Podcasts about Runway

Dynamite's new X-Files comic reveals new details. DC GO! is kicking off its first every digital crossover, Runway to Ruin. Writer Steve Orlando exits Scarlet Witch.SUBSCRIBE ON RSS, APPLE, SPOTIFY, OR THE APP OF YOUR CHOICE. FOLLOW US ON BLUESKY, INSTAGRAM, TIKTOK, AND FACEBOOK. SUPPORT OUR SHOWS ON PATREON.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

You promoted your best person. So why does it feel like something has gone wrong?In this Marketing 4 Business episode, Scott welcomes back Amy Jones, leadership coach and founder of Human Impact leadership, to unpack why capable people struggle when they step into leadership, and what business owners can do about it. Amy works with teams across New Zealand and now Australia. She shares practical tools from her Emerging Leaders Programme, including:Why leadership is 80% psychology and 20% skillThe heart emoji that came up in an exit interview, and what it taught Amy about leading across ages and channelsHow to make conflict healthy, and "kill the monster while it's little"Why new leaders dive in and do the work, and how that pattern leads to burnout as teams growClearing the runway: how leaders spot and remove roadblocks, including when the roadblock is themWhy you should build the leader before the role existsThe mindset trap of only training people who are underperformingWhy time and energy matter as much as money for business ownersIf you're a business owner trying to grow leaders who take ownership, keep good people longer, or get your time back, this episode is well worth your time.Download the Local Business AEO Playbook HERE. A free, step-by-step guide showing you how to position your business to be recommended by AI.If you found this episode valuable, please share it with another business owner who could benefit. Don't forget to follow Marketing 4 Business on your favourite podcast platform, and if you enjoyed the episode, we'd really appreciate a five-star review. Your support helps us reach more business owners with practical marketing insights.Connect with us:Follow the Marketing 4 Business podcast on Instagram HERE.Follow Digital Influence on Instagram HERE.Visit Digital Influence's website HERE.Book a complimentary marketing strategy session HERE.Connect with Scott Wilson on LinkedIn HERE.Connect with Amy Jones on LinkedIn HERE.Have Fun & Take Action

Poolbeg Pharma PLC (AIM:POLB) CEO Jeremy Skillington spoke with Proactive's Stephen Gunnion about the company's interim results for the first half of 2026, progress with POLB 001 and the milestones investors can expect as its clinical development programme advances. Skillington said Poolbeg Pharma made "incredible progress" during the period, successfully transitioning POLB 001 from trial preparation into active clinical development. The programme is being studied in relapsed or refractory multiple myeloma patients, aiming to prevent cytokine release syndrome associated with cancer therapy. The company has completed its first interim safety cohort review and is continuing with the same dose as recruitment progresses across UK clinical trial sites, with additional sites approaching Poolbeg about participating in the study. Skillington also discussed the company's expanding intellectual property portfolio, engagement with the US FDA and commercial research with US payers, work he said has strengthened the package Poolbeg can present to potential pharmaceutical partners. Poolbeg also completed a £3.5 million fundraising, giving it a cash runway into 2028. Skillington said this funds both the POLB 001 trial and the oral GLP-1 proof-of-concept trial, allowing the company to approach potential business development transactions from a position of financial strength. Looking ahead, Skillington highlighted accelerating patient recruitment, the expected start of the oral GLP-1 trial in H2, and ongoing discussions with pharmaceutical companies, saying Poolbeg expects access to POLB 001 data in the near term, providing an early indication of the programme's direction of travel. Visit Proactive's YouTube channel for more interviews and market updates. If you found this video useful, give it a like, subscribe to the channel and enable notifications for future content. Read Proactive's Editorial Policy here: https://www.proactiveinvestors.co.uk/pages/editorialPolicy #PoolbegPharma #POLB001 #Biotech #Biotechnology #ClinicalTrials #Pharma #Pharmaceuticals #CancerTherapy #CancerImmunotherapy #MultipleMyeloma #CytokineReleaseSyndrome #CRS #GLP1 #DrugDevelopment #HealthcareInvesting #Investing #AIMStocks #Proactive

The MLB playoffs are upon us! Can Sean name all 12 teams participating in this year's postseason? We're also diving into some cute on-field moments, some hilariously juvenile celebrations, and some silly penalties that perhaps swung games. Plus, Joey runs the Run the Runway 5k on at the Corpus Christi International Airport, and the Cowboys also somehow lost against the Ravens in regulation after tying the game with seven seconds left. Sean vows to quit football. We'll see how long it lasts.Referenced in this episode:Genevieve Verlander surprises her dadCollins Simmons with an unsportsmanlike conduct penaltyRams' pass interference call against the Broncos

Most founders start thinking about Black Friday the week before. The ones who actually win it start four weeks out and are already closing sales before they ever make a public announcement. In this episode of Running With Wolves, Savannah walks through the complete Black Friday marketing playbook, the promotion options, the four week countdown and the exact moment you stop teasing and start selling, so that when Black Friday arrives you are converting an audience you already warmed instead of trying to warm and convert at the same time. Here's what this episode covers: Why a massive discount is not always the right Black Friday move and two other promotion options that protect your brand and your price point Week by week breakdown of what your marketing needs to do in the four weeks leading up to Black Friday Why the people who buy from you on Black Friday discovered you weeks before Black Friday and what that means for your October strategy How to capture Black Friday sales before you ever publicly announce your promotion Apply to work with Savannah HERE: http://bit.ly/applywlfpodcast or DM her on Instagram @itssavannahjordan ( / itssavannahjordan ) with your takeaway. Black Friday marketing strategy, Black Friday sales, holiday marketing, Q4 marketing, marketing strategy 2026, female founder, organic marketing, content that converts

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Brought to you by the English Programme. Featuring news, politics, popular culture, celebrity trivia, quizzes, book readings, and a whole host of fun.Support Our Rescue Cats | Our Blog | Get New Episodes By Email | Rumble | X | YouTube | NewsK365 on Spreaker | Get New Blog Posts By Email | Throne Wishlist |

