Podcasts about Terminus

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

As we've been telling anyone who'll listen, seeing EBM legends Portion Control attack the Terminus stage with unaging menace and aggression was one of the main highlights of our recent trip to Calgary, and we were able to interview John Whybrew and Dean Piavanni about their legacy as electronic pioneers and, perhaps more importantly, what's compelling them to push forward into the present, with much of the strongest Portion Control material having been released in recent years. We're also discussing our showcases at Edmonton's Purple City Festival, as well as a recent Dark Chisme show.

Tim Buckley - Buzzin' Fly Zager & Evans - In the Year 2525 (Exordium & Terminus) 23nd Turnoff - Michael Angelo Garden Odyssey Enterprise - Sad & Lonely Ronnie Earl - Mutcika Ministry of Music Official - Velvet Circuit (Pomodoro II) Tim Hardin - Green Rocky Road The Growing Concern - Hard Hard Year Jimmy Carter and Dallas County Green - Travelin' Pentangle - Cruel Sister Buffalo Springfield - Nowadays Clancy Can't Even Sing Van Morrison - Bulbs Fred Neil - That's The Bag I'm In

We answer questions from folks looking to find other people to play games with, including organising game groups, dealing with anxiety, and age gaps. We share first thoughts on Terminus and get FlipToons to the table and wrap up with three game reviews: Crabs in a Bucket, Our Secret Society, and The Ticket Booth We usually try to record Wednesdays at 8 PM Eastern at https://www.twitch.tv/tabletopbellhop Find full detailed show notes at https://tabletopbellhop.com/310 Disclosure: Links may be affiliate links. As an Amazon Associate, we earn from qualifying purchases. Games mentioned may be review copies provided by publishers. (00:00:00) CHECK-IN (00:02:19) Announcements (00:03:07) Ask The Bellhop (00:29:00) The Bellhop's Tabletop (00:42:19) The Game Room - Crabs in a Bucket Pick up Crabs in a Bucket direct from Blue Rondo Games: https://shop.bluerondogames.com/products/crabs-in-a-bucket-1 Check out the Shrimpocalypse expansion: https://shop.bluerondogames.com/products/crabs-in-a-bucket-shrimpocalypse Get both, with a playmat in a bundle: https://shop.bluerondogames.com/products/super-bundle-base-game-shrimpocalypse-collectors-box-play-mat (00:56:03) The Game Room - Our Secret Society Pick up Our Secret Society direct from uloomi: https://www.uloomi.com/games/our-secret-society Check out our review of uloomi's other game The Vibe: https://tabletopbellhop.com/podcast/ep304/ Pick up a copy of The Vibe: https://www.uloomi.com/games/the-vibe (01:04:13) The Game Room - The Ticket Booth Remember you can always save 15% off when shopping direct from Grandpa Beck's Games with our code BELLHOP Pick up The Ticket Booth: https://www.grandpabecksgames.com/products/the-ticket-booth?sca_ref=9131133.6jeLXLbaBX Check out their other games: https://www.grandpabecksgames.com/collections/all?sca_ref=9131133.6jeLXLbaBX Visit the Grandpa Beck's Games Amazon Store: https://amzn.to/4wZebsg Check out our other Grandpa Beck's Games Content: https://tabletopbellhop.com/search/?q=Grandpa%20Beck%27s (01:14:34) Closing the Doors Send feedback to moe@tabletopbellhop.com deanna@tabletopbellhop.com or sean@tabletopbellhop.com TIP THE BELLHOP: Get bonus content by becoming a Patron: https://www.patreon.com/tabletopbellhop Shop Tabletop Bellhop merch https://tabletopbellhop.com/merch Buy us a coffee https://ko-fi.com/tabletopbellhop FIND US: Webpage: https://tabletopbellhop.com Discord: https://discord.tabletopbellhop.com Blue Sky: https://bsky.app/profile/tabletopbellhop.com Instagram: https://www.instagram.com/tabletopbellhop/ Facebook: https://www.facebook.com/tabletopbellhop/ YouTube: https://www.youtube.com/tabletopbellhop Twitch: https://twitch.tv/tabletopbellhop

Part 1 of our Terminus 2026 interviews kick off with E.T., Haunt Me and Home Front! Plus, this week's edition of Into The Vault features Vromb!Playlist: Mort d'Homme - Bench Of SorrowsChurch of Trees - AngryThe Library is On Fire - Ground Of The LastFeaster - GeneTelehealth - Maria, MachineVromb - Dans La MaisonVromb - Le Facteur Humain 1Vromb - La RayureParlour Magic - EmbassyJoseph Tholl - It Might Be ArtManicburg - All Together Now - Recorded Live at The Brooklyn PearlCheckmate - Favorite SongMoonspell - Far From GodE.T. - Alien BabyHaunt Me - DevourHome Front - For The Children (Fuck All)BIG|BRAVE - an uttering of antipathyGaldorcraeft - LegacyViolet Grohl - Pool Of My DreamsDevon Parkin - I WishWidowspeak - RosesCherry Pick - :3 / Asleep With The Fishes

We're back home and semi-rested after one of if not the best Terminus Festivals yet. Four days of legendary acts delivering, bands just entering their heyday making excellent showings, and a handful of unexpected surprises from hitherto unknown to us acts still has us buzzing, so join us on our day-by-day recap on this week's podcast. 

Our pair of records on the podcast this week tilts towards the Germanic, with Die Krupps' 2013 release The Machinists Of Joy holding up as one of the veterans' strongest efforts upon review, and Oklahoman act Karger Traum's III still shining as an homage to classic NDW experimentation. We're also looking ahead to Terminus next week and playing America's favourite game show, "Giallo or Inkubus Sukkubus?". 

Steve & Izzy continue Tubi July (pronounced Tu-bee Ju-lee or Tu-bi Ju-li?), the month dedicated to post-apocalyptic movies available on Tubi, as they discuss 1987's "Terminus" starring Jurgen Prochnow, Karen Allen, French Elvis & more!!! How will our dog Tess joining the podcast for the first time go? Do you like Steve trying out French & German accents? Should a computer system be sassy?!? Let's find out!!! So kick back, grab a few brews, choose the light, and enjoy!!! This episode is proudly sponsored by Untidy Venus, your one-stop shop for incredible art & gift ideas at UntidyVenus.Etsy.com and be sure to follow her on Twitter, Facebook, Instagram & Patreon at @UntidyVenus for all of her awesomeness!!! Try it today!!! Twitter - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.twitter.com/eilfmovies⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Facebook - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.facebook.com/eilfmovies⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Etsy - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.untidyvenus.etsy.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ TeePublic - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.teepublic.com/user/untidyvenus⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices

The Lake Radio og spRadio får i dag besøg af fotografen Emilie Grønning og gruppen spellchestra. Først er husets professionelle fotograf på banen, og vi snakker om at finde folk der græder til koncerter og at få bank med en oppustelig krokodille og circle pits. Spellchestra taler om den romerske gud Terminus, og gør regnskab over mængden af spørgsmål overfor mængden af svar, hvilket resulterer i en rabatkode på 1 million. Vi lytter til haloplus+, Salver og Los Thutanaka.

This episode originally aired in September of 2024, however it was jam-packed with so many valuable insights I wanted to share it again. In this throwback rewind we're thrilled to welcome Jason Yarborough, a seasoned professional with a diverse background that includes roles such as:Director of OperationsAssistant Store Manager at StarbucksSales Representative/Account ExecutiveDirector of Marketing/StrategyVP of PartnershipsT-Ball Coach He currently guides partner programs to scalability through GTM training, program development, and coaching. He co-hosts the "Friends with Benefits" podcast with his wife, Sam. In this week's episode, we discussed:His journey from being a generalist to becoming a strategic partner in the business world.How he bridges the gap between agencies and leadership challenges.His diverse career experience, from operations at Starbucks to marketing and partnerships at companies like Garden of Life, Social Fresh, Terminus, and Arcadia.The importance of building long-term relationships and creating engagement through thoughtful experiences.Jason also emphasized the importance of partner experience, long-term relationship building, and creating engagement through thoughtful moments. He highlighted the "Disney Experience" approach, where partners feel seen, heard, and known, and discussed the need to move beyond transactional relationships by offering advanced training and focusing on where to invest time effectively. Please enjoy this week's episode with Jason Yarborough! I am now in the early stages of writing my first book! It will cover my journey into sales, the lessons learned, and include stories and advice from top sales professionals around the world. I'm excited to share these interviews and bring you along on this journey!Like the show? Subscribe to the email: Subscribe HereI want your feedback! Reach out at 20percentpodcastquestions@gmail.com or connect with me on LinkedIn.If you know anyone who would benefit from this show, please share it! If you have suggestions for guests, let me know!Enjoy the show!

Castanheira, bálsamo, cumaru e amburana. Enquanto o mundo cervejeiro olha para o carvalho americano e europeu, a Daora Vida foi buscar identidade nas madeiras nativas brasileiras, e o resultado chegou ao topo do World Beer Cup 2026.Neste episódio, Henrique Boaventura conversa com Wagner Falci, co-fundador da Daora Vida, sobre a construção do projeto Terminus: uma Barley Wine envelhecida em madeiras nativas brasileiras que acumula medalhas nos maiores concursos do mundo.O que você vai aprender:Por que madeiras brasileiras oferecem um diferencial real em concursos internacionaisO perfil sensorial de castanheira, bálsamo, cumaru e amburana, e o tempo ideal de cada umaA técnica de double mash por trás da Terminus: brasagens de 26 a 40 horas para atingir OG acima de 1.135Por que barris pequenos não funcionam bem para caseiros, e quais alternativas usarComo fazer uma infusão sensorial em álcool neutro para aprender o perfil de cada madeira antes de usá-la na cervejaCom Wagner Falci, co-fundador da Daora Vida, cervejaria de Campinas referência no uso de madeiras nativas brasileiras.

O que pode virar manchete nesta semana?

