Podcasts about Population

The news of Texas covered today includes:Our Lone Star story of the day: Good news for Taylor and Ector County taxpayers – your county officials are not raising your property taxes this next year. Overall, going on 20-years, taxpayers in Texas have been getting a raw deal from local governments, especially municipalities as city council folk have increased the size of government spending grossly beyond population and inflation. This story at The Texan gives a good summary of such looking at the cities of the Texas Triangle.Our Lone Star story of the day is sponsored by Allied Compliance Services providing the best service in DOT, business and personal drug and alcohol testing since 1995.Attorney General Ken Paxton Secures Over $1 Billion from Meta in Historic Settlement that Protects Texas Kids Online. Massive Meta settlement targets teenage social-media addiction.The 87-year-old federal judge from New York needs to retire and go back to the Empire (formerly) State because he would be more comfortable living under Leftist Gov. Hochul: Texas' limits on some drag shows found unconstitutional again.Gov. Greg Abbott wants three-year bachelor's degrees in Texas. Governor Abbott Directs THECB To Develop Three-Year Bachelor's Degree Pathways.Ross Fire in Texas grows to 80,000 acres as winds shift.Listen on the radio, or station stream, at 5pm Central. Click for our radio and streaming affiliates.www.PrattonTexas.com

The Prism of America's Education with Host Karen Schoen – How do you create a society that is so dependent, and void of free thought, that they become obedient drones, too afraid to step out of line? Compliant and obedient. The camera. The camera ties it all together; it helps them anticipate and manipulate your behavior, and keeps you in line...

Stephen Grootes spoke to Miyelani Holeni about the business of improving the performance and financial sustainability of South Africa’s public institutions, Graeme Codrington about the economic risks posed by China’s ageing population and falling birth rate, Wendy Knowler about the latest fraud reports revealing billions lost and prevented in financial crime, and Nomvuyiso Batyi about her leadership journey and the transformation of South Africa’s communications and technology sector. The Money Show is a podcast hosted by well-known journalist and radio presenter, Stephen Grootes. He explores the latest economic trends, business developments, investment opportunities, and personal finance strategies. Each episode features engaging conversations with top newsmakers, industry experts, financial advisors, entrepreneurs, and politicians, offering you thought-provoking insights to navigate the ever-changing financial landscape.    Thank you for listening to a podcast from The Money Show Listen live Primedia+ weekdays from 18:00 and 20:00 (SA Time) to The Money Show with Stephen Grootes broadcast on 702 https://buff.ly/gk3y0Kj and CapeTalk https://buff.ly/NnFM3Nk For more from the show, go to https://buff.ly/7QpH0jY or find all the catch-up podcasts here https://buff.ly/PlhvUVe Subscribe to The Money Show Daily Newsletter and the Weekly Business Wrap here https://buff.ly/v5mfetc The Money Show is brought to you by Absa     Follow us on social media   702 on Facebook: https://www.facebook.com/TalkRadio702 702 on TikTok: https://www.tiktok.com/@talkradio702 702 on Instagram: https://www.instagram.com/talkradio702/ 702 on X: https://x.com/CapeTalk 702 on YouTube: https://www.youtube.com/@radio702   CapeTalk on Facebook: https://www.facebook.com/CapeTalk CapeTalk on TikTok: https://www.tiktok.com/@capetalk CapeTalk on Instagram: https://www.instagram.com/ CapeTalk on X: https://x.com/Radio702 CapeTalk on YouTube: https://www.youtube.com/@CapeTalk567 See omnystudio.com/listener for privacy information.

SpaceTime Series 29 Episode 100 The ingredients for planets formed far earlier than thought A new study suggests that the basic ingredients needed to form planets - and possibly life - may have existed just a hundred million years after the big bang -- far earlier in the history of the Universe than previously thought. Hunting for the hypothetical axion For years scientists have been hunting for a hypothetical elementary particle called the AXION which could lead to new physics unlocking some of the greatest mysteries of the universe. Now the German Research Foundation has given a green light to the construction of a new six million Euro experiment called the BabyIAXO – a first step in the search for the elusive and as yet undetected particle. NASA's Swift rescue mission back on track Katalyst Space has successfully uploaded a new flight software update designed to return its Link spacecraft into a more stable configuration.  Link is on a rescue mission to save NASA's Swift gamma ray space telescope from crashing back to Earth. The Science Report A new potential cure for baldness. Study shows people are most ticklish on the neck, armpits, belly, and the soles of their feet. Scientists have discovered a fossil of the earliest known siphuncle-bearing cephalopod. Study shows moving a pet cat from an outdoor lifestyle to living indoors is easier than you think. Skeptics guide to chasing the Moon.   Our regular guests: Alex Zaharov-Reutt from techadvice.life Tim Mendham from Australian Skeptics And Senior science writer and Sky and Telescope magazine contributor Jonathan Nally  

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

In this episode of Leupold's Hunt Talk Radio, Randy interviews Joe Rahn, the Director of Operations and Chief Pilot for Montana Fish, Wildlife and Parks. They talk through the complexities of managing the state's aerial wildlife survey fleet. These flights are vital for conservation efforts, enabling biologists to track herd populations and determine sustainable hunting tag quotas. This episode gives a look into the behind the scenes work that fish and wildlife agencies perform to balance hunting seasons and game populations. Learn more about your ad choices. Visit megaphone.fm/adchoices

We're talking about why our city is getting older, not figuratively but quite literally. We also have updates on the Grasshopper Wildfire and tips on how to be fire safe when recreating outdoors. Plus we're diving into our mailbag and hearing from you, our listeners. Joining host Claudia Meza are Willamette Week reporter and author Brianna Wheeler as well as outdoor educator and founder of Wild Solitude Guiding, Norther Emily.  Become a member of City Cast Portland! Join today, and we'll send you some exclusive City Cast Portland swag, while supplies last. Get all the details and sign up here.  Discussed in today's episode: 2 Portland spots make New York Times list of America's ‘greatest Mexican restaurants' [Oregonian] PSU Forecasts Multnomah County Could Lose More Than 17,000 School-Aged Children in the Next Decade [Willamette Week] Mt. Hood National Forest Fire Restrictions [usda.gov] Who would you like to hear on City Cast Portland? Shoot us an email at portland@citycast.fm, or leave us a voicemail at 503-208-5448. Want more Portland news? Then make sure to sign up for our morning newsletter and be sure to follow us on Instagram. Looking to advertise on City Cast Portland? Check out our options for podcast and newsletter ads at citycast.fm/advertise. Learn more about the sponsors of this August 20th episode: Salishan Coastal Lodge Stacked Piercing - take 20% off your first booking with code CITYCAST20 PaintCare Grand Central Bakery

In this B-side episode of Set Lusting Bruce, host Jesse Jackson talks with Joey Register, who records as itsrihhomie, about his path from growing up in Rochester, New York to making melodic rap as an emotional outlet and running his own studio to help others create. Joey describes his freestyle, bar-by-bar recording process, early influences from friends and artists like Juice WRLD and Lil Wayne, and how his album Population Mars pulled together songs written from ages 18 to 25 across sessions in places like Boston, Tampa, and Chicago. He discusses the challenges independent artists face in smaller markets, how streaming and short-form content shape careers, and his plans to release more music, collaborate locally in San Francisco, and experiment across genres. The episode closes with Joey's take on whether Mary gets in the car in “Thunder Road,” plus where to find his music and social accounts. New Album - https://music.apple.com/us/album/rih-university/6798003629 https://open.spotify.com/album/6vYZs5I63juyntRHf8oCjI?si=TRsU_9SlTSW4exS-eWl-Zg&utm_source=copy-link - Instagram: https://www.instagram.com/itsrihhomie/ - Apple Music: https://music.apple.com/za/album/population-mars/1834633510 - Spotify: https://open.spotify.com/album/50p0UKuBYmUhp9cZ7A5JDM?si=BXKtxVW4TLmTDUib7TlaRQ 00:00 B-Side Detour Intro 01:03 Meet Joey Register 02:35 Finding Rap and Freestyle Flow 11:11 Studio Life and Community 13:10 Defining the Sound 14:42 Indie Artist in Streaming Era 17:57 Next Moves and New Genres 20:34 Surprises and Creator Culture 23:17 Where to Find the Music 24:09 Spirituality and Mindset 28:41 Thunder Road Mary Question 31:29 Socials and Farewell 32:17 Podcast Outro and Support Learn more about your ad choices. Visit megaphone.fm/adchoices

Another sign of New Zealand's growing demographic problem. Stats show our natural population growth has fallen to 18,700 for the year to June – the lowest rate since World War II. Births are at their lowest since 2003, and the number of 25 to 34 year olds is down 1.7% – adding to our productivity woes. Infometrics' Lead Demographer Nick Brunsdon told Mike Hosking the supply of young people around the world, and with other countries facing the same issue, we can't expect to bring in an exponential number of migrants every year. He says industries will be forced to improve productivity through automation and machinery and treat workers as more of a scarce resource than something they can swap in and out as needed. LISTEN ABOVE See omnystudio.com/listener for privacy information.

