CordeBass - Quinten MetkeDrums - Todd CummingsRecorded, mixed, & mastered by Todd Cummings Hosted on Acast. See acast.com/privacy for more information.

Mary & Blake recap and give reaction to Outlander Season 8 Episode 9, "Pharos." In this episode, we discuss why Lord John Grey finally gets the emotional spotlight, why the Jamie and Lord John chess scene may be the best payoff of Season 8, and why "Pharos" works as both a literal lighthouse clue and a symbolic title for the episode. We also get into Richardson's reveal as a time traveler, Claire letting him go, Lord John shooting him anyway, Percy's betrayal, William's two-fathers reckoning, Bree giving birth, Claire writing "our story," and whether this episode actually works as the penultimate chapter of the entire series. Plus, Mary brings the heat on Under The Tuscan Sun, cannoli, cribbage, Kelly Clarkson, mouth farts, and why Lord John walking away from Percy may be his Miss Independent moment. In this episode, you'll hear: Why "Pharos" is a strong episode title How Diana Gabaldon's writing shapes the Lord John material Why the chess scene between Jamie and Lord John works so well Whether Percy's betrayal and death hit hard enough Why Richardson's plan feels underbuilt Claire's hope that history can still change Lord John as the emotional engine of the episode William's complicated love for both Jamie and Lord John Whether "Pharos" gives enough momentum going into the finale Support the show and get bonus content at JoinTheNerdClan.com. Follow Mary & Blake at MaryandBlake.com, YouTube, Facebook, and Instagram. Slàinte Mhath.

We're back in Barry's Bay! In this episode of Previously On, Jillian and Claire break down Every Year After Episode 2, "Young Blood." The past refuses to stay buried as Percy finds herself pulled deeper into old memories, old feelings, and old relationships she may never have truly left behind. From sneaking back into The Tavern to reconnecting with Sam over childhood memories, this episode makes one thing very clear: nobody has moved on.We're discussing the growing tension between Percy and Sam, Delilah stirring the pot with Truth or Dare, and why Barry's Bay seems determined to drag everyone back to who they used to be. Plus, we dive into our Top 5 "Nobody Has Moved On" Moments and talk about all the signs that these characters are still haunted by their pasts.If you're already screaming at these characters to communicate, congratulations, you've officially settled into life in Barry's Bay. We're unpacking all the tension, questionable decisions, and emotional damage one episode at a time.00:00 Reenactment00:57 Intro to pod03:26 Ep 2 "Young Blood" recap03:59 Truth or dare05:56 Top 5 Nobody's Moved On06:41 Percy breaks into the Tavern09:12 Delilah hooks up with Charlie14:12 Percy finds mixtape22:10 Sam's horror movies28:13 Percy cries and calls mom33:46 Mom's a lesbian?37:37 Sam at the doorThank you to Matt Buechele (@mattbooshell) for creating our new theme song. You can listen to "Sunscreen" on Spotify: https://open.spotify.com/artist/1gFHHF3QyQxjbbKXV3qLu9Buy our merch: ⁠https://www.etsy.com/shop/PreviouslyOnTeenTV⁠Follow Previously On Teen TV on Instagram: ⁠⁠https://www.instagram.com/previouslyon_teentv/Follow Previously On Teen TV on TikTok: ⁠⁠https://www.tiktok.com/@previouslyon_teentv⁠⁠Subscribe to our YouTube: ⁠⁠https://www.youtube.com/channel/UCe2lgvvZGKMrQ8v24FmDdWQ?sub_confirmation=1⁠

What if everything you were taught about demons, deliverance, and spiritual warfare was incomplete — or worse, intentionally left out?Percy Burns is a Presbyterian pastor and deliverance minister with over 50 years of experience who has ministered to thousands — and it all started the night Derek Prince nearly got him kicked out of his denomination. Percy believes the church has been silent on one of the most critical areas of the Christian life for far too long.In this episode:⇨ How Percy received deliverance and was filled with the Holy Spirit in the same week⇨ Why the church has suppressed deliverance ministry for generations⇨ Whether Christians can have demons — and what scripture actually says⇨ How generational spirits enter family lines and what to do about it⇨ What a real deliverance session looks like from start to finish⇨ How to minister deliverance to your own children and loved ones⇨ Why demonic oppression may be behind physical symptoms you can't explain⇨ How to keep demons from coming back after deliveranceIf you have ever felt like something was holding you back, oppressing you, or attacking your family — this episode is for you.

"He's Percying as hard as anybody can Percy. Nobody can Percy that much harder than Percy can Percy right now because Percy is Percying as much as Percy can possibly Percy."Hey Little Paulsters! Your hosts, Jeff Macanovich and Jaime Cavazos, welcome Beast back to drink some beers and watch the second half of WWF In Your House 21: Unforgiven 1998. Notwithstanding that, Jaime and Beast serve up a hell of an intro to the festivities, Beast peruses Sunny's IMDB and Goth Mom Terri gets even more backstory.The guys enjoyed beers from Miller Brewing Company, Goose Island Beer Co., Sierra Nevada Brewing Co. and El Segundo Brewing Company.New episodes drop every other Tuesday morning and follow the show @WorkTheArmPod, on Twitter, Instagram, Blue Sky and (I guess) Threads.Check out our merch from the mind of Starman here: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠T-Shirts by Starman's Podcasting Buddies | TeePublic⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Grab something with the Work The Arm logo here: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠T-Shirts by WorkTheArm | TeePublic⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