In this triumphant (if bite-sized) return for I Hate Video Games, your host examines Crimsonland, an obscure early 00s twin-stick shooter that just might be the best of its genre. Terminus links: Terminus on Youtube Terminus on Patreon TDMG on Substack thetrueterminus@gmail.com

Ilka Hein spricht mit dem evangelischen Pfarrer Martin Michaelis aus Quedlinburg, der vor zwei Jahren als parteiloser Kandidat für die Liste der AfD für den Stadtrat der Harzstadt in Sachsen Anhalt angetreten ist. Mittlerweile ist er stellvertretender Vorsitzender des Stadtrates, darf aber nicht mehr predigen, gegen ihn wurde ein Disziplinarverfahren von der Mitteldeutschen Kirche angestrengt, obwohl seine Bürgerrechte ihm das politische Engagement gestatten. Die EKD argumentiert, Teile des AFD Programmes seien mit christlichen Werten nicht vereinbar. Die katholische Kirche ihrerseits hat vor 14 Tagen bei ihrem Kirchentag den Solgan „Demokratiekirche“ ausgegeben, dem widerspricht der katholische Theologe und Blogger Peter Winnemöller, der sagt, die katholische Kirche sei per se keine demokratische, sondern eine hierarchisch organisierte Einrichtung, insofern der Terminus in keiner Weise greifen könne. Mit beiden rede ich über die immer größere Einmischung  - ja Agitation  -  der Kirchen innerhalb des politischen Geschehens und darüber wie demokratisch und wie christlich es ist, mit gewählten Parteien oder Volksvertretern nicht zu reden, sondern an gesellschaftlichen Feindbildern mitzuarbeiten.Achgut unterstützen: https://www.achgut.com/seite/achgut_spendenaufrufMit Paypal unterstützen: https://www.paypal.com/paypalme/achgutAchgut Pate werden: https://paten.achgut.comAchgut Buch-Shop: https://shop.achgut.comAchgut Newsletter bestellen: https://newsletter.achgut.com

The completed station was formally opened for use on 29 May 1854 to link London with the west of England and South Wales, reflecting the broader growth of rail transport during the mid-nineteenth ...

In his first work of nonfiction, poet chaun webster blends memoir, archival research, visual poetics, and cultural criticism to trace the ways structural anti-Black violence has shaped his inheritance, and grapples with the question of how to know—and mourn—the kin he was never able to meet.webster is particularly drawn to his grandfather Reginald, who worked for years as a Pullman porter, who was denied rest while his labor enabled rest for others, and who died without receiving a pension before webster was born. Returning to the figures of Reginald and the train, webster explores the relationship between comportment and confinement, speaking in tongues in the Pentecostal church, the ancestral meeting place of dreams, his fraught relationship with his mother, and moments with his own child. Throughout, webster also reflects on nonbiological kinship, tethering his and his predecessors' lives to those of several historical Black figures—Harriet Jacobs, John Henry, Henry “Box” Brown, and Henry Dumas, a writer who was killed by New York City police while riding the subway.Attempting to exhaust the possibilities of the sentence and the grammar of anti-Blackness, webster riffs and rails on the debris within reach. Part elegy, part archival detective story, and part visual poem, Without Terminus: untraining an archive (Greywolf, 2026) is a philosophically rigorous and deeply moving text that takes us beyond the archive of loss. You can find the works chaun references during our conversation, as well as a further discussion about literary form, at the Additions to the Archive Substack. Follow chaun webster on Instagram. Subscribe, like, follow, and rate Additions to the Archive with Sullivan Summer on Instagram, Substack, and wherever you get your podcasts. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/new-books-network

In his first work of nonfiction, poet chaun webster blends memoir, archival research, visual poetics, and cultural criticism to trace the ways structural anti-Black violence has shaped his inheritance, and grapples with the question of how to know—and mourn—the kin he was never able to meet.webster is particularly drawn to his grandfather Reginald, who worked for years as a Pullman porter, who was denied rest while his labor enabled rest for others, and who died without receiving a pension before webster was born. Returning to the figures of Reginald and the train, webster explores the relationship between comportment and confinement, speaking in tongues in the Pentecostal church, the ancestral meeting place of dreams, his fraught relationship with his mother, and moments with his own child. Throughout, webster also reflects on nonbiological kinship, tethering his and his predecessors' lives to those of several historical Black figures—Harriet Jacobs, John Henry, Henry “Box” Brown, and Henry Dumas, a writer who was killed by New York City police while riding the subway.Attempting to exhaust the possibilities of the sentence and the grammar of anti-Blackness, webster riffs and rails on the debris within reach. Part elegy, part archival detective story, and part visual poem, Without Terminus: untraining an archive (Greywolf, 2026) is a philosophically rigorous and deeply moving text that takes us beyond the archive of loss. You can find the works chaun references during our conversation, as well as a further discussion about literary form, at the Additions to the Archive Substack. Follow chaun webster on Instagram. Subscribe, like, follow, and rate Additions to the Archive with Sullivan Summer on Instagram, Substack, and wherever you get your podcasts. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/literary-studies

In his first work of nonfiction, poet chaun webster blends memoir, archival research, visual poetics, and cultural criticism to trace the ways structural anti-Black violence has shaped his inheritance, and grapples with the question of how to know—and mourn—the kin he was never able to meet.webster is particularly drawn to his grandfather Reginald, who worked for years as a Pullman porter, who was denied rest while his labor enabled rest for others, and who died without receiving a pension before webster was born. Returning to the figures of Reginald and the train, webster explores the relationship between comportment and confinement, speaking in tongues in the Pentecostal church, the ancestral meeting place of dreams, his fraught relationship with his mother, and moments with his own child. Throughout, webster also reflects on nonbiological kinship, tethering his and his predecessors' lives to those of several historical Black figures—Harriet Jacobs, John Henry, Henry “Box” Brown, and Henry Dumas, a writer who was killed by New York City police while riding the subway.Attempting to exhaust the possibilities of the sentence and the grammar of anti-Blackness, webster riffs and rails on the debris within reach. Part elegy, part archival detective story, and part visual poem, Without Terminus: untraining an archive (Greywolf, 2026) is a philosophically rigorous and deeply moving text that takes us beyond the archive of loss. You can find the works chaun references during our conversation, as well as a further discussion about literary form, at the Additions to the Archive Substack. Follow chaun webster on Instagram. Subscribe, like, follow, and rate Additions to the Archive with Sullivan Summer on Instagram, Substack, and wherever you get your podcasts. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/literature

In his first work of nonfiction, poet chaun webster blends memoir, archival research, visual poetics, and cultural criticism to trace the ways structural anti-Black violence has shaped his inheritance, and grapples with the question of how to know—and mourn—the kin he was never able to meet.webster is particularly drawn to his grandfather Reginald, who worked for years as a Pullman porter, who was denied rest while his labor enabled rest for others, and who died without receiving a pension before webster was born. Returning to the figures of Reginald and the train, webster explores the relationship between comportment and confinement, speaking in tongues in the Pentecostal church, the ancestral meeting place of dreams, his fraught relationship with his mother, and moments with his own child. Throughout, webster also reflects on nonbiological kinship, tethering his and his predecessors' lives to those of several historical Black figures—Harriet Jacobs, John Henry, Henry “Box” Brown, and Henry Dumas, a writer who was killed by New York City police while riding the subway.Attempting to exhaust the possibilities of the sentence and the grammar of anti-Blackness, webster riffs and rails on the debris within reach. Part elegy, part archival detective story, and part visual poem, Without Terminus: untraining an archive (Greywolf, 2026) is a philosophically rigorous and deeply moving text that takes us beyond the archive of loss. You can find the works chaun references during our conversation, as well as a further discussion about literary form, at the Additions to the Archive Substack. Follow chaun webster on Instagram. Subscribe, like, follow, and rate Additions to the Archive with Sullivan Summer on Instagram, Substack, and wherever you get your podcasts. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/poetry

In Episode 2 of Mini Matters we sit down with Rivers Hedrick to get a brief preview of LAO, winning ROTY, plans for the 2026 season, and what she's up to now that her home park Terminus closed. We also dive into pro shops and run through some thoughts and ideas she has on how to continue to establish them as “home bases” for the wakeboard community. Follow Rivers: https://www.instagram.com/rivershedrick/Support the show: https://www.patreon.com/GrabMattersPodcastGrab Matters Website: https://www.grabmatters.com/Chapters:00:00 - 1:00 Intro1:15 LAO Preview3:50 ROTY7:40 Retailers/Community 28:00 2026 plans36:00 Boat riding..?38:00 ROTY TripLinks:https://alliancewake.com/wake/2025-rider-of-the-year-rivers-hedrick/Shoot us a text!Patreon: https://www.patreon.com/GrabMattersPodcastWebsite: https://www.grabmatters.com/YouTube: https://www.youtube.com/@grabmatters/videosInstagram: https://www.instagram.com/grabmatters/TikTok: https://www.tiktok.com/@grabmatterspodcastFacebook: https://www.facebook.com/grabmatters

On the second part of our goth extravaganza, your hosts review two seminal records by Danzig and Type O Negative. Danzig's eponymous debut presents a fascinating take on goth rock which maintains a strident hardcore discipline, while Type O Negative's fourth shows the band at their darkest and most extreme doom metal form. Throughout it all: an exploration of how Danzig and Steele use the same DNA to produce wildly different animals. 0:00:00 - The Agnostic Front Incident 0:10:19 - Key Aesthetic Distinctions 0:25:35 - Danzig - Danzig I (Def American Recordings, 1988) 1:41:11 - Albert King - “The Hunter” fr. Born Under a Bad Sign (Stax Records, 1967) 1:43:55 - Type O Negative - World Coming Down (1999) 2:44:29 - Dishell - “Xero Tolerance” fr. Blast No. 1 - Blastbeat Tribute to Type O Negative (783punx, 2023) Terminus on Youtube Terminus on Patreon TDMG on Substack thetrueterminus@gmail.com

“Bienaventurados los muertos que mueren en el Señor”, dice el libro del Apocalipsis. ¿Preparamos ese momento? Los antiguos decían: Memento mori, y decían también: Terminus vitae, non amoris. Nos llevaremos al amor con que nos muramos: mors, mortem superávit. Así las cosas, comprenderemos la importancia de la pastoral de los que están cerca del trance por enfermedad o vejez, y los podremos ayudar.  

durée : 00:52:10 - Le Cours de l'histoire - par : Xavier Mauduit - De nos jours, la période médiévale est perçue comme un âge d'or par le récit national hongrois. Décryptage de l'Europe centrale au Moyen Âge, entre conquête magyare, christianisation et invasion des Mongols. - réalisation : Anne-Toscane Viudes, Jeanne Delecroix, Marion Dupont, Milena Aellig, Sophie-Catherine Gallet, Maïwenn Guiziou, Anna Grumbach - invités : Marie-Madeleine de Cevins Professeure d'histoire du Moyen Âge à l'université Rennes 2 et membre senior de l'Institut Universitaire de France Vous aimez ce podcast ? Pour écouter tous les épisodes sans limite, rendez-vous sur Radio France