Earlier this month, world model company Runway introduced GWM Worlds 2, a research preview that “turns high-fidelity video and audio generation into real-time interactive simulation.” Runway calls this an “autoregressive diffusion” model; with autoregressive describing how it generates over time.One new feature in particular caught our eye: WorldPrompt, a proposed input format for specifying a generated world and the actions within it. It allows you to fix some aspects of a simulated environment — including the first frame — and then create a series of timestamped events. The events, or actions, can even be prompted in real-time.To understand the implications of WorldPrompt, we spoke to Kamil Sindi, Runway's CTO, and Robin Kahlow, its Principal Research Scientist for generative video and multimodal AI. We also have exclusive comments from Anastasis Germanidis, co-founder & co-CEO of Runway, courtesy of a podcast swyx and Vibhu did with him.Who's building real-time interactive world models?First, some context about world models that can generate interactive video and audio in real-time.Runway is reportedly valued at $5.3 billion, based on its most recent fund raise of $315 million in February. Its first release, GWM Worlds, was launched last December.Alongside Runway, there are several other notable projects in this domain: Google DeepMind's Genie 3 (which also generates at 720p and 24 fps), Odyssey-2 Pro, and World Labs' RTFM (Real-Time Frame Model). We've summarized their differences in the following table:Given the complexity and massive latency demands of real-time video and audio generation (which we'll get into below), all of the projects listed above have limitations. For instance, Google notes that Genie 3 “can currently support a few minutes of continuous interaction, rather than extended hours.”But as our interviews with Runway show, real progress is being made.The central idea of WorldPromptWorldPrompt, a new feature in GWM Worlds 2, helps differentiate Runway from its competition. You can think of it as a control layer for characters, cameras and the environment. As Kahlow put it, it's a way to “control all the different subjects in the world” — similar to a computer game.“Like, if there's an NPC [Non-Player Character] somewhere, the NPC might walk up to you and say something. So you could achieve the same thing with this kind of model, where you can have very detailed control over everything in the scene.”As the name suggests, WorldPrompt is a prompting mechanism — not a programming language. So, unlike virtual world games like Minecraft or Roblox, GWM Worlds 2 doesn't offer scripting capabilities or the ability to control state. But there's a power to that, as Sindi pointed out.“You can create promptable worlds on-demand with video and audio in sync, across all these different domains and environments. That's not a distant-future hypothetical thing,” he said.But there are also limitations to prompting a world model. We asked how reliably the model would follow an instruction to create, for example, a law of gravity or a certain ability in a character?“Yeah, so it's a research preview,” Kahlow replied. “So it's not perfect, of course, and there are still flaws. It really depends on how difficult the action is. I would say movement works quite reliably.”Sindi added that more training plus scaling the data and models is resulting in “better following.”How a video model becomes a real-time runtimeDespite the current limitations of GWM Worlds 2 — especially if you compare it to pre-designed and scriptable worlds like Minecraft or Roblox — the true promise of world models like Runway is that they'll eventually lead to fully self-generated, real-time games and experiences. Which is an extremely hard engineering problem, as Kahlow reminded us.“There are two challenges. One is making the model not generate a whole clip at once. So instead, you want it to generate frame by frame while you're looking at it. And the other challenge is actually making the generation fast, so you can play it in real time.”GWM Worlds 2 offers real-time interactive worlds streamed in continuous 720p video at 24 frames per second (fps) and audio at 48,000 Hz.Runway achieved this firstly by taking its foundational audio-video generation model and fine-tuning it to the new WorldPrompt format, so the model can follow that. It then post-trains the model to generate autoregressively.“And after that, we work on making it real-time through distillation methods,” Kahlow added.Co-CEO Anastasis Germanidis offered more technical details in our podcast with him. He told us that the process starts from “bidirectional diffusion that basically generates an entire video at once and [makes] it autoregressive.” This allows the model to “generate one frame or a few frames at a time.”Germanidis described two possible forms of distillation in order to make it real-time: distilling a larger model into a smaller one or reducing its diffusion steps. As a general example, he said a model might go from around 50 denoising steps to four, with some quality loss but potentially comparable results.The challenges of real-time generationGermanidis admitted that there were issues with how it generates real-time interactive video.“The biggest challenge with autoregressive models is error accumulation,” he said. “You're feeding generated frames back into the model to generate the next frames, and if there are any small errors, they accumulate over time.”Sindi told us there are also challenges dealing with “infinite generations” of content.“There's all these challenges around what context to keep, what to discard that's not important. And so there's all these optimizations we have to think about, so we're not blowing up our GPU memory.”Another current limitation is long-term memory. “The model does not have perfect memory,” Kahlow said. “That's still an open research problem.”Causality and correctnessWhile performance is the primary challenge for Runway at this time, its world model also has to produce plausible consequences when a user takes different actions.Germanidis used the example of simulating football; he pointed out that online video training data contains more successful goals than failed goal attempts, so a video model might render the first more convincingly.“If I take this action versus this action, you want it to generate equally realistic outcomes,” he told us. “That's, I think, the big gap between video models and world models: that idea of counterfactual generation.”Sindi told us that evaluation gets harder the more complex interactions get.“If you have this multi-prompt, multi-character, multi-scene [environment], how do you really understand what was causal and what was not?”To try and solve that, Runway has some automated verifiable tests. But since GWM Worlds 2 is a research preview, Kahlow noted that doing tests yourself is also advisable — “trying out your model to see what doesn't work is really important.”More than gaming — there are agent use cases tooGaming is the obvious use case for what Runway is building, but there are others. Kahlow mentioned robotics — for example using a simulated environment to test how a robot works.Another, more intriguing, use case is to use it to test agents at scale.“Having thousands of simulated environments is much less challenging if you have a suitable model like GWM Worlds,” Kahlow said.But how does an agent know what's changed in the world — is there a structured state that it can read, or is it just the generated video and audio that it's consuming and understanding?“So there's no structured state here,” Kahlow replied. “It's just observing the same thing you might observe in real life, just [in this case] from cameras.”Sindi noted that GWM Worlds can also be used for “synthetic data generation for agents.”Finally, Germanidis suggested there's potential to use these world models alongside reasoning models.“You're maybe using some reasoning [for] planning of the scene, and then you're passing it into the diffusion head that's actually generating the pixels.”Anastasis Germanidis* LinkedIn: https://www.linkedin.com/in/agermanidis/* X: https://x.com/agermanidisTimestamps00:00:00 Introduction00:05:17 Runway's Origins and the Bet on Generative Video00:12:23 The Stable Diffusion Story00:18:44 Gen-2, Controllability, and the Weekend Hack00:23:02 From Video Generation to World Models00:28:03 Learning From the World, Not Just Language00:35:04 Sora, Runway's Existential Crisis, and Gen-300:39:39 Why Real-Time Video Is Inevitable00:43:06 Interface World Models: Software Without Code00:50:25 The Fully Neural Operating System00:55:11 World Models for Robotics01:02:32 Robot Policies and World Action Models01:07:47 The Lucid Dream Test01:11:41 Video Agents and Omni Models01:23:12 Artists, AI, and Creative Workflows01:27:14 Physical AI and the Future of World ModelsTranscriptIntroduction: Runway, Creative AI, and the Early ThesisSwyx [00:00:00]: Okay, we're here with, Anastassios from Runway, with, me and Vibhu in the studio. Welcome.Anastasis [00:00:08]: Good to be here.Swyx [00:00:09]: Congrats on all your success and progress with Runway. You're opening offices all over the world. Did you envision this when you first started out?Anastasis [00:00:16]: Not quite. I think even when we started, we had this idea that, It was more a matter of when, not if, we were seeing the early generative models of 2016, 2017, and just extrapolating, assuming, we resolution, quality increases predictably over time. There's gonna be a point where most of content will be generated, and that was maybe the initial thesis of Runway was we will need, as a result of those generative models, rethink how creative tools are made. and as we built out the research behind, our generative models, it then became clear that they were useful far beyond that as well.Anastasis' Background: Art, Simulation, and Machine LearningSwyx [00:00:57]: And it is more obvious now with, like, the real-world stuff and the world models that we'll talk about later. I'm just kinda curious how you go from a background in, like, Zocdoc and, computer vision into Runway. Like, take us back to that early conversations with Chris and, whoever else is on your founding team.Anastasis [00:01:14]: I was always splitting through those two worlds. One was the I had my own art practice. I was making a lot of interactive art, I think for a long time. and then on the other side, I was working in startups, and I was working as a ML engineer, as a backend engineer at different companies. I've always been interested in, coding and computation, and especially interested in simulation and brought it back into my early artwork as well. And at the same time, I was interested inSwyx [00:01:43]: The personal site has a few, right?Anastasis [00:01:44]: Yeah.Swyx [00:01:45]: Is there one that we should pull up? Just in case there's something that's like. I just like to go down memory lane.Anastasis [00:01:50]: Yeah.Swyx [00:01:50]: Okay, what is this?Anastasis [00:01:51]: So this was, a project that I made, I think back in 2015, where I built this software that would give, voice instructions to people in a gallery space. So it would coordinate interactions between people. And so it will first give you an identity, like you're an, architect, you're 30 years old, and, you like sports. and then it would match you with another person, and you have this completely generated interaction. language models were not quite there at the time, and so it was it was a mix of some templates and some, like, some Markov chain-generated text, and it would just completely simulate these small talk conversations between, everyone in the gallery space. so was always very fascinated on the one hand with, generative models and, like, the early machine learning work that was being at that time. But at the same time, there was this separate thread of simulation and what it means. Like, what can we learn about humans by creating those very simple models of their interactions and their behavior?Early Generative Art: pix2pix, GANs, and Uncanny ValleyVibhu [00:02:56]: Did you generate the prompts or, the 30-year-old, whatever? Was it you generating them? How'd you, how'd youAnastasis [00:03:03]: Exactly. So the program would just generate- those, from. Yeah, a lot of it would be Mad Libs style of justVibhu [00:03:10]: YesAnastasis [00:03:10]: You have lists of different professions, lists of different,Vibhu [00:03:14]: HobbiesAnastasis [00:03:15]: Personality types, lists of different, ages, things like that. And then it would just combine those things together. And then maybe the next project we go is, Uncanny Valley, Uncanny Road, which wasSwyx [00:03:27]: GansAnastasis [00:03:27]: One of the first projects that, we built with, one of my two co-founders, Chris. This was taking, pix2pixHD, which was one of the early image-to-image models that NVIDIA released back in 2016 or 2017. and it was a model that would take a semantic map of a scene and then generate a photorealistic, let's call it, output. very early days, so it was not very high-fidelity outputs, but it w I think was the first image-generation model that could generate at 1K resolution. And it was all trained on self-driving datasets. So the semantic categories it would support were only, things you would encounter on the road. So it would be pedestrians, traffic signs,Vibhu [00:04:16]: StoplightsAnastasis [00:04:17]: Bikes, stoplights. And so that was one of our first indications that we built this and people were making all this, like, very surreal imagery of, yeah, a million plus a million pedestrians or a million traffic signs or, like, gigantic humans. And it was a indication that you could take a model that was trained on this very boring dataset, essentially, of, like, not that many interesting things happen when you're on the road, and then you can repurpose it and go very out of distribution and make something that was artistically compelling. And that was It's a summary of the thesis of Runway in some ways, that you can take the same generative models, and if you look at them from another direction, if you build interesting tools around them and you give them to artists, they're gonna do things that you don't expect.Vibhu [00:05:02]: Very cool. I like the, UX of it. You're just given an empty canvas, try whatever, do whatever. And then the other one, like, you see everyone with wired headphones? Like, that's, that's a sign that it's, it's veryAnastasis [00:05:16]: The AppleVibhu [00:05:17]: YeahAnastasis [00:05:17]: Apple, your version.Vibhu [00:05:17]: Original ads. Yeah. Take us to today. You've been doing this for seven years at Runway. How have we got to this? Like, how do we go from driving simulator data to all this? And you cover the whole stack of generative media?From Creative Tools to a Research LabAnastasis [00:05:33]: Interestingly, we're almost back in, we're, we're full circle. We're, we're now applying our models and beyond creative tools into real-world scenarios. But it was a, it was a long journey. It was very early on we realized the first version of Runway was a way to easily use the, all the open source model of the day, things like pix2pix to. and give them to artists. That was the initial idea, is those models are too difficult to use if you're not a machine learning engineer. Like, what happens when you give them to artists? Very quickly, we realized we needed to build a research org, inside of Runway, and that happened maybe on year one. And, a lot of the mandate there was. The image-generation models of the time, the video generation models of the time, or there were barely any video generations all the time, but they were not quite there where they could be productionized and brought into tools that would be part of creative workflows. so we need to push the frontier of the research. And so maybe the first four years of Runway, research was almost happening on the background until there was a moment in 2022, with latent diffusion, with, DALL-E 2, where, there was that step function change, and you guys maybe remember around the time.Swyx [00:06:49]: I started in this space because of latent diffusion and Stable Diffusion.Anastasis [00:06:54]: Yeah.Swyx [00:06:54]: Because I was like, “Wow, this is not only, like, feasible, it is doable on consumer hardware.”Anastasis [00:07:01]: Exactly, yeah.Vibhu [00:07:01]: I think the delta is also huge. Like, I learned pix2pix. Like, this was intro to ML, the TensorFlow, like, Jupyter, Google Colab notebooks were like this, and then you have a sudden step function change, with diffusion and whatnot. Any other ones since that. Like, there were clear examples of what early diffusion were to get to here. Any other changes in key technology research?Green Screen, Rotoscoping, and Early RunwayAnastasis [00:07:26]: Between, 2018 when we started and 2022?Vibhu [00:07:29]: Yeah.Anastasis [00:07:29]: So one of the early work that we did in Runway was solving segmentation, image and video segmentation. It was a very important problem because most VFX involves essentially separatingSwyx [00:07:42]: RotoscopeAnastasis [00:07:42]: Subjects. Yeah, rotoscoping. Extremely manual process. Nobody enjoys doing that. and so a lot of the early days of Runway was building this tool. It was called Green Screen, and it was for a long time the main thing that people were using Runway for. It ended up being used in, Everything Everywhere All at Once and a bunch of other high-visibility films and series. But that was essentially, Runway for a long time was a post-production tool until latent diffusion and generat- Gen-1, Gen-2, happened.Swyx [00:08:12]: Cool. let's, let's go past that moment. You've come a long way. Then you started releasing your own models. Maybe describe that journey as well.Scaling Video Models and the Bet on 1,000 A100sAnastasis [00:08:20]: Yeah, so we go to the other point, yeah, in mid-2022 when it became clear that we're doing research at a fairly small scale of compute, and it became clear that, like, scaling laws would apply to, image and video gen in the same way that we're applying to language generation. So we made a big bet, and I think at so at the time, we signed this deal to build a cluster of a thousand A100s, which at the time we were a Series B startup. That was a almost, slightly irrational decision maybe, but we really believed that if we trained a video model at a large scale, we would get, like, a great model at the end. And at the time, the goal or we set the goal around fall of 2022 of what is, what does the latent diffusion, Stable Diffusion moment look like for video? And at the time, the best model of the time was called CogVideo. it was one of the early video models. It was very 256 by 256 resolution, very not very high quality. and so we decided we're gonna build out this cluster, and we're gonna just invest in, like, in building out our own video model. it became clear as we're training Gen-1 that it was difficult to get to fully. we wanted to build text-to-video, but it became clear to us that an easier starting point would be to start from video to video. Because when you have a stronger conditioning, it's, it's an easier problem to restylize an existing video versus generate the video from scratch. And so we released Gen-1 first back in, it was January of, 2023. Yeah.Vibhu [00:10:04]: It's just a fun visual podcast, honestly. Like, if we can see February 2023, what was the state of stuff?Gen-1: Video-to-Video and Depth ConditioningAnastasis [00:10:10]: It's so interesting ‘cause at the time when you see those results, you think this is so incredible, and this is like, it's almost like image generation or video generation is solved. And then you look back a few years after, and it's like, it's It's just like you get used to the results very quickly, with those models. But at the time when we started seeing those results, it was, it felt quite incredible, and the level of, like, quality that you could get. And, so the Gen-1 was a depth-conditioned video model, so it would turn. it would take a input video, it would predict. it would it would first convert it into the depth map, and then we would generate, pixels with a latent diffusion model.Swyx [00:11:01]: Yeah, very effective.Vibhu [00:11:02]: Yeah. I didn't realize how distracting the blog post would be. Sorry.Anastasis [00:11:05]: Yeah, but, one of my favorite examples of on those, on Gen-1 was both, if you go up to mode three or mode two, there was this storyboard use case where people would makeVibhu [00:11:18]: OohAnastasis [00:11:18]: WouldVibhu [00:11:20]: You can mess around with theAnastasis [00:11:20]: Make a city out of books or out of boxes, and then they would shoot a video with their phone and then translate it into a photo-photorealistic output. There was all these ways in which those models were starting to be used for storyboarding and also for really. and then if you go to mode four, like, of taking untextured 3D scenes and then turning them into photorealistic output. So we saw a lot of use cases early on where people that were familiar, were power VFX editors would just take a blender, render, and then they would get translated in with Gen-1 or create a scene in Unity and then take a capture a video of it and then translate into, restylize it. So I still think video to video is powerful. I think we had a recent video-to-video model as well, and it's one of my favorite ways of using those models is essentially using them to use ground truth video as, like, the initial inspiration and then translate into different styles or different outputs.Stable Diffusion, Stability AI, and Open SourceSwyx [00:12:23]: But I think we're gonna go into, like, the rest of Runway and catch people up to speed today. I did wanna cover the, let's call it the Stable Diffusion controversy, or, what happened with Stability AI, whatever. I think there was a two sides of the story. I think there's part of that is a normal thing of, like, people, join and leave companies, but what is the, retrospective now that, there's been some years behind it?Anastasis [00:12:49]: Yeah, it's a very, it's a very long story to go into. I think it wouldSwyx [00:12:53]: Which I remember you wrote a really long post about.Anastasis [00:12:56]: We would probably cover the whole hour to go into it in more detail. But, essentially, there was the latent diffusion paper that came in, I think that was at the end of, 2021. And then Patrick Esser, who was one of the researchers behind, latent diffusion, and he worked at Runway at the time, he built latent diffusion in collaboration with Robin Rumbach and a few other folks back, in the in, CompVis, which was, a labSwyx [00:13:26]: Like a research group, yeah.Anastasis [00:13:27]: And, after releasing the early latent diffusion model, they, essentially they were. the goal was to keep working on versions of the model, scale it up, incorporate new data, incorporate new tasks. And Stable Diffusion was the same model, but trained on more compute, and then with a few more tricks, like a classifier-free guidance paper came at some point, I think in the early 2022. And thatSwyx [00:13:52]: Which, like, was a big prompting improvement.Anastasis [00:13:55]: Yeah.Swyx [00:13:55]:?Anastasis [00:13:56]: That improved results. it was trained on better data, so like, the esthetic subset of LAION, but it was effectively, the same underlying architecture. And there was that big training run, that, happened on Stability's cluster. Stability financed that run. And looking back at that story, I think it was the work to build and train that model was done. It was a, it was a research project. It was done as part of, like, continuation of the latent diffusion work. It then, I think it the model became very successful, and it, I think there were the. And I think as a result of its success, other companies tried to, figure out the commercialization path for it. But for us, it was very important that we try to, we make sure that we. It was meant to be an open source research project, and so the we decided that we should continue releasing versions of it, since that was the original goal of Stable Diffusion, and that led to releasing Stable Diffusion 1.5. There was maybe a day of, a bit of, miscommunication there, but ultimately that was resolved very quickly within hours. so yeah, there wasSwyx [00:15:12]: OkayAnastasis [00:15:12]: Not a niceSwyx [00:15:13]: I just wanted to. you have toAnastasis [00:15:15]: Yeah.Swyx [00:15:15]: You're one of the main players in that journey, and so it's nice to hear from the source of, like, what happened. Yeah.Anastasis [00:15:22]: Yeah. I think it's all, it's all in the past nowSwyx [00:15:26]: YeahAnastasis [00:15:26]: I would say. and, like, both companies, Stability took its own path, Runway took its own path.Swyx [00:15:32]: Yeah. There's still. James Cameron is backing the new Stability, whatever they're doing with the Hollywood studios.Anastasis [00:15:38]: Right.Swyx [00:15:38]: I don't know what they are doing. I think one thing that impresses me, and I'm happy to move on, is that back in the that time, let's say, like 2021, 2022, there was this community of people that you were involved in that was researching all this stuff, right? And, like, from everyone I talked to who was active then, it seemed like it was fairly obvious that somebody would do the hero training run that would produce Stable Diffusion. So, like, I guess the question is, like, you had the you were you had made investments. You were you had the foresight. Is it accurate to say, like, that is reflective of, like, what people were thinking at the time? Or was it still very much like, “Well, we'll use it as, like, a post-production tool or something. I don't know.”? Like, where in the sentiment were we that maybe you can think back to, like, what the community was like back then?The Early Creative AI CommunityAnastasis [00:16:28]: I reminisce and I think very fondly those early years, from like 2018 to 2022, because it was a very small community that, as you said, were very convinced that this was gonna be a big thing. And at the time, anyone who. Because it was such a small circle and, everyone who would, like, be part of that circle and, like, make projects with it would, immediately get, go viral. so likeSwyx [00:16:55]: And you didn't know who they are, right? They're just some name on a, GitHub or Hugging Face somewhere.Anastasis [00:16:59]: Exactly, yeah. So I remember one of the first big viral moments of creative AI was, there was the neural style transfer paperSwyx [00:17:09]: HuhAnastasis [00:17:09]: ThatSwyx [00:17:10]: Something dreaming?Anastasis [00:17:11]: I think it was called neural style transfer.Swyx [00:17:14]: Okay.Anastasis [00:17:14]: There was also Deep Dream, the puppy sliceSwyx [00:17:16]: YesAnastasis [00:17:16]: Which was, also really cool. but, yeah, there was this project that, Jim Kogan, who was an early advisor of Runway and one of those,Swyx [00:17:25]: Marketing guysAnastasis [00:17:26]: Big, creative AI, folks, he literally just, like, showed a video of himself taking the New York Subway and going over the Williamsburg Bridge and then stylized it with, I think in the style of Van Gogh or, like, one, painter. And that was. Like, at the time, that was, like, so cool and it went viral and it was completely revelation to people that you could do this with generative models. And that was only, it was less than. It was maybe 10 years ago. So just, like, as an indication of, like, how quickly things have gone.Vibhu [00:18:02]: It's pretty crazy. Like, even since then, you've got people at every level of the stack. You've got devs, creatives, artists, hobbyists. You've got everyone using it. And for people that tried stuff early, they'll remember how hard it was to use regular diffusion, right? Like, nowadays, you can use your favorite ChatGPT image gen or whatever, give a sentence, get a beautiful output. But diffusion was like, the whole ultra HD, 4K, high resolution. Like, prompting these things was very different. anything you learned on the tooling side, like from the offerings you guys have now, so like creatives, devs, you really took the. Research and brought it to everyone to use. anything interesting there to share?From Gen-2 to Controllable Video GenerationAnastasis [00:18:44]: We had to build the entire model serving infrastructure for video diffusion models. There was nothing else, already, like, because we had Gen-2 was the first text-to-video model, I think, out in the market. So many things that we learn over time. I think the I think the biggest one was, like, we. it was very clear early on that text-to-video was not gonna be the answer. Like, you. Like, people wanted a lot more control than that, and so we invested in, like, control building on top of those models very quickly. how do you use the camera trajectory as control? How do you use an initial input frame as control? So that was a very early learning for us. With text-to-video was, like Gen-2 was an amazing, step function improvement in the quality of video models, but it was used much more in an exploratory way because there was nothing to ground it to. There was no reference that you could bring into it. There was no. You couldn't really control the camera motion. You couldn't control the object motion. And so the first year, in 2023, was really all about what are all the interesting ways in which we can condition those models? And it was a lot of just post-training rounds on top of the base model to figure out, like, what, -- how do people wanna control them? And so there was, like, this quick succession of the we it was called Motion Brush, which was you could, like, you could draw arrows and dictate where things should move in the scene.Vibhu [00:20:09]: That's so cool.Anastasis [00:20:09]: There was camera control that was you could just describe, like, how you want the camera to move in the scene. And because we work with filmmakers from the most of the history of Runway, we immediately got this feedback and got this, decided that this was worth investing in. And so control ability became a big theme, I think, very early on as we were building, as we were building those models. Something fun that I haven't really talked about too much was just how Gen-2 came to be out of Gen-1. So it was a bit strange because we announced Gen-2 two months after Gen-1 andHow Gen-2 Came From a Weekend HackVibhu [00:20:43]: We're accelerating.Anastasis [00:20:44]: It was before Gen-1 was even generally available. But Gen-1 was a depth-to-video model, so it would take a depth map and it would convert it into RGB. and we couldn't get, text or image-to-video to work directly, and that's why we started from depth to video. but, and we had discussions of like, okay, we need to spend the next six months investing in text-to-video, maybe increasing the compute scale or the model scale, like train a larger model. And I had this weekend project idea, which was, what if I take a model that, starts from text input and converts to depth maps and then use Gen-1 to convert the depth maps Into RGB?Vibhu [00:21:29]: It would probably work.Anastasis [00:21:30]: And so Gen-2 was that.Vibhu [00:21:32]: Oh. The hackathon pipeline.Swyx [00:21:35]: The weekend hackathon pipeline.Anastasis [00:21:36]: Yeah.Vibhu [00:21:37]: But it looks good.Anastasis [00:21:38]: And it worked pretty well. there were if you, with the knowledge that it has this, like, two-stage pipeline, you can tell in some cases that the structure of the video looks a bit off because you had to generate the depth first before you go into the output video. But it worked and it allowed us to bring this to our, to users very quickly. But it's now it's interesting because, like, people are coming back to this almost two-stage approach. Like, if you look at the Reve text-to-image model that came a few months ago, it had this planner model that would generate bounding boxes before it fed that into the diffusion transformer.Swyx [00:22:19]: Yeah, Ideogram also the same day.Anastasis [00:22:22]: Yeah.Swyx [00:22:22]: I remember that was very strange that both of them came out the same day with the same exact innovation.Anastasis [00:22:26]: It's a small community, I think.Swyx [00:22:28]: I'm like, this is like, this is completely coincidental, right?Anastasis [00:22:32]: People talk. So yeah, there's, there's definitely something