U.S. Representative Dan Newhouse says with the labor shortages and high expenses, there is a lot of misinterpretations of the ag labor force in general.

In this episode, Dr. Ruscio and Dr. Scott Spiridigliozzi break down why mold and fungal treatments often fail—and what may improve the odds of success. They discuss how to get clearer on the diagnosis, why herbal therapies may not be enough for some patients, the importance of reaching therapeutic antifungal levels, why underdosing can backfire, and how targeting the right tissues may help prevent relapse. They also share insights from their own experiences with chronic fungal illness and how those lessons are shaping their evolving treatment approach.   ✅ Start healing with us! Learn more about our virtual clinic:  https://drruscio.com/virtual-clinic/  

durée : 00:15:06 - Les journaux de France Culture - Il y a cinq ans, le 15 août 2021, les talibans reprenaient le pouvoir en Afghanistan. Cela fait cinq ans que les Afghans, et notamment les femmes, voient leurs droits se restreindre de plus en plus. - équipe : La Rédaction de France Culture, Thomas Cluzel, Aloïs Guérin Vous aimez ce podcast ? Pour écouter tous les épisodes sans limite, rendez-vous sur Radio France

durée : 00:15:06 - Journal de 12h30 - Il y a cinq ans, le 15 août 2021, les talibans reprenaient le pouvoir en Afghanistan. Cela fait cinq ans que les Afghans, et notamment les femmes, voient leurs droits se restreindre de plus en plus. - équipe : La Rédaction de France Culture, Thomas Cluzel, Aloïs Guérin Vous aimez ce podcast ? Pour écouter tous les épisodes sans limite, rendez-vous sur Radio France

In the oldest Japanese municipalities, close to half the residents are already over 65. As young people move to cities, the retailers close, then the clinics, then the bus that used to reach the next town. Rural Japan is not simply ageing: it is emptying.Elisa Giannone (CREI, CEPR) and her co-authors have analysed Japan's 1,741 municipalities from 1980 onwards. The oldest quarter of them lost around 26% of their population by 2010; the youngest quarter grew by 22%, and the gap between them is still widening. Taxing city dwellers could reverse the trend. But that's a century-long policy, that would also lower national income per head by about 1.3%. There is no version of this without a bill attached, she warns.The research behind this episode:Giannone, Elisa, Yuhei Miyauchi, Nuno Paixão, Xinle Pang, and Yuta Suzuki. 2026. "Living in a Ghost Town: The Geography of Depopulation and Aging." CEPR Discussion Paper 21447 (gated).To cite this episode:Phillips, Tim, and Elisa Giannone. 2026. "What price to save Japan's ghost towns?" VoxTalks Economics (podcast).About the guestElisa Giannone is a researcher at CREI, an Adjunct Professor at Universitat Pompeu Fabra, an Affiliated Professor at the Barcelona School of Economics. She works on internal migration, regional income divergence, the spatial consequences of local shocks and the question of why people move.Research cited in this episodeSocial and natural population change. Demographers separate population movements through migration, known as social change, from births and deaths, known as natural change. Giannone's team runs both counterfactuals separately. Shut down migration and the oldest municipalities still age, but the population loss between 1980 and 2010 falls from nearly 0.3 log points to under 0.1. The framework follows Stanley Smith, Jeff Tayman and David Swanson's standard treatment of state and local population projections.Scale economies in local public services. A 1% increase in local population is associated with a 0.53% fall in municipal government spending per head. Roads, schools, clinics and administration carry a large fixed cost, so the cost of serving each remaining resident rises as a town shrinks. This is the fiscal arithmetic that makes depopulation expensive.Consumption-equivalent flow utility. The paper's measure of quality of life, amenity-adjusted real income. It captures what the residents of a place can actually buy and enjoy rather than what they earn on paper, which matters when the shops and the doctors are leaving.The five oldest prefectures. Kochi, Shimane, Tokushima, Tottori and Yamagata, ranked by elderly share in 2015. They are the target group in every policy simulation, and their combined elderly share reaches nearly 60% by 2215 under the baseline projection.Municipal extinction. Hiroya Masuda's 2014 book Chiho Shometsu warned that unipolar concentration in Tokyo would drive hundreds of rural municipalities out of existence. It set the terms of Japan's regional revitalisation debate, and the paper's projections give that warning a number.United Nations World Population Prospects. Giannone's figures for the global picture, including the count of countries that have already passed peak population and those projected to do so by the mid 2050s, come from the UN projections rather than from the paper itself.More VoxTalks Economics episodesEconomic decline and the rise of populism. Andrés Rodríguez-Pose explains what happens politically in the places this episode watches emptying, and why long term regional decline shows up at the ballot box.Related reading on VoxEU.orgLiving in a ghost town: The geography of depopulation and ageing. The authors' own column, with the charts behind this episode.Japan's age wave: Challenges and solutions, a column by Andrew Stawasz, Paige Kirby, JP Sevilla and David Bloom on the national scale of the problem this episode breaks down by region.Mobile seniors and local economic development. Marco Badilla-Maroto, Benjamin Faber, Antoine Levy and Mathilde Munoz find that retirees moving into poorer French regions bring economic gains with them, a useful counterweight to the Japanese story.Population shrinking and the future of European municipalities, in which Friedrich Heinemann, Alexander Kalb and Benny Geys set out the scale economies problem for Europe's own shrinking towns.

As Diane Meier remarks to start today's podcast, palliative care has come a long way from the days when we were the "brink of death" consult. We're seeing patients earlier and earlier in the course of illness.  In fact, the evidence base for specialist palliative care is arguably stronger in the outpatient setting than the inpatient setting. In some ways, as Eric remarked, we are a victim of our own success. We've pushed on the boundaries of seeing patients earlier in the course of illness, we've demonstrated remarkable value to our colleagues and health systems: now they want us to see more and more patients, with conditions we would not have previously considered core to palliative care practice. Our guests modeled respectful disagreement, and we were somewhat surprised that there was more agreement than we expected.  I'm sure you will all have strong feelings about the opinions expressed, please let us know! In addition to Diane Meier, we welcome back Bob Arnold and Justin Sanders to talk through these issues, including: We agree specialist palliative care is for people with "serious illness" - but what constitutes "serious illness" Is a limited prognosis part of the definition of serious illness?  We discuss the Center to Advance Palliative Care definition of palliative care and Amy Kelley's oft-cited definition of serious illness.   Many patients with conditions that overlap with palliative care would benefit from our help, e.g. chronic pain, opioid use disorder, mental illness. Our health system is not meeting their needs.  Should palliative care see them, in the absence of a clear life-limiting illness? How limited a prognosis should we consider here - months, years…decades? We have a tremendous workforce shortage.  There are not enough specialist palliative care providers to see all patients with advanced cancer, much less the many other conditions whose guidelines now say should include palliative care.  The reality does not match the mission.  Does that change our mission?  Should local workforce issues dictate who should see palliative care? See this article by Pelleg in which clinicians at Mt Sinai agreed that patients with serious illness and high risk of mortality should be prioritized, explicitly excluding patients with chronic pain or psychosocial distress in the absence of serious illness. What is the role for Patient Reported Outcomes (PROs)? e.g. patients regularly reporting pain or other symptoms and an escalation in symptoms triggering a palliative care intervention.  How is the definition of who should see palliative care expanding in Canada, and is there a linkage to who is eligible for medical aid in dying in Canada.  Justin makes a good plug for the McGill National Palliative Care Grand Rounds Programme What is our vision for where palliative care should be 10 years from now? Population health specialists, or healing patients one visit at a time? To be sure, these are not mutually exclusive. How long should palliative care fellowship be - should we expand it to 3 years so palliative care specialists can care for people with a wider range of conditions?   What is Precision Palliative Care? Diane mentions this article by Ramy Sedhom on a couple of occasions.   Should palliative care see patients with sickle cell disease? How about survivorship clinics? How about very elderly patients with multiple mild chronic conditions (e.g. mild heart failure, mild COPD, mild cognitive impairment, arthritis, diabetes, hypertension)? And much more! Please listen to the audio only version of Stand by Me - my son Renn added an upright base, snap, and triangle parts - it's much better than the live version for YouTube that I accidentally started in a much too high key!  