A snack shop pops up on night selling detergent, rocks and human teeth. But the most enticing of all is a glowing lava lamp in the corner. Go to https://lolablankets.com/ and get 40% off select Lola Blankets products by using code CREEPCAST at checkout. Experience the world's #1 blanket with Lola Blankets. Over 2.5 Million Butts Love TUSHY. Get 10% off Tushy with the code CREEPCAST at https://hellotushy.com/CREEPCAST! #tushypod #sponsored Read Lucille's Late Night Snack Bar here: https://substack.com/@alanadavis2/p-1... Pick up a copy of Terminus 3: https://www.mvmediaatl.com/product-pa... Insta:   / alana_writes_stories   Join the Creep Cast patreon to get exclusive content, interviews and more!   / creepcast   Listen to CreepCast on ApplePodcasts: https://podcasts.apple.com/us/podcast... Follow us on Twitter:   / creepcastactual   Learn more about your ad choices. Visit megaphone.fm/adchoices

We have the second ever guest on Grab Matters, Daniel Jarrett, and joined by a staple of the show, Garrett Cortese, down in Orlando to chop it up. We are talking women being back on the PWT, Olympics 2032, WSIA Summit recap, Cable/Boat etiquette, brand imaging, Terminus, and a preview of the 2026 season. Hear all that and much more in Episode 12 of Shop Talk!Follow Daniel: https://www.instagram.com/danielstorzjarrett/Follow West Rock Wake Park: https://www.instagram.com/westrockwakepark/Follow Garrett: https://www.instagram.com/garrettcortese/Follow Hunter: https://www.instagram.com/hunterthane/Thank you to this shows sponsors! Liquid Force: https://www.liquidforce.com/ Slingshot: https://slingshotsports.com/Support the show: https://www.patreon.com/GrabMattersPodcastChapters:00:00 - 1:40 Intro1:50 Favorite grab 6:00 Women are back on the PWT18:00 Olympics/Cable tour30:30 WSIA Summit 35:40 LF'n Hot Seat45:00 Industry talk58:10 Slings Hot Takes1:14:00 Patreon Questions1:19:00 Etiquette 1:25:00 Exposure1:38:00 Brand imaging 1:55:20 Terminus2:00:20 2026 seasonShoot us a text!Patreon: https://www.patreon.com/GrabMattersPodcastWebsite: https://www.grabmatters.com/YouTube: https://www.youtube.com/@grabmatters/videosInstagram: https://www.instagram.com/grabmatters/TikTok: https://www.tiktok.com/@grabmatterspodcastFacebook: https://www.facebook.com/grabmatters

Industrial Talk is onsite at PowerGen and talking to Bridget Youngs, Founder at Terminus Industrials about "Disrupting the transformer manufacturing market". Bridget Youngs, founder of Terminus, discussed her company's innovative approach to transformer manufacturing. Terminus aims to reduce production time from months to under two weeks by automating processes and using AI and robotics. They focus on 138-34.5 kV transformers, a critical need in the ERCOT territory. Bridget highlighted the challenges of standardizing equipment across 1,700 utilities and the inefficiencies in current manufacturing. Terminus plans to launch products in Q3 2027, leveraging a team with expertise from companies like GE and Tesla to streamline design and manufacturing. Outline Introduction and Welcome to Industrial Talk Scott introduces the episode of Industrial Talk, sponsored by the Propane Education and Research Council, focusing on safety, training, and innovative propane power technology.Scott thanks listeners for joining the top industrial podcast, celebrating industry professionals who solve problems daily.The podcast is broadcasting live from Power Gen in San Antonio, focusing on asset management and power generation. Introduction of Bridget Youngs Scott introduces Bridget Youngs, who is in the "hot seat" to discuss transformers.Bridget thanks Scott for having her and mentions the presence of many interested buyers and sellers at the event.Bridget shares her background in power development, including 10 years in oil and gas, renewables, and working for the federal government.She explains her decision to start Terminus, a company manufacturing large power transformers. Challenges and Opportunities in Transformer Manufacturing Bridget discusses the long lead times for interconnection with utilities, which can take 2 to 5 years.She highlights the shift in the longest lead time item from bureaucratic processes to equipment availability, particularly power transformers.Bridget explains her work on automating shipbuilding and how similar principles can be applied to power transformers.Terminus is focused on retooling and engineering equipment to quickly manufacture dynamic assets, reducing labor costs and production time. Specifics of Terminus' Transformer Manufacturing Bridget details the size range of transformers Terminus is focusing on, starting with 138 to 34.5 KV.She explains the demand for these transformers in the ERCOT territory, which has the longest 138 KV line.Bridget discusses the challenges of standardizing transmission voltage and the variations among different utility territories.She emphasizes the need for engineering order due to the different standards and safety measures required for equipment. Manufacturing Process and Innovations Bridget outlines the five major steps in transformer manufacturing: cutting and stacking cores, winding coils, drying in an autoclave, assembling the tank, and testing.She describes Terminus' approach to setting up a manufacturing line that can handle different sizes of transformers efficiently.Bridget highlights the team's mix of experienced engineers and robotics experts from companies like Tesla and John Deere.She discusses the importance of iterating quickly and carefully to avoid catastrophic failures in the deployed assets. Future Plans and Market Impact Bridget mentions that Terminus plans to start rolling out products in Q3 2027, primarily focusing on 138 to 34.5 KV transformers.She explains the design process, which involves pairing experienced engineers with software engineers to streamline the design and manufacturing process.Bridget emphasizes the importance of automation in reducing downtime and costs, despite higher labor and material costs in the US.She highlights the potential for delivering cheaper, safer, and more reliable assets to users on the grid and developers. Conclusion and Call to Action Scott praises Bridget's innovative approach to transformer manufacturing and the potential impact on the market.Bridget provides contact information for Terminus, encouraging listeners to reach out on LinkedIn or through the company's website.Scott encourages listeners to connect with Bridget and other problem solvers at events like Power Gen.The podcast concludes with a call to be bold, brave, and disruptive in the industry, inspired by Bridget's story. If interested in being on the Industrial Talk show, simply contact us and let's have a quick conversation. Finally, get your exclusive free access to the Industrial Academy and a series on “Why You Need To Podcast” for Greater Success in 2026. All links designed for keeping you current in this rapidly changing Industrial Market. Learn! Grow! Enjoy! BRIDGET YOUNGS' CONTACT INFORMATION: Personal LinkedIn: https://www.linkedin.com/in/bridget-youngs/ Company LinkedIn: https://www.linkedin.com/company/terminusindustrials/ Company Website: https://www.terminusindustrials.com/ PODCAST VIDEO: https://youtu.be/eMBfz5peKU0 THE STRATEGIC REASON "WHY YOU NEED TO PODCAST": OTHER GREAT INDUSTRIAL RESOURCES: NEOM: https://www.neom.com/en-us Hexagon: https://hexagon.com/ Arduino: https://www.arduino.cc/ Fictiv: https://www.fictiv.com/ Hitachi Vantara: https://www.hitachivantara.com/en-us/home.html Industrial Marketing Solutions:  https://industrialtalk.com/industrial-marketing/ Industrial Academy: https://industrialtalk.com/industrial-academy/ Industrial Dojo: https://industrialtalk.com/industrial_dojo/ We the 15: https://www.wethe15.org/ YOUR INDUSTRIAL DIGITAL TOOLBOX: LifterLMS: Get One Month Free for $1 – https://lifterlms.com/ Active Campaign: Active Campaign Link Social Jukebox: https://www.socialjukebox.com/ Industrial Academy (One Month Free Access And One Free License For Future Industrial Leader): Business Beatitude the Book Do you desire a more joy-filled, deeply-enduring sense of accomplishment and success? Live your business the way you want to live with the BUSINESS BEATITUDES...The Bridge connecting sacrifice to success. YOU NEED THE BUSINESS BEATITUDES! TAP INTO YOUR INDUSTRIAL SOUL, RESERVE YOUR COPY NOW! BE BOLD. BE BRAVE. DARE GREATLY AND CHANGE THE WORLD. GET THE BUSINESS BEATITUDES! Reserve My Copy and My 25% Discount

On this episode of The 3DO Experience, we are joined by Jake from Press B To Cancel to discuss the South Korean exclusive fighting game for the 3DO The Eye of Typhoon created by Viccom!Check Out Call of Duty: Thrak Ops: https://superpodnetwork.com/podcast/call-of-duty-thrak-opsCheck out Terminus by Retro Love Letter at: https://github.com/retroloveletter/terminus/releases/tag/game-demo-aFollow Jake at: https://pressbtocancel.com/Proud Member of https://superpodnetwork.com/Follow us at: https://linktr.ee/ThebarberwhogamesFollow Thrak at: https://bsky.app/profile/thrak.bsky.social

It's been a while, terminators- you may have suspected us of succumbing to the mainstream. Well, on this episode, perhaps we have- but with good reason. In the first half of this two-part project, The Black Metal Guy presents his Greater Unified Danzig/Steele Theory, in which Peter Steele's career trajectory eerily mirrors Glenn Danzig's, and how the work of each can shine new light on the other. Join us on a tour through the early days of these artists, through The Misfits, Carnivore, Samhain, and Repulsion, as we gather our powers for reviews of some of our favorites by both in the next installment. 0:00:00 - Intro/The Greater Unified Danzig/Steele Theory 0:40:24 - Interlude - Carnivore - “Carnivore” fr. Nuclear Warriors (Independent, 1984) 0:44:02 - Step 1 - Thrashing Hardcore (Late Misfits/Carnivore) 1:14:47 - Step 2 - Weird Transitional Albums (Samhain/Slow, Deep, and Hard) 1:47:11 - Interlude - The Misfits - “Last Caress” fr. Static Age (Caroline Records, 1978/1996) 1:49:08 - Step 3 - Full Gothic Metal Arrival (Danzig/Type O Negative) 2:58:04 - Outro - Danzig - “On a Wicked Night” fr. Deth Red Sabaoth (AFM Records, 2010) Terminus on Youtube Terminus on Patreon TDMG on Substack thetrueterminus@gmail.com

On January 20, a fatal derailment in Catalonia, just two days after the high-speed rail disaster in Andalusia, led to unprecedented levels of disruption, with the entire Rodalies network suspended several times due to safety concerns.  But the problems with Catalonia's rail network stretch much further back. In this episode of Filling the Sink, Lorcan Doherty and Cillian Shields examine Catalonia's Rodalies commuter rail network: decades of underinvestment, the recent Gelida accident and subsequent strikes and shutdowns, and the planned transfer of management from Spanish to Catalan authorities. Francisco Cárdenas, UGT union representative for Renfe workers in Catalonia, explains how years of neglect and insufficient maintenance have created a network that train drivers no longer feel safe operating. Rail expert Joan Carles Salmerón, director of private research center Terminus, provides his diagnosis of the structural weaknesses in Catalonia's rail infrastructure, including a disproportionate focus on high-speed lines at the expense of local commuter services.