into this approach. And, now, like every single like, video generation model in production uses a complex prompt completion pipeline under the hood. I think that's no secret that there is. ThatSwyx [00:22:48]: Humans are terrible at prompting.Prompt Rewriting, Camera Control, and the Seed of World ModelsVibhu [00:22:51]: I think across the board.Anastasis [00:22:51]: Yes.Vibhu [00:22:52]: But yeah, I think like the original Sora one blog post even told you that what happens after your input is rewriting your prompt. It's much more descriptive about what you would want.Anastasis [00:23:02]: Exactly. I, And there was the DALL-E 3 paper beforehand that, was the first public, description of the fact that synthetic captions and really detailed captions work really well. And then Sora built on that. Yeah, so it was 2023. We were releasing all these updates to Gen-2, like the camera control, Motion Brush. And there was something very interesting about camera control because it was the first time that you felt that instead of, like, you were creating video, you were creating a short video, you were navigating inside the world. And I think camera control was maybe the seed of some of the ideas that we had around world models and really opening up that research direction. We realized, it was this era and this series of, Gen-1 and Gen-2 models really proved to ourselves, yeah, this is theSwyx [00:23:56]: Cool.Anastasis [00:23:57]: So this is not the original camera control. This was the updated camera control on top of Gen-3. But yeah, I think it made those models usable to filmmakers, I would say. The so camera control was very popular. And so we realized, there is one way of seeing those models, which is, you're just as content creation machines, and there is the other way, which is you're. As you're predicting video in order to predict video well, you need to simulate the world in an increasing and increasing capacity. And if scaling laws apply on video, just like they apply on language models, then as we scale the compute that we put into those models, then they're gonna be able to simulate physics, they're gonna be able to simulate human actions and dynamics increasingly well and predictably well. That was the thesis about around our efforts on world models, and we spin up this research group to just focus on the world models and how do we turn the video generation models that we're building into something broader and something that would be useful beyond, also content creation as well.Swyx [00:25:04]: And that was roughly when?Anastasis [00:25:06]: Yeah, so that was inSwyx [00:25:06]: OhAnastasis [00:25:07]: In late 2023.Vibhu [00:25:08]: Interesting. like, I think, a lot of people have been saying a lot of video gen model companies have all pivoted to world models these days, but like, 2023, you're posting it. oneWorld Models: From Video Generation to SimulationSwyx [00:25:21]: It's, it's debatable whether it's a pivot.Vibhu [00:25:23]: Yeah.Swyx [00:25:23]: Like, arguablyVibhu [00:25:24]: YeahSwyx [00:25:24]: That's what you always had to do anyway, right?Anastasis [00:25:26]: It's in a way an expansionVibhu [00:25:28]: YeahAnastasis [00:25:28]: Of the applicationsVibhu [00:25:29]: YeahAnastasis [00:25:29]: Of the models as they become more capable.Vibhu [00:25:31]: The early signs, it seems like the original models you guy had, guys had, people would say it's very not bitter lesson pilled, right? You're adding, rewriting prompts, you're having all these one-off things, but that's just the state of the tech as it was versus the future of as you said, you can scale it up as, we can scale up to world models.Anastasis [00:25:50]: Yeah. So it just became. And if you looked at the outputs of Gen-2Vibhu [00:25:56]: YeahAnastasis [00:25:56]: It was not. I think it was not obvious to people that this would scale to become a general simulator of the world. Like, you had very limited movement, you had, very low fidelity or low resolution, like obvious mistakes in human anatomy, like all kinds of limitations. But it was just, the idea was that's just GPT-two, and GPT-two, it can barely generate, like, coherent sentences. Similar, Gen-2 can barely create coherent video, but if you scale it up, you're gonna. There is no reason why it shouldn't work in a way. It's, And I think that was. That's, that's always the mindset of Runway is like this extrapolation of, like, if, like, even when we started in 2018 and you looked at the results of the day, you need to look more at the trend of, like, where we were in 2018 versus when we were at the, when the first GAN came out in twenty, four 2014 or twenty, fifteen. And, you started from, like, thirty-two by thirty-two images of faces, and then by the time in 2018, you could generate, street images at the 1K resolution. And it was the same with world models, very early signs of something much bigger.Swyx [00:27:08]: Yeah. I was gonna say, like, it's diffusing into focus. Like, if you look at our visible output from year to year, it looks like a diffusion process itself.Anastasis [00:27:17]: Yeah.Vibhu [00:27:17]: Especially watching the early, like, old blog posts, you can really see the choppiness, the details.Anastasis [00:27:24]: Yeah. Like human civilization starting from random noise and thenVibhu [00:27:27]: YeahAnastasis [00:27:27]: Denoising intoSwyx [00:27:28]: Yeah. Just run it a hundred years.Anastasis [00:27:30]: Civilization.Swyx [00:27:30]: Yeah.Vibhu [00:27:31]: That's how you're on track, you're still noising, right?Swyx [00:27:34]: Yeah. I like the way that you guys phrased it when you, announced it in June, which is, oh, that you had a video essay. “The human mind is no longer the center of AI. Our world is.” Right? Which is, let's, let's call it the past five years of LLM-based AI is very much like trying to emulate human preferences and human speech. But now that's, like, mostly solved. I think that's, like, some of the context of your essay, which you also wrote around the time. And now it's like the focus is on modeling the world accurately.Scaling Laws for Video and Why Predicting Pixels MattersAnastasis [00:28:03]: Exactly, yeah. So the way we see it is, there is that, initial mission statement of DeepMind, which is, solve intelligence and then use it to solve everything else. But I think it's starting from everything else, could be valuable of, like, starting from. there is just so much complexity, and detail in the world that in order to. That it's, it's hard to learn directly from just human descriptions of the world. Like, we're assuming that, like, language models learn from everything that humans have written about the world, like our own understanding as of, the twenty twenties. And there is just so much that we don't know and so much that's not captured by existing text, about both the low level dynamics of the world, like we're not describing in detail. if I tell you to describe, like, how do you tie your shoes, that's a very difficult thing to describe in words, but it's very obvious thing to demonstrate. And so I think there's been. And there's, more of X paradox, like we're constantly underestimating all the complexity that goes into very, like, things that we do subconsciously as humans, and we don't even necessarily always have the words to describe them. And so in my mind, the simulating the world and simulating, physics, simulating the dynamics of the world has always been underestimated, compared to, we place too much emphasis on the things that are easy to talk about. but there is just all this complexity and richness of the world that if we just try and train directly on that observational data instead of training on how people describe the world, we would learn something new that we wouldn't otherwise know.Swyx [00:29:54]: You think that the present architectural paradigm is fine? You don't need, like, another layer, like JEPA, like another famous, New York AI leader would say?Anastasis [00:30:05]: We're a very pragmatic research lab. If, we have evidence that an approach works better than the approach that we're taking, then we have no qualms to taking it. We just have seen no indication that video prediction itself doesn't scale. And even if you look now, not just our work, but the work of others, you're seeing in robotics some of the most promising work, starts from video prediction models, and then you adapt them to also the action models, for example. so there is very little evidence that you need something else and that your time is better spent on a novel architectural change compared to improving data and improving the, and scaling the current approach. And so, We don't have any indication that. the, there is that counterargument that I think there was a tweet by Yann LeCun a few days ago that, understanding the dynamics of the world is very different than, generating, cute videos.Swyx [00:31:05]: And your answer is no, they're the same thing.Anastasis [00:31:07]: Yeah, they're the same thing.Swyx [00:31:08]: My cat videos are the same as understanding physics.Anastasis [00:31:11]: Right, because if you wanna generate. video models can cheat and, like, they could you could give, like, successive dif shots of the scene in a way that doesn't require you to simulate difficult physics. There is like, all these different ways in which you can hide the deficiencies of the model, and it's important not to be too tricked by the performance of the current video models. It's easy to, cherry-pick examples and think that video models are further advanced than they are. So there is a lot more work that we need to do to improve those models. But in my mind, very similar to language, and, like, we've. you go from barely coherent sentences to something that, could hold a conversation with a human to something that could can operate autonomously for a day and, like, create entire code bases. And the main difference, there is some architecture improvements along the way, but the main thing is scale. And so it's the same bet for video, and we have no indications that this is saturating. Like, we have benchmarks that we use for measuring the physics of those models, and we see those predictably improve as we scale those models. So there is. If you want to Google up, Physics-IQ, is one of those benchmarks that measures how well does the model perform at solid mechanics or fluid dynamics or optics.Vibhu [00:32:32]: I'm curious if you've seen any emergence, any scaling law around this.Swyx [00:32:37]: Yeah, he's saying there is a scaling law, right?Anastasis [00:32:39]: Exactly.Vibhu [00:32:40]: Yeah,Anastasis [00:32:40]: So the way those models, those benchmarks work is you. the researchers have gone and, like, captured, a few videos that are representative of different physical phenomena, and then you can take the first frame and then pass it through an image-to-video model and then generate a rollout that shows what should happen next. So you have, a ball hanging from the ceiling, and then you use that as input, and then you the model predicts how the ball should fall on the ground. and this measures. we have an intuitive understanding of physics. I know, you can imagine what will happen next if I drop this bottle. So it's measuring that same intuitive physics understanding of those models, and we've measured that at different model scales, and we see, and compute scales, and we see that the score on physics IQ predictably improves. There's other, tricks and techniques that you can make to improve the score even further, but even scale alone helps, in the model learning better physics.Swyx [00:33:40]: My main sympathy with Yann LeCun is the, Plato's cave allegory, right? Like, you're, you're, like, learning on the output of a thing, not the internal process of a thing, and it's very noisy. And, if only you could observe the internals of a thing. It's hard to observe the internals of a human mind, but you can very much observe, or at least we have a whole branch of science and physics that we're ignoring on how to model Physics and movement and, gravity and, other interactions. and we're just, like, throwing away all of that and just saying just scale data, which is very much the lesson of unsupervised learning, but it feels wrong. that's the main idea.Anastasis [00:34:21]: I think the history of machine learning is, at large, it feels wrong.Swyx [00:34:25]: Yeah. It's a bitter lesson, right? Yeah. It's, it's, it's the simple answer to that.Vibhu [00:34:29]: I guess, how much can you scale? So, like, even on, let's say, the video generation side, like, there's one side of video understanding. Video generation, are we still gonna have tools where it's like, I wanna generate two hours, twenty hours? there's a infra way to do it in batches and stitch it together, but, like, do we just keep scaling? Do we just continue long generation consistency, all that at scale? And, like, tying it into where we're at now from we looked at Runway two to four point fiveGen-3, Sora, and Runway's Scaling InflectionAnastasis [00:34:58]: Yeah.Vibhu [00:34:58]: Like, technically, what advancements have we made to today, and then where do you see things still going?Anastasis [00:35:04]: So part of the answer is definitely scale. and that was. We learned that lesson in a big way for with Gen-3. So Gen-3 was the model we released the year after, like in 2024. That was a few months after Sora was released. so yeah, there's an interesting story of that came to be as well. Gen-3 for us was, the first time that we really needed to build. we had to learn all the lessons that the language model world learned in two in three years in the span of a few months. one of the biggest changes of Sora was using diffusion transformers instead of convnets. So a lot of the early, latent diffusion models were all, convnets for the diffusion model part. And the diffusion transformer paper came at some point in 2023, and it showed scaling laws for image, diffusion transformers. And we realized at that point that we needed to invest in infrastructure for model parallelism, for really scaling training to larger than, a few billion parameter models. And we spent maybe the, most of the fall of 2023 building out our infrastructure for distributed training. And we had a lot of false starts and a lot of failure in trying to scale, image and video diffusion transformers. And at that point, February 2024, Sora comes out, and the results areAnastasis [00:36:35]: Very much superior to what Gen-2 could produce. There were a lot of, a lot of chatter on Twitter about Runway. Runway's done. like, there is no way Runway will catch up. And if you remember, also OpenAI in the early twenty-It felt very, like it's aSwyx [00:36:56]: To the moonAnastasis [00:36:57]: It's a formidable opponent now, but at that point, it, they were on the top of their game. nobody could even get close to them. There was maybe Gemini was just the first version of Gemini had just released. So when OpenAI came with Sora and it was such a big jump of like quality, it gave me, there was like an existential crisis for a few hours. But that, I think the amazing thing about Runway and like I think the, we've been around eight years now, which is almost we're dinosaur in AI, and we had to like, we had there was a lot of those moments we had to learn, adapt very quickly and build out skill set in the team that we didn't have. And so, if you ask anyone what is their favorite time at Runway that was there during that time, it was that push in like three months to get to a model better than Sora. and it, we scaled 10x the model scale, the model size and the, compute that we were training on. we figured out model parallelism. We had zero expertise in that. And then we came out with Gen-3 during that summer. So that was a big turning point, I think, for the company where the research org grew very quickly, and we really started pursuing this vision of the general world model, in earnest, I think after Gen-3 was out.Swyx [00:38:12]: Yeah. that's the amazing thing about building when you're building. There's no stack to. You have to invent everything yourself. You have to be completely full stack. Now I think like there are inference specialists like Fal or whatever that can help with like, model serving, and I think you guys work with them as well. but yeah, like it's, it. But at the time, it was just. It's very interesting to think about what you do when Sora comes out and people are questioning whether your company should still exist.Distillation, Turbo Models, and Real-Time VideoAnastasis [00:38:41]: Yeah. And yeah, there was no, there was no VLM of diffusion models. Like, we had to build the whole model serving infrastructure and make things efficient. And a few months after we released Gen-3, we released the Turbo version, which I think was the first step-distilled model in production.Swyx [00:38:56]: That was a whole trend that we covered as well. Yeah.Anastasis [00:38:59]: So that allowed us, to serve those models at the larger scale, ‘cause I think the first version of Gen-3 was quite, expensive to serve.Swyx [00:39:09]: I think the whole like trend in like consistency models, Lightning and, Turbo and all these things somehow didn't really stick around. I don't know if you have any reflections on this. Because at the time, I was like, “Well, everything should start with a distilled model first, and then you can upscale,” right? It. your bigger models just turn into fancy upscalers, but like you should always draft with a smaller model and faster model, right? Because you can get it so quickly, like near real-time.Anastasis [00:39:39]: Yeah. I would not be so sure to say that didn't stick around. I think that, it's, it's likely to. that there is a lot of step-distilled models that are actively used in production. there is still a gap in quality compared to the, non-distilled model. but in my mind, we're still. there is a two to three year offset from language models. So the things that, So it's just a matter of time before there is better distillation techniques. we use. Right now we have a real-time model core character that I think is the largest deployment of real-time video models, that's a step-distilled model, and it's actively being used. It's a very specific use case compared to a general video model. So this is aSwyx [00:40:27]: Very cool, by the way.Anastasis [00:40:27]: This is avatars stuff, right?Swyx [00:40:28]: Consistency, character.Anastasis [00:40:30]: Yeah. So this is a talking avatar, model. we were able to. we optimized the hell out of it, and it generates at 24 FPS, and it's a, it's a step-distilled autoregressive video model. So if we look at our world model direction, a big component of it is starting from the bidirectional diffusion that generates entire video at once and making autoregressive shows. So you generate one frame or a few frames at a time. so there's a lot that goes into that pipeline of getting to a real-time model. It's first you need to make it into a causal autoregressive model, and then you just turn it into. You need to do some additional step distillation to get it to be real-time. and I think that part is just starting. I'll be very surprised if we're, two years from now, we don't primarily use real-time models. To me, real-time video generation is just inevitable that, it has much better user experience, it's much cheaper to serve, and, the quality gap between the base model and the real-time model is only gonna close as we figure out better, distillation techniques. And we made a lot of progress there internally on maintaining the quality of the base model when we distill them.Swyx [00:41:49]: How much of this is transferable? So is it the same base model? Like if you're doing diffusion across the whole sequence and you're converting it to step autoregressive distillation, is this like distillation where you still need to train both, you can use the same base and converter? What's that process like to go from regular model to something that's real-time on a technical level?Anastasis [00:42:11]: So the nice thing about diffusion models is you have, two axes of distillation. So there is the. You can distill to a smaller model, which resembles what you do in LLMs, or you can distill in terms of taking less steps, less diffusion steps. So you could take a model that generates in fifty steps and generate in four steps and get to, You have some performance, degradation, but very often you get comparable outputs. So you can even take the large frontier model and distill it with step distillation and get to a real-time performance, and that's what we've seen. So, depending on the use case, in some cases we might also serve with a smaller model, but in a lot of use cases, we just use theSwyx [00:42:56]: Step distillationAnastasis [00:42:56]: The frontier model, and we're able to make it work in real-time.Swyx [00:42:59]: I think this might be a good time to cut over to his laptop to show off some of the real-time stuff that you're doing.Interface World Models and Neural SoftwareAnastasis [00:43:06]: This is one of the research updates that we did recently. so we've been working and f in getting our general world models to, different applications. one of them that we think is very compelling is using general world models as essentially, an interface, a universal interface to software. This is a version of our world model that's called an interface world model. and the idea is that it essentially, replaces, the, front end of a software application. It renders the pixels directly of an interface and is trained to predict what happens next as a result of, a click or another interaction you have with the interface. So this is all pixels. it's there is no HTML, CSS, React that's powering this interface. This is directly at the output of our real-time, video generation model, and it takes clicks directly as input.Swyx [00:44:09]: And drags, click and drag.Anastasis [00:44:12]: Right. So it supportsSwyx [00:44:13]: Ooh.Anastasis [00:44:14]: Yeah, clicks. It supports drags. it also supports scrolling. and the amazing thing about this is that you can effectively describe in the prompt how you want different elements, like what do you want the behavior of different elements to be. So it's almost you're you can turn, an interface from, markup language description of, like, an HTML interface, and instead you can just describe the interface. if I press this button, I expect this to happen. If I press this button, this should happen. And it's useful, we believe, both for prototyping, for, like, just testing, like, what different interactions would feel like. you can also add audio to it. So it's a video audio generation model. So you get you essentially can describe both what the visual outcome should be of your click and also what the if there is a sound effect that comes out of it. So we believe that's gonna be a much more flexible way of building software. Just render. It just, in why generate the code that generates the pixels? Just generate the pixels directly.Anastasis [00:45:18]: It's the end-to-end philosophy applying applied to front ends.Anastasis [00:45:25]: So we think there is a few interesting use case. So you can build creative tools on top of it.Anastasis [00:45:32]: We think that, for any use case that involves a lot of exploration or, like, educational use case where you wanna learn about a new concept and you want some visualization and like, and open-ended exploration, we think those this is a very powerful, approach. you can imagine new forms of, design, industrial design software that could emerge as a result of those models. And this is all, generated in real-time as well. So, you can build a lot of interesting camera transitions and forms of interaction that are very difficult to build otherwise. And one way in which we evaluate this is what if you try to generate the same interface with Claude by just, prompting Claude, “Here's an image reference of my interface that I made in Figma or that I created somewhere else. create this particular interaction,” which in this case it's, drag that object, upwards. and beyond it being slower, it's also very difficult to capture some interactions by just fully, with just LLMs. So we think that this is likely to be the way that a lot of the future, like, software in the future will be created. and one of the additional benefits is personalization might be a lot easier done with those models. Like, you can essentially try out different prompts based on who is visiting the interface. You can, more easily, prompt engineer the interface to have larger size, text for more accessibility reasons, or you can make this or, like, if you have a particular aesthetic preferences. So we're very excited about this approach. It's early days, and I think we'll need to, make it more cost-effective as well to serve those models ‘cause, running a real-time video model versus just purely rendering HTML, there's -- the computational needs are much higher. but we do see a lot of potential in this approach to building front-end interfaces.Swyx [00:47:47]: So we covered this similar thing with Flipbook before with our, Ethan Hara episode with Groq, video. And yeah, I think it's very engaging visually. I think it's maybe very good for education, but it's it does sound expensive. I think there's an upper bound to how expensive it will be, though, right? Like, the inference cost will go down over time. You'll figure out ways to optimize it. Effectively, when it pauses, you don't you're not receiving human input. You don't have to generate anything, right? So.Anastasis [00:48:14]: Yeah, you could also. Like, in this case, you have ambient motion, so there is parts of the screen that might. if you're let's say you wanna, visit Paris and then you get this interface that allows you to explore.Swyx [00:48:29]: People walking. Yeah.Anastasis [00:48:29]: You have people walking or, like, things happening. But, it's, it's a no Yeah, it makes it more expensive because you need to run the model all the time. Maybe you have some looping mechanism so you don't need to do that. But all those things, I think, is stuff we'll need to figure out.Toward a Fully Neural Operating SystemSwyx [00:48:44]: Yeah.Anastasis [00:48:44]: I think our first consideration is let's make this clearly find some use cases where it's clearly a much more compelling interaction compared to traditional interfaces. And then it's a matter of time before it becomes more cost-effective to serve.Swyx [00:48:58]: Yeah. When it comes to the people walking, I think the approach that makes the most sense to me is Nick.Anastasis [00:49:04]: Nick.Swyx [00:49:04]: Oh, God. I keep messing up their name. With Chris Manning and Fanny Yan. I don't know if you've come across them, where they. Mapped to some game engine. I think it's Unity or something, or Godot. And they you can script some NPC behavior behind that and train on that. Whereas here, you can really imagine whatever you want. Like, that is a UI, right? Like, and it feels, like, more tractable, I guess, to, create a world model of software that is interactable because we have many of examples of that, and you can, do your fancy RL environment stuff on that than it is scaling up to embodied and real-world physical use cases. But this is a nice first step.Vibhu [00:49:43]: Or, there's the opposite of you have, like, one B models, three 50 million parameter language models. It just gets so small that they're just predicting, like, fishes moving.Swyx [00:49:53]: Small models are now 120 B, so.Vibhu [00:49:57]: Ultra mini on device.Vibhu [00:49:58]: But, no, I think it, like, it puts it into perspective, at least the car one for me, like, the applications, right? The amount of work to do that, sure, you only make one model year car per year, but applying this, it's also a cost-saving to have to manually make all this, right? So it opens up a lot of possibilities, too. I'm curious if you extend this out two, three years, so where do you see things going even further?Anastasis [00:50:25]: Effectively, the end game of something like interface world models is you have, a fully neural operating system. So I think, Andrej Karpathy has written about that quite a while back. But it's, You, I think to me it's, it's a bit, it's a bit odd that, we have, for example, with an interaction with an LLM of today, you have this LLM that can talk to you about anything. It can You can take the conversation in any direction. You can It's very general, so it can solve all those different tasks, but you interact with it through a very rigid interface. And so to me, it's just a matter of time before the interface itself becomes learnable and becomes, part of the whole loop of, like, you're not just delivering. You're delivering an application end-to-end, and that means you're delivering the language model, but you're also delivering the render and the pixels and that's also a learnable component. And the concept of applications might not necessarily. I think we'll need to figure out new abstractions for software. the concept of application comes from this idea that you need, separate code bases to describe, to, for, to power each individual, tool and each individual application. But you might think of something a lot more unified if you're. if you have, a video model that's generating the interface as you go. so it can take context from an LLM and allow you to combine different functionalities that traditionally would live in different applications. So it's a, it's a way to solve, software end-to-end, effectively. We also see this as a powerful way to train computer use agents as well. so this is, one way to see this as. And in general, with world models, there is those two directions. One is world models for humans and world models forSwyx [00:52:24]: AgentsAnastasis [00:52:24]: To train agents.Swyx [00:52:25]: Yeah.Anastasis [00:52:25]: And so for every new work of, world models that we do, we have this both uses become possible. So this is a powerful synthetic data generator for training computer use models. It could become, a live, RL environment that you could use to do online RL with a computer use agent, and you can get wide diversity of different interactions, kinds of interfaces, just generated on the fly that, to improve the how robust the, your agent, becomes. So that's the same also with the world models that we're working on for a robotics use case as well.Long Context, Error Accumulation, and Autoregressive VideoSwyx [00:53:02]: Is there a research breakthrough that you're Waiting for that would unlock the next set of use cases that you really wanna pursue?Anastasis [00:53:10]: Long context is a very important one, so being able to maintain consistency for long periods of time, and that depends on the use case. So for our characters model, for example, or for the interface world model, it's easier to maintain long sessions of interaction. If you go into more open-ended worlds that you navigate and you take arbitrary actions in, we, like, there is more the context at which you can and duration which you can generate becomes limited much more quickly.Swyx [00:53:40]: Yeah.Anastasis [00:53:40]: So we see more degradation and error accumulation happening. so the biggest challenge with autoregressive models is error accumulation, is you're feeding generative frames back into the model to generate the next The next frames. And if there is any small errors, they accumulate over time. That's not a new problem. It's a problem that LLMs also have, and we've seen the ability to generate now really long outputs. So it's a solved problem, but it's definitely still a challenge.Swyx [00:54:08]: Yeah. And what is the state of the art? so for Grok, it would be like 10 to 20 seconds of context going in there for video.Anastasis [00:54:16]: With our characters models, we're able to generate up to 30 minutes of video autoregressively.Swyx [00:54:21]: Yeah. But that's just for the avatars.Anastasis [00:54:24]: Yeah. So if we look at, GWM Worlds, which is more our open-ended world exploration model, it's, it's on the order of a few minutes, which is Yeah, soSwyx [00:54:35]: Probably enough for people because you have to cut to the next scene anyway, right?Anastasis [00:54:40]: Yeah, it's not, it's not the ideal game experience if you have to restart every few minutes. So I think. But, I think it's. Yeah, for certain kinds of game experiences, you can work around it.