Joel Skousen has spent nearly five decades helping people answer one question: where should you live when the systems around you start to fail? This talk has never been available publicly. Joel delivered it at Exit & Build 2, and we're releasing it now for the first time. In it he walks through the core of his life's work: Strategic relocation and how to evaluate where you live right now. Population density, prevailing winds, nuclear and military target proximity, water access, growing season, state law, and the neighbors you'd actually be depending on. Joel breaks down why he looks west of the Mississippi, which states he's changed his mind about, and the mistakes people make when they relocate for the wrong reasons. Home and retreat security. Joel is an architect who's designed high security residences across North America, Canada, and Latin America. He gets into secure room design, EMP-protected power, water and food storage, and what actually holds up versus what just feels safe. And the honest assessment of the threats. Grid failure, EMP, economic collapse, war, and the long-term consolidation of surveillance and control. Joel doesn't sugarcoat any of it, and he'll tell you why he refuses to. His view is that optimism is what keeps people from preparing. About Joel Skousen Former Navy and Marine Corps fighter pilot turned architect. He began writing The Secure Home in 1979, making him one of the genuine pioneers of the modern preparedness movement. He's the author of Strategic Relocation: North American Guide to Safe Places, still the definitive reference on threat-based relocation, and co-author of The High Security Shelter Book with his son, a structural engineer. He has published the World Affairs Brief every week for decades. Joel is speaking at Exit & Build 6 We just announced it. Joel is joining us in person at Exit & Build 6, November 5 through 8, 2026, at Sovereignty Ranch in Bandera, Texas. He's giving a full talk plus a hands-on workshop, going deeper than he could in the time he had here. Nuclear and fallout protection, secure water and food storage, EMP-protected long-term power, evading social unrest, and the secure room design he's spent a career refining. You'll be able to walk up and ask him about your own property, your own plan, your own situation. Exit & Build 6 is four days on a working regenerative ranch in the Texas Hill Country with speakers and builders across the counter-economy, decentralized tech, private realm structures, food and land, and lawful remedy. The whole event is built around implementation zones, where you don't just take notes. You leave with your crypto wallet funded, your privacy gaps closed, your land or community plan drawn up, and your private realm pathway mapped. Ticket prices go up August 31st. Get your ticket: https://exitandbuild.com  Brought to you by Live Free Academy. Stay free out there.

The Daily Quiz - Geography Today's Questions: Question 1: What American city, with a population of 2 million people, is nicknamed "Space City"? Question 2: Which river is joined by the Atbarah River in northern Sudan as its last tributary? Question 3: In which country would you find the Lut Desert? Question 4: Which of these cities is in China? Question 5: Which Rock Is On The South Coast Of Spain? Question 6: Which country has the oldest national flag? Question 7: Which of these cities is in New Zealand? Question 8: What two US states are rectangular? Question 9: The Hagia Sophia is an iconic structure in what city? This podcast is produced by Klassic Studios Learn more about your ad choices. Visit megaphone.fm/adchoices

Everyone's calling it a crash. Louis Christopher runs SQM Research, one of Australia's biggest property data houses, and he says that word is wrong. What we're in is the largest downturn in 10 to 15 years, but the one ingredient every genuine housing crash has ever needed is missing here. Louis breaks down where the market actually is, which cities are falling hardest, and which pockets are barely moving at all. We get into what the budget's tax changes are really doing to investor behaviour, why rents have stalled when everyone expected them to spike, and what he'd buy if he were putting money in today.   WHAT YOU'LL GET OUT OF IT The difference between a correction and a crash, and why a 10% property fall hurts more than a 10% sharemarket fall Why Australia isn't set up for a US or Ireland style collapse The city by city forecasts for the rest of the year What happened to rents after the negative gearing changes, and why the answer is more concerning than it looks Which markets are holding up, and the ones carrying the most risk right now How long this downturn runs, and what the long term growth rate looks like from here Whether the 6.8% long term average still holds   CHAPTERS 00:00  Intro 00:25  Where the property market actually is right now 02:24  Crash or correction, and why the difference matters 03:15  Why a 10% property fall hurts more than a 10% sharemarket fall 04:00  How APRA and the RBA really behave in a downturn 05:00  How long downturns last, and why this one is structural 06:30  What the budget tax changes did to the investor maths 08:45  The flow-on to the economy and state budgets 11:25  Rents went up $2 a week, and why that is the worrying part 13:00  Which suburbs are most exposed 16:18  Semi-rural and lifestyle property, and the risk nobody prices 18:09  Airbnb income and the wealth effect 19:00  The city by city forecasts 21:08  Adelaide and Perth 26:02  What actually drives values over the long term 28:37  How people are coping with record rents 30:17  Population growth and the 6.8% question 34:52  Where Louis put his own money Smarter money moves start here. Learn how to cut through the noise, avoid expensive mistakes, and get ahead faster. FREE 7-DAY MONEY CHALLENGES Pick one and see what changes in a week: https://pivotwealth.com.au/challenges/ WORK WITH US Book a no-strings call: https://www.pivotwealth.com.au/booking More about Pivot Wealth: https://www.pivotwealth.com.au BEN'S BOOKS Virgin Millionaire: https://amzn.to/3VFPPDM Replace Your Salary by Investing: https://amzn.to/3J9Ta8g Get Unstuck: https://amzn.to/3xo0MQG All books: https://www.pivotwealth.com.au/books FOLLOW Instagram: https://www.instagram.com/pivotben TikTok: https://www.tiktok.com/@bentalksmoney YouTube: https://www.youtube.com/c/BenNashPivot Facebook: https://www.facebook.com/pivotwealth/ DISCLAIMER This podcast is for education only and doesn't take into account your personal circumstances. It's not financial advice. If you buy a financial product, read the PDS and TMD, and seek advice tailored to your situation. Ben Nash and Pivot Wealth are authorised representatives of Fish Tacos Pty Ltd, ABN 14 649 248 082, AFSL 533055.

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More from VPM News:  Chesapeake Bay osprey populations are struggling  ICYMI, Amending Virginia: Reproductive Rights Why is Virginia's Reproductive Rights Amendment? (YouTube)  Listen to the Team No perspective  Listen to the Team Yes perspective   Other links:  Analysts predict Newport News lacks room to build Trump's battleships (WHRO)  Public housing board member resigns, citing ‘loss of confidence in leadership' (Richmond Times-Dispatch)*  Fired RPS facilities director is hired by one of the district's contractors (The Richmonder)  Henrico teen launches statewide water quality, lead pipe risk tool (Axios Richmond)  Montgomery County rejects agreement with MVP aimed at stalled compressor station permit (The Roanoke Times)*  *This outlet uses a paywall.  Our award-winning work is made possible with your donations. Visit vpm.org/donate to support local journalism. 

