Podcasts about Smallville

Hey, it's almost time for Dragon Con! Nerds, geeks, and weirdos from around the globe shall descend upon Atlanta for a long weekend of mirth, merriment, antics, hijinks, and perhaps even a shenanigan or two. And this week our Dragon Con coverage begins with a preview of what you can expect to find there. Including: Stars from Land of the Lost, Battlestar Galactica, Firefly, Smallville, and The Jeffersons! (We might just be dreaming about that last one.) The 120 Minutes dance party! The Sc-Fi Explosion video show! Very long lines! Bunny costumes! Puppets! Teeth! (Teeth? Really? Yes. Teeth.) And lots more miscellaneous nerdity. We even address the question of whether or not this is Dragon Con's 40th anniversary. (It's not. There, that was easy.) Next week: We'll reveal exactly what we're doing at Dragon Con. (Mostly silly things. Okay, that was easy too.) The Flopcast website! The ESO Network! The Flopcast on Facebook! The Flopcast on Instagram! The Flopcast on Bluesky! The Flopcast on Mastadon! Please rate and review The Flopcast on Apple Podcasts! Email: info@flopcast.net Our music is by The Sponge Awareness Foundation! This week's promo: Earth Station Trek!  

Send us a text or a voicemailA TikTok film review superstar must survive an evening trapped in a frostbitten studio with a group of drunken applejack salesmen who are trying to become North America's greatest podcast by killing one hundred bottles of Zima! On Episode 731 of Trick or Treat Radio we are joined by Creepygirl for our August Patreon Takeover! Creepygirl has chosen the films Borderline (2025) and Hundreds of Beavers for us to discuss! We also pay tribute to the late great Screaming Mad George, debate the difference between real and fake monsters, and reflect on the charlatanry of the Warrens. So grab your cold weather gear to survive the frozen frontier, make sure to hire a fully capable bodyguard, and strap on for the world's most dangerous podcast!Stuff we talk about: The difference between Monsters and MONSTERS, Ed Gein, Jeffrey Dahmer, Lizzie Borden, serial killers, Rebecca Hall, Sarah Paulson, Charlize Theron, Christina Ricci, Creepygirl Movie Reviews, RIP Screaming Mad George, Freaked, Society, A Nightmare on Elm St 3: Dream Warriors, Faust, surrealistic special FX, Silent Night Deadly Night 4, Predator, Guyver, Poltergeist II: The Other Side, Screaming Jay Hawkins, Heroes, RIP Hayden Panettiere, Kurando Mitsutake, Zachary Quinto, The Beastmaster, Teaching Mrs. Tingle, Universal Soldier: The Return, The Erotic Rites of Countess Dracula, The Exorcist: The Beginning, Piranha 3D, Vampire High, Misha Collins, Amy Adams, Smallville, Charmed, James Marsters, Peter Horton, Brimstone, Fade to Black, Mickey Rourke, 1941, John Noble, Fringe, Ray Wise, Sylvester McCoy, The Blood On Satan's Claw, Tom Duggan, Frankenstein (1970), The Giant Behemoth, The Mummy's Shroud, H.P. Lovecraft, Ed and Lorraine Warren, being superstitious, Matt Rife, The Warren Museum, Ghostbusters is a documentary, The Outsiders, Grave Encounters, Amityville, Borderline, Samara Weaving, Jimmy Warden, Leonardo Dicaprio, Ray Nicholson, Eric Dane, Jimmie Fails, Inde Navarrette, Heat 2, X-Men, stalking is bad mmkay, Margot Robbie, Colleen Camp, Clue, Police Academy, Whalefall, Brian Duffield, Junior, Gary Gotzman, Belial, Basket Case, Hundreds of Beavers, Mike Cheslik, Ryland Brickson Cole Tews, Lake Michigan Monsters, El Topo, Forbidden Zone, Sin City, The Mad Painter, Paul Benedict, Wizards, Cannibal: The Musical, Chess King, Buster Keaton, Vinegar Syndrome, Multiplicity, Michael Keaton, Deep Roy, Butt Boy, Applejack, Richard Elfman, Hostel, Rocky Horror Picture Show, Batgirl, Coyote Vs. Acme, Blood Shine, and Faces of Breast.Support us on Patreon: https://www.patreon.com/trickortreatradioJoin our Discord Community: discord.trickortreatradio.comSend Email/Voicemail: mailto:podcast@trickortreatradio.comVisit our website: http://trickortreatradio.comStart your own podcast: https://www.buzzsprout.com/?referrer_id=386Use our Amazon link: http://amzn.to/2CTdZzKFB Group: http://www.facebook.com/groups/trickortreatradioTwitter: http://twitter.com/TrickTreatRadioFacebook: http://facebook.com/TrickOrTreatRadioYouTube: http://youtube.com/TrickOrTreatRadioInstagram: http://instagram.com/TrickorTreatRadioSupport the show

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

Clark & Lex 5ever

Sam Jones III (Smallville, Blue Mountain State) finally comes by and this one goes everywhere I hoped it would. We start with the Pete Ross days, meeting Tom Welling in the van, the chemistry read with Allison Mack, and the Seinfeld night a crowd chased us down the street. Then Sam opens all the way up about the one bad decision that sent him to prison, the DEA setup posing as the Mexican mafia, and the friend who walked free while Sam took time. He tells me about Brother Elam, the man who changed his life inside, the depression that nearly took him when Elam was gone, and the father who talked him back from the edge. Thank you to our sponsors: Thank you to our sponsors:

Buy Paul Anleitner's new book BASED ON A TRUE STORY: https://a.co/d/00Kb0R2a Philip Levens is a long-time writer, producer, and showrunner best known for his work on Smallville, Ascension, Knight Rider, and more. https://philiplevens.com/about-philip-levens Find out more about Goodmakers at: www.goodmakers.co 

Mikey & Jeremy watch S8E3 of Smallville, "Toxic". They discuss beards, origin stories, and love quadrilaterals. 

Kevin Miller, the author of The Crisis Companion (available August 2026 from TwoMorrows Publishing), joins the podcast to talk about his book, why he wanted to write it, and what impact the seminal DC Comics maxi-series has had on fandom and comics publishing. Then we talk about his other endeavors, including portraying Lex Luthor in Smallville, his comic book Meth, and other books he's written. Finally, we talk about his comic book collection and tracker app, The Comic Locker (listen to the end for a special offer from Kevin!). Links: Kevin Miller's website The Crisis Companion from TwoMorrows The Comic Locker Promo: Infinite Earths: A Guide to the DC Multiverse LBR Merch! Feedback! longboxreview@gmail.com 208-953-1841 Bluesky longboxreview.com Thanks for listening! episode 280

This week, Eric and Josh are joined by loyal Mayfair patron, and talented filmmaker, Nolan Tucker! Nolan's new film, Restless in the Dust, makes its World Premiere at the Mayfair the week of August 21! They also discuss: The Fablemans, The Evil Dead, The Texas Chain Saw Massacre, E.T., Smallville, movie ratings, Enter the Drag Dragon, Disclosure, Odd Burger, and more! They also mention the movies screening the week of Friday August 14 - Thursday August 20: The Invite, The Little Foxes, Obsessed, The Love Bug, and Saturday Night Sinema! They neglect to mention Mary Oliver: Saved by the Beauty of the World, and I Want Your Sex, which were booked after the podcast recording. You can always check up to the moment showtimes and Coming Soon movie listings at mayfairtheatre.ca.