This week we are all about London fashion week. I absolutely loved walking down the catwalk, and I can't wait to fill you guys in on it all. From sharing the catwalk with Kelly Osbourne, to everything that happened behind the scenes. We also give you an update about mum and Harvey's mounjaro journey. Plus we answer so of your listener questions and play our favourite game Katie vs Sophie. I LOVE IT! Learn more about your ad choices. Visit megaphone.fm/adchoices

Digital Content Editor, Barbara Friedman, shared her top three stories trending online. Views and News with Clarence Ford is the mid-morning show on CapeTalk. This 3-hour-long programme shares and reflects a broad array of perspectives. It is inspirational, passionate and positive. Host Clarence Ford’s gentle curiosity and dapper demeanour leave listeners feeling motivated and empowered. Known for his love of jazz and golf, Clarrie covers a range of themes including relationships, heritage and philosophy. Popular segments include Barbs’ Wire at 9:30 am (Mon-Thurs) and The Naked Scientist at 9:30 on Fridays. Thank you for listening to a podcast from Views & News with Clarence Ford Listen live on Primedia+ weekdays between 09:00 and 12:00 (SA Time) to Views and News with Clarence Ford broadcast on CapeTalk https://buff.ly/NnFM3Nk For more from the show, go to https://buff.ly/erjiQj2 or find all the catch-up podcasts here https://buff.ly/BdpaXRn Subscribe to the CapeTalk Daily and Weekly Newsletters https://buff.ly/sbvVZD5 Follow us on social media: CapeTalk on Facebook: https://www.facebook.com/CapeTalk CapeTalk on TikTok: https://www.tiktok.com/@capetalk CapeTalk on Instagram: https://www.instagram.com/ CapeTalk on X: https://x.com/CapeTalk CapeTalk on YouTube: https://www.youtube.com/@CapeTalk567 See omnystudio.com/listener for privacy information.