Music Video for The Stairs: https://youtu.be/-9FOYTwxfcU?si=mFPQVDCKASBR1oFuLive from Wembley Stadium: https://youtu.be/N8CIBNJB2FM?si=sF_SoLZtDrzyaszvThere's a kind of loneliness that has nothing to do with being alone.You can live surrounded by hundreds—or thousands—of people, pass the same faces every day, share elevators, hallways, sidewalks and city blocks…and never truly know one another.  This week on The Songs That Made Us, Gunter explores INXS' “The Stairs,” a haunting meditation on the anonymous lives unfolding around us and the strange human experience of being physically close while remaining emotionally separate.Through the song, Gunter examines the psychology of loneliness, our biological need for connection, the phenomenon of “familiar strangers,” and the surprising role architecture and urban design play in determining whether people simply pass one another—or actually meet.And more than three decades after The Stairs appeared on INXS' X, its observations may be even more relevant in a digital world that gives us unprecedented proximity while often leaving genuine human connection painfully out of reach.In This EpisodeThe story and ideas behind INXS' “The Stairs”Why loneliness can exist even when we're surrounded by peopleLoneliness as a biological signal rather than a personal failingThe evolutionary importance of human connectionThe psychology of the “familiar stranger”How urban environments can create proximity without interactionSocial infrastructure and the spaces where relationships formWhy cities designed primarily for movement can unintentionally discourage connectionPsychological overload and why we sometimes withdraw from people around usHow digital environments reproduce the same paradoxWhy The Stairs remains strikingly relevant todaySmall acts of recognition that can begin closing the distance between strangersChapter HighlightsIntroduction: The Stairs and the Loneliness of Being SurroundedINXS and the Album XThe Psychological Need to BelongSocial Overload in Urban EnvironmentsLoneliness as a Biological SignalWaiting, Recognition and the Structure of The StairsHow Urban Design Shapes Human ConnectionFrom Physical Cities to Digital LonelinessProximity Without ConnectionSmall Acts That Bridge the DistanceSharing Our Experiences of LonelinessKey TakeawaysLoneliness is a signal. Like hunger or pain, it can alert us that an important human need isn't being met.Proximity isn't the same as connection. We can encounter the same people repeatedly without ever crossing the invisible boundary between stranger and acquaintance.Our environments matter. The spaces we build can either encourage spontaneous human contact or quietly discourage it.The digital world hasn't eliminated this paradox. In some ways, it has recreated the apartment building on a global scale: millions of people occupying the same space while remaining strangers.Connection can begin remarkably small. Recognition, conversation and simple acknowledgment can interrupt anonymity.GratitudeWe want to extend a huge thank you to our listeners in Fairborn, Elyria (uh-lee-ree-uh), Columbus, Grafton, Northfield, Lorain, Ashland, and Cincinnati for keeping Ohio securely at the #2 spot on the Top 10 USA listeners list.And to our Global Listeners, we extend our gratitude to two countries reaching our top 20 list for the very first time ever! First, our listeners in Karachi (kr-aa-chee) for bringing Pakistan to #20! And also to our listeners in Jos (pronounced like loss with a J) Plateau State for bringing Nigeria to #18! CONGRATULATIONS!! you made the Top Listeners List.Become a supporter of this podcast: https://www.spreaker.com/podcast/inspire-change-with-gunter--3633478/support.PatreonIf this episode resonates with you and you'd like to go deeper into practical exercises and guided reflection, Gunter offers extended self-development resources and exercises through our Patreon community: www.patreon.com/inspirechangeSponsorDistil UnionThis episode of Inspire Change with Gunter is brought to you by Distil Union, creators of beautifully designed, functional everyday carry accessories that help bring organization, simplicity, and intention into your daily life.Distil Union blends craftsmanship with thoughtful design to help you carry what matters most — without the clutter.

This lecture was delivered at the University of St Andrews on 26 November 2025. Alison Bashford is Scientia Professor in History and Director of the Laureate Centre for History & Population at the University of New South Wales (Sydney). Her work connects the history of science, global history, and environmental history into new assessments of the modern world, from the eighteenth to the twentieth centuries. She has written about the geopolitics of world population, specifically in two books: The New Worlds of Thomas Robert Malthus: Re-reading the Principle of Population, with Joyce E. Chaplin (Princeton University Press, 2016) and Global Population: History, Geopolitics and Life on Earth (Columbia University Press, 2014). Get full access to Institute of Intellectual History at standrewsiih.substack.com/subscribe

Hometown Radio 08/10/2026 5p: Annie Lorenzen ponders the decline in population

In this episode of the Econ Dev Show Dane Carlson talks with Mike Swesey, president and CEO of the St. Petersburg Area Economic Development Corporation, about how St. Pete has worked to become known as a business destination as well as a place with beaches, culture, and quality of life. Mike shares lessons from recruiting companies from markets like New York and Europe, explains why responsiveness can determine whether a community even stays on a site selector's list, and makes the case for targeting companies that genuinely fit your workforce and community. He also discusses using existing companies as your best salespeople, taking every project lead seriously, resisting the pressure to chase bad-fit wins, knowing your market deeply, and communicating constantly with your board so they understand the work happening before the announcements arrive. Like this show? Please leave us a review here — even one sentence helps! 10 Actionable Takeaways for Economic Developers Make responsiveness part of your competitive strategy. Mike argues that companies are making decisions faster and communities may be shortlisted before they even know a project exists. Have your data, website, property information, and team ready so you can respond accurately within hours or days rather than scrambling after the request arrives. Treat every legitimate-looking lead seriously until you know otherwise. Mike tells the story of nearly dismissing what sounded like a questionable data-center inquiry that turned out to be Google. Unknown company names, informal inquiries, or unusual approaches should be investigated rather than automatically discarded. Target companies that fit the workforce you actually have. St. Pete focuses on industries and companies that align with its existing workforce rather than simply pursuing any company willing to listen. Build recruitment targets around the skills, occupations, graduates, and industry experience already present in your market. Use existing companies as third-party validators. Successful companies can become some of your strongest recruiters. Mike describes connecting prospects with executives who have already relocated or expanded in St. Pete and letting those executives talk candidly about their experience without the EDC in the room. Look beyond complete headquarters relocations. A company does not have to abandon its existing headquarters for your community to win. Expansion operations, new growth, regional offices, and future hiring can produce substantial economic impact even when the original location remains open. Know your product well enough to answer hard questions without bluffing. Companies and consultants often already know the answer when they ask about your workforce, education system, demographics, or costs. Know the numbers well enough to respond confidently and accurately instead of trying to “fake it till you make it.” Don't oversell your community just to get an announcement. A recruitment win becomes a problem if the company arrives and discovers that the promised workforce, costs, or operating conditions do not exist. Focus on creating successful long-term customers rather than maximizing short-term announcements. Understand who is actually moving into your community. Population growth alone is not enough. Mike recommends knowing the ages, skills, education levels, graduation pipeline, and workforce characteristics of the people entering your market so you understand whether your growth supports your business recruitment strategy. Communicate activity to your board before they have to ask about results. Economic development is a long game, and announcements do not happen on a predictable schedule. Keep board members informed about marketing campaigns, prospect activity, outreach, and other leading indicators so they understand the work underway even during quiet periods. Build trust through authenticity and consistency. Mike emphasizes being real, professional, transparent, and trustworthy. Economic developers are asking executives and site-selection professionals to make decisions with long-term consequences, so credibility matters as much as salesmanship.