In this episode of Culture and Consequence, Carmen and Andrea dive into the ongoing shift in political rhetoric across America and what many call "The Trump Effect."They unpack the recent political attacks surrounding Dr. Abdul El-Sayed following the Michigan primary, addressing how 9/11 continues to be weaponized as a political tool. The conversation touches on personal reflections, regional racial dynamics from Boston to Vermont, and the exhaustion of dealing with open, unmasked prejudice in modern politics.Plus, a lighter wrap-up on classic sci-fi and pop culture—including Andrea's attempt to sit through Stanley Kubrick's 2001: A Space Odyssey, a look back at Smallville, and a breakdown of political terminology.Topics Covered in This Episode:Dr. Abdul El-Sayed & Political Rhetoric: Unpacking xenophobia, the post-9/11 narrative, and weaponizing tragedy.The "Trump Effect": How public discourse and civility have shifted over the last decade.Personal & Regional Perspectives: Systemic racism, living through different eras, and community dynamics.Political Literacy: Distinguishing between socialism, democratic socialism, and progressivism.Pop Culture Wrap-Up: 2001: A Space Odyssey, Smallville, and classic cinema dynamics.Link to Carmen Talk about words politicians keep using wrong: https://www.buzzsprout.com/1777404/episodes/19585161-bakeries-star-trek-and-breaking-down-political-buzzwords.mp3?download=trueThank you for stopping by.  Please visit our website: All About The Joy and add, like and share.  You can now watch the livestream version of the show on YouTube at @CarmenLezeth You can also support AATJ by shopping at our STORE - Or by and buying us a coffee. We'd appreciate that greatly.  Also, if you want to find us anywhere on social media, please check out the link in bio page. Music By Geovane Bruno, Moments, 3481Editing by Team A-JHost, Carmen Lezeth DISCLAIMER:  As always, please do your own research and understand that the opinions in this podcast and livestream are meant for entertainment purposes only. States and other areas may have different rules and regulations governing certain aspects discussed in this podcast.  Nothing in our podcast or livestream is meant to be medical or legal advice. Please use common sense, and when in doubt, ask a professional for advice, assistance, help and guidance. 

Welcome back to the WCPE Book Club. This month, we are in for a treat from the great Alan Davis, with his take on a Justice League without Superman. Join us today for JLA: The Nail, a three-issue Elseworlds tale from 1998. Also joining us in the studio today to discuss this title is friend of the show Terry LaCaze. The Kents are driving into Smallville one night when a nail in the tire leaves them stuck, and keeps them from meeting up with a rocket carrying a baby from Krypton. What is the world like, and specifically, what is the Justice League like without a Superman to inspire them? Stick around to the very end to find out about next month's selection for WCPE Book Club. Cullen is taking a cue from the new Spider-Man movie with his choice of a D. C. comic. i  We would love to hear your comments on the show. Let us know what you've been reading or watching this week. Contact us on our website, Facebook, Instagram, or by email. We want to hear from you! As always, we are the Worst. Comic. Podcast. EVER! and we hope you enjoy the show. The Worst. Comic. Podcast. EVER! is proudly sponsored by Clint's Comics, 815 N Noland Road in Independence, Missouri. Whether it is new comics, trade paperbacks, action figures, statues, posters, or T-shirts, the friendly and knowledgeable staff can help you find exactly what you need. You should also know that Clint's Comics has the most extensive collection of back issues in the metro area. If you need to find a particular book to complete a title's run, head to Clint's or check out their website at clintscomics.com. Tell them that the Worst. Comic. Podcast. EVER! sent you.

You're the G.O.A.T. to our W.O.A.T.The official punctuation mark to the infamous award shows. Once again, can't thank the fans enough for getting us all the way here. So many awards, so many disagreements, so many tears and perverted jokes. Join us in part two of the last awards episode dedicated to the entire series of Smallville. LEAVE THE FIVE STARS DAMMIT!

Clark and Lois are finally starting to feel like the heart of Smallville, and “Echo” gives us everything we've been waiting for. In this episode of Going Back to Smallville, our Smallville Season 9 rewatch podcast and series retrospective, we're talking about Clark's temporary ability to read minds, the adorable chaos that comes from hearing Lois's unfiltered thoughts, and why their growing connection works so well. From maple donuts and a not-quite-date at a monster truck rally to Lois arriving in a gown after Clark stands her up, this episode understands exactly what makes these two special. We also break down Toyman's return, Oliver's heartbreaking downward spiral, and Clark realizing that saving his friends means noticing when they need him. We loved this one, but more than anything, we loved watching Clark and Lois move closer to becoming the couple we know they're meant to be.Support the show: https://patreon.com/hopefullyawesomeBecome a Member on Youtube: https://www.youtube.com/channel/UCHRvjz_pKP1Th5Y8ZIwFMtQ/joinCheck out our Merch! - https://hopefullyawesome.creator-spring.com/This video is NOT sponsored. Some product links are affiliate links which means if you buy something we'll receive a small commission.Mail to: Matt & Maggie - PO Box 3924, Kingsport TN, 37664, United StatesMatt & Maggie - 1001 N Eastman Road # 3924, Kingsport TN, 37664, United States

Brian is still in the grave, so Zach and Vince travel to Kansas for some Lana Lang weirdness.

A sample from our latest patrons-exclusive TVChat, wherein Cole and our long time friend and recurring guest Seqarts continue their retrospective on the 2000s superhero-monster-of-the-week-teen-melodrama Smallville.  Support us on Patreon if you'd like to hear the rest and other exclusive episodes!

It's Smallville: The Ultimate Season! This time we're going through the twenty second episodes of every season and by process of elimination determining the ultimate episode 22 of Smallville. And at the end, we recap the final results for The Ultimate Season!Zach is joined by Lance Laster from Always Hold On To Arrow, Matt Truex from Lois & Clark'd: The New Podcasts of Superman and Victoria Male.Check out Lance on Always Hold On To Arrow!Check out Matt's work including Lois & Clark'd: The New Podcasts of Superman at The Daily Knockoff!Check out Victoria's work on her website!Always Hold On To Smallville is brought you to by listeners like you. Special thanks to these Meteor Freaks on Patreon who's generous contributions help produce the podcast!Chris FuchsCory MooreIsaiah GoodridgeAtif SheikhJohn CurcioThomas NavenMarc-ids FoppenPatricia CarrilloRhythm ChameleonJim CrawfordKasey VachRouie HumphreyAlex HamiltonMatt DouglasDaniel CurielMeryl SmithTrevis HullAmy J.Mike FranzEvery/Day/AprilNathan MacKenzieSteve RogersMollie FicarellaJames LeeJason DavisPatrick BravoAlex RamseyTae TaeTina BJakeJacobJohn BobNathan RothacherDylan DiAntonioNick Ryan MagdozaEddie BissellNicholas FanslerJohn LongRuth Anne HamonTravis KillMike ThomasNeena JGordon BombayRajAlexander VerticchioJoey DienbergDJ DoenaDaryn KirschtJarrett GibbsAnthony AndersonKeith FaulsJames HartAnthony DesiatoCrystal CrossKirin KumarTroy LangloisPATREON: patreon.com/alwaysmallvilleTWITTER: twitter.com/alwaysmallvilleFACEBOOK: facebook.com/alwaysmallvilleEMAIL: alwaysmallville@gmail.comMatt Truex is a Warner Bros. Discovery employee. The views and opinions expressed in this podcast are his own and do not necessarily reflect the views or positions of Warner Bros. Discovery.

Most people think ranking the best DC movies and shows is about favorites, but what if I told you there's a hidden game-changing system that flips the entire hierarchy upside down? Imagine discovering that your absolute favorite might actually be in dead last, while the most underrated gems claim the top spots—this episode will blow your mind and challenge everything you thought you knew about superhero rankings. Dive deep into a wild, no-holds-barred ranking of DC's most iconic films, cartoons, and TV shows. We break down: the true greatness of Justice League Unlimited, the surprising placement of Batman: The Brave and the Bold, and how Batman Year One shocks as one of the top-tier masterpieces. You'll discover exactly where classics like Wonder Woman (2017), Joker (2019), and even Harley Quinn (2019–present) really land — and why the rankings might just be wrong! Every pick is a story, every placement a revelation—this is not your average list.We also uncover startling truths: why Batman Ninja is underrated, how Smallville and Lucifer revolutionized superhero TV, and which animated gems Hollywood forgot. Fail to listen, you risk missing out on hidden treasures—and the chance to see your favorite DC favorites in a whole new light. It's bold, emotional, and packed with surprises that will make you rethink what's possible in superhero storytelling. Perfect for superfans, casual viewers, and anyone craving a fresh perspective on DC's rich universe. This episode will leave you inspired to explore the overlooked, question the status quo, and maybe even re-rank your own favorites. Hit play—your new secret list awaits.

We're revisiting Smallville Season 9, Episode 3, “Rabid,” a horror-inspired rewatch that feels like the show's love letter to zombie movies like Dawn of the Dead and 28 Days Later. We had an absolute blast with this one as Clark races to save a zombie-infected Lois, leading to some fantastic Clois moments, creepy action, and one of the most fun standalone episodes of the season. We also talk about why Smallville's movie homage episodes work so well, Oliver's downward spiral, the eerie outbreak across Metropolis, and how the ending quietly sets up even bigger things to come with Zod.Support the show: https://patreon.com/hopefullyawesomeBecome a Member on Youtube: https://www.youtube.com/channel/UCHRvjz_pKP1Th5Y8ZIwFMtQ/joinCheck out our Merch! - https://hopefullyawesome.creator-spring.com/This video is NOT sponsored. Some product links are affiliate links which means if you buy something we'll receive a small commission.Mail to:Matt & Maggie - PO Box 3924, Kingsport TN, 37664, United StatesMatt & Maggie - 1001 N Eastman Road # 3924, Kingsport TN, 37664, United States

It's Smallville: The Ultimate Season! This time we're going through the twenty first episodes of every season and by process of elimination determining the ultimate episode 21 of Smallville.Zach is joined by Lance Laster from Always Hold On To Arrow, Matt Truex from Lois & Clark'd: The New Podcasts of Superman and Victoria Male.Check out Lance on Always Hold On To Arrow!Check out Matt's work including Lois & Clark'd: The New Podcasts of Superman at The Daily Knockoff!Check out Victoria's work on her website!Always Hold On To Smallville is brought you to by listeners like you. Special thanks to these Meteor Freaks on Patreon who's generous contributions help produce the podcast!Chris FuchsCory MooreIsaiah GoodridgeAtif SheikhJohn CurcioThomas NavenMarc-ids FoppenPatricia CarrilloRhythm ChameleonJim CrawfordKasey VachRouie HumphreyAlex HamiltonMatt DouglasDaniel CurielMeryl SmithTrevis HullAmy J.Mike FranzNathan MacKenzieSteve RogersMollie FicarellaJames LeeJason DavisPatrick BravoAlex RamseyTae TaeTina BJakeJacobJohn BobNathan RothacherDylan DiAntonioNick Ryan MagdozaEddie BissellNicholas FanslerJohn LongRuth Anne HamonTravis KillMike ThomasNeena JGordon BombayRajJoey DienbergDJ DoenaDaryn KirschtJarrett GibbsAnthony AndersonKeith FaulsJames HartAnthony DesiatoCrystal CrossKirin KumarTroy LangloisPATREON: patreon.com/alwaysmallvilleTWITTER: twitter.com/alwaysmallvilleFACEBOOK: facebook.com/alwaysmallvilleEMAIL: alwaysmallville@gmail.comMatt Truex is a Warner Bros. Discovery employee. The views and opinions expressed in this podcast are his own and do not necessarily reflect the views or positions of Warner Bros. Discovery.

Annette O'Toole, the acclaimed actress best known for playing Hope McCrea on Netflix's hit series Virgin River and Martha Kent on Smallville, joins us for this inspiring replay conversation about her remarkable career, aging in Hollywood, marriage, motherhood, and finding lasting success in an ever-changing entertainment industry. Fans of Annette O'Toole will enjoy hearing behind-the-scenes stories from some of her most memorable projects, including Smallville, Rose Kennedy, The Kennedys of Massachusetts, Cross My Heart with Martin Short, Copacabana, Vanities, and her acclaimed collaborations with filmmaker Christopher Guest. She also explains why she chose to leave Smallville after six seasons despite the show's success, sharing how family priorities, long commutes between Vancouver and Los Angeles, and a desire to return to theater shaped that decision. Annette also opens up about her enduring marriage to Emmy-winning actor, writer, and musician Michael McKean. She shares the touching story of how their friendship became a lifelong love story, how they co-wrote the Oscar-nominated song "A Kiss at the End of the Rainbow" for Christopher Guest's A Mighty Wind, and why their shared love of acting, music, books, and creativity continues to strengthen their relationship. She also reflects on McKean's memorable Celebrity Jeopardy! championship and why spending time together has become even more meaningful as they've grown older. The episode explores the realities of a long career in Hollywood, including the iconic roles Annette narrowly missed in Body Heat and Terms of Endearment. Rather than dwelling on disappointment, she explains how every missed opportunity ultimately led to another meaningful role, reinforcing her belief that resilience, gratitude, and adaptability are the keys to career longevity. One of the most inspiring parts of this interview focuses on healthy aging, women aging in Hollywood, and embracing authenticity. Annette speaks candidly about rejecting Hollywood's pressure to stay forever young, embracing her gray hair, choosing not to pursue cosmetic surgery, and discovering the confidence to speak her mind after years of trying to please others. She also shares how daily walking, nutrition, and exercise have helped her naturally manage osteoporosis while feeling healthier, stronger, and more energized than ever in her 70s. Show Notes/Links: www.hotflashescooltopics.com JOIN THE HOT FLASHES & COOL TOPICS PODCAST COMMUNITY: Website: www.hotflashescooltopics.com Newsletter: Link Mail hotflashescooltopics@gmail.com Instagram https://www.instagram.com/hotflashesandcooltopics Facebook : www.facebook.com/hotflashescooltopics YouTube https://www.youtube.com/@HotFlashesCoolTopics  

Mikey & Jeremy watch Season 8 Episode 2 of Smallville, "Plastique". They discuss Clark's new clothes, Clark's new job, and Clark's new outlook on life in the big city. 

It's Smallville: The Ultimate Season! This time we're going through the twentieth episodes of every season and by process of elimination determining the ultimate episode 20 of Smallville.Zach is joined by Mary Kwiatkowski from The KowSkiCast, Chris Clow from Discovery Debrief, Craig McKenzie from Kneel Before Blog and Isaiah Goodridge.Check out Mary on The KowSkiCast!Check out Chris on The Comic Binge and Discovery Debrief!Check out Craig and his work including the Kneel Before Pod podcast at Kneel Before Blog!Always Hold On To Smallville is brought you to by listeners like you. Special thanks to these Meteor Freaks on Patreon who's generous contributions help produce the podcast!Chris FuchsCory MooreIsaiah GoodridgeAtif SheikhJohn CurcioThomas NavenMarc-ids FoppenPatricia CarrilloRhythm ChameleonJim CrawfordKasey VachRouie HumphreyAlex HamiltonMatt DouglasDaniel CurielMeryl SmithTrevis HullAmy J.Mike FranzNathan MacKenzieSteve RogersMollie FicarellaJames LeeJason DavisPatrick BravoAlex RamseyTae TaeTina BJakeJacobJohn BobNathan RothacherDylan DiAntonioNick Ryan MagdozaEddie BissellNicholas FanslerJohn LongRuth Anne HamonTravis KillMike ThomasNeena JGordon BombayRajJoey DienbergDJ DoenaDaryn KirschtJarrett GibbsAnthony AndersonKeith FaulsJames HartAnthony DesiatoCrystal CrossKirin KumarTroy LangloisPATREON: patreon.com/alwaysmallvilleTWITTER: twitter.com/alwaysmallvilleFACEBOOK: facebook.com/alwaysmallvilleEMAIL: alwaysmallville@gmail.com