Tamara and Lucinda are back together on the mic after Lucinda’s trip to LA, and there is so much fashion news to unpack! From the "lacklustre" Emmys red carpet (and why Shailene Woodley’s controversial Balenciaga look sent the internet into overdrive) to the biggest takeaways from New York Fashion Week—including the return of DVF, Carolyn Bessette-Kennedy minimalism, and models walking completely barefoot—the girls are covering all bases. Plus, they tackle the serious news on home soil with iconic Aussie powerhouses Cue and Veronica Maine entering administration. Is corporate wear dying, or are online-native brands changing the game? To wrap things up, Tamara shares the three dress trends taking over spring/summer, and the girls bring you their top Bougie to Budget picks featuring taffeta shorts and colourful retro stripes. BOUJIE TO BUDGET: Tamara's items: Stripes Foxwood Tides Pant Chocolate, $89.95 Vrg Grl Kinsley Polo Green Stripe, $109 Palm Noosa Eddy Dress Anana Stripe, $480 Lucinda's items: Taffeta shorts BUDGET: Top Shop A Line Oyster Bermuda short, $79.50 MID-RANGE: Reformation Dusty Rose Mini Nora short, $128 BOUJIE: Revolve Majorelle Tilda Short in Graphite, $214 HELPFUL LINKS: SUBSCRIPTION GIVEAWAY: The You Beauty hosts have bundled together their all-time favourite beauty products and two Mamamia subscribers are winning the lot. Subscribe to Mamamia to be automatically entered to win. Current subscriber? You're already in the draw. T&Cs apply. Become a Mamamia subscriber and get an all-access pass to everything we make, including exclusive podcasts and early listening, subscriber-only articles, monthly giveaways, discounts and our home workout app, MOVE. Subscribe here. Get access to Very Peri, Mamamia's exclusive perimenopause series, for just $59. 25 world-leading experts, over 20 on-demand sessions, available now. We’ve sorted through the noise so you don't have to. Go to veryperi.com.au today. You hot? Same. GET YOUR FASHION FIX: Watch us on YouTube here. Follow us on Instagram & TikTok: @nothingtowearpod Shop the Pod: Sign up to the Nothing To Wear Newsletter to see all the products mentioned plus more, delivered straight to your inbox after every episode. Feedback? We're listening! Email us at podcast@mamamia.com.au CREDITS: Hosts: Tamara Holland & Lucinda Pikkat Producers: Talissa Bazaz, Ella Maitland & Zara Sengstock Audio Producer: Scott Stronach Video Producer: Artemi Kokkaris Just so you know—some of the product links in these notes are affiliate links, which means we might earn a small commission if you buy through them. It doesn’t cost you anything extra, and it helps support the show. Happy shopping! Mamamia acknowledges the traditional owners of the land on which we have recorded this podcast.Become a Mamamia subscriber: https://www.mamamia.com.au/subscribeSee omnystudio.com/listener for privacy information.

Following Didier Deschamps' 14-year reign, Zinedine Zidane has officially taken charge of the French national team. In this episode, we explore Zidane's immediate cultural reset at Clairefontaine—banning media from player arrivals to refocus on football—his transition from Deschamps' pragmatic counter-attacking baseline to a proactive, possession-oriented system, and how his management style will shape stars like Kylian Mbappé, Michael Olise, and Bradley Barcola. ZinedineZidane LesBleus FFF DidierDeschamps Clairefontaine KylianMbappe FrenchFootball FootballPodcast

Brought to you by the English Programme. Featuring news, politics, popular culture, celebrity trivia, quizzes, book readings, and a whole host of fun.Support Our Rescue Cats | Our Blog | Get New Episodes By Email | Rumble | X | YouTube | NewsK365 on Spreaker | Get New Blog Posts By Email | Throne Wishlist |

Brought to you by the English Programme. Featuring news, politics, popular culture, celebrity trivia, quizzes, book readings, and a whole host of fun.Support Our Rescue Cats | Our Blog | Get New Episodes By Email | Rumble | X | YouTube | NewsK365 on Spreaker | Get New Blog Posts By Email | Throne Wishlist |

WWelcome to our new rendition of the Best of BPR Podcast! In this new version, we will be publishing the week's top segments. In case you're missing us over the weekend... now you have something to listen to!On today's Show: Ken Casey, frontman of the Dropkick Murphys, on the pressures on artists to not be political these days, and why the Murphys have been Very Punk about that since the 1990s.We hosted a special BPR/BPL red carpet fashion show, with “Love Your Labels” President and Founder Joshua Croke, and designer Anita Tension, ahead of their Queer AF show in WorcesterThen, it's Paul Giamatti and Diana Paulus discussing theie new showcase of Rhinoceros at the Armory Repertory Theater in Cambridge

John sits down with Christine Handy to talk about her upcoming film, "Hello Beautiful." Christine wrote the book Walk Beside Me after being diagnosed with cancer. The book is based on her own experience and the people who showed up for her during some of the hardest moments of her life. The book became the film, "Hello Beautiful," which releases in theaters on September 25, 2026. Christine talks about how cancer changed the way she saw herself, the importance of faith, true friendships and community, and the nearly 10-year journey of bringing her book to the big screen. About Christine Handy: Christine Handy is not just a name — she is a voice of hope, courage, and transformation. As a model, breast cancer survivor, mother, international speaker, influencer, and author, Christine uses her platform to uplift, inspire, and empower others to overcome adversity with faith, grace, and grit. Listen to this episode to learn more: [00:00] - Intro [00:44] - "Hello Beautiful" movie releases on September 25, 2026 [01:30] - Christine's bio [02:13] - Story behind writing Walk Beside Me [05:29] - Rebuilding her identity during chemo [08:42] - The friends who showed up [09:57] - What her sons went through during her illness [12:42] - How the book started becoming a movie [15:43] - Finding the right people for "Hello Beautiful" [18:41] - Casting Tricia Helfer as the lead [23:00] - Some of the wins and disappointments of the film journey [25:26] - The personal cost of making the film [26:04] - Filming schedule and locations [28:11] - Music by Marco Werba and London Symphony Orchestra [28:41] - What comes next for "Hello Beautiful" [29:35] - Initial theatrical release markets [30:17] - Attending red carpet events now as a writer and producer [31:35] - The incredible response "Hello Beautiful" has received [35:23] - Is there a second book for Christine? [36:14] - When John's mom was diagnosed with cancer [39:23] - Christine's unsustainable schedule over the past years [41:44] - The unexpected impact of the film on hospitals [42:39] - The physical and emotional toll of constant working [47:46] - Best way to connect with Christine [48:33] - Closing remarks NOTABLE QUOTES: "I was determined to become a light instead of a victim in this world." "Your beauty is an internal job. It has nothing to do with whether I have breasts or not. My beauty was not dissected because I lost my chest. I am whole. I am made in God's image, and that's why my value has not changed one bit." "I kind of skipped that season of my life. And so, when I was faced with a rebuild, I made a conscious decision that I was going to rebuild and do the work to know who I was and to find the reasons that people were showing up for me." "I am a very courageous young woman and somebody that had great grit and determination, which is why I was able to rebuild and to use that pain that I had gone through to help other people. Because I also rebuilt myself with a lot of self-confidence." "I talk very freely about the things that I wasn't doing well in life and aren't very flattering. But I think that's more important than just showing the highlight reels in social media or in life, because how does that really help anybody?" "There really isn't any ceiling to what any of us can accomplish. It's all in our head what we can accomplish. And if we take no from other people and we listen to that, then it's going to stop us. But if you say to yourself, when people say no, it just means I have to go to a different door." "The people that quit in the middle, that don't get to the finish line. You can't quit in the middle. The hard part is the middle. You can't quit." USEFUL LINKS: Listen to Christine's 2021 episode with John: https://relationshipsandrevenue.libsyn.com/episode-047-christine-handy  https://christinehandy.com/ https://www.rottentomatoes.com/m/hello_beautiful https://www.imdb.com/title/tt9018874/ https://www.linkedin.com/in/christine-handy-3056ba125/ https://www.instagram.com/christinehandy1/ https://www.facebook.com/christine.handy.2025 https://x.com/handychristine1 https://www.youtube.com/watch?v=fVw3xG426-c https://www.youtube.com/@christinehandy132 "Walk Beside Me" (https://amzn.to/4xTvOdH) CONNECT WITH JOHN Website - https://iamjohnhulen.com    LinkedIn - https://www.linkedin.com/in/johnhulen Instagram - https://www.instagram.com/johnhulen    Facebook - https://www.facebook.com/johnhulen    X - https://x.com/johnhulen    YouTube - https://www.youtube.com/@iamjohnhulen    EPISODE CREDITS Intro and Outro music provided by Jeff Scheetz - https://jeffscheetz.com/ 