Medverkande i detta avsnitt är: Fredrik. Poki och Vickan.I detta avsnitt bjuder vi på samtal om spel, film och mycket mer - allt i ett späckat format!Spel & spelrelaterat som tas upp:Carmageddon: Rogue Shift,The Eternal Life of Goldman (demo),REANIMAL (första intryck),Diablo II: Reign of the Warlock,The Last Spell,Film/TV/Anime/Musik som tas upp:"The book that broke the world" av Mark Lawrence,"RuriDragon" av Masaoki Shindo,Terminus,Keyflower,A place for all my books,Ex LibrisRaiders of Scythia,Reincarnated as a Dragon Hatchling,Noble Reincarnation: Born Blessed, So I'll Obtain Ultimate Power,Övrigt som tas upp:Q & A för podden; Denna gång blir det tankar mest om Bluepoint Games som läggs ner - samt lite av varje från vår lyssnarskara.Kom med i vår Discord här! - Nördliv på iTunes – Nördliv på Spotify

À l'occasion de la Saint-Valentin, Claudy Siar reçoit Eric Virgal et Annie Flore Batchiellilys pour une soirée exceptionnelle au Terminus Night Club de Mouila, entre rythmes caribéens, sonorités africaines et live festif. Ils répondent aux questions de Claudy Siar et Laura Mbakop. Eric Virgal  - Viv epiw Annie Flore Batchellilys - Diboti Eric Virgal ft Orlane - Et pourtant Annie Flore Batchellilys - Ino (exclusivité Couleurs Tropicales) Eric Virgal  - Coupable Annie Flore Batchellilys - Je t'invite.   Pour visionner les clips, cliquez sur les titres des chansons. Retrouvez la playlist officielle de RFI Musique.

À l'occasion de la Saint-Valentin, Claudy Siar reçoit Eric Virgal et Annie Flore Batchiellilys pour une soirée exceptionnelle au Terminus Night Club de Mouila, entre rythmes caribéens, sonorités africaines et live festif. Ils répondent aux questions de Claudy Siar et Laura Mbakop. Eric Virgal  - Viv epiw Annie Flore Batchellilys - Diboti Eric Virgal ft Orlane - Et pourtant Annie Flore Batchellilys - Ino (exclusivité Couleurs Tropicales) Eric Virgal  - Coupable Annie Flore Batchellilys - Je t'invite.   Pour visionner les clips, cliquez sur les titres des chansons. Retrouvez la playlist officielle de RFI Musique.

Terminus broke away from old habits in 2025 to concentrate on investigating older records and new types of content. But many of you desperately sought our sage advice on the best records of 2025, so here it is: a different version of our usual yearly Omega episode. This time, your hosts tackle the project of evaluating a pretty quiet year in two different ways. TBMG provides a sampler platter of ten records with lightning round reviews, concentrating on dark heathen black metal, and TDMG provides a tight top 5 of his favorites for the year, with an emphasis on vision and ambition. Welcome to 2026, Terminators. 0:00:00 - Intro/TBMG Presents 10 1:58:59 - Interlude - Brazen Horde - “Purgation, Thy Foul Lash” fr. Behold! The Ashen Cross (Nithstang/Blackseed, 2025) 2:04:43 - TDMG's Top 5 4:01:33 - Outro - Umulamahri - “Leaked Photo of Heaven” fr. Learning the Secrets of Acid (Ordovician Records, 2025) Terminus on Youtube Terminus on Patreon TDMG on Substack thetrueterminus@gmail.com

Discover how combining strategic thinking, integrated campaigns, and strong team execution transforms marketing from a chaotic expense into a predictable growth engine. In this episode of Sharkpreneur, Seth Greene interviews Andrew Seidman, COO and Co-Founder of Digital Reach Agency, a former professional poker player turned marketing strategist who helps global enterprises and well-funded startups achieve measurable growth. With over a decade of experience leading multi-channel campaigns using platforms like Google, LinkedIn, Facebook, Demandbase, and 6sense, Andrew is known for turning complex digital challenges into streamlined, high-impact solutions. In this episode, he shares lessons on building repeatable processes, integrating teams, and leveraging data to drive meaningful results. Key Takeaways: → The importance of focusing on process rather than short-term results in marketing and operations. → Understanding the core challenges companies face in generating qualified leads and pipeline. → The value of integrating branding, content, digital experience, and revenue operations into one cohesive strategy. → How multi-channel campaigns deliver measurable impact across platforms like Google, LinkedIn, and social media. → Scaling teams effectively while maintaining culture, accountability, and alignment across geographies. Andrew Seidman is the COO and Co-Founder of Digital Reach Agency, where he has played a key role since 2013. Based in Brooklyn, New York, Andrew works closely with global enterprises to develop and implement strategies for Account-Based Marketing (ABM), Demand Generation, and Product-Led Growth (PLG) motions. He leads global advertising campaigns using platforms like Google, LinkedIn, Bing, Facebook, Demandbase, 6sense, and Terminus. Andrew coordinates resources to drive the agency's growth while providing support to the sales and technology teams to ensure exceptional customer service. With over 12 years of experience, Andrew is dedicated to delivering end-to-end digital strategies that drive success for clients around the world. Connect With Andrew: Instagram: https://www.instagram.com/digitalreachagency/ X: https://x.com/digitalreachb2b Facebook: https://www.facebook.com/DigitalReachAgency/ LinkedIn: https://www.linkedin.com/company/digital-reach-agency/ Youtube: https://www.youtube.com/c/Digitalreachagency Learn more about your ad choices. Visit megaphone.fm/adchoices

Discover how combining strategic thinking, integrated campaigns, and strong team execution transforms marketing from a chaotic expense into a predictable growth engine. In this episode of Sharkpreneur, Seth Greene interviews Andrew Seidman, COO and Co-Founder of Digital Reach Agency, a former professional poker player turned marketing strategist who helps global enterprises and well-funded startups achieve measurable growth. With over a decade of experience leading multi-channel campaigns using platforms like Google, LinkedIn, Facebook, Demandbase, and 6sense, Andrew is known for turning complex digital challenges into streamlined, high-impact solutions. In this episode, he shares lessons on building repeatable processes, integrating teams, and leveraging data to drive meaningful results. Key Takeaways: → The importance of focusing on process rather than short-term results in marketing and operations. → Understanding the core challenges companies face in generating qualified leads and pipeline. → The value of integrating branding, content, digital experience, and revenue operations into one cohesive strategy. → How multi-channel campaigns deliver measurable impact across platforms like Google, LinkedIn, and social media. → Scaling teams effectively while maintaining culture, accountability, and alignment across geographies. Andrew Seidman is the COO and Co-Founder of Digital Reach Agency, where he has played a key role since 2013. Based in Brooklyn, New York, Andrew works closely with global enterprises to develop and implement strategies for Account-Based Marketing (ABM), Demand Generation, and Product-Led Growth (PLG) motions. He leads global advertising campaigns using platforms like Google, LinkedIn, Bing, Facebook, Demandbase, 6sense, and Terminus. Andrew coordinates resources to drive the agency's growth while providing support to the sales and technology teams to ensure exceptional customer service. With over 12 years of experience, Andrew is dedicated to delivering end-to-end digital strategies that drive success for clients around the world. Connect With Andrew: Instagram: https://www.instagram.com/digitalreachagency/ X: https://x.com/digitalreachb2b Facebook: https://www.facebook.com/DigitalReachAgency/ LinkedIn: https://www.linkedin.com/company/digital-reach-agency/ Youtube: https://www.youtube.com/c/Digitalreachagency Learn more about your ad choices. Visit megaphone.fm/adchoices

A handful of videos on social media depict a recent gathering, reportedly in Georgia, where a group of people were gathered to chant “Atlanta” is “Atlantis.” Supposedly they were there to create an “energy vortex” in order to summon the spirit of Atlantis and reclaim the city for black people. What exactly is this supposed to mean?Atlanta was founded in 1837 as a railroad terminus originally named "Terminus,” because the city marked the end of the Western & Atlantic Railroad. It was renamed "Marthasville" in 1843 and then changed to "Atlanta" in 1845. Some believe the city name is a shorthand for “Atlantica,” as in the Atlantic Ocean. Others believe the city was named after Atalanta, a mythologized heroin known for her speed and independence (the wild boar hunt and race against her suitors) which were qualities of the growing rail hub that is Atlanta. The mythical land and concept of Atlantis in some ways even predates Plato, though he is credited with its story. Writing in his Timaeus and Critias Plato derived the Atlantis story from Solon, an Athenian lawmaker who learned of the same from an elderly priest in the land of Egypt at the Temple of Sais. At the time, around 630-560 BC, the records were already at least 8,000 years old. Reportedly a global cataclysm destroyed Atlantis sometime between 9,600 to 11,600 years ago. Later on Francis Bacon termed his ideal city the New Atlantis or Platonopolis. The timeframe noted by Plato places the destruction within the window of the Younger Dryas, 12,900 to 11,700 years ago (10,900-9,7000 BC). It's one thing to be unaware of seemingly lost, drowned or buried history, but another to be so shockingly unaware of basic mythology and recent local history. It is understandable so many are disenfranchised by the lies and ego of mainline historical narratives, but the turn to Q-Anon, Flat Earth, Tataria, and World Fair conspiracies appears to be another layer of disinformation rather than the truth. The “Atlanta is Atlantis” video exemplifies a growing stupidity about human history. *The is the FREE archive, which includes advertisements. If you want an ad-free experience, you can subscribe below.WEBSITEFREE ARCHIVE (w. ads)SUBSCRIPTION ARCHIVE-X / TWITTERFACEBOOKINSTAGRAMYOUTUBERUMBLE-BUY ME A COFFEECashApp: $rdgable PAYPAL: rdgable1991@gmail.comRyan's Books: https://thesecretteachings.info - EMAIL: rdgable@yahoo.com / rdgable1991@gmail.comBecome a supporter of this podcast: https://www.spreaker.com/podcast/the-secret-teachings--5328407/support.