We're breaking down Smallville Season 9 Episode 2, “Metallo,” and we freaking loved this one. Clark and Lois are finally back in the same scene, Clark is stepping away from the whole “cutting off his humanity” era, and the show instantly feels more alive because of it. We talk about why John Corben works so well as Metallo, how his kryptonite heart makes him a genuinely tragic and dangerous antagonist, and why all those Terminator references made us so happy. Add in Lois being thrilled Clark is back, the Blur drama, Chloe pushing Clark, and the first real sparks of Season 9 Clois energy, and this Smallville series retrospective gave us exactly the kind of episode we've been waiting for.Support the show: https://patreon.com/hopefullyawesomeBecome a Member on Youtube: https://www.youtube.com/channel/UCHRvjz_pKP1Th5Y8ZIwFMtQ/joinCheck out our Merch! - https://hopefullyawesome.creator-spring.com/This video is NOT sponsored. Some product links are affiliate links which means if you buy something we'll receive a small commission.Mail to:Matt & Maggie - PO Box 3924, Kingsport TN, 37664, United StatesMatt & Maggie - 1001 N Eastman Road # 3924, Kingsport TN, 37664, United States

It's Smallville: The Ultimate Season! This time we're going through the ninteenth episodes of every season and by process of elimination determining the ultimate episode 19 of Smallville.Zach is joined by Anthony Desiato from Digging for Kryptonite, Billy Pollihan from See You Next Summer, and Mateo Santiago.Check out Anthony and his podcasts including Digging for Kryptonite at Flat Squirrel Productions!Check out Billy's podcast See You Next Summer!Always Hold On To Smallville is brought you to by listeners like you. Special thanks to these Meteor Freaks on Patreon who's generous contributions help produce the podcast!Chris FuchsInsaiyanIsaiah GoodridgeAtif SheikhJohn CurcioThomas NavenMarc-ids FoppenPatricia CarrilloRhythm ChameleonJim CrawfordKasey VachRouie HumphreyAlex HamiltonMatt DouglasDaniel CurielMeryl SmithTrevis HullMatt B.Amy J.Mike FranzNathan MacKenzieSteve RogersMollie FicarellaJames LeeJason DavisPatrick BravoAlex RamseyTae TaeTina BJakeJacobJohn BobDylan DiAntonioNick Ryan MagdozaEddie BissellNicholas FanslerJohn LongRuth Anne HamonTravis KillMike ThomasNeena JGordon BombayRajJoey DienbergDJ DoenaDaryn KirschtNicholas CosoJarrett GibbsAnthony AndersonKeith FaulsJames HartAnthony DesiatoCrystal CrossKirin KumarTroy LangloisPATREON: patreon.com/alwaysmallvilleTWITTER: twitter.com/alwaysmallvilleFACEBOOK: facebook.com/alwaysmallvilleEMAIL: alwaysmallville@gmail.com

Mikey & Jeremy watch Season 8 Episode 1 of Smallville, "Odyssey". They discuss new cast members, Aquaman's power level, and French Maids.

More like the LEAST horrible yearNo better way to end a series than with a Showtime children's special starring Allison Mack. One could say this is a prequel to Smallville, others would say it's an Eric Stoltz masterpiece. It's neither! Join us in reviewing a story by Nic Faulkner, who claims the worst year of her life was the year she had braces, got a boyfriend, gets a car built up by her dad, and sets up her two best friends to fall in love. Shout out Bret Hart and chickenpox!

Everyone is wrong, Supergirl absolutely rules. Tonight we're talking about Supergirl (2026), the 4th project in James Gunn's DCU, and why Kara's story hits so differently from Superman's. We loved the deeper look at Kara as a person, shaped by loss, anger, survival, and a life that never gave her the same warmth Clark had on Earth. This just-released DCU movie gave us a Supergirl who feels messy, wounded, funny, and heroic in her own way, plus Krypto, Ruthye, a brutal space revenge quest, and Jason Momoa's Lobo being exactly as awesome as we hoped. Mostly, we're here to happily defend this movie from the “it's bad actually” crowd, because nope. Not today.Support the show: https://patreon.com/hopefullyawesomeBecome a Member on Youtube: https://www.youtube.com/channel/UCHRvjz_pKP1Th5Y8ZIwFMtQ/joinCheck out our Merch! - https://hopefullyawesome.creator-spring.com/This video is NOT sponsored. Some product links are affiliate links which means if you buy something we'll receive a small commission.Mail to:Matt & Maggie - PO Box 3924, Kingsport TN, 37664, United StatesMatt & Maggie - 1001 N Eastman Road # 3924, Kingsport TN, 37664, United States

Can you guess Dr. Bobb's very favorite Legion story ever? Well you won't have to guess if you just listen to this episode. Bonus points if you can hear Dr. Husband yawning through Dr. Bobb's extemporaneous spitting out of Legion lore! It's all right here in Adventure Comics #355! Chapters (00:00:00) - Oh, My!(00:00:17) - Adventure Comics 355: And The Six Legged Legionnaire(00:03:03) - How to Deal With A Heat Wave in the US(00:05:33) - A stray dog runs through the streets(00:08:06) - The War of the Legions(00:12:19) - Legion of Supervillains: Kidnapping Brainiac(00:14:58) - Cosmic Man: The Master of Sound(00:16:33) - Saturn Woman vs Hypnosee(00:20:29) - What To Do If Your Leg Falls Off On The Rollercoaster(00:21:03) - Lightning Man vs. Lightning Lord(00:21:54) - Polar Man vs. Beauty Blaze(00:24:05) - Legion of Supervillains vs The supervillains(00:29:21) - Lex Luthor vs The Legion of Supermen(00:32:39) - The New Members of the Legion of Superheroes(00:36:31) - The Forgotten Legion of Superheroes(00:40:05) - Supergirl Movie Review(00:41:44) - Are Green Suns Bad For Superman?(00:44:56) - Smallville(00:48:15) - In the Dark: Lana Lang Turns Into a Legionnaire(00:51:09) - Superboy and the Legionnaires(00:56:05) - Shrinking Violet vs Augur Khan(01:00:11) - The Legion of Superboy(01:03:36) - The Legion of Superheroes Story

It's Smallville: The Ultimate Season! This time we're going through the eighteenth episodes of every season and by process of elimination determining the ultimate episode 18 of Smallville.Zach is joined by Tyler Patrick from The Krypton Report, Anthony Polinick from The Grund, and Amanda Rose.Check out Tyler on Krypton Report!Check out Anthony on The Grund!Always Hold On To Smallville is brought you to by listeners like you. Special thanks to these Meteor Freaks on Patreon who's generous contributions help produce the podcast!Chris FuchsInsaiyanIsaiah GoodridgeAtif SheikhJohn CurcioThomas NavenMarc-ids FoppenPatricia CarrilloRhythm ChameleonJim CrawfordKasey VachRouie HumphreyAlex HamiltonMatt DouglasDaniel CurielMeryl SmithTrevis HullMatt B.Amy J.Mike FranzNathan MacKenzieSteve RogersMollie FicarellaJames LeeJason DavisPatrick BravoAlex RamseyTae TaeTina BJakeJacobJohn BobDylan DiAntonioNick Ryan MagdozaEddie BissellNicholas FanslerJohn LongRuth Anne HamonTravis KillMike ThomasNeena JGordon BombayRajJoey DienbergDJ DoenaDaryn KirschtNicholas CosoJarrett GibbsAnthony AndersonKeith FaulsJames HartAnthony DesiatoCrystal CrossKirin KumarTroy LangloisPATREON: patreon.com/alwaysmallvilleTWITTER: twitter.com/alwaysmallvilleFACEBOOK: facebook.com/alwaysmallvilleEMAIL: alwaysmallville@gmail.com

This week on Toon'd In!, Jim Cummings welcomes acclaimed actor, voice actor, and musician Sam Witwer for an unforgettable conversation celebrating a remarkable career spanning film, television, animation, and video games! Best known to fans around the world as Starkiller in Star Wars: The Force Unleashed and the definitive voice of Darth Maul across numerous Star Wars animated series and games, Sam has also captivated audiences with memorable performances in Smallville, Being Human, Battlestar Galactica, and Supergirl. With an incredible range as both a screen actor and voice performer, Sam has become one of the most respected talents working in genre entertainment today.In this engaging and wide-ranging episode, Jim and Sam explore his journey into acting, voice performance, and performance capture, discussing how a lifelong passion for storytelling and classic cinema led him to some of the most iconic roles in modern pop culture. Sam shares fascinating behind-the-scenes stories from bringing Darth Maul back to life, portraying Starkiller in the Star Wars universe, and collaborating with legendary filmmakers, directors, and fellow performers. The conversation also offers unique insight into the creative process of building emotionally rich performances for animation, video games, and live-action productions.Jim and Sam also dive into the artistry of voice acting, the evolution of performance capture, and the dedication required to create characters that resonate with audiences across generations. Together, they discuss the challenges of balancing voice work with on-screen acting, the enduring legacy of Star Wars, and the opportunities that have shaped Sam's remarkable career. Along the way, they share stories about auditions, fan interactions, creative collaboration, and the passion that continues to drive their work in entertainment.The episode also provides valuable insight into character development, storytelling, and the collaborative spirit behind some of the world's biggest franchises. Jim and Sam explore what makes legendary characters like Darth Maul endure, the importance of authenticity in performance, and the friendships and creative experiences that make a career in entertainment so rewarding. Their conversation is filled with humor, nostalgia, behind-the-scenes memories, and an inspiring appreciation for the craft of acting.

This one's for the fans. Showrunners Kelly Souders and Brian Peterson join us for an insightful and heartwarming discussion. They tell us what it's like to inherit the show after 7 seasons, keep it fresh, and deal with pushback from all angles. It wasn't easy, but they rose above and beyond the task of running Smallville for its final seasons. In the episode, we get a glimpse into Davis's arrival and the magnitude of his destruction. It begs the question: what if the boy from Krypton first fell into the hands of the Luthors? This is a big episode jam-packed with behind the scenes details about our favorite show. __________________________________________________

It's Smallville: The Ultimate Season! This time we're going through the seventeenth episodes of every season and by process of elimination determining the ultimate episode 17 of Smallville.Zach is joined by Lance Laster from Always Hold On To Arrow, Anthony Desiato from Digging for Kryptonite, Mary Kwiatkowski from The KowSkiCast, and Eddie Bissell.Check out Lance on Always Hold On To Arrow!Check out Anthony and his podcasts including Digging for Kryptonite at Flat Squirrel Productions!Check out Mary on The KowSkiCast!Check out Eddie's animal rescue Valley Cats & Friends!Always Hold On To Smallville is brought you to by listeners like you. Special thanks to these Meteor Freaks on Patreon who's generous contributions help produce the podcast!Chris FuchsInsaiyanIsaiah GoodridgeAtif SheikhJohn CurcioThomas NavenMarc-ids FoppenPatricia CarrilloRhythm ChameleonJim CrawfordKasey VachRouie HumphreyAlex HamiltonMatt DouglasDaniel CurielMeryl SmithTrevis HullMatt B.Amy J.Mike FranzNathan MacKenzieSteve RogersMollie FicarellaJames LeeJason DavisPatrick BravoAlex RamseyTae TaeTina BJakeJacobJohn BobDylan DiAntonioNick Ryan MagdozaEddie BissellNicholas FanslerJohn LongRuth Anne HamonTravis KillMike ThomasNeena JGordon BombayRajJoey DienbergDJ DoenaDaryn KirschtNicholas CosoJarrett GibbsAnthony AndersonKeith FaulsJames HartAnthony DesiatoCrystal CrossKirin KumarTroy LangloisPATREON: patreon.com/alwaysmallvilleTWITTER: twitter.com/alwaysmallvilleFACEBOOK: facebook.com/alwaysmallvilleEMAIL: alwaysmallville@gmail.com

THIS KID IS HOMELANDER'S DREAM! We react to Brightburn (2019) for the FIRST TIME — James Gunn's evil Man Of Steel horror movie, right before Milly Alcock's Supergirl hits theaters! This full Brightburn reaction and review dives into Brandon Breyer's terrifying origin story, the Superman and Smallville parallels, the jaw scene, the ending, and that wild post-credits evil justice league tease. What if Clark Kent landed on Earth… and instead of becoming Superman, he became something much darker? Brightburn takes the superhero origin story and turns it into a brutal horror movie, with Brandon Breyer discovering his powers in the worst way possible. Andrew & Aaron go in completely unspoiled and break down the mother-son relationship, Elizabeth Banks' performance, the creepy alien possession angle, the gruesome kills, the Man of Steel comparisons, and why this movie still hits as one of the most disturbing evil Superman stories ever made. With James Gunn's DCU continuing and Supergirl on the way, this felt like the perfect time to watch Brightburn for the first time and see how this superhero horror experiment holds up. Comment below with your thoughts on Brightburn, Brandon Breyer, the ending, and whether you still want a sequel! Follow Aaron On Instagram: https://www.instagram.com/therealaaronalexander/?hl=en Follow Andrew Gordon on Socials:  YouTube: https://www.youtube.com/@MovieSource Instagram:  https://www.instagram.com/agor711/?hl=en Twitter:  https://twitter.com/Agor711 Intense Suspense by Audionautix is licensed under a Creative Commons Attribution 4.0 license. https://creativecommons.org/licenses/... Support The Channel By Getting Some REEL REJECTS Apparel! https://www.rejectnationshop.com/ Follow Us On Socials:  Instagram: https://www.instagram.com/reelrejects/  Tik-Tok: https://www.tiktok.com/@reelrejects?lang=en Twitter: https://x.com/reelrejects Facebook: https://www.facebook.com/TheReelRejects/ Music Used In Ad:  Hat the Jazz by Twin Musicom is licensed under a Creative Commons Attribution 4.0 license. https://creativecommons.org/licenses/by/4.0/ Happy Alley by Kevin MacLeod is licensed under a Creative Commons Attribution 4.0 license. https://creativecommons.org/licenses/... POWERED BY @GFUEL Visit https://gfuel.ly/3wD5Ygo and use code REJECTNATION for 20% off select tubs!! Head Editor: https://www.instagram.com/praperhq/?hl=en Co-Editor: Greg Alba Co-Editor: John Humphrey Music In Video: Airport Lounge - Disco Ultralounge by Kevin MacLeod is licensed under a Creative Commons Attribution 4.0 license. https://creativecommons.org/licenses/by/4.0/ Ask Us A QUESTION On CAMEO: https://www.cameo.com/thereelrejects Follow TheReelRejects On FACEBOOK, TWITTER, & INSTAGRAM:  FB:  https://www.facebook.com/TheReelRejects/ INSTAGRAM:  https://www.instagram.com/reelrejects/ TWITTER:  https://twitter.com/thereelrejects Follow GREG ON INSTAGRAM & TWITTER: INSTAGRAM:  https://www.instagram.com/thegregalba/ TWITTER:  https://twitter.com/thegregalba Learn more about your ad choices. Visit megaphone.fm/adchoices

Special guest star Serinda Swan mystifies the podcast today to chat about the 17th episode of season 8, Hex and what it meant to inhabit the role of the iconic super magician, Zatanna Zatara. Smallville was Serinda's crash course on the business, from set etiquette to how not to land an off-color joke. In the episode, Zatanna hexes Chloe into Lois's body and Clark into...a wet blanket. It's all in an effort to bring her father back to life but is it all worth it? Can she be contained? Join us for what we can honestly say is Smallville's funniest episode to date. ... ❤️ Sign up for therapy and get 10% off at ⁠https://betterhelp.com/talkville⁠

The race to build superintelligence is producing models that keep getting better at objective problems, but not at behaving like actual people. Joon Sung Park, founder and CEO of Simile and creator of Stanford's "Smallville" generative agents study, argues that simulating human society requires a fundamentally different kind of model. He frames today's frontier models as the "CPU of intelligence"—rational, superhuman at problems with right answers—and Simile as creating the "GPU of intelligence," built to encode the diversity of people's values, preferences, and tastes. It simulated 1,000 Americans and predicted their behavior 85% as accurately as people reproduce their own answers. CVS uses it for concept testing; some customers simulate their own earnings calls. Joon's larger bet: a "CERN of human society" that could one day model bank runs, climate cooperation, or the early signals of a collapsing democracy. Hosted by Sonya Huang, Sequoia Capital

It's Smallville: The Ultimate Season! This time we're going through the sixteenth episodes of every season and by process of elimination determining the ultimate episode 16 of Smallville.Zach is joined by Tyler Patrick, Anthony Polinick, and Amanda Rose.Check out Tyler on Krypton Report!Check out Anthony on The Grund!Always Hold On To Smallville is brought you to by listeners like you. Special thanks to these Meteor Freaks on Patreon who's generous contributions help produce the podcast!Chris FuchsInsaiyanIsaiah GoodridgeAtif SheikhJohn CurcioThomas NavenMarc-ids FoppenPatricia CarrilloRhythm ChameleonJim CrawfordKasey VachRouie HumphreyAlex HamiltonMatt DouglasDaniel CurielMeryl SmithTrevis HullMatt B.Amy J.Mike FranzNathan MacKenzieSteve RogersMollie FicarellaJames LeeJason DavisPatrick BravoAlex RamseyTae TaeTina BJakeJacobJohn BobDylan DiAntonioNick Ryan MagdozaEddie BissellNicholas FanslerJohn LongRuth Anne HamonTravis KillMike ThomasNeena JGordon BombayRajJoey DienbergDJ DoenaDaryn KirschtNicholas CosoJarrett GibbsAnthony AndersonKeith FaulsJames HartAnthony DesiatoCrystal CrossKirin KumarTroy LangloisPATREON: patreon.com/alwaysmallvilleTWITTER: twitter.com/alwaysmallvilleFACEBOOK: facebook.com/alwaysmallvilleEMAIL: alwaysmallville@gmail.com

Mikey & Jeremy watch S7E20 of Smallville, "Arctic". They discuss Jimmy Olsen's particular set of skills, unceremonious departures, and the shortcomings of season 7 as a whole. 

Its time to return to Earth-167! Which you would obviously know as the universe of Smallville, the smash hit ten season long Superman original series that managed to introduce EVERY. SINGLE. DC. CHARACTER. before Clark Kent decides to put on the suit. This time we're going to be covering the storyline of Kara Zor-El aka Supergirl as played by Laura Vandervoort introduced in Season 7. And we've discovered so much more about this show including how many character get clones or are clones (it's a lot which is exciting). Thanks for watching our Caravan Of Garbage reviewSUBSCRIBE HERE ►► http://goo.gl/pQ39jNHelp support the show and get early episodes ► https://bigsandwich.co/Patreon ► https://patreon.com/mrsundaymoviesJames' Twitter ► http://twitter.com/mrsundaymoviesMaso's Twitter ► http://twitter.com/wikipediabrownPatreon ► https://patreon.com/mrsundaymoviesT-Shirts/Merch ► https://www.teepublic.com/stores/mr-sunday-movies The Weekly Planet iTunes ► https://itunes.apple.com/us/podcast/the-weekly-planet/id718158767?mt=2&ign-mpt=uo%3D4 The Weekly Planet Direct Download ► https://play.acast.com/s/theweeklyplanetAmazon Affiliate Link ► https://amzn.to/2nc12P4 Hosted on Acast. See acast.com/privacy for more information.

How does this teenage retelling of Superman's origins hold up? Is Lex Luthor likeable? And who would Mitu befriend in the Smallville universe? Tune in to find out! Edited with thanks to Playlyst Studios Connect with us:   Buy us a coffee at buymeacoffee.com/thepilotpodcast | Visit us at thepilotpodcast.com | Email us at askthepilotpodcast@gmail.com | Follow us @ThePilotPod on Twitter, Instagram, and TikTok | Please leave a rating and review on Apple Podcasts

Host Anthony Desiato and guest Zach Moore (Always Hold On To Smallville) dig into Kara Kent on SMALLVILLE as portrayed by Laura Vandervoort across Season 7 and return appearances in Seasons 8 & 10.They discuss her arrival, characterization, & backstory; dynamics with Clark, Lara, Zor-El, Lex, & Jimmy; mid-season amnesia & powerlessness; banishment to the Phantom Zone & subsequent returns; and ultimate departure to the 31st Century.Support the show and receive exclusive podcast content at Patreon.com/AnthonyDesiato, including the spinoff podcasts BEYOND METROPOLIS and DIGGING FOR JUSTICE!Visit BCW Supplies and use promo code FSP to save 10% on your next order of comics supplies. Get your DFK merch at the podcast's TeePublic storefront!FACEBOOK GROUP: Digging for Kryptonite: A Superman Fan GroupFACEBOOK PAGE: @diggingforkryptonitepodINSTAGRAM: @diggingforkryptonitepodTWITTER: @diggingforkrpodBLUESKY: @diggingforkrpod.bsky.socialEMAIL: flatsquirrelproductions@gmail.comWEBSITE: FlatSquirrelProductions.com Digging for Kryptonite is a Flat Squirrel Production. Theme music by Dan Pritchard. Key art by Isaiah Simmons. Mentioned in this episode:Drunken AvengerSingle Bound PodcastThis Podcast Will Never DieAw Yeah ComicsFat Moose Comics

It's Smallville: The Ultimate Season! This time we're going through the fifteenth episodes of every season and by process of elimination determining the ultimate episode 15 of Smallville.Zach is joined by Leah Vogel, Ronit Troner, and Eddie Bissell.Check out Eddie's animal rescue Valley Cats & Friends!Always Hold On To Smallville is brought you to by listeners like you. Special thanks to these Meteor Freaks on Patreon who's generous contributions help produce the podcast!Chris FuchsInsaiyanIsaiah GoodridgeAtif SheikhJohn CurcioThomas NavenMarc-ids FoppenPatricia CarrilloRhythm ChameleonJim CrawfordKasey VachRouie HumphreyAlex HamiltonMatt DouglasDaniel CurielMeryl SmithTrevis HullMatt B.Amy J.Mike FranzNathan MacKenzieSteve RogersMollie FicarellaJames LeeJason DavisPatrick BravoAlex RamseyTae TaeTina BJakeJacobJohn BobDylan DiAntonioNick Ryan MagdozaEddie BissellNicholas FanslerJohn LongRuth Anne HamonTravis KillMike ThomasNeena JGordon BombayRajJoey DienbergDJ DoenaDaryn KirschtNicholas CosoJarrett GibbsAnthony AndersonKeith FaulsJames HartAnthony DesiatoCrystal CrossKirin KumarTroy LangloisPATREON: patreon.com/alwaysmallvilleTWITTER: twitter.com/alwaysmallvilleFACEBOOK: facebook.com/alwaysmallvilleEMAIL: alwaysmallville@gmail.com