DESCRIPTION The engines roar, the nose lifts, and the runway falls away beneath you. The safest thing a pilot can do is the one thing passengers hate: not land. Here is the rule behind it, the night I broke it, and what the recorders show from the Miami 767 crash. This is A Pilot Explains: one story, twenty minutes, told from the flight deck. Every airline flies to the same rule: by 1,000 feet the aircraft is set up for landing or you go around, and nobody gets in trouble for it. In 2003, as a brand-new DC-9 first officer, Bryan flew into a dust storm at Bamako, ignored the captain's calls, and landed anyway because there were beers planned at 7:00. The aircraft forgave him. Then, number by number, the NTSB's recorder summary from the Boeing 767 freighter that ran off the end of Runway 30 at Miami on 6 September 2026 and killed five people on the ground. The investigation is open, and nothing here is based on any official finding. IN THIS EPISODE What a go-around feels like from the cabin, and why it is planned before every landing The stabilized approach: the five things that must be right at 1,000 feet Bamako, 2003: the dust storm, the captain's calls, and the approach Bryan should have abandoned Why getting away with it teaches you exactly the wrong lesson How fast a runway runs out: 10% too fast costs 20% more runway, a 10-knot tailwind costs 21% Miami, 6 September 2026: the wind, the runway, and the NTSB recorder timeline second by second Why 97 out of 100 unstable approaches still land, and the one sentence in the FAA report that explains it Plan continuation bias, and the two lines every pilot has to watch across a career Two pilots, one rule: why the decision is taken out of your hands at the exact moment you cannot make it Airline safety in 2025, South Africa's roads, and why Africa has the world's highest runway excursion count Rules written in blood, and the promise the 1,000-foot rule makes to you The NTSB preliminary report is due in October, and Bryan will take you through it I'm Bryan Roseveare. I was an airline captain. I still go to work on the flight deck. It's just a full flight simulator now, and the pilots I train are the ones who fly you around. SOURCES NTSB Investigative Update, Boeing 767 runway excursion at Miami International Airport, 9 September 2026 → https://www.ntsb.gov/news/press-releases/Pages/NR20260909.aspx 21 Air 767 overruns runway on landing in Miami, Flightradar24 → https://www.flightradar24.com/blog/flight-tracking-news/major-incident/21-air-767-overruns-runway-on-landing-in-miami/ Amazon suspends use of 21 Air after fatal Miami crash, PBS News (Associated Press) → https://www.pbs.org/newshour/nation/amazon-suspends-use-of-21-air-the-cargo-carrier-whose-plane-careened-off-miami-runway-and-killed-5 FAA Advisory Circular 91-79A, Mitigating the Risks of a Runway Overrun Upon Landing → https://www.faa.gov/documentLibrary/media/Advisory_Circular/AC_91-79A.pdf Flight Safety Foundation, Go-Around Decision-Making and Execution Project, Final Report → https://flightsafety.org/wp-content/uploads/2017/03/Go-around-study_final.pdf FAA Air Carrier Training Aviation Rulemaking Committee, Recommendation 24-2: Stabilized Approach Policy, 19 September 2024 → https://www.faa.gov/about/office_org/headquarters_offices/avs/offices/afx/afs/afs200/afs280/act_arc/act_arc_reco/ACT_ARC_Recommendation_24-2.pdf IATA 2025 Annual Safety Report, released 9 March 2026 → https://www.iata.org/en/pressroom/2026-releases/2026-03-09-01/ Flight Safety Foundation 2024 Safety Report, runway excursions by region → https://flightsafety.org/wp-content/uploads/2025/02/FSF-2024-Safety-Report-FINAL.pdf RTMC State of Road Safety in South Africa, 2025 report → https://www.rtmc.co.za/images/rtmc/docs/reports/State_of_Road_Safety/State-of-road-safety-report-2025.pdf SUPPORT THE SHOW Bryan Air → https://bryanairpodcast.com/ Support on Patreon → https://www.patreon.com/bryanair

In this episode of The Doers, we sit down with Himal Karmacharya, Founder and President of Leapfrog Technology. Himal shares the playbook on how he built a world-class technology company from Nepal and scaled it to serve major healthcare and fintech enterprises across the United States.   This conversation goes far beyond surface-level startup advice. Himal unpacks how AI is forcing tech service firms to shift from headcount billing to outcome-based contracts, what it takes to crack international sales, and why finding a trusted on-the-ground ally abroad changes everything. He also breaks down national policy blueprints such as the "Israel Model" to demonstrate how emerging markets can build a $1B+ tech ecosystem.   ⏱️ TIMESTAMPS 00:00 - Beginning 01:42 - Introduction: The Leapfrog Story & Building Global Tech from Nepal 02:25 - How AI is Disrupting Traditional Software Outsourcing & Agency Models 04:27 - The Pricing Shift: Moving from Headcount Billing to Outcome-Driven Value 07:55 - Why Generic Dev Shops Die: Carving Deep Niches in Healthcare & Fintech 11:42 - Nepal's $1B IT Roadmap: Unlocking Policy Reform & Global Visibility 13:42 - Enterprise Readiness: Tackling Global Legal, Compliance & Insurance Hurdles 15:22 - Cracking U.S. Business Development: Outbound Sales Strategy from Day One 17:02 - Diaspora Power: Bridging the Cultural & Credibility Gap in Western Markets 22:42 - Operating at Global Speed: Matching the Relentless Velocity of the U.S. Market 24:02 - Expanding Overseas: Why Every Founder Needs an "Ally" on the Ground 25:17 - The Crucial Pivot: Shifting from Local Mobile Cash to a $150K U.S. Deal 27:42 - Emerging Market Traps: Why Small Domestic TAMs Cap Company Growth 33:42 - The Israel Policy Playbook: How Governments Can Act as Early-Stage VCs 37:00 - NAS-IT Blueprint: Building $50M–$100M Anchor Tech Companies 39:22 - The Golden Founder Rule: Why You Must Pay Yourself from the Start 40:57 - Surviving Phase A-to-B: Managing Cash Flow, Runway & Micro-Seed Capital 44:52 - What Makes an Outlier Founder: Extreme Ownership, Resilience & Drive 48:32 - Angel Investing Philosophy: Why You Back Dynamic People Over Static Ideas 53:52 - Personal Story: From Budhanilkantha to MIT & Breaking Language Barriers 59:42 - Playing the 10-Year Game: Weathering Downturns & Mentoring Next-Gen Talent   Want to become a video podcaster? Get info: https://becomeadoer.com/programs/become-a-video-podcaster?utm_source=Youtube&utm_medium=Episode+Description&utm_campaign=BAVP_C2     For Collaborations ✉ Reach out to us at partners@doersnepal.com   

RAF Brize Norton is one of the busiest air bases in the RAF, so imagine the impact on operations if the runway was put out of action. Well, that's exactly what's going on right now during a 4 month resurfacing project. InsideAIR spoke with RAF Brize Norton's Commander Air Wing to find out more. InsideAIR is produced for the Royal Air Force by RAF Media Reserves. Theme music by RAF Music Services.

#452 In this podcast episode, Guy talked with RJ Spina about moving from spiritual consumerism into true creation, presence, and self-realization. RJ explained that people had often become trapped by predictions, internet noise, and the constant search for more information, while the real work had required turning inward, observing the mind, and discovering the creator within. He also shared how his own life-threatening illness and paralysis had forced him into deep surrender, where he remembered a deeper intelligence beyond thought, emotion, and the body.  The conversation also explored RJ's view that true change had come through letting go of false identity, subconscious programming, victimhood, and ownership of past trauma rather than adding more spiritual knowledge. By the end, RJ encouraged listeners to reclaim their attention, develop presence, take repeated aligned action, and trust that the beauty of life was found in the unfolding rather than chasing external validation or results. ==================== Guy in the USA: immortaltaoistrites.com/matt-and-guy-lawerence Online Healing Sessions with Guy:https://shorturl.at/rzee4     Guy's Official Partners: The DNA Company – Get 10% Off https://thednacompany.com/letitinpodcast FLFE – 2 Week Free Trial (No Credit Card Required) https://www.flfe.net/rp-affiliates.php?p=LiveInFlow&w=TryFLFEfree ====================  Referenced in This Episode Supercharged Self-Healing Change Your Mind LIVE IN FLOW You Are The Sun (RJ's newest book released on Aug 11) The Mechanics of Money — a TV show launching this fall, based on a 9-week course RJ ran with 10 students on manifesting wealth Stuart Wilde's short book The Trick to Money is Having Some ====================  Key Points Discussed:  (00:00) - The 5D Spiritual Distraction! (01:20) - Consumerism vs Creation: Why More Information Won't Save You (03:04) - The False Progress of Mentally Understanding Everything (04:42) - Why the Five Senses Keep Pulling You Outward (05:33) - Gentle Tenacity in a Low-Frequency World (08:14) - 48 Hours to Live and the Surrender That Changed Everything (10:37) - Observation: The Driver's Seat of the Miracle Machine (12:09) - Boredom as the Runway for Enlightenment (14:06) - The Childhood Knowing That He Could Heal Himself (15:00) - Remembering the God Within Beyond the Conditioned Mind (18:00) - Losing the Mind and Living in Perpetual Flow (20:08) - When "Knowledge" Became Labeled Ignorance (22:32) - The Leaky Bucket of Attachments, Judgments and Expectations (25:01) - Self-Realization Is Letting Go, Not Adding More (27:43) - LIVE IN FLOW — Experience This Work in Person (28:40) - Different Sense of Self, Different Actions, Different Results (32:09) - "You Are the Sun" and the Truth Beyond Trauma (38:12) - Identification, Ownership and Why Trauma Keeps Repeating (47:36) - Attention Is the New Oil: Where Your Energy Builds Reality ==================== Guy's Offerings  www.liveinflow.co ====================  How to Contact RJ Spina:www.ascendthefrequencies.com www.youtube.com/@AscendtheFrequencies ====================  Listen on Podcast Spotify Apple Podcasts ====================  Connect with Guy Instagram www.instagram.com/guyhlawrence Live In Flow www.instagram.com/live.in.flow ====================  Continue Your Journey Explore Guy's complete collection of solo podcast episodes: www.youtube.com/show/VLPLKOgPYwzskDo?sbp=Kgt1clRBdHJGem9pd0AB

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AP correspondent Julie Walker reports Amazon suspends use of the cargo carrier involved in a deadly Miami plane crash.

On this week's episode of AvTalk, the more we learn about last Sunday's fatal runway overrun in Miami, the more confusing the circumstances become. We break down what we know from the ADS-B data and the limited flight data recorder information released by the NTSB thus far. A computer failure at NATS leads to the […] The post AvTalk Episode 386: The Miami runway overrun appeared first on Flightradar24 Blog.

AP correspondent Ben Thomas reports cockpit voice recordings are providing some sense of what was happening as an Amazon cargo plane careened off a Miami runway over the weekend.

Στο τέταρτο επεισόδιο των Outliers, ο Αναστάσης Γερμανίδης, μάς μιλά για τη διαδρομή από την Αθήνα μέχρι τη δημιουργία της Runway, της εταιρείας που βρίσκεται πίσω από μερικά από τα πιο εντυπωσιακά εργαλεία τεχνητής νοημοσύνης στον κόσμο. Τι συμβαίνει όταν ένας άνθρωπος που αγαπά εξίσου την τεχνολογία και την τέχνη αποφασίζει να μην επιλέξει ανάμεσα στα δύο; Από τα παιδικά του χρόνια στην Αθήνα και την πρώτη επαφή του με τα νευρωνικά δίκτυα, μέχρι τη Νέα Υόρκη, τη συνάντηση με τους co-founders του και τη δημιουργία μιας πλατφόρμας που χρησιμοποιείται από κορυφαία studios, δημιουργούς και brands παγκοσμίως, ο Αναστάσης μοιράζεται την ιστορία πίσω από το επόμενο μεγάλο κεφάλαιο της τεχνολογίας και της τέχνης.   Μιλάμε για το πώς η Runway έφτασε να ηγείται στον χώρο του AI video, πώς τα world models αλλάζουν τον τρόπο που κατανοούμε τον πραγματικό κόσμο και γιατί το μέλλον της τεχνητής νοημοσύνης δεν αφορά μόνο τη δημιουργία περιεχομένου, αλλά και τη ρομποτική, τα αυτόνομα συστήματα και την επιστήμη. Μέχρι σήμερα η Runway έχει συγκεντρώσει συνολική χρηματοδότηση που ξεπερνά το 1 δισεκατομμύριο δολάρια, με επενδυτές όπως οι General Atlantic, Google, Nvidia, Adobe, Salesforce Ventures και SoftBank. Μόνο τους τελευταίους 12 μήνες, η εταιρεία ολοκλήρωσε γύρους χρηματοδότησης ύψους 308 εκατ. δολαρίων και 315 εκατ. δολαρίων, φτάνοντας σε αποτίμηση άνω των 5 δισεκατομμυρίων δολαρίων.   Τα εργαλεία της χρησιμοποιούνται από περισσότερους από 50 εκατομμύρια χρήστες παγκοσμίως, ενώ συνεργάζεται με κορυφαία studios, agencies και εταιρείες του Fortune 500. Ανάμεσα στους συνεργάτες και χρήστες της βρίσκονται η Lionsgate, η AMC Networks, η Madonna και η New Balance, ενώ η τεχνολογία της έχει αξιοποιηθεί ακόμη και στην πολυβραβευμένη ταινία «Everything Everywhere All at Once».   Πέρα όμως από τα εντυπωσιακά νούμερα, αυτή είναι μια συζήτηση για το μέλλον της τεχνητής νοημοσύνης, αλλά κυρίως για τους ανθρώπους που το χτίζουν. 

When sci-fi movies take a big swing in depicting futuristic fashion, sometimes they end up creating iconic outfits and other times they create fashion which looks laughably outdated in a few years. I've became fascinated by three fashion designers whose work took center stage in sci-fi films and transcended the films themselves. I talk with fashion historians and authors Raissa Bretaña and Thèresa Winge about the influence of Paco Rabanne on Barbarella, the work of Jean-Paul Gaultier on The Fifth Element and the way Alexander McQueen was influenced by dystopian sci-fi, which informed the McQueen style in The Hunger Games: Catching Fire. Each of these collaborations left a lasting impact on cinema and fashion, from the runway to the shopping mall.  Thèresa's book Fashion Adventures in Science Fiction Cinema comes out in December. This episode is sponsored by Quince. Download the Quince app for app exclusive offers or go to Quince.com/imaginary. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Big K Hour 02: The latest updates after Amazon cargo plane overruns runway at Miami International Airport, killing five people full 1537 Tue, 08 Sep 2026 12:17:02 +0000 ARrRuJiJQpGrz9Uy8cPihmTRWHhDCzc1 news The Big K Morning Show news Big K Hour 02: The latest updates after Amazon cargo plane overruns runway at Miami International Airport, killing five people The Big K Morning Show 2024 © 2021 Audacy, Inc.