"A second chance at first love." Welcome to Barry's Bay!In this episode of Previously On, Jillian is joined by fellow yearner Claire Wojciechowski to break down the premiere episode of Prime Video's Every Year After, which they were lucky enough to watch at the Tribeca Film Festival.From Percy's emotional return to Barry's Bay to the immediate tension between Percy, Sam, and Charlie, the series wastes no time reminding us why Carley Fortune's beloved book "Every Summer After" has captured so many hearts. We discuss our first impressions of the adaptation, whether it lived up to the book, and why Barry's Bay might be the most beautiful TV setting of the summer.Plus, we're counting down our Top 5 "Take Me to Barry's Bay" Moments, including the Bay Breeze Motel, Sue's famous perogies, Delilah's mysterious social network, and the awkward, but yearning-filled reunion between Sam and Percy that already has us emotionally invested.We also share a few highlights from the cast Q&A and discuss why this show feels poised to become the next emotionally devastating summer obsession. If Barry's Bay has already worked its magic on you, we're breaking down everything that made this first episode so special!00:00 Intro to pod00:25 Every Year After premiere02:18 Book adaptation06:08 Top 5 Barry's Bay06:22 Bay Breeze Motel Room12:25 Tavern Pierogies17:59 Delilah's social network22:59 Brothers Sam and Charlie31:34 Percy, Sam, and Charlie37:38 Percy and Sam Reunite Ending41:52 Taylor46:00 Cast46:44 Carley Fortune and Season 2Thank you to Matt Buechele (@mattbooshell) for creating our new theme song. You can listen to "Sunscreen" on Spotify: https://open.spotify.com/artist/1gFHHF3QyQxjbbKXV3qLu9Buy our merch: ⁠https://www.etsy.com/shop/PreviouslyOnTeenTV⁠Follow Previously On Teen TV on Instagram: ⁠⁠https://www.instagram.com/previouslyon_teentv/Follow Previously On Teen TV on TikTok: ⁠⁠https://www.tiktok.com/@previouslyon_teentv⁠⁠Subscribe to our YouTube: ⁠⁠https://www.youtube.com/channel/UCe2lgvvZGKMrQ8v24FmDdWQ?sub_confirmation=1⁠

Well, we thought we were getting back to full strength, but the podcast curse strikes again! This week, Tash is missing in action lol, but the show must go on! Becky is back behind the mic to join Emma, which means we still have two absolutely wild stories lined up to keep you up at night.First up, Becky takes us to August 2003, when a silent, invisible monster crept across France. What started as a beautiful summer turned into the deadliest weather event in European history—the infamous 2003 Heat Wave (La Canicule). This wasn't just a couple of sweaty days; it was an unprecedented catastrophe that caught the nation entirely off guard, overwhelming hospitals, breaking temperature records, and claiming over 14,000 lives in France alone. Becky dives into the dark, heartbreaking reality of what happens when the climate turns deadly, institutions fail, and the weather itself becomes a serial killer.Then, Emma takes the reins for Part Two of The Dagg Demon—and no, we aren't at the end just yet, that's coming next week! This week, the plot thickens as we finally meet the man, the myth, the legend: Percy Woodcock. As a local investigator and a man of faith, Percy steps right into the middle of the 1889 Quebec farmhouse chaos to figure out if they are dealing with a massive hoax or a genuine, terrifying entity. Emma breaks down exactly what happened when Percy tried to communicate with the voice, and the chilling answers he got back.

In this episode of Reading With Your Kids, Jed welcomes back Tim Wright from Arizona to celebrate book five in The Adventures of Toby Baxter series, Revenge of the River Home, Rutabagas. Jed shares the exciting news that this latest installment has, like the first four books, been named a Reading With Your Kids Certified Great Read, praising its powerful emotional core and hopeful message. Tim explains how a long-running family joke about "fried rutabagas" inspired the title, and how he used that playful seed to explore serious themes like anger, distraction, and hope. Set in the magical land of River Home, Toby's adventures function as a year-long rite of passage for a 13-year-old boy who doesn't like reading, yet finds himself literally living inside a story. Each book features a compass word—heroism, goodness, wisdom, love, hope—that guides Toby's growth. Book five becomes the "fulcrum" for an overarching arc that will carry through books six and seven, touching deeply on social media, AI, and how kids can stay hopeful in an often angry, screen-saturated world. Tim and Jed also talk about modern parenting, the loss of meaningful rites of passage, and the powerful role of grandparents and intergenerational relationships—especially Tim's special bond with his five grandkids, who appear as characters in the series. Later in the episode, Jed chats with author and Yorkie breeder Jane Lumen about her picture book Monkey Mae, Noble and Percy's Farm of Strength, a warm, dog-centered story that gently teaches kids about acceptance, inclusion, and differences, inspired by her life as a mom of special needs children.

Before he became a familiar face on screen, appearing in over 70 films like 'The Bridge on the River Kwai', 'The Cockleshell Heroes', 'The Guns of Navarone' and 'The Wild Geese', Percy Herbert survived one of the most brutal chapters of the Second World War. Captured during the fall of Singapore in 1942, he endured life as a prisoner of war, facing starvation, violence, and witnessing events like the Alexandra Hospital massacre. Those experiences would stay with him and later shape the performances that made his name. His story is told in his autobiography, Time Will Pass Johnny, a remarkable account that traces his journey from the camps of the Far East to a long and successful acting career. To talk about her father's life, I'm joined by Katrina Wood.   Patreonpatreon.com/ww2podcast