Thinking about moving to Wasilla, Alaska or relocating to the Mat-Su Valley? In this full episode of the Alaskan Journey Podcast, host Jamin sits down with Logan and Courtney, who recently made the big move to Wasilla from Minnesota.They share their honest experiences navigating the relocation process—from renting an Airbnb with pets to discovering how much the Mat-Su Valley has grown in recent years. Courtney breaks down what it's like working remotely for an out-of-state company while living in Alaska, while Logan shares insights into local employment opportunities in the trades and tree care industry. Plus, they dive into the realities of extreme Mat-Su winter windstorms, town dynamics between Wasilla, Palmer, and Anchorage, cost of living comparisons, local volunteer opportunities (like Beluga whale watching and water rescue), and the pros and cons of living in Alaska's fastest-growing valley!Jamin Goecker Website (For Relocation Guide): https://jgoecker.kw.comPodcast: https://open.spotify.com/show/2AgBLvg...LinkedIn: https://www.linkedin.com/in/jamingoecker/Instagram: / jamin_goecker App: https://jgoecker.kw.comFacebook: / gojaminrealestate Keller Williams Realty Alaska Group00:00 – Welcome to the Alaskan Journey Podcast: Meeting Logan & Courtney01:01 – Why Choose Wasilla? Finding a Central Location in Southcentral Alaska01:27 – Relocating from Minnesota: Renting an Airbnb & Moving with Dogs02:03 – First Impressions of Wasilla: Growth, Population, & Expectation vs. Reality03:30 – Coming from Minnesota: Small Town Living in the Shadow of the Twin Cities03:56 – Lifestyle & Vibe in Wasilla: Community Connections & Local Culture04:22 – Alaska Fishing Adventures: Exploring Parks Highway Rivers & Montana Creek05:02 – Working Remotely from Alaska: The Remote Work Challenge & Social Connection05:39 – Plugging Into the Community: Finding Church Groups & Local Women's Networks06:06 – Wasilla Amenities: Big Box Stores (Target, Walmart, Home Depot) vs. Small-Town Alaska07:10 – Anchorage vs. Wasilla: Big City Vibe vs. Mat-Su Valley Freedom07:44 – Living on the Outskirts: Balancing Convenience with Space & Seclusion08:28 – The Surprising Reality of Wasilla Winds: High-Wind Storms & Power Outages09:28 – Preparing for Alaskan Windstorms: Generators, Power Lines, & Fallen Trees10:03 – Generator Setups & Location Tips for Maintaining Power in Winter11:21 – Extreme Arctic Winds: Clocking 80+ MPH Wind Gusts in the Valley11:30 – If You Had Magic Powers: 4 Things We Would Change About Wasilla11:43 – Problem 1: Traffic Infrastructure & Parks Highway Congestion13:00 – Problem 2: Seclusion vs. Wind Storms (A Tree Worker's Perspective)14:03 – Dealing with Hazard Trees & Tree Removal Around Alaskan Homes16:06 – Problem 3: Cost of Living Realities (Groceries, Housing, & Land Prices)16:41 – Groceries & Scratch Cooking: Managing High Food Costs in Alaska17:44 – Problem 4: Alaskan Tree Diversity & Woodworking Realities18:50 – Employment Opportunities in Wasilla & the Mat-Su Valley19:46 – Job Market Breakdown: Blue-Collar Trades vs. Corporate Office Roles20:57 – Keeping an Open Mind: Career Shifts & Community-Based Work in Alaska22:17 – How a Local Spends a Long Weekend in Wasilla22:58 – Outdoor Access: Hatcher Pass, ATVing, Snowmachining, & Trail Hiking23:29 – Exploring Nearby Towns: Talkeetna, Denali, Girdwood, & Palmer Friday Fling24:19 – Community Events: Endless Things to Do in the Mat-Su Valley25:01 – Town Personalities: Comparing Wasilla, Palmer, and Anchorage26:10 – What Would Drive Us Away? Growth, Commercial Malls, & Proposed Knik Arm Bridge28:31 – Wasilla's Growth Ceiling: Lack of Early Zoning & Unplanned Expansion29:47 – The Pros of Wasilla: High Civic Engagement & Unique Opportunities (Water Rescue Team)31:08 – Becoming a Community Scientist: Volunteering for Beluga Whale Observation

In Usap Tayo, we discussed data from the 2021 Census revealing a rapidly growing Filipino community across Australia, with the population expected to climb further in the upcoming 2026 Census. - Gaganapin ang 2026 Census ngayong Agosto 11. Sa Usap Tayo, balikan muna natin ang bilang ng mga Pilipino sa Australia noong huling census.

You can spend 15 years buying property, building equity, paying down debt and doing all the things that look financially responsible, yet still be no closer to buying back your time. That’s the danger of disconnected investing. In this solo episode of Get Invested, Bushy Martin brings together the critical pieces investors often consider separately: the life you actually want, the income that life will require, when you want the freedom to live it, what your current financial position can support, and exactly what job your next property needs to do. Using the example of Michael and Jessica, Bushy shows how an aspirational $200,000 annual lifestyle income can translate into a $4 million future nest egg, a daunting $3.89 million future shortfall — and then, importantly, a much more practical $1.78 million Freedom Number in today’s terms. But this isn’t about convincing you that you suddenly need to rush out and build a multimillion-dollar portfolio. It’s about working backwards from the destination and identifying the next sensible move. For Michael and Jessica, despite the longer-term numbers potentially pointing towards two or three properties, their current capacity suggests a working purchase ceiling of around $750,000, and one property as the next move. And that property still needs to pass the right tests. Because a good property can be a bad investment for you if it doesn’t match your purpose, capacity or ability to comfortably hold it. Bushy also compares two hypothetical $750,000 investments to demonstrate just how different the holding experience can be. In the examples explored, an established property could require around $705 a week to hold, compared with approximately $217 a week for a qualifying new build — around 69% less in year one. That doesn’t automatically make one better than the other. It means the numbers, the growth evidence and the job the property needs to perform all have to connect. In this episode you’ll discover: Why owning investment property doesn’t automatically mean you’re creating freedom The five numbers that can turn a vague financial future into something measurable The difference between your future GAP and your Freedom Number today Why achieving freedom before super access generally requires accessible assets outside super Why borrowing capacity and usable equity are different, and why neither alone tells you what you should spend How to turn a much larger long-term wealth target into one practical next property decision Why two properties at the same purchase price can have dramatically different holding costs When growth should be the priority, and why cash flow can become increasingly important later How Infrastructure, Industry, Incomes, Population, Position and Property help test the growth case The five questions every potential investment property should pass before you say yes Why your strategy needs to be recalculated when your life, finances or goals materially change You don’t need to solve the next 20 years today. But you do need to know what you’re trying to build, what your current position can safely support and what your next investment is actually being employed to achieve. Start with the numbers. Test the property against its job. Then make the next move — not every move. Because real strategy isn’t collecting tactics or properties. It’s diagnosing what’s stopping you, choosing the right pathway, aligning your actions and adjusting as life changes. FREE PROPERTY INVESTOR’S FIELD GUIDE How Should I Invest In Property Now? After months of post-Budget analysis, modelling and conversations with investors around Australia, Bushy has distilled the key insights into a practical guide designed to help you cut through the confusion and identify the opportunities that still exist for strategic property investors. Download your free copy here: https://bushymartin.com.au/fieldguide Take the next step with Bushy Personal Solutions Session Get clarity and personalised guidance: Book now Property W.E.A.L.T.H Program - live now! Be first to access discounts + free Module 1: Find out more https://courses.bushymartin.com.au/property-wealth Find your Freedom Formula Success in property starts with your 'why', and then the 'what' and 'how'. Let me, Bushy Martin, lead you through it! Sign up for my Freedom Formula program. The first session is absolutely free, and it only takes around an hour! Find out more https://bushymartin.com.au/freedom-formula-course Subscribe to Property Hub for free now on your favourite podcast player. Take the next step - connect, engage and get more insights with the Property Hub community at linktr.ee/propertyhubau Get property investment and wealth resources, and book a Personal Solution Session with Bushy. All the links and info are here: linktr.ee/propertyhubau About Get Invested, a Property Hub show Get Invested is the leading weekly podcast for Australians who want to learn how to unlock their full ‘self, health and wealth’ potential. Hosted by Bushy Martin, an award winning property investor, founder, author and media commentator who is recognised as one of Australia’s most trusted experts in property, investment and lifestyle, Get Invested reveals the secrets of the high performers who invest for success in every aspect of their lives and the world around them. Subscribe now on Apple Podcasts, Spotify and YouTube to get every Get Invested episode each week for free. For business enquiries, email andrew@apiromarketing.com. This content provides general information only and has been prepared without taking into account your objectives, financial situation or needs. It does not constitute legal, tax or financial advice and you should always seek professional advice in relation to your individual circumstances.See omnystudio.com/listener for privacy information.

Ohio researchers have been working on a conservation plan to bolster the native Eastern massasauga. Their efforts may be the first of their kind.

In the final episode, Veeru Kasivisvanathan discusses the future of prostate cancer diagnosis, including AI-assisted MRI interpretation, genomic risk prediction, polygenic risk scores, and the opportunities and challenges of population screening. Discover how precision technologies could reshape prostate cancer care over the next decade. Timestamps: 00:57 – AI and MRI 02:25 – PARADIGM study 02:51 – Large-scale MRI screening 04:56 – Genomics and polygenic risk scores 06:45 – Future optimism of prostate cancer

Text the Show⭐️ Affiliate item of the week: BLAVOR Solar Power Bank 20000mAh Built-in Cables, Wireless Charger for Phones & Apple Watch, 20W Fast Charging Battery Pack with USB C, Flashlight, Solar Charger for iPhone, iPad, iWatch, Samsung. https://link.amazon/B08FQ9e59Tonight our friend Kate Dalley is back with us. Kate is a cutting-edge nationally recognized radio host. She is nationally syndicated in multiple markets and can be found on many online platforms and apps. Her daily LIVE show is turned into a daily podcast. She has 7 amazing weekly co-hosts with different points of view! No parameters or politically correct talking points- she says things people are afraid to say out loud- an equal opportunity offender to both sides of the aisle. Kate's links:The Kate Dalley radio show : https://www.katedalleyshow.com/ Facebook: https://www.facebook.com/thekatedalleyshowInstagram: https://www.instagram.com/katetalksabouteverything/Linktree: https://linktr.ee/KatetalksabouteverythingKate's Shopify: https://katetalks.myshopify.com/What if the world ended... and nobody noticed? What if history changed, but only some people remembered the way it used to be? SUPPORTBuy Me A Coffee http://buymeacoffee.com/DangerousinfopodcastSubscribeStar http://bit.ly/42Y0qM8Super Chat Tip https://bit.ly/42W7iZHBuzzsprout https://bit.ly/3m50hFTPaypal http://bit.ly/3Gv3ZjpPatreon http://bit.ly/3G3 SMART is the acronym that was created by technocrats that have setup the "internet of things" that will eventually enslave humanity to their needs. Support the showLeave Voicemail: https://www.speakpipe.com/DangerousInfoWebsite https://www.dangerousinfopodcast.com/Discord chatroom: https://discord.gg/8feGHQQmwgEmail the show dangerousinfopodcast@protonmail.comJoin mailing list http://bit.ly/3Kku5YtWatch LiveYouTube https://www.youtube.com/@DANGEROUSINFOPODCASTRumble https://bit.ly/4q1Mg7Z Twitch https://www.twitch.tv/dangerousinfopodcastPilled.net https://pilled.net/profile/144176  Facebook: https://www.facebook.com/DangerousInfoPodcast/SocialsInstagram https://www.instagram.com/dangerousinfo/TwitterX https://twitter.com/jaymz_jesseYouTube https://bit.ly/436VExnFacebook https://bit.ly/4gZbjVa

In this episode of The Canadian Macro Investor Podcast, Simon and Dan break down the latest Fed decision and why the bond market may be starting to challenge Kevin Warsh’s inflation message. They discuss the split reaction across the yield curve, with short-term yields moving differently than longer-term yields, and what that could mean for inflation, recession risk and future rate hikes. They also look at Canada’s population data problem and why undercounting temporary residents could distort unemployment, mortgage delinquency trends and the broader read on the Canadian economy. From there, they dig into big tech earnings, including Microsoft and Meta, and why investors are paying closer attention to AI capex, free cash flow, depreciation, and credit default swaps across the hyperscalers. They also discuss Anthropic, open-weight AI models, data privacy concerns, tariffs, copper demand, and what the AI infrastructure build-out could mean for energy and markets. Tickers discussed: MSFT, META, GOOG, GOOGL, AMZN, NVDA, ORCL, AAPL, SKM Watch the full video on Our New Youtube Channel! Check out our portfolio by going to Jointci.com Our Website Canadian Investor Podcast Network Twitter: @cdn_investing Simon’s twitter: @Fiat_Iceberg Braden’s twitter: @BradoCapital Dan’s Twitter: @stocktrades_ca Want to learn more about Real Estate Investing? Check out the Canadian Real Estate Investor Podcast! Apple Podcast - The Canadian Real Estate Investor Spotify - The Canadian Real Estate Investor Web player - The Canadian Real Estate Investor Asset Allocation ETFs | BMO Global Asset Management Sign up for Fiscal.ai for free to get easy access to global stock coverage and powerful AI investing tools. Register for EQ Bank, the seamless digital banking experience with better rates and no nonsense.See omnystudio.com/listener for privacy information.

In this episode, my guest is Dr. Sean Cain, PhD, a Harvard Medical School-trained expert in the impact of light on the human circadian system, a Matthew Flinders Professor at Flinders University, and Co-Founder and CEO of Circadian Health Innovations. Today, he discusses how people differ more than fiftyfold in how sensitive their circadian systems are to evening light, that nearly half of modern homes are bright enough at night to suppress melatonin by fifty percent, and that most of us have no conscious awareness of any of it. We discuss the large observational studies he and his team have published linking bright days and dark nights to depression, type 2 diabetes, cardiovascular disease, and mortality, as well as his research on impaired light sensitivity in depression and why the amplitude of your circadian rhythm may matter more than its timing. We also discuss MiEye, the wearable light sensor his team developed, and practical changes to home and daytime lighting that anyone can make tonight.CLICK HERE FOR THE FULL SHOWNOTESThis includes all other resourcesSponsor: Brighter Lamphttps://getbrighter.com/?sjram=P2jrTbowzJOdCode: JONATHANJ   Subscribe to the newsletter: https://jonathanjarecki.substack.com/?utm_campaign=profile_chipsTimestamps 00:00 Intro03:54 Dr. Sean Cain04:42 Dr. Cain's Love for Science and Research10:25 Understanding Circadian Rhythms: Anatomy and Function10:56 Setting the stage: Circadian Biology, Rhythms, SCN, ipRGCs16:20 Light, Circadian Entrainment, Mechanisms19:57 High Sensitivity and Interindividual Variability in the Response of the Circadian of the Human Circa22:02 Individual Sensitivity to Light and Circadian Disruption27:22 Home Lighting, Sunset, LEDs, Fluorescents, Incandescents27:37 Home Lighting and Its Effects on Circadian Health33:46 Tools: circadian friendly home lighting39:24 Population health outcomes; UK BioBank39:29 Psychiatric Disorders47:52 SPONSOR: Brighter Lamp49:34 The Link Between Light Exposure and Mental Health01:04:18 Light Exposure and Longevity: Key Findings01:09:45 The Importance of Daylight for Health01:17:41 Understanding Circadian Rhythms and Light Exposure01:17:52 The Impact of Light on Mood and Self-Perception01:23:39 Innovations in Circadian Health: My Eye Device01:34:15 Jet Lag Management and the Jet Lag App01:39:09 Support, YouTube, Spotify & Apple Follow, Reviews & Feedback, Social Media, Substack Newsletter

Australia conducts a population census every five years. One of the benefits of the census is that it provides an opportunity particularly for the government to obtain valuable information about the population that would otherwise be unavailable. The next census is scheduled for August 11, 2026. - Setiap lima tahun sekali Australia melakukan sensus kependudukan. Salah satu keuntungan dengan adanya Sensus adalah memberikan kesempatan bagi pemerintah terutamanya untuk memperoleh informasi berharga mengenai penduduk, yang jika tidak demikian tidak dapat diperoleh. Kali ini Sensus akan diadakan pada tanggal 11 Augustus 2026.

HEADLINES:• Dubai's Population Has Officially Reached 4.74 Million• The UAE Could See More Rain Until August 3• Dubai Residents Can Now Donate To Feed Stray Cats Through Smart Feeding Stations• The Wizard Liz Reveals on a Dubai Podcast She Had a Gut Feeling Her Ex Was Cheating While Pregnant• Deon And Aeben Break Down How They Took Over Everyone's FYP

Stand Up is a daily podcast. I book,host,edit, post and promote new episodes with brilliant guests every day. This show is Ad free and fully supported by listeners like you! Please subscribe now for as little as 5$ and gain access to a community of over 750 awesome, curious, kind, funny, brilliant, generous soul Subscribe and Watch Interviews LIVE : On YOUTUBE.com/StandUpWithPete ON SubstackStandUpWithPete The Committee to Protect Health Care, composed of over 36,000 doctors and advocates across the United States, drives lasting change in health care by using our tested and proven strategies across everything we do. Through our physician-led initiatives and targeted advocacy, we push for accessible, affordable, and equitable health care. Our programs reflect our commitment to advancing policies that put patients first and safeguard the health and freedom of every family. Nearly 25 years as an emergency medicine physician has provided Dr. Rob Davidson with a wealth of knowledge in practicing health care. Two years ago, however, he decided that he needed more. He began pursuing a Master of Public Health degree in the online Population and Health Sciences program at the University of Michigan School of Public Health.  "I've always been right at that point of health care where you meet people at significant moments in their life," said Davidson, a West Michigan-based physician. "The ER seems far removed from the goals of population health and public health, but you come to realize just how much people's wider world has an impact on what brought them to the ER at that point in time."  Davidson pondered earning his master's degree for a while, having seen colleagues who earned their MPH go on to impact local health outcomes. When the COVID-19 pandemic hit, he knew that pursuing an MPH was the right next step.  Listen rate and review on Apple Podcasts Listen rate and review on Spotify Pete On Instagram Pete on Blue Sky Pete on Threads Pete on Tik Tok Pete on Twitter Pete Personal FB page Stand Up with Pete FB page Gift a Subscription https://www.patreon.com/PeteDominick/gift Send Pete $ Directly on Venmo All things Jon Carroll  Buy Ava's Art  Subscribe to Piano Tuner Paul Paul Wesley on Substack Listen to Barry and Abigail Hummel Podcast Listen to Matty C Podcast and Substack Follow and Support Pete Coe Hire DJ Monzyk to build your website or help you with Marketing

Who should control Britain's biggest water company? Chris Weston, the chief executive of Thames Water, says he "completely agrees" with the Prime Minister that the industry, and Thames Water, needs greater public control. But he draws a clear distinction between stronger public accountability and public ownership, arguing that nationalisation or special administration could delay investment, increase uncertainty and ultimately leave taxpayers carrying the financial risk.Thames spent more than £1bn more than it received last year, with the shortfall currently funded by creditors. Under special administration, Weston says that funding would instead have to come from government while a new owner was sought. Full nationalisation, he argues, would place Thames Water's decade-long infrastructure programme on the public balance sheet alongside defence, health and education. His preferred solution is the proposal from more than 100 creditors to write off around £9bn of debt, inject fresh equity and rebuild the company under a model that promises no dividends for at least ten years. He argues this private-sector restructuring can sit alongside stronger public oversight, clearer government direction, greater regional representation and a more company-specific regulatory regime.The debate over ownership comes as Weston warns Britain faces a much bigger challenge. Drought, he says, is no longer an exceptional event but "the new normal". Despite an unusually wet January and February, no rain fell across the Thames Valley in July, exposing a shortage of water storage across the South East.Thames has not built a reservoir since Farmoor B in 1977. A replacement scheme proposed around 2010 was rejected after the company failed to make its case successfully, and Weston believes the region would not be facing a hosepipe ban today had it been approved. The proposed Whitehorse reservoir near Abingdon remains in the planning process and is not expected to begin filling until 2038, with another three years needed before it reaches capacity.Population growth, government housebuilding targets and the rapid expansion of data centres will place even greater pressure on supplies. Weston questions whether data centres should rely on drinking water for cooling, suggesting treated effluent from sewage works could provide an alternative. He also says households will need to become more mindful of how they use water, with government playing a greater role in encouraging behavioural change.Weston also makes a notable concession about how the industry reached this point. Customers, he says, have "paid too little for water for too long". Thames operates 440 treatment works and a network stretching four times around the circumference of the Earth. Keeping bills low, he argues, meant insufficient investment in maintaining and modernising ageing infrastructure, although he accepts the company's current debt levels are unsustainable.On pollution, Weston accepts Thames must improve but refuses to promise sewage incidents can ever be eliminated entirely. The company treats around 4.3 billion litres of wastewater every day and, he says, succeeds 99.5% of the time on average. Extreme weather, ageing infrastructure and illegal connections mean completely eliminating pollution incidents remains "very, very slim".Presenter: Simon Jack Producer: Olie D'Albertanson/Ollie Smith00:00 BBC Editor, Simon Jack introduces podcast 03:09 Chris Weston joins pod, explains Thames Water's situation 06:18 Bills were too low for too long. 09:32 Unrealistic targets, swage and pollution 12:31 Privatisation of Thames Water 14:50 What's on the table now? 17:28 Greater public control, special administration and nationalisation 28:41 Drought, reservoirs and the new normal 34:29 Staff abuse and his own pay

Louisiana's population is growing again, and the gain is more about current residents choosing to stay than new people moving in. We break down the numbers with Barry Erwin, Chief Policy Officer for Leaders for a Better Louisiana.

After decades of elite fearmongering concerning overpopulation, a new terror has lifted its head and is slouching toward us: underpopulation.   What will the world look like when the population begins to crater?  Should we be worried?  Peter leads a discussion about the trend of declining birth rates, why this is bad, and some possible solutions.

Welcome to Science Quest!

Western snowy plovers are tiny, shy shorebirds that are slowly making a recovery along the West Coast. Reporter: Erin Malsbury, KAZU Doctors are announcing an effort to unionize nearly 10,000 senior physicians at the University of California. Reporter: Farida Jhabvala Romero, KQED Learn more about your ad choices. Visit megaphone.fm/adchoices

In this episode of the Awareness to Action Enneagram podcast, Mario Skora, María José Munita and Seth “Creek” Creekmore talk about coaching Enneagram Type Six.TIMESTAMPS[00:01] Intro[02:12] Striving to Feel Secure[04:38] Population selection[07:40] Fixation on the negative[11:07] Always look behind the behavior[13:22] The subtype distinctions[17:25] Subtypes in leadership roles[20:55] The connecting points[27:06] Opportunities for growth[36:09] Six's accelerator: evidence[40:31] Final thoughtsConnect with us:Awareness to ActionATA on DemandIG: @ataenneagrampodYouTube: ATA Podcast NetworkEmail: info@awarenesstoaction.comSend a voice message: speakpipe.com/AwarenesstoActionMario Sikora:IG: @mariosikoraTikTok: @mariosikoraWeb: mariosikora.comPod: Enneagram in a MoviePod: Thinking Well & WhySubstack: mariosikora.substack.comBook: How to Think Well, and Why: The Awareness to Action Guide to Clear ThinkingMaría José Munita:IG: @mjmunitaWeb: mjmunita.comSeth "Creek" Creekmore:IG: @_creekmorePod: Fathoms | An Enneagram PodcastPod: Delusional OptimismPod: International Enneagram Association PodcastPod: Thinking Well & Why

Episode 5527: Using Fear To Manipulate The Population

Gregory Copley critiques the stalemate in the Persian Gulf, suggesting that US air strikes alone cannot win without a plan for regime change. He advocates for supporting the domestic Iranian population against the clerical leadership. Turkey's opposition to empowering Kurdish forces remains a significant complication. (9)1904

Samuel Ben-Ur — Israel controls 70% of Gaza, creating a buffer zone while Hamas remains on the coast; 98% of the population resides on the Hamas-controlled side, where the group exploits humanitarian aid for revenue, and the Board of Peace proposes a "pilot zone" in Tel Sultan for non-Hamas civilians. (1)14922

Preview for Later Today: Samuel Ben-Ur analyzes the precarious status of Gaza, noting that disarmament of Hamas is the prerequisite for rebuilding. He highlights that nearly the entire population remains under Hamas control, stalling any peace conversion efforts.1898

────────────────────────────────────────[00:02:08]Journalist John Rappaport Dies — Knight Contrasts Him With Lindsey Graham, Who Died the Same WeekendRappaport questioned official COVID narratives when nobody else would; Graham spent his career pushing wars, coups, and mass death from behind the scenes.────────────────────────────────────────[00:05:22]Graham and McCain Flew to Ukraine to Stoke the Coup — Told Troops in 2016 "Next Year We Go on Offense Against Russia"Putin is not primarily responsible for the Ukraine war; Graham and McCain were pushing this outcome for years before Russia invaded.────────────────────────────────────────[00:15:04]Graham Never Saw a War He Didn't Like — His Last Act Was Pushing Trump to Strike Iran"We're killing all the right people" — his own words; he told Trump now was the time because Trump "thinks he runs the world."────────────────────────────────────────[00:22:16]Hamas AK-47 Fire Cannot Vaporize Cars — Israeli Apache Helicopters CanDocumentary evidence shows melted engine blocks at the Nova festival; AK rounds can't do that; Hellfire missiles from Israeli Apaches can; orders caught on video.────────────────────────────────────────[00:33:45]Graham Said "If America Pulls the Plug on Israel, God Will Pull the Plug on Us" — God Has Pulled the Plug on GrahamNetanyahu confirmed Graham kept pushing for more US funding even when Israel didn't want it; he'd go over Netanyahu's head to demand more.────────────────────────────────────────[00:40:05]Christian Zionists Replaced Christ and Abraham With the Nation of Israel — Cruz Says "We Are Commanded to Support Israel"They replaced promises to Abraham with promises to a corrupt warmongering government that kills for land; a convenient, not unfortunate, interpretation.────────────────────────────────────────[00:54:08]McConnell's Weekend at Bernie's Has Run 29 Days — Republicans Changed Kentucky Law in 2024 to Block a Special ElectionThey knew McConnell was in poor health and changed the law; hold out to August 3 and the governor cannot appoint a replacement.────────────────────────────────────────[00:55:10]CNN About to Fire Scott Jennings After Claiming to Speak With McConnell for 20 Minutes — RepeatedlyCNN said his claims don't represent the network; every GOP insider claimed the same 20-minute conversation, suggesting coordinated talking points.────────────────────────────────────────[01:18:11]WHO Reports Cancer Exploding Globally — Expected to Affect 90% of the Population by 2050Before the mRNA rollout, cancer affected ~20% of men and 17% of women; after 70% global vaccination turbo cancers are accelerating toward the WHO's 90% projection.────────────────────────────────────────[01:19:02]Dr. Ryan Cole Warned in Spring 2021 That T-Cell Suppression Would Cause a Cancer Explosion — He Was RightHe observed destroyed T-cell counts immediately after vaccination and predicted the wave of aggressive cancers now being confirmed globally. ──────────────────────────────────────── Money should have intrinsic value AND transactional privacy: Go to https://davidknight.gold/ for great deals on physical gold/silver For 10% off Gerald Celente's prescient Trends Journal, go to https://trendsjournal.com/ and enter the code “KNIGHT” For high quality made in America products go to HomeSteadProducts.shop and use promo code “Knight” for 10% off your purchases Find out more about the show and where you can watch it at TheDavidKnightShow.com If you would like to support the show and our family please consider subscribing monthly here: SubscribeStar https://www.subscribestar.com/the-david-knight-show Or you can send a donation throughMail: David Knight POB 994 Kodak, TN 37764Zelle: @DavidKnightShow@protonmail.comCash App at: $davidknightshowBTC to: bc1qkuec29hkuye4xse9unh7nptvu3y9qmv24vanh7Become a supporter of this podcast: https://www.spreaker.com/podcast/the-david-knight-show--2653468/support.

────────────────────────────────────────[00:02:08]Journalist John Rappaport Dies — Knight Contrasts Him With Lindsey Graham, Who Died the Same WeekendRappaport questioned official COVID narratives when nobody else would; Graham spent his career pushing wars, coups, and mass death from behind the scenes.────────────────────────────────────────[00:05:22]Graham and McCain Flew to Ukraine to Stoke the Coup — Told Troops in 2016 "Next Year We Go on Offense Against Russia"Putin is not primarily responsible for the Ukraine war; Graham and McCain were pushing this outcome for years before Russia invaded.────────────────────────────────────────[00:15:04]Graham Never Saw a War He Didn't Like — His Last Act Was Pushing Trump to Strike Iran"We're killing all the right people" — his own words; he told Trump now was the time because Trump "thinks he runs the world."────────────────────────────────────────[00:22:16]Hamas AK-47 Fire Cannot Vaporize Cars — Israeli Apache Helicopters CanDocumentary evidence shows melted engine blocks at the Nova festival; AK rounds can't do that; Hellfire missiles from Israeli Apaches can; orders caught on video.────────────────────────────────────────[00:33:45]Graham Said "If America Pulls the Plug on Israel, God Will Pull the Plug on Us" — God Has Pulled the Plug on GrahamNetanyahu confirmed Graham kept pushing for more US funding even when Israel didn't want it; he'd go over Netanyahu's head to demand more.────────────────────────────────────────[00:40:05]Christian Zionists Replaced Christ and Abraham With the Nation of Israel — Cruz Says "We Are Commanded to Support Israel"They replaced promises to Abraham with promises to a corrupt warmongering government that kills for land; a convenient, not unfortunate, interpretation.────────────────────────────────────────[00:54:08]McConnell's Weekend at Bernie's Has Run 29 Days — Republicans Changed Kentucky Law in 2024 to Block a Special ElectionThey knew McConnell was in poor health and changed the law; hold out to August 3 and the governor cannot appoint a replacement.────────────────────────────────────────[00:55:10]CNN About to Fire Scott Jennings After Claiming to Speak With McConnell for 20 Minutes — RepeatedlyCNN said his claims don't represent the network; every GOP insider claimed the same 20-minute conversation, suggesting coordinated talking points.────────────────────────────────────────[01:18:11]WHO Reports Cancer Exploding Globally — Expected to Affect 90% of the Population by 2050Before the mRNA rollout, cancer affected ~20% of men and 17% of women; after 70% global vaccination turbo cancers are accelerating toward the WHO's 90% projection.────────────────────────────────────────[01:19:02]Dr. Ryan Cole Warned in Spring 2021 That T-Cell Suppression Would Cause a Cancer Explosion — He Was RightHe observed destroyed T-cell counts immediately after vaccination and predicted the wave of aggressive cancers now being confirmed globally. ──────────────────────────────────────── Money should have intrinsic value AND transactional privacy: Go to https://davidknight.gold/ for great deals on physical gold/silver For 10% off Gerald Celente's prescient Trends Journal, go to https://trendsjournal.com/ and enter the code “KNIGHT” For high quality made in America products go to HomeSteadProducts.shop and use promo code “Knight” for 10% off your purchases Find out more about the show and where you can watch it at TheDavidKnightShow.com If you would like to support the show and our family please consider subscribing monthly here: SubscribeStar https://www.subscribestar.com/the-david-knight-show Or you can send a donation throughMail: David Knight POB 994 Kodak, TN 37764Zelle: @DavidKnightShow@protonmail.comCash App at: $davidknightshowBTC to: bc1qkuec29hkuye4xse9unh7nptvu3y9qmv24vanh7Become a supporter of this podcast: https://www.spreaker.com/podcast/the-real-david-knight-show--5282736/support.

--{ "Dead Loss if You Don t Know Who's Boss"}-- Jon Rappoport's death - Is the US Congress merging the US and Israeli militaries? - United States-Israel Defense Technology Cooperation Initiative - Is Turkey Israel's next target? - Living through a script - Century of Change - Integration of the Americas - General Wesley Clark, planned wars - US military worldwide - AIPAC supports US strike in Syria - Israeli policy statement on Syria - New York Times self-censorship - Power of lobby groups - Libya - Greater Israel Plan - Exportation of "progressive" literature - Israel missile test - The Silent Majority - John Holdren and Paul Ehrlich, "Science Diplomacy", Population control - Mass immigration - Forced abortion and sterilization - Nations "Obsolete" - Global system - Plunder of pensions - Austerity - Pharmaceutical clinical trials and side effects - Natural Capital, Green Banks.

Today on AirTalk: Homelessness in California (0:30) Drive-thru bans (35:42) Growing wolf population (51:06) California citrus crate labels (1:08:16) Best grades to teach (1:23:47) Visit www.preppi.com/LAist to receive a FREE Preppi Emergency Kit (with any purchase over $100) and be prepared for the next wildfire, earthquake or emergency

Worried about a ballooning population, the Chinese government introduced its infamous one-child policy in 1980. At the time it seemed urgent to find ways to reduce the number of babies being born. China today has the opposite problem - too few births. Since the one-child policy was scrapped 10 years ago, there have been increasingly desperate attempts to encourage couples to have more children. But nothing has worked. China's population has already started to fall. That process will gather pace over the coming decades. The population is on track to halve by the end of the century. Micky Bristow, who has reported on China over more than 20 years, looks at why this is happening, and what the consequences could be.