Jacob who fronts the band "All Hell" out of North Carolina comes on the show to talk to us about the band, their latest album, shows, and more. Their new album "Sunsetter" was released October 10th this year and is a must hear for metal releases this year! check it out on all streaming services and hit the links below to follow them on Instagram and pick up the record released from "Terminus Hate City"Noise Avocation | All Hell | Terminus Hate City | Sunsetter Vinyl

The worm turns back in The Death Metal Guy's direction with an episode centered on Vehemence, cult melodic death metal legends from Phoenix, Arizona. Covering the band's two early 00s masterpieces, your hosts attempt to crack the code on how a band from the deserts of the west managed to beat every band from Gothenburg at their own game, with a uniquely American style and flair. 0:00:00 - Intro/What is Gothenburg? 0:21:30 - God Was Created (Metal Blade, 2002) 1:10:42 - Interlude - Eucharist - “Into The Cosmic Sphere” fr. A Velvet Creation (Wrong Again Records, 1993) 1:15:05 - Helping the World to See (Metal Blade, 2004) 2:12:04 - Outro - Vehemence - “Murdered by the Earth” fr. Forward Without Motion (Battleground Records, 2015) Terminus on Youtube Terminus on Patreon TDMG on Substack thetrueterminus@gmail.com

Charles Skaggs and Jesse Jackson discuss "Terminus", the fourth serial from Doctor Who Season 20 in 1983, featuring Peter Davison as the Fifth Doctor, Janet Fielding as Tegan Jovanka, Mark Strickson as Vislor Turlough, and the departure of Sarah Sutton as Nyssa! Find us here:Instagram: @nextstopeverywherepodcast Facebook: Facebook.com/Nextstopeverywherepodcast Bluesky: @charlesskaggs.bsky.social, @jessejacksondfw.bsky.social Email: NextStopWho@gmail.com Listen and subscribe to us in Apple Podcasts and leave us a review!

After much anticipation, innumerable references on the show, and a shocking number of technical issues, we have arrived with an episode that The Black Metal Guy has been threatening for years. For those unfamiliar, Dawn is one of the finest and also one of the most underappreciated bands of the Swedish 90s melodic black/death metal scene, and one very near and dear to The Black Metal Guy's heart. Join us as we investigate the band's two full-length records and discover what makes them far more than merely another band in the established style. 0:00:00 - Intro/Background of Dawn 0:15:08 - Nær Sólen gar Niþer for Evogher (Necropolis Records, Jan 6 1994) 1:29:34 - INTERLUDE - Taake - “Hordaland doedskvad I,” fr. Hordalands doedskvad (Dark Essence, 2005) 1:37:17 - Slaughtersun (Crown of the Triarchy) (Necropolis Records, May 7 1998) 3:28:47 - OUTRO - Dawn - “Incantation of Unholyness,” fr. the Apparition demo (December 1992) Terminus on Youtube Terminus on Patreon TDMG on Substack thetrueterminus@gmail.com

This episode on MUP, Keepers Dave & Bridgett discuss Systemless Horror Game with creator Sarah Cole! Patreon Plug & Update If you would like to support the podcast and engage with other backers, please consider backing.  So yes - please back us on Patreon! To back us you can click the button on the sidebar of our website, mu-podcast.com or head over to Patreon directly at www.patreon.com/mup! Oh! We have a new backer! Jason Wiebe! Thank you to everyone who backed us and contributed to our longevity. We're so thankful for all of you. Who we regularly see on… The Discord Plug Our MUP Discord and we are all there! We invite all of our listeners to come and enjoy the community of horror gaming and cute pet pics. Link in the show notes: MU Discord server invite link: https://discord.gg/vNjEv9D  And thank you to our editor Ben for editing this episode.  Bridgett's Pet Pick Shout Out Tonight I'd like to shout out … from JZ! Cowboy is the biggest of my cats and all muscle but such a sweet softie. They often have to run water at the vet to distract him from purring so they can listen to his heart and lungs. Main Topic Welcome to Sarah Cole. For those who don't know you, please introduce yourself. How we got here Dave has opinions on systemless horror - we should do it more Dave backed Terminus and bought and consumed DH&D quickly Welcome! Let's start with the most important question: https://www.patchworkfez.games/

Keith discusses strategies for amplifying investing returns and reducing lifetime tax burdens through real estate, geography, and industry.  He compares tax burdens by state and explains how investors can leverage low-income tax states and low-property tax states.  Podcast host, investor and developer, Victor Menasce, joins the conversation to highlight the industrial real estate market, emphasizing the demand for warehousing and logistics.They touch on the potential in industrial outdoor storage and the complexities of data center investments. Reach out to Y Street Capital to learn more about their projects and the real estate espresso podcast. Resources: Switch to listening to the podcast on the Apple Podcasts or Spotify app, as the dedicated GRE mobile app will be discontinued at the end of the month. Show Notes: GetRichEducation.com/577 For access to properties or free help with a GRE Investment Coach, start here: GREmarketplace.com GRE Free Investment Coaching: GREinvestmentcoach.com Get mortgage loans for investment property: RidgeLendingGroup.com or call 855-74-RIDGE  or e-mail: info@RidgeLendingGroup.com Invest with Freedom Family Investments.  For predictable 10-12% quarterly returns, visit FreedomFamilyInvestments.com/GRE or text  1-937-795-8989 to speak with a freedom coach Will you please leave a review for the show? I'd be grateful. Search “how to leave an Apple Podcasts review”  For advertising inquiries, visit: GetRichEducation.com/ad Best Financial Education: GetRichEducation.com Get our wealth-building newsletter free— text ‘GRE' to 66866 Our YouTube Channel: www.youtube.com/c/GetRichEducation Follow us on Instagram: @getricheducation Complete episode transcript: Keith Weinhold  0:00   Welcome to GRE. I'm your host. Keith Weinhold, we're talking about how you can use real estate, geography and industry to amplify your investing returns over the course of your life and permanently reduce your lifetime tax burden today on Get Rich Education.   Keith Weinhold  0:21   You know, most people think they're playing it safe with their liquid money, but they're actually losing savings accounts and bonds don't keep up when true inflation eats six or 7% of your wealth. Every single year, I invest my liquidity with FFI freedom family investments in their flagship program. Why fixed 10 to 12% returns have been predictable and paid quarterly. There's real world security backed by needs based real estate like affordable housing, Senior Living and health care. Ask about the freedom flagship program when you speak to a freedom coach there, and that's just one part of their family of products. They've got workshops, webinars and seminars designed to educate you before you invest, start with as little as 25k and finally, get your money working as hard as you do. Get started at Freedom, family investments.com/gre, or send a text. Now it's 1-937-795-8989 77958989, yep, text their freedom coach directly. Again, 1-937-795-8989,   Corey Coates  1:34   you're listening to the show that has created more financial freedom than nearly any show in the world. This is get rich education.   Keith Weinhold  1:49   Welcome to GRE from Milford, Delaware to Milford, Utah and across 188 nations worldwide. I'm Keith Weinhold, and this is get rich education, the voice of real estate investing since 2014 now, what do you think about a multi week government shutdown? That means there's a cut in your service level, but of course, oh geez, there's no commensurate cut in the amount of taxes that you pay. This is the government's version of charging rent on a vacant unit. That's what's happening. That's what we've been looking at in the biggest expense you'll ever pay in your life. It isn't housing, it's taxes. Before I get to how you can reduce the amount of taxes that you'll pay throughout the course of your life, which is huge. Let's pull back, and I guess it's a bit of a real estate geography riddle for you, imagine if there were a place that existed, and this place is within a 15 minute drive of a seacoast, 15 minutes of mountains, within 15 minutes of an urban core of about 300,000 people, and within 15 minutes of an international airport and a decent airport that has direct, non stop flights to Europe. Even, could that place exist all of that? I mean, it almost sounds too good to be true when I put it like that, yes, it does, and it's in the United States. On top of that, this same place with proximity, within 15 minutes of all four of those things, has zero state income tax and zero sales tax. Yes, all this is in the same place, and that's where I am coming to you from today, Anchorage, Alaska. I traveled a good bit, and I can't think of another place in the US quite like it. A quick check of Chad GPT corroborates this, saying that the US places that come closest are Honolulu, Juneau and Bellingham, Washington. They come the closest to that. Now, the biggest downside, in my opinion, is a long, dark, cold winter. Well, that's when I do more traveling, but I spend many months of the year right here in Anchorage. And my guest today, who you'll hear from later, I haven't had him on the show in years, where recently he I and his wife, Natasha, toured Anchorage. I drove them around.   Keith Weinhold  4:29   first, let me tell you about a creative way to pay both a low property tax and a low income tax, and that is no matter what state or province that you live in now, the big three taxes that people pay throughout their lives are income tax, sales tax and a property tax. Those are the big three, and when you combine those to come up with the highest and lowest tax burdens by state, you'll notice that coastal states often pay the most. They generally have the biggest burden, because coasts attract people, and therefore those highly populated areas, they need infrastructure, say, for example, more bridges, and they often have more social services for people, and it costs tax money to maintain all of that. Now, look, will people move to an area specifically because they can get low taxes there? Like is that amenity in itself an attractant? Actually, not so much. No, you do get some people to move to Puerto Rico, predominantly for that reason. But interestingly, the two states with the lowest overall tax burden, that is, when you combine income, sales and property tax, the lowest are Alaska and Wyoming, and yet they have the fewest people living there, under 1 million people each. So the two states with the lowest tax burdens are also the two least populous states. So it is not making people flock there. So where you choose to live? Oh, that has more to do with your overall quality of life. And you know that's probably as it should be. Well, whether you own your home or you rent your home, you effectively do pay property tax, because tenants end up subsidizing the landlord's expenses. Most property tax maps that you see out there, those national property tax maps, they show the average tax bill that a household pays by state, regardless of real estate values. Well, that's not so useful. You might remember that a few weeks ago in our newsletter, I sent you the best and the smartest property tax map that I have by county. You'll remember that it showed the property tax paid as a percentage of the home value, so that relative basis is what matters more. When we look at property tax paid that way, we can more transparently see that the highest property taxes are generally paid in three US regions. Those three regions with the highest property taxes are the northeast, much of the Great Plains and Texas now a 1% property tax rate is, for example, when you have to pay 4000 bucks a year on a property value of 400k That's that 1% and the lowest are in the Western US and the nation's southeast quadrant, often under 1% we're just talking about the property taxes only here. Now out west, lower property taxes, they still rarely create investor cash flow, and that's because purchase prices are too high out west, and rents don't keep up with them proportionally. But low taxes, they do adequately sweeten the most investor advantaged areas, that is in the southeast Indiana, Missouri, Oklahoma, Hawaii, and a bunch of the Mid Atlantic states. All right, so they are the investor advantaged areas that also have low property tax. The nation's lowest property tax rate is in Alabama. Roll tide, I think I've mentioned that on the show before. All right, so that's property tax, but states have to get their revenue somewhere, so oftentimes, if their property tax is low, well then they have to make up for that. So therefore their income or sales tax can be high. Now as far as income tax, each state has their own of course, the high ones are New York, New Jersey, California and Hawaii. Those are many of the high ones. But there are nine states with zero, absolutely zero, state income tax, and those nine states that are free of income tax are the aforementioned, Alaska, Florida, Nevada, New Hampshire, South Dakota, Tennessee, Texas, Washington and Wyoming and Washington gets somewhat of an asterisk that has a little wrinkle in it. That's one of the nine with the wrinkle, you'll pay zero income tax on your wages in Washington. It only applies to high earners, capital gains tax income there, all right. Well, all of that is true for everybody there, every US citizen. But here's the arbitrage that a real estate investor can create. If you live in one state and you own property in another state, you always pay property tax where the property is physically located, not where you live. I mean, any longtime out of state real estate investor knows that. So you can therefore live in a state with little or no income tax, for example, Texas, and then a Texas resident can skirt Texas's higher property tax by investing in a different state that has low property tax, like, say, Alabama or Tennessee. Oh, well, now both your property tax and your income tax are low this way. And congratulations, you have just legally exploited the tax system. Some examples of a low income tax home state where you live and a low property tax investor state where your investment property is, so that you get the best of both worlds. They are, Texas is your home state, and Alabama is your investment property state, like I just described, and then a few other scenarios, so that you can legally use the system to pay both a low income tax and low property tax. Are having Pennsylvania as your home state and Missouri as your investor property state, having New Hampshire as your home state and Tennessee is your investor property state. And then another example, having Washington as your home state and Arkansas as your investor state. Those are just some examples of combinations there about how you can live in a low income tax state and then also enjoy having your investment property in a low property tax state and see perhaps now you're doing this without having to move. Yes, investing in low property tax states. Now, of course, property taxes are set at the county or city level. They're not set federally, but just within one state. Sometimes property tax can vary dramatically, which you probably know, but two of the biggest examples of this are in Illinois, Cook County, which is Chicago, and also Miami, Dade County, Florida. I mean those jurisdictions, they have tax rates that can make wallets cry more than their surrounding counties do, and some states have maximums, legal limits ceilings on property taxes. California proposition 13 famously limits property tax to 1% of assessed value, and then the increases are capped as well. I mean this means the two California neighbors with identical homes can pay wildly different taxes, and Florida is still looking to completely eliminate the property tax. Can you imagine that? I mean, it seems doubtful that that will happen, but you can conceive of how much more desirable that would make Florida properties, and that would probably make all Florida housing values skyrocket now, just because a property has a high property tax rate that doesn't disqualify it as an investment property alone, it's just one consideration that'll show up in your proforma, your cash flow. So the bottom line is that as an income property owner, property tax is mostly passed on to your tenant, but paying a low rate still keeps you more flexible and profitable. So think of a map of states with low property taxes, sort of like a treasure map, but instead of x marking the spot, it marks where your money will go the furthest.    Keith Weinhold  13:36   And if you want real estate maps like I'm talking about here, and stories and great charts and investment opportunities that I cannot fit onto the channel. Here, you can grab them in my free weekly newsletter at gre letter.com and part of this is because I just cannot adequately describe a map or a chart to you here in an audio format. You get more in the letter free wealth, building insight every week. And it comes straight from me. 1000s of investors read it every week. Don't live below your means. Grow your means. Get It At gre letter.com Again, that's gre letter.com   Keith Weinhold  14:20   something interesting just happened when Wells Fargo released their housing forecast for the next two years. Let's discuss that between today and 2027 they expect the federal funds rate to drop by a full 1% but they don't expect mortgage rates to drop as much only about a quarter point drop over the next two years in the 30 year fixed rate. For next year, they expect home prices to rise three and a half percent, and then the year after 3.7%. looking down the road a couple years here, and this is sorced by Wells Fargo economics and the US Department of Labor and the FHFA and more. All right, so only a small reduction in mortgage rates and a pickup in home price appreciation, although still pretty moderate. Now you gotta take any interest rate prediction with a grain of salt, like I've told you here before. I personally, I do not forecast interest rates, and when you're looking at interest rate predictions, you are squarely looking at a waste of your time.   Keith Weinhold  15:34   Now, a recent Gallup poll wanted to find out what Americans consider to be the best long term investment. That's the question that the pollsters asked, what is the best long term investment? And the findings were that 16% said stocks. I mean, despite the fact that stocks only seem to make insiders wealthy, still somehow 16% of Americans consider stocks to be the best long term investments, a higher share of Americans, 23% said gold. That actually surprises me, that nearly one quarter of Americans say that gold is the best long term investment, when only about 10% of Americans own gold in the physical form, like bars or coins. And part of this could be driven by the recent hype, where the gold price has more than doubled just since last year, and it broke above $4,000 an ounce for the first time in history this month. All right, so 16% said stocks, 23% said gold. And what's number one in the Gallup poll for what Americans believe is the best long term investment? It's real estate. Ah, well, they got that right. That actually gives me a little more faith than Americans there. Now, when it comes to real estate investment, you know, there's this long running mantra or catchphrase out there that I really disagree with. I mean, you've certainly heard this before, but it just does not resonate with me. And that is, appreciation is just the icing on the cake. That's the catchphrase I am not feeling the vibe there. How in the heck is appreciation just the icing on the cake? The presumption, the inference here, is that cash flow is the main driver of an investment philosophy, and then if you just happen to get appreciation too, oh, well, that's a little sweetener. Like the mantra would say cash flow is the cake, the majority piece, and then appreciation since the icing, oh, that's only a little thing. No, that's misleading. You usually get more of a return from appreciation than you do cash flow.   Keith Weinhold  17:56   I mean, on, say, a 400k income property, what if you only get $200 of cash flow? That can happen? That's $2,400 a year. But instead, 5% appreciation on that property gives you $20,000 a year. That is almost 10x. I think what the icing on the cake, curious catchphrase means is that cash flow is important because it controls the mortgage. Well, then I think it's just better to say that appreciation is not an inconsequential thing. It's often the biggest thing. So is appreciation just the icing on the cake? No, it certainly is not. In fact, I'm going to talk more about that next week when I've got something special planned for you here on the show. What I'm going to do then is look at the ways real estate pays you five ways in a slow market, the real estate market is slow. If you look at it on a basis of transaction volume, say that you buy a property today and over the next year, you don't even get what Wells Fargo forecasts say you only get 2% appreciation and zero cash flow. Just break even on a monthly basis. I mean, there's surely some disappointing numbers, but just say that's what happens. Well, next week, I'm going to add up what your total rate of return would be even in this dour scenario, and I think that you are going to Marvel be flabbergasted at how profitable you are if you just got 2% appreciation and zero cash flow. That's next week.    Keith Weinhold  19:36   As far as today, I'm about to bring in a super smart guest that hasn't been on the show here in a few years. He's usually a fellow faculty member on the real estate guys invest or summit at sea. But he wasn't there with me this year, so we met up in Anchorage. Instead, we're talking about changes to commercial real estate that market, and the opportunities that you might be able to find there from Industrial land, an activity that well generates noise, like Bitcoin mining operations and growing data centers with the increased use of AI. And as you listen, see if you know what I mean about how he feels professorial in his approach, and I mean that in the best possible way you can learn from him. He's from Ottawa, Canada, an international conversation coming up next. I'm Keith Weinhold. You're listening to Episode 577, of get rich education.   Keith Weinhold  20:34   If you're scrolling for quality real estate and finance info today, yeah, it can be a mess. You hit paywalls, pop ups, push alerts, Cookie banners. It's like the internet is playing defense against you. Not so fun. That's why it matters to get clean, free content that actually adds no hype value to your life. This is the golden age of quality email newsletters, and I write every word of ours myself. It's got a dash of humor. It's direct, and it gets to the point, because even the word abbreviation is too long, my letter takes less than three minutes to read, and it leaves you feeling sharp and in the know about real estate investing, this is paradigm shifting material, and when you start the letter, you'll also get my one hour fast real estate video, course, completely free as well. It's called the Don't quit your Daydream letter. It wires your mind for wealth, and it couldn't be simpler to get visit gre letter.com while it's fresh in your head, take a moment to do it now at gre letter.com Visit gre letter.com   Keith Weinhold  21:46   the same place where I get my own mortgage loans is where you can get yours. Ridge lending group and MLS, 42056, they provided our listeners with more loans than anyone because they specialize in income properties. They help you build a long term plan for growing your real estate empire with leverage. Start your prequel and even chat with President chailey Ridge personally while it's on your mind, start at Ridge lending group.com, that's Ridge lending group.com,   Tarek El Moussa  22:19   what's up? Everyone. This is hgtvs Tariq al Musa. Listen to get rich education with Keith Weinhold, and don't quit your Daydream.   Keith Weinhold  22:27   Hey, it's great to welcome back a longtime industry friend. He's a senior partner at y street capital. He owns a development company that's active in nine US states and two Canadian provinces, and he's the host of the real estate espresso podcast. Hey, it's great to have back. It's been a few years. Victor Menasce, great to be here. Keith, well, you know what's different? I mean, we were together doing some sightseeing around Anchorage, Alaska. You I and your wife here just a few weeks ago. That was great to have you. And then you had a nice Alaskan cruise after that. It was lovely. It was great to spend time with you in person, where you and I have spent time together at conferences all around the nation. So thank you for that. Yeah, it was great to do some fun stuff and like, Oh, hey, this guy knows a world outside of just talking about cap rates all the time. So Victor, the commercial side is pretty dynamic, and it sure has been lately with all the changes that we've had in the world, really starting with the pandemic almost six years ago, now, that includes the industrial space and how the need for warehousing and storage has changed. So from a real estate perspective, tell us about what you're seeing there.    Victor Menasce  23:41   We're seeing a lot of changes. Of course, there's a lot of uncertainty that's been injected by the current administration in Washington in terms of international trade. But even if you put that aside the flow of goods from wherever they're manufactured to the end customer, that flow is still there. It's one of these things that often creates inefficiencies, especially as you start to think about really optimizing the overall cost. You know, if you think about what inventory costs you to have on a retail floor where you might be renting that retail space at, I don't know, 55 $60 a square foot, and it's occupying very, very expensive real estate, if you can instead put that in a warehouse that's maybe at 10 to $15 a square foot. Oh, but wait a minute, you've got a 27 or a 35 or a 40 foot ceiling height, and you're stacking it seven to nine levels high. Really, the cost of that inventory has gone way, way down because you're putting it much less expensive real estate, right? Okay, so here is one of the efficiencies of a retailer doing e tail instead of brick and mortar retail, absolutely. And you know, we often see situations where the last mile, you know, we want to get that instant gratification as a consumer, but we don't necessarily want to be having to drive to that retail space. And we don't that's. Supplier doesn't necessarily want to pay Amazon for warehousing that particular product. So often, the fulfillment is done locally, that last mile Logistics is extremely important. That's putting a lot of pressure on this category of product that has traditionally been called Flex industrial. These are those places in the industrial park that you might see an electrician or a landscaping company or a plumber or anyone like that that has an office at the front of 14 or 18 foot Bay at the back and a bit of inventory. A lot of that product right now is being pulled off the market for many different reasons. Some of that's just disappearing and that land is getting repurposed for residential. Some of it's disappearing because people are putting gyms and pickleball courts and things like that and those types of products. Some of it's disappearing because people with exotic car collections want to use that space for a man cave. There's many different things that are demanding that particular product, and there's very little of it getting built. So that's another area right now that is under a lot of pressure. On the demand side, not a lot of new supply and rents are going up much, much faster than they otherwise should be. Talk to us more about the industrial space from the supplydemand perspective, what do people want and what do people need? It varies widely. There are companies that are in manufacturing, they will often look to refresh their investment in equipment. They may not have the capital, so they will sometimes do a sale, lease back of their building, of their facilities, so that they can then repurpose some of that capital onto into the equipment side, so that they can maybe modernize their manufacturing. That's another area where we see significant shifts happening. In industrial we also see a lot in logistics, where the most efficient way to move goods is a 200 year old technology called rail, and it's still alive and well. I mean, if you think about the cost of shipping a container across the country, you're going to spend about two cents per ton mile to move that by rail, or about 10 cents per ton mile to do it by truck. So that's a five times difference in price. That means a container from Los Angeles to New York is going to cost you about $1,400 if you're moving it by rail, or about $7,500 if you're moving it by truck. But if you're now part of the rail system, there's now logistics that you have to worry about at either end. And so if you want to make all of that work, those transfer hubs become extremely important, and there's just not a lot of them,    Keith Weinhold  27:38   okay, so it might only cost 1/5 as much per ton mile to move a good over rail as it does road. But you're sort of talking about the logistical challenge of, oh, getting it that last mile from the rail Terminus to the end user.   Victor Menasce  27:53    absolutely. And there can be a lot of cost associated with that last mile. So if you can solve that problem for the logistics companies and lower their cost for that last mile. That's got significant value, and that's another demand for industrial land. And very few cities are adding industrial land to their master plan. You know, warehouses don't vote, so they don't tend to take other land and zone industrial In fact, if anything, it goes the other way. There's a lot of pressure to take land that was zoned industrial and rezone it for commercial or for residential. In fact, we see that in a lot of cities.    Keith Weinhold  28:30   Now, you the listener, if your entrepreneurial wheels are turning, you can see the opportunity for, Hey, can I get in and help solve the problem in that last mile demand creatively. How do I think I could get in? How do I think I could do that, as long as that demand is sustainable? Victor, when we talk about industrial real estate, like we are here as real estate investors, one of the things that we often think about is site selection. Tell us more about that through the industrial lens   Victor Menasce  28:58   I think there's a couple things that matter. Number one, you can't pay too much for it. It's got to be at the right price. So you've got to be thinking about, you know, we always do what's called residual land value analysis and and that happens in residential, commercial, every single asset class, everyone works backwards from the answer to the question. So the answer is, here's how much profit I need to generate. Here's my capital cost. Here's, you know, you keep backing up and you say, well, now what's left over? That's what I can afford to pay for the land. So you always gotta be working backwards from the answer to the question. And this is no different. We do this in industrial as well. So you gotta make sure that that situation where the numbers work. Number two, you've gotta make sure that there is the right supply, demand dynamics. Got to make sure that the property itself is not contaminated. That can be a liability. If that was once a heavy industry site, then there could be contamination. You want to make sure that that's somebody else's problem, not yours, or if it is your problem, that you can mitigate it where the cost is bounded. So you got to. You know, look at all of these things together. And then, of course, there has to be good connectivity, good access to freeways, to major arterial roads, good access to rail. If you can get a Rails per on the property, even better. But even if you can't, as long as you have good access to major roads. You know, I always look at this through the lens of product design, where you're designing a product for a very specific customer. And so it's really, it starts with the end customers need in mind. And it's not a speculative process. It's really understanding who that customer is designing a product for them and making sure that you're delivering it at the right price. So it's always, always working backwards from the answer   Keith Weinhold  29:43   nowwhen we think about site selection and geography of where we're putting this real estate cities are often located on a body of water, like a bay or a river, often runs through a city, but yet you think of industrial use. Land is not your priciest land, but yet you think of a city center as your priciest land. Oftentimes, where do you put the industrial real estate with regard to the city center? I usually think of it as far outside of that. But are there other trade offs or nuances there?   Victor Menasce  31:11   it can be. You know, it's a question of whether you're doing a greenfield project or an infill project. If the land was previously zoned industrial and you're now just redeveloping it, that can make a lot of sense. If it is a greenfield project where you're looking to build new then, yeah, it's probably going to be in the outskirts, because that's where you're going to get the best land cost. And then, of course, you got to be thinking about what the end product is, and it what's it going to cost you to get it where it needs to be. Most of these projects are built slab on grade, which means that the surface has to be suitable for that sort of building. The land might be cheap, but if you've got to bring in half a million yards of gravel to get the site where it needs to be, it might not look cheap anymore, because you could import so much material. So you have to think of the cost of the land in a shovel ready context, because you can spend an awful lot of money moving dirt, moving gravel, things like that that will be necessary for an industrial project. So when we look at land for that product, we're always looking at it through the lens of, is it in a floodplain? Is it high enough ground? Is it drain? Well, all of those things that come into the cost of preparing the site to accept that kind of a building.   Keith Weinhold  32:23    Now, when we think about what goes on in an industrial space in your mind's eye, you might think of an asphalt plant, or you might think of the noise in some rumbling concrete trucks. With regard to that, what are your thoughts about nimbyism? Do you see much, not in my backyardism among communities with industrial real estate.    Victor Menasce  32:44   Oh, absolutely, without a doubt. And oftentimes that's one of the reasons why industrial land often gets pushed out away from those residential zones. So once you're outside the radius of people who can object, then there's no objection. So that's one way to solve it, and often a good way to solve it, by the way, but you also have to be mindful the fact that if there is potential contaminants coming off of that site, you don't want to be near a body of water that can carry it down into an aquifer and so on. So you've got to be thinking through containment issues. You've got to be thinking through noise propagation issues. There's been, in fact, a lot of issues with data centers, where the air handling and the the air conditioning systems right generate a lot of noise, and that noise often carries over very large distances. And you know, we're talking noise levels that would be very offensive to most homeowners. Some people have had to move because the noise levels have just been so continuous.    Keith Weinhold  33:42   I like the way you put that Victor. It's sort of like, yes, industrial parks are built outside the radius of the loudest objectors. That's right where they're going to go. But that's really the way that it is sometimes when we think about more contemporary uses for how we use industrial real estate today. You touched on data centers, also Bitcoin miners, you know, these are some of the things that generate noise. So what are some of the considerations with those two?   Victor Menasce  34:06    If you're looking at a data center, they consume a lot of power and they generate a lot of heat. The most efficient way to get rid of heat is with water. And that sounds a little bit strange, but you think about it this way, if you heat a molecule of water by one degree. I'm going to actually give you the textbook definition of a calorie. You take that water and you heat it by one degree, that'll consume one calorie of water. That's the definition of a calorie. And if you take it from the liquid state to the vapor state, just that phase change at 212 degrees Fahrenheit, or 100 degrees centigrade, that phase change is going to consume 500 calories. So you're getting rid of tremendous amount of heat by evaporating water, and that's why data centers consume so much water, is because they evaporate the water. That's the way they get rid of the heat. They evaporate it into the atmosphere. And that's how they get rid of the heat. It's the most efficient way to do it, but it consumes a lot of water resources. And then, of course, you've got to have the power to get into the data center, and a lot of places don't have the electric infrastructure to provide what's needed on a sustained basis. So you need not just good power, you need good power redundancy. So if there's a power failure here, you've got maybe redundant paths. So if one transmission line goes down, you've got alternate paths to keep the data center running. And you need the same thing also with communication, so multiple redundant fiber pathways in and out of the data center. So all of these things come into site selection. And then if you got all of that right, you got to overcome the neighborhood objections.    Keith Weinhold  35:45   Yes, that's right. We're doing a little science here with Victor Menasce, experienced international developer, and Victor when we think about industrial real estate, and we're here on an investing show. You know, maybe an investor sees potential in data center real estate or something like that. So for the individual investor, what can they do? Can they do anything individually? Are there funds to invest in, to either avoid or be attracted, to tell us about how the investor can get in?    Victor Menasce  36:15   We're not active in data centers. We're active more on the industrial side. I know the existence of data center funds. I know, for example, Kevin O'Leary, very famous Shark Tank, is a major investor in data centers. If you look him up, there might be some potentials there. Many of the major players in artificial intelligence, Oracle right now is taking on a boatload of debt to build data centers for open AI, so they're going to both build and operate those data centers. And I don't know where they're getting their capital, but they're getting a lot of it, or at least that's what's been announced publicly. Data centers require a lot of at least at that scale, require tremendous amount of infrastructure. We're talking hundreds of acres. We're not talking a small warehouse here that might be a million square feet. We're talking big, big acreage for those scale projects and for more localized projects. Yeah, there are smaller data centers, but they're not that economical to run. So it's usually the large ones that are the most cost efficient.   Keith Weinhold  37:16   Well, two things Victor is there anything else about industrial real estate? Our listeners should know maybe something I did not think about asking you and then tell our audience how they can learn more about what you're doing.    Victor Menasce  37:27   We see opportunity in particular. We think of it almost like a covered land play. We're very active in the industrial outdoor storage space where there is need for things to be stored outdoors. It might be landscaping companies that want to buy materials by the truckload. It might be car dealerships that have an excess of inventory. It might be boat and RV storage. There's many different uses for secured outdoor storage, and these are products that are designed very specifically for customers that have those needs. And as a covered land play, frankly, some of the best returns that are available in the marketplace. We've looked at a number of different things, and this is where we're placing majority of our energy right now as a development company is in that space, because we see it as an underserved segment of the market where there is not a lot of institutional money that's come into the play yet, so we're very active in that space.    Keith Weinhold  38:22   And how can our audience learn more about what you're doing   Victor Menasce  38:25   best is to reach out to us at y Street, capital com. Be happy to have if folks want to learn more about our projects. There's a place where they can sign up on the website to get more information. And love to have you as guests or as listeners to the real estate espresso podcast, and that's a daily show, seven days a week, so love to have you as a listener for that show as well.    Keith Weinhold  38:46   And that's the letter Y, Y Street, capital.com,Victor Mesance, it's been enlightening as always. Thanks so much for coming back onto the show.    Victor Menasce  38:55   Thank you so much.   Keith Weinhold  39:02   Oh yeah, good stuff from Victor as always. Another thing that he, I and his wife did in Anchorage when he was here recently is visit, well, it was not an AI data center, but we went to a mint that sells gold bars, nuggets and bullion. I really just looked. It was fun to look with Victor and actually pick up and hold gold nuggets, something that you cannot do online. I didn't have any intent to buy anything with the run up in precious metals prices. I made my last purchase of those in the middle of last year. So a year and four months ago today, I hear about lots of people rushing to buy precious metals. Now, amidst this big price run up and the run up might still have a ways to go, but no, the time to buy was like a year and a half ago or more. It's not now getting caught up in the euphoria this sort of exhaltation where you're paying double the price.   Keith Weinhold  40:03   next week here on the show, I've got more that I want to share with you on today's opportunity in new build rental property. How real estate pays five ways in a slow market, which is just fascinating. And I've got a GRE live event to tell you about next week as well, and more, lots of intriguing wealth building material here in future weeks, and then sometime after that, my own right hand assistant here at GRE is going to come out of the show and ask me some of your listener questions. It's the first time you'll hear her voice on the show. But more importantly, get my answers to your investing questions. If you'd like your question answered on a listener questions episode down the road, as always, you can write into us at get rich education.com/contact, that's get rich education.com/contact, until next week, I'm your HOST. Keith Weinhold, don't quit your Daydream.   Unknown Speaker  41:02   Nothing on this show should be considered specific, personal or professional advice. Please consult an appropriate tax, legal, real estate, financial or business professional for individualized advice. Opinions of guests are their own. Information is not guaranteed. All investment strategies have the potential for profit or loss. The host is operating on behalf of get rich Education LLC, exclusively,   Keith Weinhold  41:30   The preceding program was brought to you by your home for wealth. Building, get richeducation.com  

Join us this episode as we ask the big question: How does the Big Bang happen because of something that happens after the Big Bang? See if we ever find out as we discuss the second story of the Black Guardian trilogy, Terminus.   It should come as no surprise that this story garnered some strong feelings from our crew. Did Anthony really want to rewrite almost all interactions and plot regarding the Doctor and his companions? Absolutely. And did Reilly have lots of thoughts regarding redheads in this story? Seems so. But nothing beats Diana and Julie's horror in the treatment of Hansen's disease. Honestly, we really did not need a leper spaceship. Oh, and Reilly might have annoyed Anthony in his sleeping through his behind-the-scenes section.   If you would like to watch along with us, you can find this story available for streaming on Britbox in the USA (http://www.britbox.com) and BBC iPlayer in the UK (https://bbc.in/48GSaCB). If you're a little old fashioned and prefer physical media (like our very own Anthony), you can also find it on the Doctor Who Season 20 Blu Ray box set from Amazon US (https://amzn.to/3VyxIPe) and Amazon UK (https://amzn.to/3V2IL34)   Other media mentioned in this episode*: Community – The Complete Series (Amazon US: https://amzn.to/3hPClB0 | Amazon UK: https://amzn.to/39hGzwz) Barbarella (Amazon US: https://amzn.to/4nabKxq | Amazon UK: https://amzn.to/4qiZz4g) Futurama – Seasons 1-8 (Amazon US: https://amzn.to/3jfbkaQ | Amazon UK: https://amzn.to/3aQeMUL) Alien (Amazon US: https://amzn.to/3nbhOZt | Amazon UK: https://amzn.to/3BX7I4X) Star Trek: Deep Space Nine: The Complete Series (Amazon US: https://amzn.to/3JX2A4F | Amazon UK: https://amzn.to/35wGdnA) Bram Stoker's Dracula (Amazon US: https://amzn.to/3n7Fn5I | Amazon UK: https://amzn.to/3pk4iFM) Blake's 7 – The Complete Collection (Amazon US: https://amzn.to/2Zh7045 | Amazon UK: https://amzn.to/39luyGI) Assassin's Creed Valhalla (Amazon US: https://amzn.to/3yWEhzi | Amazon UK: https://amzn.to/3HoBlyr) Don Quixote, by Cervantes (Amazon US: https://amzn.to/3vKVfPl | Amazon UK: https://amzn.to/3B8wxcI)   Finally, you can also follow us and interact with us on Facebook and Instagram. You can also e-mail us at watchers4d@gmail.com, and you can join us on our Discord server. If you're enjoying this podcast, please subscribe to the show, and leave us a rating or review.   *Support Watchers in the Fourth Dimension! We are an Amazon affiliate and earn a small commission from purchases through Amazon links. This goes towards the running costs of the podcast.

In this episode of Insights Unlocked, host Nathan Isaacs sits down with Sangram Vajre—co-founder of Terminus and GTM Partners, bestselling author, and pioneer of the Flip My Funnel movement—to explore how customer-first thinking reshapes business growth. Sangram recounts the moment of inspiration that led to flipping the traditional sales funnel on its head and how that napkin sketch evolved into a movement that transformed B2B marketing. Sangram also shares insights from his MOVE framework (Market, Operations, Velocity, Expansion), offering a fresh lens for diagnosing go-to-market (GTM) challenges at every stage of business growth. He dives into the rise of fractional leadership, the role of AI in driving customer insight and product innovation, and why focusing on Net Revenue Retention (NRR) may be the single best way to align teams around growth. Whether you're in marketing, product, UX, or customer experience, this episode will challenge how you think about pipeline, growth, and what it really means to put the customer first. What you'll learn in this episode:  The origin story behind Flip My Funnel and how it reshaped ABM and B2B marketing Why most marketing and sales funnels fail—and what to do instead The MOVE framework: a diagnostic tool for GTM strategy How Net Revenue Retention (NRR) is the ultimate measure of customer-centric growth The rise of fractional roles and what it means for the future of work How AI is changing the way we listen to and serve customers at scale Resources & Links: Sangram Vajre on LinkedIn (https://www.linkedin.com/in/sangramvajre/) GTM Partners (https://gtmpartners.com/) MOVE and other books (https://sangramvajre.com) GTM Mondays newsletter on Substack (https://gtmonday.substack.com/) Nathan Isaacs on LinkedIn (https://www.linkedin.com/in/nathanisaacs/) Learn more about Insights Unlocked: https://www.usertesting.com/podcast

At the Gathering of the General's conference today, President Trump said that the plan for troops in the inner cities is all part of the war at home. At the same time, Secretary of War Pete Hegseth's pep talk included how he plans to eliminate the "wokeness" of the military. Could this get-together be a precursor to a coming war, especially here at home, where Battlefield America seems to be part of the agenda in the Devil's business model? Meanwhile, traditional religion is declining across the U.S. as church attendance is dropping and Christians are now being attacked. The category of “spiritual but not religious” is expanding, while witchcraft, Theistic Satanism, and occultism grow at unprecedented rates. From a biblical perspective, this appears to be precisely the kind of moral deterioration that precedes Judgment Day. Listen to Ground Zero with Clyde Lewis M-F from 7-10 pm, pacific time on groundzeroplus.com. Call in to the LIVE show at 503-225-0860. #groundzeroplus #clydelewis #judgementday #war #religion

Redox is embracing Wayland, Ubuntu is supporting CUDA, and Fedora is introducing Fedora Forge. The eBPF foundation has $100,000 worth of grant money to award, BcacheFS works out DKMS packaging, and Mesa moves towards guidelines for AI code. Fedora 43 and Plasma 6.5 both hit beta this week, with releases coming soon. For tips, we have Semaphore UI for managing ansible and other DevOps tools, wpctl set-profile for more WirePlumber management, and Terminus for gamifying command line learning. You can catch the show notes at https://bit.ly/3KdSukS and enjoy! Host: Jonathan Bennett Co-Hosts: Ken McDonald and Rob Campbell Download or subscribe to Untitled Linux Show at https://twit.tv/shows/untitled-linux-show Want access to the ad-free video and exclusive features? Become a member of Club TWiT today! https://twit.tv/clubtwit Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord.

In the finale of the Terminus trilogy, Tilda and Madison try to escape all the forces that want to control or destroy them.See omnystudio.com/listener for privacy information.

In the penultimate chapter, Tilda confronts the people who took her son and tries to get him back.See omnystudio.com/listener for privacy information.

Tilda confronts someone from her past who places his faith in her, and gives her the tools to save her son.See omnystudio.com/listener for privacy information.