At least five people are dead after an Amazon cargo aircraft overran the runway during a landing at Miami International Airport on Sunday afternoon, striking multiple vehicles and sending a thick black plume of smoke into the air as it caught fire. Learn more about your ad choices. Visit podcastchoices.com/adchoices

//The Wire//2300Z September 7, 2026// //ROUTINE// //BLUF: UNITED STATES ANNOUNCES EYE-FOR-AN-EYE TARGETING STRATEGY OF MERCHANT SHIPPING IN THE MIDDLE EAST. UKRAINE CONTINUES TARGETING OF MERCHANT SHIPPING IN MEDITERRANEAN SEA. PLANE CRASH OBSERVED AT MIAMI AIRPORT, MULTIPLE FATALITIES REPORTED.// -----BEGIN TEARLINE-----  -International Events-Middle East: Over the weekend, the general situation remained as before. This morning, Iranian forces reportedly launched two cruise missiles toward a merchant vessel in the Strait of Hormuz, with unknown success. Otherwise, CENTCOM announced that the M/T KYLO has sunk at undisclosed coordinates in the Gulf of Oman. In Saudi Arabia, Houthi attacks from this morning targeted the Jazan Refinery once again, with locals observing large smoke plumes in the vicinity of the facility.Analyst Comment: Jazan had just come back online after making repairs due to the latest round of Houthi strikes. Less than a week after the refinery was due to come back online, the Houthis hit it again.Lebanon: Israeli attacks have intensified with a new series of attacks being reported over the weekend. Significant bombing runs were reported throughout Nabatiyeh, mostly focusing on striking residential structures in the town of Kfar Rumman.Mediterranean: Overnight Ukrainian forces targeted a Russian cargo ship off the coast of Crete. The M/V LADY MARIIA was struck by Ukrainian drones while reportedly carrying a cargo of Iranian weapons, which Iran was allegedly attempting to export to Russia.-HomeFront-Florida: Yesterday evening a plane crash was reported at Miami International Airport, after a cargo aircraft overran the runway. Prime Air Flight 7598 (an Amazon cargo plane) made a rough landing on Runway 30, touching down farther down the runway than usual. The aircraft also possibly had issues with their left landing gear, as indicated by video evidence of the landing. The aircraft failed to stop in the allotted distance, and either overran or missed the Engineered Materials Arresting System (EMAS). Once off the runway, the aircraft skidded across NW 67th Avenue, striking multiple vehicles that were on the road. A total of 5x fatalities were reported, and several others wounded.-----END TEARLINE-----Analyst Comments: Following the intensification of airstrikes on commercial shipping over the weekend, the United States has altered the Commander's Intent with regards to the American targeting of commercial shipping. Per Secretary of War Hegseth, the United States will target Iranian noncombatant civilian ships for every attempt by Iran to strike an American warship.In terms of targeting doctrine, conducting kinetic strikes on civilian ships can be interpreted in several ways. Kinetically targeting a ship so as to disable it's movement due to noncompliance with boarding procedures in one's own territorial waters is normally considered acceptable under current international maritime norms. However, verbally stating that random noncombatants will be sunk for no other purpose than for revenge, is generally not in keeping with the Department of Defense Law of War Manual, which states on page 200 that "Combatants may make military objectives the object of attack, but may not direct attacks against civilians, civilian objects, or other protected persons and objects."The deliberate targeting of random civilian ships purely for reasons of revenge/reprisal and NOT for reasons of self-defense or due to Hostile Intent or Hostile Action, is a new milestone, and the public statements by Admiral Brad Cooper and SECWAR Hegseth don't leave much room for interpretation. Regardless of how anyone spins it, in every wartime publication that has been written thus far, this conflict has now transitioned into a state of Unrestricted Warfare, and the follow-on effects of this will probably result in very bad things happening in the very near future, as it becomes common to blur the lines between civilians and military targets.From Ukraine and Russia striking civilian ships in the Black Sea, to Iran and the United States striking civilian ships in the Middle East...in many cases civilians are no longer protected by the general norms of what it means to be a noncombatant. Of course, Iran has been striking civilian merchants this entire war, so this new policy from the Pentagon does not excuse their behavior. But, the overall impact of the United States engaging in an eye-for-an-eye targeting doctrine is going to be made worse, because Iran has already stated that they will be retaliating in kind.Reflecting back on what prompted this new targeting milestone, the theories have been circulating for a few days. Over the weekend however, both the Iranian government and CENTCOM have added some context for why the United States struck the three tankers on Friday. Cutting through the narratives on both sides, the most likely explanation is that the Iranians conducted a live-fire operational test of a new missile...and it got way too close for comfort for the U.S. Navy. CENTCOM confirmed that the USS GEORGE WASHINGTON (CVN 73) had to take evasive action to avoid the missile, which is a startling admission that is not normally disclosed publicly, as it is a major indicator that the missile penetrated the Aegis missile defense screen, and possibly entered the aircraft carrier's Terminal Defense Zone...which means it got really close. The missile that was tested has not been named by official sources, but the most likely candidate is the Qasem Basir Anti-Ship Ballistic Missile (ASBM), which was unveiled in March of last year. As to whether or not the Iranians were engaging in "testing" as they claim, or if that "test" was also intended to actually target the Washington, that would be something only confirmable with the radar track of the projectile itself. Regardless of what the intent was, this effort (and the American retaliation) will keep escalating the war at a time when the energy crisis is reaching new heights.Analyst: S2A1 Research: https://publish.obsidian.md/s2underground NomadNet: 5fa68c88be727a0e1a250a75e5e79269 Disclaimer: No LLMs were used in the writing of this report. //END REPORT//

How did Joe Thomas and his co-founders keep building Loom when they had maxed-out credit cards and only 14 days of runway left?Before Loom became one of the most recognizable asynchronous video platforms, Joe Thomas, Vinay Hiremath, and Shahed Khan spent nine months testing ideas, making major pivots, and listening closely to early users. Their persistence eventually transformed a struggling user-feedback product into a new way for people to communicate at work.In this encore episode of From Start-Up to Grown-Up, executive coach and bestselling author Alisa Cohn sits down with Joe to explore Loom's earliest days, the approximately 100 fundraising rejections that strengthened his pitch, and the leadership lessons he learned while scaling the company.Joe also reveals why Loom defined its values when the team had only seven people, how meditation helped him make better decisions, and why founders must become comfortable doing the work they would naturally rather avoid.This is a candid conversation about resilience, fundraising, company culture, asynchronous leadership, and what it takes to grow from founder to CEO.You'll learn:How Joe Thomas and his co-founders discovered the idea for LoomHow Joe improved his fundraising skills after approximately 100 rejectionsWhy founders often avoid the responsibilities that make them uncomfortableHow Loom defined its company values with only seven employeesWhy values become most important during difficult decisionsHow meditation helped Joe become less reactive as a leaderWhy giving difficult feedback can be an act of beliefHow leaders can protect their energy while building a companyWhen to communicate asynchronously and when to hold a meetingWhy discomfort is an unavoidable part of growing into a leaderWe talk about:00:00 Meet Joe Thomas, co-founder of Loom01:27 The original idea behind video communication at work04:20 Nine months of experimentation, customer conversations, and pivots10:17 Starting the company with $25,000 and a mattress on the floor12:20 Reaching the final 14 days of runway16:17 Learning to fundraise after approximately 100 rejections19:44 Choosing investors for a long-term relationship22:01 Tracking time and prioritizing a founder's responsibilities31:43 Defining Loom's values with only seven employees42:13 How meditation improved Joe's decision-making46:13 Balancing empathy with difficult feedback50:33 Becoming friends with hard times51:28 Why taking care of yourself makes you a better CEO57:10 When to use asynchronous communication instead of a meeting01:01:04 Learning to live with imposter syndrome01:03:28 What Joe wishes he had understood earlier01:05:16 Joe's advice for founders growing into leadersFollow Joe onLinkedIn: https://www.linkedin.com/in/joethomasx/ Connect with Alisa!Follow Alisa Cohn on Instagram: @alisacohnTwitter: @alisacohnFacebook: facebook.com/alisa.cohnLinkedIn: https://www.linkedin.com/in/alisacohn/Website: http://www.alisacohn.comDownload her 5 scripts for delicate conversations (and 1 to make your life better) Grab a copy of From Start-Up to Grown-Up by Alisa Cohn from Amazon

AP correspondent Donna Warder reports on the investigation into Sunday's crash of an Amazon cargo jet at Miami International Airport that killed five people.

In this episode of Denoised, Joey and Addy break down the latest breakthroughs in AI world models, from World Labs' photorealistic Atlas to Runway's GWM World 2 and Solaris interface. They also dive into tech news, including OpenAI's Mac Mini hoarding ...

Fashion Week is a week away, and Ask Nyomi: Bridging the Gap is bringing on two people host Nyomi Banks calls her "fashion industry children" — Xavier Walker and Norka Vasquez, co-founders of Caribbean Fashion Collective (CFC). Nyomi has watched both of them grow from models into industry builders, and this episode is a front-row seat to that evolution.Xavier and Norka break down what it actually took to land Caribbean Fashion Collective a spot on the CFDA New York Fashion Week calendar — for the second time — and why that matters far beyond the glitz of a runway show. They talk about being recognized by Essence, the reality of being "gatekeepers" trying to open more doors instead of just one, and their long-term vision to expand CFC beyond New York into a full Caribbean tour and eventually Europe.The conversation gets personal fast. Norka shares the unvarnished story of how CFC actually got funded — an unexpected move-out payout from a landlord, a friend's spare room in Harlem, and a decision to bet that money on a company instead of an apartment. It's a real, no-gloss look at what founding something from nothing actually looks like, plus their advice for the next generation of Caribbean creators and models trying to build their own platforms.In this episode, you'll learn:What it means to be selected for the CFDA New York Fashion Week calendar — twiceHow Caribbean Fashion Collective is creating opportunities for historically excluded Caribbean creatorsXavier and Norka's vision for CFC's future: a Caribbean tour, European expansion, and mentorship for designers back homeThe real, unplanned financial risk behind founding CFCWhy having "someone in your corner" matters when you're building something from scratchTheir advice to models and creatives who want to build their own platform instead of waiting to be chosenAbout Xavier Walker & Norka Vasquez Xavier Walker and Norka Vasquez are co-founders of Caribbean Fashion Collective, a platform creating visibility and opportunity for Caribbean creators in the fashion industry. Both started as models — including work with IS By Nyomi Banks — before building CFC into a CFDA-recognized New York Fashion Week presence, with recognition from Essence and a growing footprint aimed at expanding across the Caribbean and into Europe.Connect with Caribbean Fashion Collective:Check their official website and socials for Fashion Week show details and season updatesConnect with Nyomi Banks / Ask Nyomi: Bridging the Gap:Email for love, sex & relationship advice: info@nyomi.comCatch Nyomi at New York Fashion Week this week supporting Caribbean Fashion CollectiveNew: Nyomi's Intimate Corner on PatreonUpcoming: Souls (horror film, written and executive produced by Nyomi, directed by Dog Pound Mike Mike) coming to Tubi, plus Caught 2 on the waySEO Keywords / TagsCaribbean Fashion Collective, CFDA Fashion Week, New York Fashion Week, Caribbean designers, fashion entrepreneurship, from model to founder, Xavier Walker, Norka Vasquez, building a fashion brand, Caribbean creators, fashion industry diversity, Essence recognition, Nyomi Banks, Ask Nyomi Bridging the Gap, entrepreneurship podcast, fashion week special episode ASK NYOMI: BRIDGING THE GAPHost: Nyomi Banks (Da Goddess of Self Love)Co-Host: Dog Pound Mike MikeThank you for tuning in! We appreciate you being part of the BTG community 

Brooks rapid-fires through the piece everyone questions but he'll defend till he dies, the funniest business fights with his mom Meredith, the accessory that can ruin a whole look, and the ridiculous first splurge if his brand ever goes global.See omnystudio.com/listener for privacy information.

Brooks rapid-fires through the piece everyone questions but he'll defend till he dies, the funniest business fights with his mom Meredith, the accessory that can ruin a whole look, and the ridiculous first splurge if his brand ever goes global.See omnystudio.com/listener for privacy information.

Matt Workman, creative technologist at fal, joins us to break down H3 Max, the model that makes 15 second AI videos in 5 seconds, and fal.live, a livestream where viewers prompt what happens next in real time. We get into how DLSS 5 actually works before its release with NBA 2K27, why the leaked GTA footage looked wrong, and the new wave of world models from Runway and World Labs that turn a photo into an explorable 3D space. Then Matt gives an inside view of what major studios are quietly doing with AI, how directors use it, and why it is getting hard to get hired without it.Sources:1. fal.live and H3 Max (Matt Workman, fal)- https://fal.live/- https://x.com/fal2. DLSS 5- https://x.com/NVIDIAGeForce/status/2033617732147810782- https://x.com/NVIDIAGeForce/status/2094772262545363122- https://x.com/NVIDIAGeForce/status/20947760491878401203. World Labs Atlas- https://x.com/theworldlabs/status/2094839756329041984- https://x.com/davidpantera_/status/2094841083805266401- https://www.worldlabs.ai/blog/atlas#build-with-atlas4. Runway Solaris- https://x.com/runwayml/status/20944630704666460195. Fable 5.1- https://x.com/claudeai/status/2094848572143407483

Ken and Lima analyze the Simulation Browns as they head into the season, debating whether Deshaun Watson can maintain his starting role. Daryl Ruiter joins to discuss the heartbreak of local receiver Luke Floriea being cut and the mysterious injury to backup quarterback Dylan Gabriel. They outline a four-week runway for Watson before potentially turning to Shedeur Sanders. 02:22 - Sim Browns Season Preview 06:07 - Todd Monken's Quarterback Philosophy 09:16 - Defensive Depth and Scheme 14:52 - Daryl Ruiter joins Lima 26:02 - Deshaun Watson's Final Tryout 30:04 - Roster Depth and Waivers 35:08 - Deshaun's Four Week Runway 38:35 - Dylan Gabriel Injury Theory

Today's guest is Josh Builder, Chief Technology Officer at Datavant. Founded in 2017, Datavant is a healthcare data collaboration platform that makes health data secure, accessible and actionable. Its technology connects fragmented health data, enabling compliant information exchange across providers, payers, life sciences companies and government agencies. This unified network supports faster insights, better decision-making and new AI-driven healthcare applicationsJosh is a senior technology and product leader who solves complex business challenges through advanced technology and data. He has worked alongside founders and CEOs to turn ambitious ideas into scalable solutions, drive growth and navigate significant change. Combining strategic vision with deep technical and operational expertise, Josh translates complex concepts into practical outcomes and builds diverse, high-performing teams that promote innovation and operational excellence.In the episode, Josh talks about:Driving technology-driven transformations across music, fashion, fitness and healthcareWhy technology should enhance human experiences, not replace themHelping Rent the Runway evolve from event rentals to everyday workwear subscriptionsUsing technology to securely connect fragmented healthcare data for better patient careHis focus on AI governance, developer autonomy and evaluation-driven engineering at DatavantHow AI reshapes engineering teams around evolving business needsHow AI will transform engineering, but experience, mentorship and fundamentals remain criticalPlans to scale the AI-native engineering teams in Galway, IrelandHow Datavant connects, secures and unlocks healthcare data insightsTo find out more about all the great work happening at Datavant, check out the website www.datavant.com