We all knew her as the lovable Chloe Sullivan on Smallville, but behind the scenes, Allison Mack was hiding a deeply disturbing secret. In this episode of Five's a Crowd, we dive deep into the sick reality of the NXIVM sex cult and the sinister figurehead, Keith Raniere. From executive success seminars to the terrifying dark underbelly of DOS, blackmail, and human branding, we break down how a beloved CW sweetheart became a master enforcer in one of the most shocking true-crime stories in Hollywood history.Thank you for being part of this crowd!You've got burning questions, we've got answers! Call or Text us for the worst advice imaginable, and we may feature it on an upcoming podcast! ** 801-513-3373 **Reddit- Our Subreddit: https://www.reddit.com/r/FivesACrowd- Our Account: https://www.reddit.com/user/FivesACrowdPodcastFollow Our Personal AccountsAustin - https://allmylinks.com/austinspomerCam - https://www.instagram.com/effinburch/Chris - https://www.instagram.com/thechrishummel/Tony - https://www.instagram.com/theonlytonyc/Zach - https://www.instagram.com/zvanbeekum/00:00 - Start!00:05 - A dark opening joke to set the mood00:42 - Smallville high school crushes04:00 - From Hollywood actress to federal court09:09 - Meet Keith Raniere and the "Vanguard" illusion15:29 - How NXIVM masqueraded as business coaching24:33 - DOS: The terrifying secret inner circle25:19 - Blackmail and the sinister collateral system27:17 - The horrifying branding ceremonies34:36 - Allison Mack's role as a top Cult Lieutenant45:15 - Was Mack a victim or a perpetrator?47:29 - FBI arrests and federal indictments52:12 - A shockingly short prison sentence57:35 - Marrying a former neo-Nazi and life after prison01:01:48 - Amway, MLM red flags, and pyramid schemes01:05:48 - One last terrible joke to lighten the moodHashtags#Podcast #NXIVM #AllisonMack #TrueCrime #Cults #Smallville #FivesACrowd #Podcast #HollywoodScandalsP.O. Box**Please no packages, letters only**Five's A Crowd Podcast1123 N Fairfield Rd #1373 Layton, UT 84041

Director extraordinaire and friend of the pod, Glen Winter joins us to break down the technical side of things as we dive into season 8 episode 15, Infamous. With his sparkling attitude and wealth of knowledge, Glen sheds light on the cinematic choices and production hazards that go into creating the Smallville spectacle. In the episode, Clark decides to reveal his secret to the world before he can be outed by disgraced and damp reporter Linda Lake (guest star Tori Spelling). How will the citizens respond? What will Lois think? And how much does it cost to soak all the actors with rain towers? Find out all that and more in this week's episode! ... ❤️ Sign up for therapy and get 10% off at https://betterhelp.com/talkville

Join us for the watch party on YouTube LIVE AT FIVE (PT) on episode release day: https://www.youtube.com/@birdsandbeesdontfck Phil Morris is an actor best known as Jackie Chiles on Seinfeld and John Jones on Smallville who grew up in Los Angeles and Beverly Hills, where the closest thing to sex education was basic health class, a little anatomy, and figuring out the rest through growing up in Hollywood. In this episode we talk about Good Vibes Breakfast Club, the beautiful way community can create space for men to be vulnerable, and why real connection so often happens when people drop the performance and just show up as themselves. Phil shares what it was like growing up in Beverly Hills as the son of original Mission: Impossible star Greg Morris, how early exposure to fame shaped the way he sees the world, and why curiosity, humility, and authenticity matter so much more than status. We also get into marriage, intimacy, what it actually takes to stay connected over decades, and Phil's simple but powerful advice to stay attractive, stay attracted, stay interesting, and stay interested. Phil and I are getting real honest with Reddit stories. Join Patreon and dive in! https://www.patreon.com/cw/birdsandbeesdontfck Get everything you need to Fck Like The Movies _____________________________________________________________ Where to find Phil: Instagram: @thephilmorris Where to find Arielle: Instagram: @birdsandbeesdontfck TikTok: @birdsandbeesdontfck Patreon: https://www.patreon.com/cw/birdsandbeesdontfck   Bonus stories found exclusively on Patreon STORY 1: AITA for ignoring my wife for throwing away my late wife video tapes? STORY 2: My 18M son says my brother's wife (30F) crossed boundaries with him and now my family says I'm overreacting (46F) STORY 3: Do I (F 26) tell my boyfriend (M 26) his ex cheated on him?   Like my cuffs AND my vibrator necklace? Me too. Get $15 Off Crave Pleasure Jewelry Here: https://lovecrave.com/arielle   Episode Cheat Sheet: 02:47 Good Vibes Breakfast Club, car culture, and finding community in Los Angeles 05:14 Male vulnerability, brotherhood, and emotional intimacy during the pandemic 07:39 Why real connection happens when people drop the filter 09:50 Community, commonality, and why we are more alike than we are different 12:10 Why big conversations happen best on a beautiful drive 14:30 Intimacy meetings, relationship check-ins, and how to communicate with your partner 16:54 Emotional intelligence, curiosity, and what makes relationships actually work 19:20 Marriage advice, acceptance, and why you cannot carry someone else's water 21:35 Stay attractive, stay attracted, stay interesting, stay interested 23:52 Novel thinking, personal growth, and accepting the peaks and valleys of life 26:13 Why relationships, friendships, and community all need curiosity and effort 28:28 Good Vibes, masculine friendship, and non-sexual touch between men 30:41 Growing up in Los Angeles and Beverly Hills as Greg Morris' son 31:42 Fame, Hollywood, Beverly Hills, and what Phil learned early about success 34:01 Black representation in Hollywood and being raised around groundbreaking artists 35:25 How community showed up in grief, loss, and the final days of a loved one 37:48 Grace, gratitude, and why pain does not have to define your story 40:05 Falling down, getting up, and deciding how to write your own life 42:27 Career pivots, producing, creativity, and doing the work that actually lights you up 44:48 Why Phil stopped hustling and started creating 47:13 Acting, storytelling, and what comic conventions reveal about human connection 49:40 Leadership, gender dynamics, and domestic labor in relationships 52:03 Growing up with basic sex education, Hollywood freedom, and getting married young 54:22 Marriage, desire, fidelity, and how to stay connected over time 56:43 Long-term relationships, teamwork, and the three energies inside a partnership 59:04 Relationship advice, acceptance, and what it means to stay on the same team

It's Smallville: The Ultimate Season! This time we're going through the fourteenth episodes of every season and by process of elimination determining the ultimate episode 14 of Smallville.Zach is joined by Lance Laster from Always Hold On To Arrow, Matt Truex from Lois & Clark'd: The New Podcasts of Superman and Victoria Male.Check out Lance on Always Hold On To Arrow!Check out Matt's work including Lois & Clark'd: The New Podcasts of Superman at The Daily Knockoff!Check out Victoria's work on her website!Always Hold On To Smallville is brought you to by listeners like you. Special thanks to these Meteor Freaks on Patreon who's generous contributions help produce the podcast!Chris FuchsKevonte ChilousInsaiyanIsaiah GoodridgeAtif SheikhJohn CurcioThomas NavenMarc-ids FoppenPatricia CarrilloRhythm ChameleonJim CrawfordKasey VachRouie HumphreyAlex HamiltonMatt DouglasDaniel CurielMeryl SmithTrevis HullMatt B.Amy J.Mike FranzNathan MacKenzieSteve RogersMollie FicarellaJames LeeJason DavisPatrick BravoAlex RamseyTae TaeTina BJakeJacobJohn BobDylan DiAntonioNick Ryan MagdozaEddie BissellNicholas FanslerJohn LongRuth Anne HamonTravis KillMike ThomasNeena JGordon BombayMichael H.RajJoey DienbergDJ DoenaNicholas CosoJarrett GibbsAnthony AndersonKeith FaulsJames HartAnthony DesiatoCrystal CrossKirin KumarTroy LangloisPATREON: patreon.com/alwaysmallvilleTWITTER: twitter.com/alwaysmallvilleFACEBOOK: facebook.com/alwaysmallvilleEMAIL: alwaysmallville@gmail.comMatt Truex is a Warner Bros. Discovery employee. The views and opinions expressed in this podcast are his own and do not necessarily reflect the views or positions of Warner Bros. Discovery.PATREON: patreon.com/alwaysmallvilleTWITTER: twitter.com/alwaysmallvilleFACEBOOK: facebook.com/alwaysmallvilleEMAIL: alwaysmallville@gmail.com

A gang of interstellar elites make it their business to elaborately prank the Boy of Steel, but nothing they do can top Superboy's own elaborate prank of (checks notes) flying 24 hours into the future to fake his entire family's death and also pretend to be blind. It's a laff riot, all right here in Superboy #137! Chapters (00:00:00) - Superboy 137(00:02:52) - Spring cleaning in the house(00:04:57) - In the world of managerial accounting(00:06:46) - Boring job costing class(00:09:59) - Flute Concert and Guitar(00:11:17) - Oh, My Love Boat!(00:12:06) - Ashes in the Carpet(00:14:18) - How to Create Go Go Check Comics Covers(00:16:21) - milo on The Comeback and For All Mankind(00:19:31) - The Montreal Canadiens(00:19:43) - Superboy in the New Home...(00:22:49) - Martin Gray on Biscuits Flavored Tea(00:24:04) - How Smallville Stands Up to Earthquakes(00:26:54) - When Superboy Needs To Travel Back In Time(00:30:25) - Superman and Clark Kent: The Alternate Lives(00:34:50) - The Boy Who Says He's Blind(00:35:23) - How To Pass as Superboy in Smallville(00:37:22) - How My Great Grandmother Met Her husband(00:38:34) - Superboy(00:41:14) - Chuck Kendall switches to Superboy after witnessing bank robbery(00:45:20) - Super baby from Krypton is featured in this week's podcast(00:47:02) - Baby Found in the Basement of Smallville(00:50:57) - Strawberry Scratches on a Television Set(00:53:52) - Superboy: Build a Children's Zoo(00:58:27) - Tarzan: A Super Genius(01:00:06) - Clark Kent: On Becoming Superboy(01:04:20) - Superboy meets Old Man on Geryon(01:07:01) - Superboy(01:11:06) - Superboy And The Kryptonian Fabric

Send us a text or a voicemailLong-buried wounds rise to the surface when has-been podcasters reunite with their estranged best friend and former producer, on the eve of their comeback episode. On Episode 722 of Trick or Treat Radio our featured film discussion is Mother Mary from director David Lowery! We also talk about dumb Transformer names, scream kings, and we react to trailers for the films; Hope and Blowie! So grab the outfit you wish to make your triumphant return in, steer clear of any unwanted imprints, and strap on for the world's most dangerous podcast!Stuff we talk about: Cannibal Holocaust, Grindhouse Releasing, Ruggero Deodato, 16mm aspect ratio, Sage Stallone, The Truth Commission, Sheiky Baby, Mounties, Force Insensitive, Mandalorian and Grogu, Skids, Transformers, dumb Transformer names, Beachcombers, The H Man, The Changeling, Visiting Hours, Seed People, Urban Legend, Psycho Beach Party, An Erotic Vampire in Paris, Cherry Falls, Night of the Demons, Hellraiser, Ashley Lawrence, Stepfather 3, The Andromeda Strain, The Drew Carey Show, Willard, Reflection of Fear, Zelda Rubenstein, I Hate My Body, Mummy's Revenge, Night of the Seagulls, The Bat, Karen Carpenter's The Thing, Morris Day and the Time, Young MC, The Circle Jerks, Todd Browning's Freaks, Freaked, Psychos in Love, Na Hong-Jin, Hope, Miami Connection, Drew Struzan, Blowie, Deadstream, Nightmare on Elm St Pt. 2, Scream Kings, Mark Patton, Curse of the Queer Wolf, Dice Gottfried, Smallville, The Green Knight, Dev Patel, Anne Hathaway, David Lowery, Stephen King, The Shining, Pain Cave, Hawk the Slayer, imprinting, Free Britney, Dark Knight Rises, Abigail, Elijah Wood, Ready or Not 2: Here I Come, Samara Weaving, Kathryn Newton, David Cronenberg, Anthony Michael Hall, a humble egomaniac, hope nope and rope, a beautiful nothing, and more money than Zod.Support us on Patreon: https://www.patreon.com/trickortreatradioJoin our Discord Community: discord.trickortreatradio.comSend Email/Voicemail: mailto:podcast@trickortreatradio.comVisit our website: http://trickortreatradio.comStart your own podcast: https://www.buzzsprout.com/?referrer_id=386Use our Amazon link: http://amzn.to/2CTdZzKFB Group: http://www.facebook.com/groups/trickortreatradioTwitter: http://twitter.com/TrickTreatRadioFacebook: http://facebook.com/TrickOrTreatRadioYouTube: http://youtube.com/TrickOrTreatRadioInstagram: http://instagram.com/TrickorTreatRadioSupport the show

Kristin Kreuk joins us one more time to discuss Lana Lang's final episode of Smallville. We talk about the heartbreak, deeper meanings, and contractual obligations behind her return and exit from the show. In the episode, Clark and Lana are super-powered lovers at last, until Lex reenters the fold to tear them apart with the help of demolitions expert, the Toyman. Will love outlast an obscene level of kryptonite? Tune in for what could be Kristin's last appearance on Talk Ville. And yes, Michael does get righteously upset about this portrayal of Lex. ...

It's Smallville: The Ultimate Season! This time we're going through the thirteenth episodes of every season and by process of elimination determining the ultimate episode 13 of Smallville.Zach is joined by Leah Vogel, Ronit Troner, Billy Pollihan from See You Next Summer.Check out Billy's podcast See You Next Summer!Always Hold On To Smallville is brought you to by listeners like you. Special thanks to these Meteor Freaks on Patreon who's generous contributions help produce the podcast!Chris FuchsKevonte ChilousInsaiyanIsaiah GoodridgeAtif SheikhJohn CurcioThomas NavenMarc-ids FoppenPatricia CarrilloRhythm ChameleonJim CrawfordKasey VachRouie HumphreyAlex HamiltonMatt DouglasDaniel CurielMeryl SmithTrevis HullMatt B.Amy J.Mike FranzNathan MacKenzieSteve RogersMollie FicarellaJames LeeJason DavisPatrick BravoAlex RamseyTae TaeTina BJakeJacobJohn BobDylan DiAntonioNick Ryan MagdozaEddie BissellNicholas FanslerJohn LongRuth Anne HamonTravis KillMike ThomasNeena JGordon BombayMichael H.RajJoey DienbergDJ DoenaNicholas CosoJarrett GibbsAnthony AndersonKeith FaulsJames HartAnthony DesiatoCrystal CrossKirin KumarTroy LangloisPATREON: patreon.com/alwaysmallvilleTWITTER: twitter.com/alwaysmallvilleFACEBOOK: facebook.com/alwaysmallvilleEMAIL: alwaysmallville@gmail.com

Lana's back and now we know why. In this controversial episode, we get into the Foo Fighters, 80s montages, and HBO's the Pitt. We do also analyze the episode and actually come to our own revelations about character motivations and Smallville's overarching themes. As Tom says, "it's just good drama" and boy do we have it. Join us for season 8, episode 13 Power. ... ☄️ Mars Men: For a limited time, our listeners get 50% off FOR LIFE, Free Shipping, AND 3 Free Gifts at Mars Men at https://Mengotomars.com ❤️ Better Help: Sign up and get 10% off at https://betterhelp.com/TALKVILLE __________________________________________________