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From Roadmap to Runway: What Speed to Value in Healthcare AI Actually Takes Every health system has an AI roadmap. Far fewer have a runway. Vendors sell the destination. Getting there, on time and on budget and actually live, is the part nobody demos. Scott Raymond, former CIO at Nebraska Medicine and a longtime health IT leader who still holds an active nursing license, gets specific on virtual nursing, predictive staffing and scheduling, the workflows you have to solve first, and why the gap between promise and production is where most AI quietly stalls. To stream our Station live 24/7 visit www.HealthcareNOWRadio.com or ask your Smart Device to “….Play Healthcare NOW Radio”. Find all of our network podcasts on your favorite podcast platforms and be sure to subscribe and like us. Learn more at www.healthcarenowradio.com/listen/

A founder can be burned out enough to want an exit and still not beready to let the business go.Juan Ignacio knows that tension from both sides. He built a B2B SaaSlending platform from Madrid, raised tens of millions in venturecapital along with a $100 million debt facility, and exited four yearsafter launching. The deal created relief, but it also exposed aquestion the transition could only postpone: What do I do with my lifenow?In this episode of Your NEXT, Juan joins Jerome Myers to unpack whathis own near distressed exit taught him about preparation, runway, andthe danger of waiting until the company needs a transaction. He alsoexplains how that experience led him to found L40, a sell side M&Aadvisory firm focused largely on B2B SaaS companies.Together, Jerome and Juan explore why founders sometimes sabotage thetransactions they say they want, how valuation expectations and markettiming affect the likelihood of a sale, and why “I just need themoney” may be a signal to examine the real problem before hiring anadvisor.Juan also explains the Rule of 40, what makes an advisor a genuinefit, and why a healthy company is not automatically a desirableacquisition target.The hardest part of an exit is not always finding a buyer.Sometimes it is helping the founder become willing to leave.Learn more about Juan and L40:https://www.l40.comTake the Exit Readiness Assessment:https://www.exittoexcellence.com/eraLearn more about Jerome Myers:https://www.exittoexcellence.comThank you,Jerome Learn more about your ad choices. Visit megaphone.fm/adchoices

This morning on the show, we had a wild ride with a Bruno Mars contest that had everyone on the edge of their seats. But it wasn't just the music that got our hearts racing - we also had a heartwarming conversation with Olivia, the founder of Runway for Recovery, an incredible organization that's been making a difference in the lives of women and families affected by breast cancer.This episode was a mix of laughter and tears, as we navigated a Bruno Mars contest that had some unexpected twists and turns. We also took a moment to pay tribute to the one and only Dolly Parton, who left an indelible mark on the music world. And in our topic time segment, we dived into some hilarious and relatable stories about dating and relationships.But what really stood out in this episode was the inspiring story of Olivia and her journey with Runway for Recovery. From its humble beginnings to its current success, this organization has been making a real difference in the lives of those affected by breast cancer. We also heard from a caller who won tickets to see Bruno Mars, and got to experience the excitement of the contest firsthand.If you want to hear more about the Bruno Mars contest, the inspiring story of Runway for Recovery, and the hilarious dating stories, tune in to this episode of the show. We're sharing some amazing stories and having a great time, and we can't wait to hear your thoughts.See omnystudio.com/listener for privacy information.

After four decades in the modeling industry, Christine Handy's life changed when she was diagnosed with breast cancer at 41.Her journey forced her to look beyond external beauty and discover a deeper sense of self-worth, faith, courage, and purpose. In this episode, Christine shares how she transformed a life-altering experience into a mission to help others — from writing Walk Beside Me to returning to the runway to champion women affected by breast cancer.We talk about redefining beauty, finding strength through adversity, the power of showing up for others, and how storytelling can become a powerful form of healing.In this episode, you'll discover:The danger of relying on external validation to define your worthCourage during long trials of difficulty or illnessBeing a vine not a victimThe role of faith, friendship, and self-love in healingEpisode Resources:⁠⁠⁠⁠Christine Website: https://christinehandy.com/Christine Instagram: https://www.instagram.com/christinehandy1/

Charles Robinson joined Baskin and Phelps and shared his perspective on Deshaun Watson being named the Browns' starting quarterback and why he thinks it was obvious the organization was going in that direction. He talked about the pros and cons of Deshaun Watson winning the starting job, how it will impact Shedeur Sanders, and whether or not he thinks Watson will play in all 17 games this season. He also discussed the depth and talent of the 2027 draft class and whether or not he thinks the impending rookies will live up to the hype.

In episode 301 of the Simple Flying Podcast, your hosts Tom & Channing discuss:American Airlines to bring back seatback screensVietnam Airlines Boeing 787 overrun incident in MunichDelta Air Lines boosts premium seats on new aircraftLufthansa Airbus A380 lands short of runway in MunichAlaska Airlines Boeing 787 flight attendants overextended on long-haul flights

Good Vibe Tribe - Runway For Recovery full 383 Wed, 19 Aug 2026 12:47:00 +0000 TEXfvtV2z31ju2JW91QWpAIiGDUZq0Nx latest,wbmx,society & culture Karson & Kennedy latest,wbmx,society & culture Good Vibe Tribe - Runway For Recovery Karson & Kennedy are honest and open about the most intimate details of their personal lives. The show is fast paced and will have you laughing until it hurts one minute and then wiping tears away from your eyes the next. Some of K&K’s most popular features are Can’t Beat Kennedy, What Did Barrett Say, and The Dirty on the 30! 2024 © 2021 Audacy, Inc. Society & Culture https://player.amperwavepodcasting.com?feed-link=https%3A

What if having less could actually give you more—more time, more energy, more creativity, and more freedom?In this episode of Badass Basic Bitch, Brianna sits down with Courtney Carver, founder of Be More with Less and creator of the Project 333 Challenge, to talk about simplifying your life, letting go of what's weighing you down, and redefining what “enough” really looks like.Courtney's journey toward simplicity began after a life-changing health diagnosis forced her to take a closer look at the stress in her life. What started with addressing debt, clutter, and an overwhelming career eventually became a completely different way of living—and a movement that has inspired people around the world to rethink their relationship with their stuff.Courtney breaks down her famous Project 333 Challenge: dressing with just 33 items or less for three months. But as Brianna and Courtney explore, this conversation is about much more than cleaning out your closet.They dive into the emotional reasons we hold onto things, how shopping can become a way of coping with discomfort, the influence of social media and algorithms on consumerism, and the surprising mental freedom that comes from having fewer decisions to make every day.From designer handbags and kids' clutter to online shopping and decision fatigue, this episode will have you looking around your house—and maybe opening your closet—the second it's over.In This Episode, We Discuss:How Courtney's journey toward simplicity beganWhy reducing stress became the catalyst for changing her lifeThe creation of Be More with Less and Project 333How the Project 333 Challenge worksWhat is—and isn't—included in your 33 itemsWhy Project 333 isn't about deprivation or sufferingHow having less helps redefine what “enough” actually meansThe emotional attachment we develop to clothes, handbags, and possessionsA simple trick for letting go of items you're emotionally attached toBrianna's experience letting go of designer bags and simplifying her wardrobeHow shopping can become a coping mechanism when other parts of life feel outside our controlWhy clutter isn't always made up of things we dislikeThe challenge of managing clutter when you have kidsHow fewer choices can benefit children, tooReducing decision fatigue through a simplified wardrobeWhy fewer possessions can create more room for creativityManaging your energy instead of constantly trying to manage your timeUsing services like Rent the Runway without falling back into overconsumptionHow Instagram, TikTok, algorithms, and online shopping influence what we think we needWhy Courtney intentionally reduced her own social media consumptionThe surprising realization that most people aren't paying attention to what you wearHow simplifying one area of your life can inspire changes everywhere elseMemorable Quote“One of the biggest benefits is realizing that nobody notices what you're doing.” — Courtney CarverKey TakeawaysSimplicity Isn't About DeprivationProject 333 isn't designed to make you suffer through three months with nothing to wear. The challenge is an experiment in discovering how much you actually need.By choosing 33 items—including clothing, jewelry, shoes, and accessories—and living with them for three months, you get the opportunity to step away from the constant cycle of wanting more and discover what you genuinely enjoy wearing.Sometimes You Need Space Before You Can Let GoGetting rid of something can feel surprisingly emotional, especially when the item represents a memory, identity, accomplishment, or version of yourself.Courtney suggests removing items from sight before deciding whether to permanently let them go. Creating distance can weaken the emotional connection and help you recognize whether you actually miss the item—or simply felt uncomfortable getting rid of it.Clutter Costs More Than MoneyEverything we own requires something from us. We have to organize it, clean it, maintain it, store it, think about it, or decide what to do with it.Reducing what you own isn't simply about having a cleaner closet. It can reduce decision fatigue and free up mental energy for creativity, relationships, work, problem-solving, and the things that matter more.Shopping Can Give Us the Illusion of ControlWhen something painful or stressful is happening outside of our control, focusing on something we can control—like what we buy—can feel comforting.But that temporary relief can eventually create another source of stress through clutter, spending, and the constant pressure to acquire more. Recognizing why you're reaching for something can be just as important as deciding whether to buy it.Social Media Is Constantly Telling Us We Need MoreInstagram, TikTok, online shopping, and personalized algorithms have created an environment where we're constantly being introduced to the next thing we're supposed to want.Courtney shares why she's intentionally reduced her own time on certain platforms and why becoming more conscious about what we're consuming digitally can help change what we consume physically.Fewer Decisions Can Create More CreativityWhen you remove dozens of unnecessary decisions from your day, that energy doesn't disappear—it becomes available for something else.Courtney has found that simplifying areas like her wardrobe gives her more capacity for writing, business, problem-solving, and creativity. Sometimes creating more space in your life literally begins by removing things from it.Nobody Is Paying as Much Attention as You ThinkOne of the unexpected lessons from Project 333 is discovering how little other people notice what you're wearing.The fear that someone will notice you repeating an outfit or wearing fewer things is often much bigger in our minds than it is in reality. Letting go of that perceived judgment can create freedom far beyond your closet.Ready to Try Project 333?For three months, dress with 33 items or less, including:ClothingJewelryAccessoriesShoesItems such as underwear, sleepwear, workout clothing used specifically for exercise, and special-occasion pieces aren't included in the 33.The goal isn't to find the perfect 33 pieces. It's to experiment with less and pay attention to what changes—your mornings, your decisions, your spending, your energy, and potentially much more.Connect with Courtney CarverCourtney Carver is the founder of Be More with Less and creator of the Project 333 Challenge. Through her books, writing, courses, and The Simplicity Space Community, Courtney helps people live with less and let go of what's weighing them down.

Daniel Mahncke and Shawn O'Malley take a deep dive into DLocal (NASDAQ: DLO), the first Uruguayan unicorn and the emerging markets payment provider for companies like Amazon, Uber, Spotify, Netflix, and many more. DLocal is trading at attractive multiples while growing payment volumes at over 70% and printing cash due to high operating leverage and a high-margin business model. That cash is given back to shareholders in the form of dividends and buybacks. Daniel and Shawn discuss whether the high customer concentration and the declining take rate justify the cheap valuation or whether the market is not understanding the full potential of this emerging market jewel. In the end, Daniel values the business and decides whether DLO deserves a spot in The Intrinsic Value Portfolio. IN THIS EPISODE YOU'LL LEARN: (00:00:00) Intro (00:03:01) How DLO became the leading player in emerging markets (00:07:14) What makes DLO's business model stand out (00:19:08) What two megatrends DLO benefits from (00:28:18) Whether there is a race to the bottom with take rates (00:56:10) How DLO compares to Western competition (01:00:30) How DLocal distributes cash to shareholders (01:19:00) Valuation discussion of DLO (01:21:41) Whether DLO is valued attractively (01:23:19) Whether Shawn and Daniel add DLO to the Intrinsic Value Portfolio Disclaimer: Slight discrepancies in the timestamps may occur due to podcast platform differences. BOOKS AND RESOURCES Join the exclusive ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Intrinsic Value Mastermind Community⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Track ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Intrinsic Value Portfolio⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Learn more about how to join us in NYC for our ⁠⁠⁠Intrinsic Value Conference⁠⁠⁠. Portfolio Review ⁠⁠Submit Tool⁠⁠. Value Investors Club Pitch on DLO. Interview with the CEO, Pedro Arnt. DLocal Investor Relations Podcast. Founder and CEO Interview by Stratechery. Check out our previous Intrinsic Value breakdowns: Visa,⁠⁠⁠ ⁠Amazon⁠⁠⁠, ⁠Sea Limited⁠, ⁠Mercado Libre⁠, ⁠Shopify⁠. Related ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠books⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ mentioned in the podcast. Ad-free episodes on our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Premium Feed⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. NEW TO THE SHOW? Get smarter about valuing businesses through ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Intrinsic Value Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Check out ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Investor's Podcast Starter Packs⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Follow our official social media accounts: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Try our tool for picking stock winners and managing our portfolios: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TIP Finance⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Enjoy exclusive perks from our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠favorite Apps and Services⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Learn how to better start, manage, and grow your business with the ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠best business podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. SPONSORS Support our free podcast by supporting our ⁠⁠⁠sponsors⁠⁠⁠: ⁠⁠Plus500⁠⁠ ⁠⁠Netsuite⁠⁠ ⁠⁠Shopify⁠⁠ ⁠⁠Plaud References to any third-party products, services, or advertisers do not constitute endorsements, and The Investor's Podcast Network is not responsible for any claims made by them. Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm