Podcast appearances and mentions of Justin Johnson

Come have a taste of the high life and get an exclusive taster of our premium Patreon episodes. In this one, we're delving into the hometown of another dear Teulu member, Justin Johnson. Join us as we focus our keen (drunk) eyes across the Atlantic and have a look at the city of murals AKA Toppenish, WA. If this has tickled your pickle and you want more, click this linky bad boy and make a purchase you'll never forget.

Send us Fan Mail This week Greg sat down with Justin Johnson. He is the Owner and President of High Calling Fitness. This episode was packed full of fitness information, myths, conspiracy theories that keep you lethargic and slow, and new breakthroughs that can help you get and stay in shape. If its finally time to get in shape, tone up, or start lifting real weight, Justin or one of his coaches can help! CLICK HERE to schedule a free consultation. Enjoy the episode! Get 10% off your bible rebind with Deus Vult Rebinding with the code "DEADMANWALKING" at checkout! My favorite coffee and now yours! Get your mystery gift from Squirrelly Joes Coffee by clicking here! Covenant Real Estate: "Confidence from Contract to Close" Facebook: Dead Men Walking PodcastYoutube: Dead Men Walking PodcastInstagram: @DeadMenWalkingPodcastTwitter X: @RealDMWPodcastExclusive Content: PubTV AppSupport the show Check out out the Dead Men Walking snarky merch HERE! Build something for God's glory through Covenant Real Estate! Greg Moore Jr. can help you buy, sell, and invest! Call him at (734) 731-GREG or visit www.covenant.realestate 10% off a rebound bible from Deus Vult Rebinding with the code DEADMANWALKING Get you the best darn coffee in the country at Squirrelly Joes

Send us Fan MailThis week Greg sat down with Justin Johnson. He is the Owner and President of High Calling Fitness. This episode was packed full of fitness information, myths, conspiracy theories that keep you lethargic and slow, and new breakthroughs that can help you get and stay in shape. If its finally time to get in shape, tone up, or start lifting real weight, Justin or one of his coaches can help! CLICK HERE to schedule a free consultation. Enjoy the episode! Are you a Christian company looking to partner with a low-cost, high-return service that shares like-minded principles? Then AdventDS is for you!Are you ready for your church conference? Contact Striving For Eternity HERE!Dominion Wealth: "All of Christ for all of life, All of Finance for Christen Covenant Real Estate: "Confidence from Contract to Close" Facebook: Dead Men Walking PodcastYoutube: Dead Men Walking PodcastInstagram: @DeadMenWalkingPodcastTwitter X: @RealDMWPodcastExclusive Content: PubTV App

Send us Fan Mail This week Greg sat down with Justin Johnson. He is the Owner and President of High Calling Fitness. This episode was packed full of fitness information, myths, conspiracy theories that keep you lethargic and slow, and new breakthroughs that can help you get and stay in shape. If its finally time to get in shape, tone up, or start lifting real weight, Justin or one of his coaches can help! CLICK HERE to schedule a free consultation. Enjoy the episode! Get 10% off your bible rebind with Deus Vult Rebinding with the code "DEADMANWALKING" at checkout! My favorite coffee and now yours! Get your mystery gift from Squirrelly Joes Coffee by clicking here! Covenant Real Estate: "Confidence from Contract to Close" Facebook: Dead Men Walking PodcastYoutube: Dead Men Walking PodcastInstagram: @DeadMenWalkingPodcastTwitter X: @RealDMWPodcastExclusive Content: PubTV AppSupport the show Check out out the Dead Men Walking snarky merch HERE! Build something for God's glory through Covenant Real Estate! Greg Moore Jr. can help you buy, sell, and invest! Call him at (734) 731-GREG or visit www.covenant.realestate 10% off a rebound bible from Deus Vult Rebinding with the code DEADMANWALKING Get you the best darn coffee in the country at Squirrelly Joes

Two Major ALM Conferences back-to-back … Two years in a row!   There were skeptics.  The proverbial "they" said it couldn't be done.  Once again, Legal Speak believed it … and was there to see it for themselves. For over 20 years now, the General Counsel Conference Midwest has been the premier event in the industry.  Delivering practical solutions and key insights that today's General Counsel need to successfully overcome a litigation crisis, manage and better leverage C-Suite relationships, and do more with fewer resources.  For the 3rd year, Legal Speak was there live to bring you interviews with interesting attendees as well as moderators and speakers from various panels from this year's event at the Chicago. In this episode, host Cedra Mayfield is joined by returning guest Justin Johnson, the Chicago President & Partner of Latitude Legal.   Host: Cedra Mayfield Guest: Justin Johnson Producer: Charles Garnar

Imagine a world where brainless human clones can provide spare organs... well, scientists are pitching this idea.  Kirk and Marianne discuss the ethics of artificial wombs and the how this new technology can be misused.  Also, Justin Johnson, 98 Rock program director shares his opinion on one of the most controversial ideas in modern science.

We've been on a bit of a mini World Models series over the last quarter: from introducing the topic with Yi Tay, to exploring Marble with World Labs' Fei-Fei Li and Justin Johnson, to previewing World Models learned from massive gaming datasets with General Intuition's Pim de Witte (who has now written down their approach to World Models with Not Boring), to discussing the Cosmos World Model with with Andrew White of Edison Scientific on our new Science pod, to writing up our own theses on Adversarial World Models. Meanwhile Nvidia, Waymo and Tesla have published their own approaches, Google has released Genie 3, and Yann LeCun has raised $1B for AMI and published LeWorldModel.Today's guests have a radically different approach to World Modeling to every player we just mentioned — while Genie 3 is impressive, its many flaws demonstrate the issues with their approach - terrain clipping, noninteractivity (single player, no physics/no objects other than the player move), and maximum of 60 second immersion. Moonlake AI (inspired by the Dreamworks logo) is the diametric opposite - immediately multiplayer, incredibly interactive, indefinite lifetime, capable of MANY different kinds of world models by simulating environments, predicting outcomes, and planning over long horizons. This is enabled by bootstrapping from game engines and training custom agents: In Towards Efficient World Models, Chris Manning and Ian Goodfellow join Fan-Yun in explaining why their approach to efficiency with structure and casuality instead of just blind scaling is sorely needed:SOTA models still show physical or spatial understanding glitches, such as solid objects floating in mid-air or moving “inside” other solid objects.If the goal is to plan for the next action, how often is a high-resolution pixel view necessary for modeling the world? Our bet is that there is a disproportionately large share of economically valuable tasks where such detail is not required. After all, humans with a wide variety of sensory limitations have little difficulty doing almost everything in the world. Furthermore, for a large number of purposes, describing a scene or a situation in a few words of language (“the car's tires squealed as it cornered sharply”) is sufficient for understanding and planning.Experiments also show that humans only partially process visual input in a top-down, task-directed way, often making use of abstracted object-level modeling. In almost all cases, partial representations combined with semantic understanding are sufficient.…If the goal is to facilitate the understanding of causality in multimodal environments, then the world model—whether it is used in the virtual world or the physical world—must prioritize properties such as spatial and physical state consistency maintained over long time periods, and an ability to evolve the world that accurately reflects the consequences of actions. That's what Moonlake is building.Game engines are the right starting point abstraction to efficiently extract causal relationships, and building the interfaces and community (including their new $30,000 Creator Cup) to kickstart the flywheel of actions-to-observations.We were fortunate enough to attend their sessions at GDC 2026 (the Mecca of Game Devs), and were impressed by the huge variety and flexibility of the worlds people were building with Moonlake's tools already! Live videos on the pod.Full Video Pod on YouTube!Timestamps00:00 Benchmarking Gets Hard00:47 Meet Moonlake Founders01:26 Why Build World Models03:12 Structure Not Just Scale05:37 Defining Action Conditioned Worlds07:32 Abstraction Versus Bitter Lesson14:39 Language Versus JEPA Debate20:27 Reasoning Traces And Rendering Layer37:00 Gameplay Over Graphics38:02 Fiction Rules And World Tweaks39:15 Code Engines Beat Learned Priors41:10 Diffusion Scaling Limits43:23 Symbolic Versus Diffusion Boundary46:14 Platform Vision Beyond Games50:24 Spatial Audio And Multimodal Latents54:23 NLP Roots Hiring And Moon Lake NameTranscript[00:00:00] Cold Open[00:00:00] Chris Manning: Think this whole space is extremely difficult as things are emerging now. And I mean, it's not only for world models, I think it's for everything including text-based models, right? ‘cause in the early days it seemed very easy to have good benchmarks ‘cause we could do things like question answering benchmarks.[00:00:20] But these days so much of what people are wanting to do is nothing like that, right? You're wanting to get some recommendations about which backpack would be best for you for your trip in Europe next month. It's not so easy to come up with a benchmark, and it's the same problem with these world models.[00:00:41] Meet the Founders[00:00:41] swyx: Okay. We're back in the studio with Moon Lake's, two leads. I, I guess there's other founders as well, but, sun and Chris Manning. Welcome to the studio.[00:00:54] Fan-yun Sun: Thanks. Thanks, Chris. Thanks for having us.[00:00:56] swyx: You've got, you guys have, come burst onto the scene with a really refreshing [00:01:00] new take of mold models.[00:01:01] I would just want to, I guess ask how you, the two of you came together. Chris, you're a legend in NLP and just AI in, in, in general. You're, you're his grad student, I guess[00:01:10] Fan-yun Sun: Actually my co-founder.[00:01:11] swyx: Oh, yeah.[00:01:12] Fan-yun Sun: I should give a lot of credit to my co-founder, Sharon. Yeah. She was, she was actually working with Professor Fe Androgyn and then she ended up working with, Ron and Chris Manning here.[00:01:22] And then, so I got connected through to Chris initially, actually through my co-founder,[00:01:26] What is Moon Lake?[00:01:26] swyx: what is Moon Lake? What, what is, actually, I'm also very curious about the name, but like why going into world models?[00:01:33] Fan-yun Sun: So I was working a lot. With actually Nvidia research during my PhD years on essentially generating interactive worlds to train reinforcement learning agents or embody EA agents.[00:01:44] And then there's two observations. One in academia and one in industry. An industry like folks at Nvidia are actually paying a lot of dollars to purchase these types of interactive worlds, whether it's for the sake of evaluation or training the robots, or policies or models. And [00:02:00] then, in academia, same thing is happening.[00:02:02] And more specifically, when I was actually working with Nvidia on the synthetic data foundation model training project, we were actually generating a lot of these synthetic data and showing that, hey, you can actually, these synthetic data are actually as useful as real world data when it comes to multimodal pre-training.[00:02:16] But then, like I said, there's a lot of dollars being paid out to like external vendors or, or like. Other folks to manually curate these types of data. It was very clear to us that, okay, on our way to, let's call it embody general intelligence models need to learn the consequences behind their actions, which means that they need interactive data and the demand for those types of data are growing exponentially.[00:02:38] But everybody's sort of thinking about it from a pure, say, video generation perspective or something else. But we feel like the true actually opportunity is actually building reasoning models that can do these things, like how humans do these things today. So that's a little bit on the genesis of Moon Lake, and I think the reason I got into world models was partly.[00:02:59] A philosophical [00:03:00] take of the on the world where I like, believe the simulation theory and stuff like that. But on the other, on the other hand, it's really just like, oh, like there's an opportunity there that I feel like nobody's doing it the way I think should be done.[00:03:10] Structure, Not Scale: The Vision[00:03:10] Chris Manning: I can say a little bit about that.[00:03:12] Yeah. So of the overall goal is the pursuit of artificial intelligence and most of my career has been doing that in the language space and that's been just extremely productive. As we all know, the story of the last few years, I don't have to tell about how much we've achieved with large language models, but, uh.[00:03:31] Although they have been extremely effective for ramping language and general intelligence, it's clearly not the whole world. There's this multimodal world of vision, sound, taste that you'd like to be dealing with more than just, language. And then the question is how to do it. And despite, a huge investment in the computer vision space, right, as the research field computer [00:04:00] vision has been for decades, far, far larger than the language space, actually.[00:04:05] I think it's fair. Say that, vision, understanding sort of stalled out, right? You got to object recognition and then progress just wasn't being made right? If you look at any of these, vision language models, it's the language that's doing 90% of the work and the vision barely works. And so there's really an interesting research question as to why that is and at heart, the ideas behind Moon Lake are an attempt to answer that, believing that there can be a really rich connection between a more symbolic layer of abstracted understanding of visual domains, which aren't in the mainstream vision models, which are still trying to operate on the surface level of pixels.[00:04:50] swyx: I think one of your blog posts, you put it as structure, not scale. Is that, a general thesis?[00:04:57] Chris Manning: Yeah. Well, scale is good too.[00:04:58] swyx: Yeah. Scale is good. Too[00:04:59] lot,[00:04:59] Chris Manning: [00:05:00] lots of data is good as well and scale, but nevertheless, you want the structure Yeah. To be able to much more efficiently learn.[00:05:07] swyx: Yeah. The other thing I really liked also is you put out an example of what your kind of reasoning traces look like.[00:05:12] Right. Which you would distill is the word that comes to mind. I don't even think that's a good, good description, but it would involve, for example, geometry, physics, affordances, symbolic logic, perceptual mappings, and what, what have you. But like that, that is the kind of example that involves, let's call it spatial reasoning, role model reasoning as as compared to normal LM reasoning.[00:05:35] Yeah.[00:05:36] Defining World Models vs Video Generation[00:05:36] Vibhu: But also like taking it a step back. So how do you guys define world models? A lot of people see okay, you can do diffusion, you can do video generation. But, you guys put out quite a few blog posts. You put out a essay recently, we can even pull it up about efficient world models. You have a pretty like structural definition here, but for the general audience that don't super follow the space, right.[00:05:55] What's, what's the difference in what we see from like a video generation model to [00:06:00] a world gen A simulator? How do you kind of paint that last[00:06:02] Chris Manning: year? Yeah, so I think this is actually a little bit subtle because, people look at these amazing generative AI video models, SAWA VO three, one of these things, and they think Genie, they think, oh, this is amazing.[00:06:17] This is we've solved understanding the world because you can produce these generative AI videos, but. The reality is that although the visuals do look fantastic, those visuals actually are accompanied by an understanding of the 3D world, understanding how objects can move, what the consequences of different actions are, and that's what's really needed for spatial intelligence.[00:06:49] So I mean, a term we sometimes use is that you need action condition, world models. That you only actually have a world model if you can predict, [00:07:00] given some action is taken, what is going to change in the world because of it. And in particular, that becomes hard over longer time scales. So if you're simply, trying to.[00:07:12] Predict the next video frame. That's not so difficult. But what you actually want to do is understand the consequences, likely consequences of actions minutes into the future. And to do that, you actually much more of an abstracted semantic model of the world.[00:07:32] The Bitter Lesson & Data Abstraction[00:07:32] swyx: Yeah, the question comes where you want to have more structure than is available in just predicting the next token.[00:07:41] And typically, well, let's, let's call it the experience of the last five years has been that is just washed away by scale, right? So what is the right middle ground here that, you don't ignore the bitter lesson, but also you. Can be more efficient than what we're doing today.[00:07:57] Chris Manning: One possibility [00:08:00] is, look, if we just collect masses and masses and masses and masses of video data, this problem will be solved.[00:08:11] Under certain assumptions that could be true, but there are sort of multiple avenues in which it could not be true. The first is what's really essential is understanding the, the consequences of actions producing an action conditioned world model. And if you are simply, collecting observational video data, which is the easy stuff to collect, when you're sort of mining online videos, you don't actually.[00:08:41] Know the actions that are being taken to see how the video is changing. And so if you are never collecting directly actions and you are having to try and infer them from what happened in the observed video, that's not impossible. But it's very [00:09:00] hard and it's not really established that you can get that to work at any scale yet.[00:09:05] And so there's a lot of premium on collecting action condition video data, which is part of why there's been a lot of interest in using simulation so that you can be collecting data where you do know the actions, which isn't quite limited supply, but there's also in the limit of as much data as you could possibly have.[00:09:28] Maybe the problem is eventually solvable, but. Even though we collect huge amounts of text data is always at a great level of abstraction, right? Language is a human designed, abstracted representation where there's meaning in each token and it's representing and abstraction of the world, right?[00:09:51] As soon as you are describing someone as a professor, and as soon as you are saying that they're condescending, right? These are very [00:10:00] abstracted descriptions of the world. It's not at what you're observing as pixel level, and to get to that kind of degree of abstraction, starting from pixels is orders and magnitude of extra data and processing.[00:10:14] And so, although, we absolutely want to exploit, get as much data as possible, use the bitter lesson. Nevertheless, if there are ways in which you can work with five orders of magnitude less data than people working purely from pixels, you're gonna be able to make a lot more progress, a lot more quickly.[00:10:34] And that's the bet here. And so you could just say that's only wanting to be able to, do it more efficiently, do it more quickly, do it more cheaply. But I think it's actually more than that, I think. One should be making the analogy to how human beings work at one level. You know? Yes, we have these high [00:11:00] resolution eyes and we can look and see a scene like a video, but all of the evidence from neuroscience and psychology is that most of what comes into people's eyes is never processed.[00:11:13] Right. That you are doing fairly fine ated processing of exactly what you're focusing on. But as soon as it's away from that of yeah, there's another guy over there that you've sort of only processing top down this very abstracted semantic description of the world around you. And so, that's what human beings are doing.[00:11:33] They're working with semantic abstractions and so. I think it is just the right representation. ‘cause we also have other goals we want to be able to do, real time worlds. So that means there's a limit to how much processing you can do and we want to do long-term planning and consistency. And again, that favors abstraction.[00:11:55] I mean, I guess there was actually a recent. Blog posts that [00:12:00] came out from our Friends of physical intelligence and, they were sort of heading in the same direction they were saying Oh, to the pay[00:12:06] swyx: pay model.[00:12:07] Chris Manning: Yeah. Yeah. To maintain a long term memory of what's happening in the world. So we can, do longer term we actually storing text of what is, been happening in the world.[00:12:19] Right. It is not such a successful strategy of trying to keep it all at a pixel level.[00:12:24] Vibhu: And yeah, I mean, you can see it in video models like that Temporal consistency. We're at a scale of train on, all the video data we have. We have it for maybe 30 seconds, a few minutes. That's not the same as a game state played for half an hour.[00:12:37] Right. I thought you guys break it down pretty well. You have a, you have a blog post about. Building multimodal worlds with an agent. I dunno if you guys wanna talk about this. This is one of the things I read, I[00:12:48] swyx: thought, yeah, it's the thing I talked about with the reasoning chain. Yeah.[00:12:51] Vibhu: So there's like different phases to this.[00:12:53] It seems like it's more of an agent, a scaffold, very different approach than just, type in a prompt and you, you don't have the same consistency. [00:13:00] It also, like, for people that are listening, I, I would highly recommend reading it. It breaks down the problem in a different light, right?[00:13:06] So like, what do you need to consider when you're talking about video, like world game models, right? How would, what do you need to consider? What are the factors? What are the elements? What's the state? So I don't know if you guys have stuff to talk about for this one.[00:13:19] Fan-yun Sun: Yeah. Actually, I wanted to add on a little bit Yeah.[00:13:22] On our previous point, which is just like, change topics so quickly. I, I do feel like sometimes people confuse like, oh, like we're taking an an, an method with abstraction. That means they don't believe in bitter lesson. Like that's just false, right? Like we are believed is a bitter lesson. But then I feel like the question that we always discuss is like, what is the right abstraction level today?[00:13:42] The analogy I like to make is like, let's just say we can encode and decode. Represent all of images, videos, audio and bytes. Then the most bitter lesson approached is to train a next byte prediction model as opposed to the next token prediction model where it's just like, okay, it's natively multimodal, can just, but it's like, yeah, like [00:14:00] to, to Chris's point, it's like the scale and computing you need to achieve that.[00:14:03] So that's why we always come back to like, okay, what is the most efficient way to do it? And reasoning models to the point of this blog post is a showcase of like, Hey, we're actually just like reasoning about the world and reasoning about. The aspects of the world that CAGR that matter for me to learn what I want to learn from this role model.[00:14:21] swyx: Yeah, it's like you're improving the en encoder of whatever you're, trying to model. And like a better representation would just represent the important things in less space. Yeah. Which would just be more efficient.[00:14:33] Fan-yun Sun: Yeah.[00:14:34] swyx: So yeah, I, I, I fully agree that it is not, antagonistic to, bitter lesson.[00:14:38] I do wanna wanna mention one more thing. Is there any philosophical differences with the JPA stuff that, Yun is working on? I gotta go there. You, you, you, you're, you're imagining like some latent abstraction. I'm like, okay, fine. Let's, let's talk about it, right? Like it's an elephant in the room.[00:14:52] Chris Manning: Yeah.[00:14:53] JEPA & Philosophical Differences with LeCun[00:14:53] Chris Manning: There are philosophical differences. Jan Lacoon is a dear friend of mine, but. [00:15:00] He has never appreciated the power of language in particular, or symbolic representations in general. Yarn is a very visual thinker. He always wants to claim that he thinks visually and there are no words, symbols, or math in his head.[00:15:21] Maybe that's true of yarn. It's certainly not the way I think. Um. But at any rate, the world according to yarn is the basic stuff of the, the world and of intelligence is visual and language is just. This low bit rate communication mechanism between humans and it doesn't have much other utility and it's far inferior to the high bit rate video, that comes into your eyes.[00:15:53] And I think he's fundamentally missing a number of important things [00:16:00] there. Think of this evolutionary argument looking at animals, right? That the closest analogies, the things with chimps, right? So chimpanzees, have fairly similar brains to human beings. They have great vision systems, they have great memory systems.[00:16:18] They've got, better memory than we do of short term memories. They can plan, they can build primitive tools that, humans. Massively ahead in what we understand about the world, what we can plan, what we can build. And essentially what took off for us was that humans managed to develop language and that gave a symbolic knowledge, representation, and reasoning level, which just, okay if this sort of vaulting of what could be done with the intelligence in brains.[00:16:59] So the [00:17:00] philosopher Dan de refers to language as a cognitive tool and argues that, humans unique among the creatures in the world have managed to build their own cognitive tools and language is the famous first example. But other things like, mathematics and programming languages are also cognitive tools.[00:17:21] They give you an ability to. Think in abstractions, in extended causal reasoning chains. And that allows you to do much more. And we use that for spatial representation and intelligence and planning and gameplay as well. So we believe, and this is, underlying the specific technologies that Moon Lake is making, that symbolic representations are powerful.[00:17:50] And you want to use that in your understanding of the visual world when you want a causal understanding, when you want to maintain long-term [00:18:00] consistency and prediction. And as I understand it, that's just not in ya Koon's worldview. So I think that's the fundamental philosophical difference. Then there's the specific model.[00:18:11] He's been advancing jpa, that's a reasonable. Research bed is a direction as to, to head for building out a model of the visual world. To my mind, it's sort of one reasonable research bed. It's not really established. It's the best one that everyone should be following,[00:18:32] swyx: at least developed at scale, at Meta.[00:18:34] But it's not just vision, right? Like, I mean, JPA is a, just joint admitting prediction can be applied to anything really. And people have done it. The argument is that there is a latent representation or that is probably more. Suited to the task, then why not let machines do it for us instead of predefining it at all?[00:18:50] And isn't something like a JPA shaped thing the right answer? And if not, why not?[00:18:55] Chris Manning: So I think there's a part of jpa that's right, which is [00:19:00] you do want to have a joint. Embedding that gives you a consistent model of the world. And Jan's argument is you can never get that from auto aggressive language models ‘cause they're sort of left to right churning out one token at a time.[00:19:22] I guess this is where we're the research arguments of the field, I'm not actually convinced that's right. ‘cause although the token production is this auto aggressive, process that's heading, left to right, I guess don't have to be left to right. But anyway, in sequence of tokens we could have right to left Arabic.[00:19:40] But although that's true, all of the weights of the model that are internal to the transformer, they are a joint model of the model's understanding of the world. And so I think you can think of the weights of the model as a form of. Joint representation, [00:20:00] and therefore it is plausible to think that could be the basis of a world model, which avoids, ya's objections.[00:20:10] swyx: I think I follow, and obviously that would touch on what Moon Lake eventually ends up doing as well. Right. Like, which it's hard to tell because you put out the end results, but we don't know the inputs that go into it. So it's, it's, that's something that we have to figure out over time.[00:20:25] Vibhu: Yeah. I mean, I guess this kind of breaks down some of the outputs. Do you wanna walk us through it?[00:20:31] Reasoning Traces & Interactive Worlds[00:20:31] Fan-yun Sun: Yeah. So this, this really just walks us through the reasoning traces of like, okay. So that just say, if we wanna build a world in this context, it's really just a game demo that, that shows the, the variety of interactions that this world model can build.[00:20:45] And yeah, it's really just a reasoning traces of like, okay it prompted to create a bowling game. Like how did it achieve what you saw? That level of causality, interaction and consistency, right? So yeah, this is almost just like a, an example of [00:21:00] like a reasoning traces. Very[00:21:01] swyx: detailed.[00:21:01] Fan-yun Sun: Yeah.[00:21:01] Vibhu: Very, very detailed.[00:21:02] You gotta you don't even realize it, right? Like when a video is generated, what happens when a ball strikes a pin, right? So first, like you, there's audio in that, like audio triggers happens, score increments, the world changes. Like pins have to start dropping. There's a timer that goes on. It's just like very similar to how now we're used to reasoning for language models.[00:21:20] There's a whole state of what happens. So geometry, physics, all this stuff. And then yeah, there's kind of that single prompt. So asset, ation all this stuff. It's like a, it's a nice view to see what's going on.[00:21:32] swyx: I think Sun is also too polite to point out that, both like Google's genie, demos as well as world Labs is marble, do not have interactive worlds.[00:21:41] Fan-yun Sun: That's the benefit of having a reasoning model, right? Like, because you can, you can say, oh, like maybe in this particular context, I want to learn how to bowl. And then you can say, okay, then what is it important when it comes to learning how to bowl? Okay, maybe it's like I need to understand the, the basic of like, physics and I want to throw it over [00:22:00] them.[00:22:00] I wanna know that when I, when it resets it's a new game. So I know that yeah, basically, you know to pick up the ball, you know that ball's gonna cause the pins to fall down. You know that what's important to this particular bowling game is to score and you know that the score corresponds to the number of pins that fell down.[00:22:19] So it's just like, if it's a model that sort of knows what it. Looks like, knows what a bowling game looks like, but doesn't actually allows you to practice over and over again and to understand that, oh, like what it takes to actually get a high score. Then it sort of doesn't actually allow you to learn what you set out to learn within the world model.[00:22:38] And I think this is really just one example of showing like the advantages of the approach that we're taking over most the, let's call it the zeitgeist, is today, when people talk about clinical role models,[00:22:51] Chris Manning: right? So it sort of seems like the question to ask when there's a world model is.[00:22:58] Can I not [00:23:00] only just wander around the world and look at the beautiful graphics, can I interact with the objects in the world and see the right consequences of actions?[00:23:11] Vibhu: And you also understand what the consequences would be if you do something right. So it's not just like, okay, there's one thing if I pick it up, something will happen.[00:23:19] But, there's 50 options and I know I can expect, I can infer what would happen if I do any of them. Right. So very different when you can actually see it play around with it.[00:23:28] swyx: There,[00:23:28] Beyond Unity: Cognitive Tools for World Building[00:23:31] swyx: there's two cheeky elements of that. I mean, the, the, the I guess, less ambitious one is, let's really establish for listeners, why is this fundamentally different than writing Unity code, right?[00:23:40] Like just creating a model to translate a prompt into Unity code[00:23:44] Fan-yun Sun: so there is an underlying physics engine. Yeah. In that sense, there's some overlapping things to Unity, but the way we think about it is like physics engine. Tools or code are cognitive tools like borrowing Chris's term, right? Like tools [00:24:00] that the model can employ as means to an end.[00:24:04] So today maybe you say, okay, in this particular context we care about physics, we care about the long-term causality consequences. Then yes, we deploy it, employ physics engine, and then maybe tomorrow we say, okay, we're we're training that. Just say drones where we only care about really fluid dynamics and the visual aspect of the world.[00:24:25] Then, then yeah, maybe we don't actually, the model actually doesn't have to use a physics engine. Or maybe it employs other types of representation or physics engine to achieve the task. So yes, writing code for Unity is sort of similar to a tool that our A model can employ, but our goal is for a model to take a representation conditioned reasoning.[00:24:46] Approach or process.[00:24:47] swyx: Yeah,[00:24:47] Fan-yun Sun: internally.[00:24:48] swyx: Yeah. Using these things as just like general two calls. Right. Which I think is very interesting. The other more ambitious one is, some kind of recursive element where it becomes multiplayer, right? Like here, there's a single player element, you're not [00:25:00] modeling any other people involved.[00:25:01] And that is a whole other thing.[00:25:04] Fan-yun Sun: But in fact, we can really do multiplayers. Oh yeah, okay. I haven't seen any double situations. So just actually just like prompt our, our model to say, Hey, like configure to multiplayer. Then it'll do like this. You'll be able to configure multiplayer[00:25:16] swyx: great[00:25:17] Fan-yun Sun: persistency database for you.[00:25:18] Easy. Yeah.[00:25:19] Vibhu: So what, what are like some of the current limitations in where we're at? So there's one approach of like, okay, scale up video predictors. Obviously there's data issues. With approaches like this, is it data constraints? What are like the next steps? Is it real time? Like, so there's one side of, write an agent to write Unity code, but okay, I want to be streaming a game real time.[00:25:38] I want to have characters being also like agent, but where, where do we kinda see this scaling up? Right?[00:25:44] Fan-yun Sun: Yeah, there's definitely a data constraint. Like the more data, the, the better. This reasoning model can almost basically act as humans to like operate a variety of tools and softwares to build whatever's necessary.[00:25:57] And then there's a sort [00:26:00] of fidelity constraint, which we're actually solving with another model, which we can talk about later. But it's like, it's not as easy to get to photorealism with the approach that we're taking. But we think there are better solutions to that, which is we can dive into later.[00:26:14] Later.[00:26:15] Vibhu: The one one thing you note here is it's a diffusion model, right? So there's, there's a few approaches, diffusion caution, splatting, yeah, so Ry diffusion model, you guys wanna[00:26:25] Fan-yun Sun: Yeah.[00:26:25] Vibhu: Introduce,[00:26:26] Fan-yun Sun: yeah, totally.[00:26:26] Rie: Neural Rendering & Skins for Worlds[00:26:26] Fan-yun Sun: So within our world modeling framework, we think there are two models that we train, right?[00:26:31] Like, there's the multimodal reasoning model that we just talked about that essentially handles. Mainly the, the causality, the persistency and logic determinism of the world. And then RY is our bet on saying, okay, like while all those model, can take care of all these things that we just talked about, it's limitations compared to existing, say, video models, is that it doesn't have as high of a pixel [00:27:00] ality right off the gate, right?[00:27:02] And EE is to say, Hey, we can actually take whatever persistent representation that we generate with our multimodal reasoning model and learn to restyle it into photo photorealistic styles or arbitrary styles you want. So this model is almost to say, Hey, I'm going to respect the persistency and interactivity of the world that you created, but my only job is to make sure that its pixel distribution is close to what we want.[00:27:29] Vibhu: Yeah.[00:27:30] swyx: Great example right there. You kept the KL divergence.[00:27:33] Fan-yun Sun: Oh. Where,[00:27:34] swyx: no, no. I mean this, this is a, a classic like, how you don't stray too far from the source material as you, you kept the kl, which is Oh yeah. Kind of cool. Yeah.[00:27:43] Fan-yun Sun: Yeah.[00:27:44] swyx: I mean, and the[00:27:44] Chris Manning: difference is, and I mean sun was pointing at this, where sort of saying it's in one way a more difficult path, but a better path that, typically the diffusion models are producing the whole scene and it looks lovely, [00:28:00] but there isn't spatial understanding behind it, which is allowing for the real time graphics gameplay, the spatial intelligence, understanding the consequences of worlds where this is, taking a path where it is assuming an abstracted semantic model of the world's state.[00:28:20] And then the diffusion model is then being used on top of that to produce the high quality graphics.[00:28:27] swyx: Is there an intended practical, or business use for this, or is it like a, like a demonstration of capabilities?[00:28:34] Fan-yun Sun: We actually believe that this is gonna be the next paradigm of rendering. So it's gonna replace how ra raizer, it's gonna replace DLSS today because it not only has these pixel prior that's learned from the world such that you can literally play any game in photo realistic styles, which is a lot of people's desire when they do GTA, right?[00:28:51] Like,[00:28:51] Vibhu: all the mods, all the people adding perfect lighting and all this.[00:28:54] swyx: So[00:28:54] Fan-yun Sun: skins[00:28:55] swyx: for worlds, let's call it[00:28:56] Fan-yun Sun: skins, let's call it skin for worlds. I,[00:28:58] Vibhu: it's also like, you can call it skin, you can call it [00:29:00] customization. You can play it how you want, right?[00:29:01] Fan-yun Sun: Yeah, exactly. And I think another thing that we really pointed out specific specifically in this blog is the programmability of it, right?[00:29:09] So what this means is that this render historically render is always a derivative of the game state, right? You're saying, oh, here's the game state, I'm rendering out a frame. But here I'm saying actually this render can be part of the gameplay loop. I can say something along the lines of, if upon getting 10.[00:29:26] Apples, I'm gonna, my weapon of choice, my bullet's gonna turn into apples. And that's, that's possible because we can say, we can basically dynamically have certain game state trigger the, the preconditions to the render such that the rendering is now part of the game loop too. One thing is to just say, okay, it's, it's, it's the appearance.[00:29:47] But the second thing is also to say there's these novel interactions that are possible because this render now has actually priors of the world.[00:29:57] swyx: It is up to the artist to figure out what to do with it.[00:29:59] Fan-yun Sun: It [00:30:00] is up to the creators. Yes.[00:30:01] swyx: Yeah.[00:30:01] Fan-yun Sun: And I also think that's actually another big argument that we're making and the reason that we're picking, taking the bet we're baking is that a lot of the times, whether it's for embody AI gaming, like you want a layer where human can inject their intentions.[00:30:15] So, for example, let's just say in the context of gaming, it's obviously like my creative intent, but maybe in the context of embodied ai, it's like, oh, like I take this foundational policy and I want to actually fine tune it to deploy in my house. So you want to almost say, inject, have a layer where human can say, oh, here's the distribution of things I want to create to achieve my goal.[00:30:35] And I think 3D graphics as it as it is today, is basic, the layer for people to say, Hey, what do I care about in this world? And it allows, basically human intent to be expressed in these worlds much more explicitly and distributionally as opposed to just saying, Hey, I'm gonna generate like, arbitrary.[00:30:54] And it's like just prompts,[00:30:55] swyx: it's one of those things where like, I think you, you're going to build up a series of models, right? [00:31:00] This is just one of, this is probably like the highest utility or heaviest, frequency one, I don't dunno what to call this. Where like you Yeah. You can immediately drop this in on any game and you don't need anything else that.[00:31:10] That you guys do. But, I, I could see, I could see that I think the, the human intent is something that people are not even used to because we're so used to static worlds or, worlds that just don't react, or, I don't know. It's, it, you're kind of blowing my mind right now with like, I'm, I wonder if you've talked to people at GDC Hmm.[00:31:27] And what are they gonna do with it?[00:31:30] Fan-yun Sun: Yeah. Now the stance that we take on this front is like, we're not gonna be more creative than our users to ship[00:31:35] swyx: it out.[00:31:35] Fan-yun Sun: Yeah. But we wanna make sure that we're building things in a way that really allows them to express their intent.[00:31:41] swyx: The thing that you said about, here's the distribution that I want.[00:31:45] I think text may be too low of a bandwidth to. To really demonstrate, because I, I, there, I'm, I'm probably just gonna want to drop in a bunch of, reference assets and then you can figure it out from[00:31:58] Vibhu: there. But you probably wanna do a, a mixture of [00:32:00] both, right? Like you throw in a few images. I wanted this style.[00:32:02] Yeah. I want it to look like this. So it, it's, it's a mixture, right?[00:32:05] Chris Manning: I, I think it's a mixture. I mean, yeah, I mean there's clearly a visual component of this, and it's not that, everything can be text. ‘cause of course you want to give a visual look, but there's also a massive amount of giving the overall picture of the look of the world and the behavior of things that you can express in a few words of text.[00:32:32] And it be very time consuming and difficult to do via visual means. So I think, yeah, you want a combination of both.[00:32:40] Evaluating World Models[00:32:40] Vibhu: So one question I kind of have is, how do we go about evaluating world models? So like, there's many axes, right? One is like, okay. I have preferences. How well do we adhere to prompts? One is the simulation.[00:32:50] One is like do things, is there core logic that's broken? So coming from we know how to evaluate diffusion, there's fidelity, there's [00:33:00] stuff like that. But what are some of the challenges that most people probably aren't thinking about?[00:33:04] Fan-yun Sun: Yeah, I think this is like a great question and probably one of the hardest questions in role models because like, I think it always comes back to what are you building this role model for?[00:33:13] And depending on your end goal and purpose, the evaluation should defer. So in the context of games, then the most direct way of measuring is how much behind are people actually spending in this world that you create? And if your goal is to say, for example, in the context that we just talked about, like, hey, deploying, deploying action in body, a agent, then your, your end.[00:33:33] Metric is then, okay, after training in these worlds that you generate how robust it is to when you actually deploy to the target environment. But then, it's, it's hard to measure these end metrics. So today people have like these proxy metrics that I call that basically try to measure what we really care about, which is the end metrics, but then frankly it's different for every use case.[00:33:57] Yeah,[00:33:57] Vibhu: which seems like quite a challenge, right? Like in [00:34:00] in language models or video models. Image models, your benchmarks are proxies, right? People aren't actually asking instruction, following tool use questions. They're proxies of how well it will do downstream. But for this, so like, should teams, should companies have their own individual benchmarks outside of games?[00:34:16] If you think of stuff like, okay, video production, movies, stuff like that, that also want to use world models. Should, should they sort of internalize like. Their own proxy. Is this something you guys do? Where, where does that connect[00:34:28] Chris Manning: go? Yeah, I think this whole space is extremely difficult as things are emerging now.[00:34:35] And I mean, it's not only for world models, I think it's for everything including text-based models, right? ‘cause in the early days it seemed very easy to have good benchmarks ‘cause we could do things like question answering benchmarks and could you answer the question based on these documents and the various other kinds of, do pieces of logical reasoning or math.[00:34:58] But again, these are sort of. [00:35:00] And there were sort of visual equivalents of things like object recognition, right? For these small component tasks. These days so much of what people are wanting to do also with language models is nothing like that, right? You're wanting to, have an interaction with the language model and get some recommendations about which backpack would be best for you for your trip in Europe next month.[00:35:25] And it's not the same kind of thing, right? And it's not so easy to come up with a benchmark as to does this large language model give you an effective interaction for guiding you in a good way for shopping, right? So, and it's the same problem with these world models. So if we take the game design case, well success is that a game designer can.[00:35:57] Produce what they are [00:36:00] imagining in a reasonable amount of time. And that's really the kind of macro task. That's a very hard thing to turn into a benchmark and I think a lot of this is actually going to turn into people walking, walking with their feet. Right? I mean, I guess that's what's happening, at the large language model level, right?[00:36:23] When people are choosing to use, GPT five or Gemini or clawed, individuals are trying out these different models and deciding, oh, I like the kind of answers that GT five gives me, or no, I feel like I get more accurate detail from Claude, right?[00:36:43] Vibhu: It's a lot of[00:36:43] Chris Manning: vitech, a lot of people just using it.[00:36:45] It's vibe checking. I realize that, but it's actually whether. People feel it's giving them utility in what they want. Right.[00:36:52] Vibhu: And the the interesting thing there is like a lot of people prefer the visual, right? This looks pretty, which is not the objective of what this is [00:37:00] for, right? It's if a, if a game designer is working on something, they care about the game engine, right?[00:37:04] The state, it's, it can look whatever. You can fix that up later. Or you can have a really good game state and you can quickly edit it to 20. 20 different versions, like Keep State,[00:37:14] Chris Manning: right?[00:37:14] Vibhu: So[00:37:14] Chris Manning: that's a really important distinction, for and for speaking to Moon Lake strength, right? So, yeah, great visuals are lovely to look at for a few seconds, but gains are really all about the concept, the game play.[00:37:33] And a lot of the time that doesn't actually even require great visuals. I mean, there are just lots of very successful games which have relatively primitive visuals, and there are other games where people have spent millions producing photo realistic, visuals, and the game sucks, right? So, keeping those two axes apart is really important in thinking about what's important in a [00:38:00] world model for different uses.[00:38:02] swyx: This conversation is reminding me of some game review and fiction discussions I've, had in my sort of non-AI related life. Some, for some people might know Brandon Sanderson, who's a very famous, fiction author, had, is is a big game reviewer. And he, he's a big fan of video games where you change one thing about a normal what you might assume about, about the world.[00:38:22] For example, Baba is you, I don't know if you might have come across that, where like the rules change as you play the game. And also like where, you can do things like reverse time selectively or like change gravity selectively. And I think this is also reminds, reminds me of other kinds of world models that are created by authors.[00:38:38] Where Ted Chang is, is my typical example where he'll take the world that, you know today, but change one thing about it and, but then create a consistent world based on that. Which is long-winded answer of me to, of. For me to say is it's it easy to create alternative roles that don't exist, but you change one thing and then let's, let's run a whole bunch of people through it to see if it works.[00:38:58] Chris Manning: My first dance will [00:39:00] be, that seems a lot easier and more conceivable to do using Techn technology like Moon Lakes than with some of the other world models out there, where the sun can actually make it happen. I'll let him give a second answer.[00:39:15] swyx: If I guess for you, you're constrained by the game engine tool, right?[00:39:18] Like at the end of the day, that's the, that's the thought, partner that you have. If I ask for something where like, if it never is allowed to reverse time or if gravity only ever works one way, then well that's it. But sometimes gravity might change,[00:39:33] Fan-yun Sun: but it's a lot easier to change with code as opposed to a model that is learned primarily on data of.[00:39:42] Real world and virtual worlds that are, I guess, like for example, junior, like there's actually trained on a lot of real world data and a lot of virtual gaming data, and it's hard to say maybe it's easier to say, okay, I wanna change the visuals in like the time period of, of the world. Like, you can't change gravity, for [00:40:00] example.[00:40:00] Vibhu: I feel like you can to light bounds, right? Everything comes down to like, code is a better way to execute it, but the models aren't that diverse and creative, right? You can say, okay, make gravity slower. It can do that, but it's limited to your representation of how you text it out, right? Like they're, they're only gonna do a few iterations, whereas programmatically, if there's a game engine under the hood, you can kind of go wild, right?[00:40:22] So one of the, I dunno, one of the limitations of most models is that they're very overtrained to one style. Right. And extracting diversity is pretty difficult. At least that's something we've seen.[00:40:35] Fan-yun Sun: I mean, are there examples you have in mind where you Existing models? Yeah. Like it would be easier to do that's not using code.[00:40:43] Certain types of creative intent or like transition state transitions,[00:40:47] swyx: Clipping, other models, other wo models are very good at clipping through things. Clipping my, my, my legs clipping through a rock because it's, it's just, it's just bad. [00:41:00] Like, you would have to struggle very hard with your stuff to actually make that happen.[00:41:04] Which I think is maybe a topic that you actually prepared on, Gian Splatting versus, the other stuff.[00:41:09] Vibhu: Yeah. Yeah. It's just for those not super familiar, right? There's a, there's gian splatting, there is diffusion. Like what works, what scales up. I feel like in February when Soro one came out the blog post was literally titled like,[00:41:21] swyx: you bring it up.[00:41:22] You never know.[00:41:23] Vibhu: World, world, video generation models are world simulators. It's super bitter lesson pilled. Yeah, emer, a lot of it is emergence, right? So, not to go through their blog post, basically their whole thing was as you scale up all this consistency, all this stuff just kind of solves, it's a very simple premise, right?[00:41:41] They just scaled up, diffusion, and from there, this is, this is Feb 2024, how much can we, it's already been two years, which is basically five years. How much more in AI time do we need to just scale up or, or do we hit a data cap? But I think we already talked about this a lot, right? Like this is back to the beginning discussion of what's [00:42:00] appropriate for the time.[00:42:01] And that seems like your approach, right?[00:42:03] Fan-yun Sun: Yeah. The point I'm trying to make is that they're very many, many different types of world simulators and like having a world simulator that can produce pixel coherency is very, very useful for games and, marketing and all these things, but it's not as useful as people think when it comes to causal reasoning.[00:42:25] When it comes to embodied ai. Yeah, like it this title is true. We're not saying that it's, it's like, not a great world simulator, but actually in the blog that we, we, we, we wrote, the bet is more so that there are gonna be disproportionately large share of value of real world tasks or, and virtual tasks where high resolution pixel fidelity is not needed.[00:42:47] Yes. Video models have their values.[00:42:50] swyx: Yeah. This is at the absolute limit of my physics understanding, but one example that comes to mind is basically having to solve like ba the equivalent of a three [00:43:00] body problem in a deterministic Well, where the video models, which is approximated good enough. Yeah.[00:43:08] Right. Like there's, there's some point at which your approach kind of runs into like the you now have to simulate the world. Please, thank you very much. And like you're trying to do that, but only to the extent that the game engine lets you and like game engines cannot do some things.[00:43:23] Fan-yun Sun: Yeah, no, I mean, I think the interesting or more technical question here actually is where do you draw the boundary between.[00:43:32] What's handled with, let's say, diffusion prior and what, when? What's handled with symbolic priors?[00:43:38] swyx: Yes.[00:43:38] Fan-yun Sun: Okay.[00:43:38] swyx: Okay.[00:43:39] Fan-yun Sun: Right. Let's go there. Because this, this boundary can actually be fluid. Like I think like maybe what you're trying to get at is like, okay, people are saying pixel prior, everything. But what we're saying is, okay, there's a boundary that we draw where this is where we think provides the most economical value for the domains and things that we care about today.[00:43:59] [00:44:00] And I actually do think, and it's something that we do internally all the time, which is like, okay, given new equations that we learn or new elements of the world and that we, we learn, or maybe some other knowledge that we acquire in the process of developing the models. Should we still be maintaining this line exactly as it is today?[00:44:22] Or should we move it a little bit left or a little bit right? Right. Like sometimes that we realize that, oh, like maybe customers or, or folks like want certain things that are better handled with preop pryor as opposed to, symbolic prior than,[00:44:34] swyx: yeah. Your, your skin thing is a, is a example moving it, right.[00:44:37] Yeah.[00:44:37] Or left. Yeah,[00:44:37] Fan-yun Sun: exactly.[00:44:38] swyx: I dunno what the, the left right is.[00:44:39] Fan-yun Sun: Yeah, yeah, yeah. No the, the model.[00:44:42] swyx: Yes.[00:44:42] Fan-yun Sun: Actually we have a few iterations of them. They're actually at slightly different[00:44:45] swyx: I know boundaries. You should, you should do that. That's a cool dimension to show.[00:44:49] Fan-yun Sun: Yeah.[00:44:50] swyx: Is quantum mechanics the diffusion prior of our world?[00:44:55] Right. It's like that's the boundary of classical mechanics versus quantum. Right? Like, that's it. At one [00:45:00] point God plays dice and the other point doesn't.[00:45:02] Fan-yun Sun: I dunno if Chris, you wanna say it, but I think, I think generally I feel like physics is better with symbol P priors.[00:45:08] Chris Manning: Even quantum physics.[00:45:09] Fan-yun Sun: Even quantum physics.[00:45:11] swyx: Yeah. This is starts against to, MLST territory is, is what I call it, where, he, he likes to get philosophical. We, we we're quite friendly.[00:45:18] Vibhu: I mean, we need to get, we need to get singularity. I heard some of that.[00:45:23] swyx: No, no, I think that is actually really helpful and man, I just want you to productize this like, as a product guy, I'm just like, oh, also[00:45:32] Vibhu: a gamer, I[00:45:33] swyx: wanna, it's like a researcher, like, it's cool.[00:45:35] Like this is a, the theoretical, like you have a very good, I don't know, like the way of thinking about these things, but I just wanna see you like, express it. I do think like your fundamentally things when, when you leave open new tools, like, okay, use, use human intent to incorporate it into how you render.[00:45:52] Artists are gonna have to take like two to three years to figure out what to do with this. And you just don't know.[00:45:57] Chris Manning: Right. But I think, this is, [00:46:00] gives a much more approachable and controllable world for the society, which is the beauty, the beauty of, NLP, that that will enable it to be adopted and used.[00:46:10] And we are very hopeful about that. Yeah,[00:46:13] Fan-yun Sun: yeah. Yeah. I mean, we are, we are very focused actually on commercialization in the sense that like we do, we do really believe in the data flywheel app approach. Yeah. Where, we put this in the hands of the creators and the users and then they will teach us when, what capability our model should improve.[00:46:27] And that's why we are, we are actually, like products and beta[00:46:31] swyx: Yeah. Focusing on gaming. What, what's like the adjacent thing to gaming[00:46:34] Fan-yun Sun: embody adjacent, basically. So maybe we can, we can I'll maybe start with where we see the platform in three years. Yeah. Which is like, okay. The users would tell us what they want to achieve.[00:46:45] The end goal could be, Hey, I just, I wanna make something to teach my kids the value of humility. Or it could be, Hey, I wanna fine tune my, drones to be really good at rescue situations. I could be vacuum robots. I want to like train [00:47:00] my manipulation or like vacuum robot to be very robust to my office, right?[00:47:04] But it's like, whatever it is, scenario robust to[00:47:06] swyx: my office[00:47:07] Fan-yun Sun: or like navigate very robustly in my office. But then it's like, whatever end goal that you want, our role model will say, okay, given what you want to achieve, let me generate a distribution of environments such that I can train and evaluate whatever it is you want.[00:47:24] Yeah. Right. Maybe for the purpose of games, it's just the end simulation and that's the end product for certain policies. It's like I can train it within these environments and then help you see where your policy is failing or not. Yeah. And then, so I think,[00:47:37] swyx: so in that case, much more of a training tool.[00:47:40] Than in other training[00:47:41] Vibhu: evaluation? Both. Right?[00:47:43] swyx: Sure. Same. Same thing.[00:47:43] Fan-yun Sun: Yeah, same thing. I think it's just this role model that allows people to train any policy that can act in any multimodal environments.[00:47:51] swyx: Would it be harder to reward hack? Is there an angle here where it is harder to reward hack? Like it's just, I'll just put it generally because I think that's a, that's obviously a key [00:48:00] problem that a lot of people face when in training agents in these environments, and I don't know, can you solve it?[00:48:07] Chris Manning: I think not necessarily. To the extent that there's a mis specified reward that. It seems like it could be hacked in a more symbolic world or in a more pixel based world. I dunno if Sun's got any thoughts, but I don't think that's really being solved.[00:48:26] swyx: The other thing that comes to mind is just you could just build a better sawa as a video generator model, right?[00:48:31] Because then you, you would move the diffusion, side a bit more further to the right. I think if I got the directionality correct. And that's it.[00:48:40] Vibhu: It's better on domains, right? Like on consistency over now, or for sure it exists versus something doesn't, right.[00:48:46] Chris Manning: So[00:48:46] swyx: yeah. Yeah. Is[00:48:49] Vibhu: is a question more like, like[00:48:51] swyx: I'm just riffing on like, how do you, what can you build, you know?[00:48:54] Oh, with the stuff that you have. I do think that the minor, the academic does go immediately to training [00:49:00] and in eval evaluation, but like art tends to take unusual directions. Like you might end up,[00:49:06] Chris Manning: okay. Yeah. But the question is, can you use this piece of software to develop compelling gameplay and. I don't think you can take SOAR and produce compelling gameplay, right?[00:49:19] If you want to have a world that you can wander around in a bit, you are good. But what are your abilities to have gameplay mechanics implemented the way you'd like them to be and to have things stay, with the long-term history of your gameplay that influences future actions. I think there's just nothing there for that.[00:49:39] swyx: Yeah, I do tend to agree. I, I'm just trying to sort of test the boundaries. I would also make the observation that as AAA games industry has developed the line between what is a movie and what is a game has blurred. And you, you, you do end up basically producing a two hour movie as part of your game.[00:49:57] Fan-yun Sun: No, honestly, there, there's so many actually [00:50:00] applications in adjacent markets that our world model can go into. Yeah. But yeah, it, it's sort of fun to riff, riff on. Although on the execution side, we we, we need to stay focused with like, okay, what are the capabilities we want to unlock over time?[00:50:11] And there's a roadmap for that. But yeah, if we're just riffing on sort of like the possibilities, I feel like, whether it's endless Yeah, it's like classic[00:50:18] swyx: and the embedding for a possibility and endless in my mind, it's very close. Yeah. I do wanna, focus on one, like weird choice. I, I don't know if it's weird.[00:50:28] Maybe I'm, I got something here. Audio, right? You could have just said no audio And audio in my mind has a lot of recursion, whereas in video you can just do recasting and that's much computationally much simpler. Audio just seems way harder. I don't know if you wanna just comment on just the special 3D audio.[00:50:46] Problem. Did you really have to do it? I guess you do to be immersive, but like a lot of people do treat it as like, well, you just stick a, a tt S model on top of[00:50:57] Vibhu: Well, there's a lot more to game audio than [00:51:00] just speech. Right. It's not just[00:51:01] swyx: tts. Yeah. Tts. S Fxt, GM Spatial in my mind Echoes[00:51:06] Chris Manning: Yeah.[00:51:06] swyx: And reflections.[00:51:07] And I, I don't even know what's, what else? I don't know what, what other problems in this space.[00:51:13] Fan-yun Sun: Yeah, I think this point like the, it's sort of a more, more pointing to the benefits of using an game engine as a tool that's available to the model, right? Because like part of the spatial audio is from the code that is underlying the simulation.[00:51:32] And while we do give our model access to other types of audio models as. Tools.[00:51:39] swyx: None of them would be spatial, I think.[00:51:41] Fan-yun Sun: But that's exactly sort of more 0.2. We're giving our model an abstraction or a suite of tools such that it's able to achieve that. And you can argue that sort of spatial is like a, like a emergence out of the, the tools that we and abstraction that we provide to the agents.[00:51:59] And I think that's the beauty of [00:52:00] this, this, this approach is like there's a lot of things kind of like how human's built technology and they're like Lego blocks that build on top of each other. And it's the same thing here. There's gonna be things that sort of just sort of emerges from being able to put these things together in like combinatorially interesting ways,[00:52:14] Chris Manning: right?[00:52:15] So this integrated audio model exploits the understanding and semantics of the Moon Lake world, right? And whereas in general for the Gen AI video models. There's no actual integration across to audio at all, right? That someone might stick some music or stick a soundscape or whatever else on top of their video.[00:52:44] So it's not a silent video, but they're in no way connected into a consistent world model. And there's nothing that's okay. An action is happening in the video. Therefore there should be a sound that's [00:53:00] coming from this part of the visual field.[00:53:03] swyx: Yeah.[00:53:03] Vibhu: Is that different than Sora too? Does it not have audio?[00:53:06] Not to say it's not like[00:53:08] swyx: amazing[00:53:08] Vibhu: isn't a spatial[00:53:09] swyx: audio.[00:53:09] Vibhu: It doesn't,[00:53:10] swyx: no. I've played around it with it enough. It just sounds like someone put an 11 laps voice on top of it and just tried to do the lip sync.[00:53:18] Vibhu: Oh, yeah. I've seen, okay. Generate a dog at the beach and reactions to big wave and move[00:53:23] swyx: around.[00:53:23] It's definitely like, so have the dog, have the dog move away from camera and see if the, the song goes down. It doesn't. ‘Cause they don't have facial audio.[00:53:32] Fan-yun Sun: We do want to basically like we, our moral model, like the one we're training is basically towards the goal of having a combined latent representation across all these different modalities.[00:53:42] Right? Such that it can like reason across these different modalities. So for example, if I close my eyes and like you play a video, you play a sound of like a car skidding away from me. I almost can like, visually extrapolate that trajectory in my mind. And I think that type of capability, we want our model to be able to reason, right?[00:53:59] And that's the reason that [00:54:00] we're sort of taking this multimodal reasoning approach. It's like we want this combine late in space that can[00:54:05] swyx: Yeah. Oh, you said late in space. We like that. Here we have to play the, the bell Every time that someone says late in space, no, you gotta train daredevil one. Where you, you, you, it's only audio, but you have to work out.[00:54:15] Where everything is.[00:54:19] Cool. I I think that that was, that was about it for our Moon Lake coverage. I do think that we have like a couple of, Chris Madden questions on, on IR and, just any, any other sort of attention topics or n NLP topics.[00:54:31] Vibhu: Okay.[00:54:31] swyx: Go ahead.[00:54:32] Chris Manning's Journey: From NLP to World Models[00:54:32] Vibhu: Well, no, I mean, yeah, it's just fun. We talked a bit about how you guys met, but you basically, you, you were like the godfather of NLP per se, right?[00:54:39] You spent the whole career from early embeddings, early early attention. You did 2015 attention for machine translation, everything. You, you had information retrieval, so RAG before rag, we just wanna shout that out and admire a lot of that. Right? So what prompted the switch over to world models?[00:54:56] How, how'd all that come about?[00:54:58] Chris Manning: To some answer it [00:55:00] is, the enthusiasms and creativity of students, but there's a bit of a history there, right? So, yeah. So clearly most of my career has been doing stuff with language and how I got into research was thinking, ah, this is just so amazing how humans can produce speech and understand each other in real time.[00:55:21] And somehow they managed to learn languages from their kids. How could this possibly happen? And so, yeah, starting off I was very focused on language, but as it sort of got into the 2000 and tens, I started, going, I'd been working on question answering, and then I started to get, interest in visual question answering.[00:55:42] And that was an area where it was very noticeable. That the visual understanding was bad. Right. These were the days when like, it sort of seemed like there's almost no visual [00:56:00] understanding. You were just getting answers that came from priors. So, if you asked how many people are sitting at the table, it'd always answer two regardless of how many, how many people you could see in the picture.[00:56:11] And so it seemed like, oh, these models actually aren't able to get semantic information outta

The Serving Spoon is a well-loved soul-food restaurant in Inglewood, Los Angeles, known for its warm, family atmosphere and hearty Southern comfort dishes. With a cozy, diner-style setting and a menu. The James Beard Foundation Awards named Los Angeles’s longstanding Inglewood restaurant, the Serving Spoon, as one of the recipients for its 2026 America’s Classics award. See omnystudio.com/listener for privacy information.

The Fork Report Hour 3 (03/14) - Jessica Bane and Justin Johnson from The Serving Spoon return to The Fork Report! The Serving Spoon is a well-loved soul-food restaurant in Inglewood, Los Angeles, known for its warm, family atmosphere and hearty Southern comfort dishes. With a cozy, diner-style setting and a menu. In 2020, during financial hardship, the restaurant rallied local support — including a donation from the LA Rams — to stay open, underscoring how much it means to residents. The James Beard Foundation Awards named Los Angeles’s longstanding Inglewood restaurant, the Serving Spoon, as one of the recipients for its 2026 America’s Classics award.See omnystudio.com/listener for privacy information.

Illini Inquirer's Jeremy Werner discusses the latest happenings with Illinois football, including a commitment from 4-star Evanston DB Justin Johnson. Werner also discusses and plays what he heard from three new Illini assistant coaches (Roger Cooper, Ronnie Bradford and Tyrone Wheatley) and transfer offensive linemen Jake Renfro and Christian Martin. Werner then answers your Illini football questions to close out the show. To learn more about listener data and our privacy practices visit: https://www.audacyinc.com/privacy-policy Learn more about your ad choices. Visit https://podcastchoices.com/adchoices

Brad Sturdy from Illini Guys breaks down Illinois Fighting Illini men's basketball's dominant win over the Oregon Ducks and what it means moving forward. He also discusses Illinois football landing cornerback Justin Johnson and the impact he could make on the program. We hit the latest Illini Headlines from around campus. Plus, we reflect on the life and legacy of legendary coach Lou Holtz following news of his passing.

Bobswinkles, it's a fizz whizzer! Yes, you heard that right, the time has come for us to climb into a giant bag and be transported to Giant Country, where we'll sample the finest snozzcumbers and frobscottle (though you'll forgive us if there's a whizzpopper or two). We're joined by the BFI Southbank's Head of Cinema Programme, Justin Johnson, for this wide-ranging discussion of Steven Spielberg's 2016 adaptation of Roald Dahl's THE BFG. It's an episode as giant as Fleshlumpeater but far less mean, taking in everything from the film's long gestation to its struggle to make an impact, from the mo-cap performances and CGI compositing to the wide array of accents (some more explicable than others). Whoopsie scrumpers!Follow the podcast on Twitter (@RamblinAmblin), Instagram (@ramblinamblinpod) and Blusky (@ramblinamblin.bsky.social). Be sure to like and subscribe so you don't miss an episode! Get in touch with us either via our socials or email rambinaboutamblin@gmail.com. Please feel free to give us a 5-star review, share your favourite Amblin movies and tell us if ET makes you cry.Ramblin is created and produced by Andrew Gaudion and Joshua Glenn. A special thanks as always to Emily Tatham for the artwork, and Robert J. Hunter & Greg Sheffield for the theme music. 

SELECCIÓN 04 2026 BLUES SYNDICATE 1- DOWN TO JOY – VAN MORRISON 2- MOON – ZIST 3- RESURGAM – FINK 4- PENETIESO BLUES – DON VILANOVA BOTAFOGO & PAPPO 5- HELPIND HAND – ROBERT FINLEY 6- VOODOO CHARM – CHRISTONE KINGFISH INGRAM 7- SPITAL U SV. JAKUBA – JAN SPALENY 8- GET BACK TRAIN – REED TURCHI 9- TOTAL DESTRUCTION TO YOUR MIND – MARCON MUSIC REVUE 10- LAST MAN STANDING – BUDDY GUY & SWITCHFOOT 11- KCNICK KNACKS ALL DAY – JIMMY DUCK HOLMES 12- BYE BYE BLUES – LARRY MCCRAY 13- GRAYER SHADE OF BLUE – JOANNE SHAW TAYLOR 14- RIVER – EVAN NICOLE BELL 15- I PUT A SPEELL ON YOU – JUSTIN JOHNSON

Get ready for a lively discussion as JSS explore the unique and often hilarious side of contemporary dating. We'll take you on a journey that includes dating app settings, personal preferences, and the intriguing idea of using Facebook Marketplace as a tool for meeting potential partners. Witness as Program Director, Justin Johnson, navigates the local dating scene in Baltimore, sharing candid thoughts on his current experiences, and learn about the clever strategies he's employing to find that special someone amidst life's unpredictable circumstances.

In this chilling episode, we unravel a haunting story that began with a simple tale from our boss, Justin Johnson. As listeners, we become drawn into the unfolding drama of accidental immolation, an unfortunate tale of arson gone wrong. Listen as our guest recounts a petrifying night that will leave you questioning right versus wrong and the fine line between spectator and savior.

At the 2025 San Antonio Breast Cancer Symposium, Justin Johnson, PhD, presented a poster detailing the final results from three groups of people in a phase I trial on a vaccine to prevent triple-negative breast cancer. Listen to the episode to hear Dr. Johnson explain: why the vaccine targets the alpha-lactalbumin protein the safety and dose results of the study what's next for the research

Blues From The Ouse #305 brings fresh releases, a tribute to Steve Cropper, a “Heartbreaker” trilogy, and listener requests from Johnny Winter to Eric Clapton. Plus gig round‑ups, quirky trivia, and rootsy closers from Left Lane Cruiser, Dusk Brothers, Mudlow, and Justin Johnson.This episode takes you on a two‑hour journey through the heart of the blues — from brand new releases to timeless tributes and listener‑powered requests.Hour OneFresh tracks from Nine Below Zero, Billy Branch & The Sons of Blues, KB Bailey, and Hubert Dorigatti with Greg Zlap.A special tribute to Steve Cropper, the quiet architect of Memphis soul guitar, featuring Sam & Dave, Wilson Pickett, The Blues Brothers, and his 2024 collaboration with Brian May.A “Heartbreaker” trilogy spanning Led Zeppelin, B.B. King, and Samantha Fish.Closing with the iconic Booker T. & The MG's “Green Onions.”Hour TwoListener requests including Johnny Winter, Mick Jagger & The Red Devils, Tommy Castro, Buddy Guy & Junior Wells, Eric Clapton, and more.Gig round‑ups across Yorkshire and beyond.Roots and swamp blues to finish: Left Lane Cruiser, Dusk Brothers, Mudlow, and Justin Johnson on his three‑string shovel guitar.Expect riffs, stories, trivia, and community spirit — celebrating legacy while spotlighting today's blues scene.Playlist:Nine Below Zero - Everyday I Have The Blues - 00:01:45Billy Branch & The Sons Of Blues - Call Your Bluff - 00:06:34KB Bailey - Don't Let The Rain Fall On My Face - 00:10:43Hubert Dorigatti & Greg Zlap - The Ocean - 00:16:22Sam & Dave - Hold On, I'm Comin - 00:20:46Wilson Pickett - 634-5789 - 00:25:48The Blues Brothers - Sweet Home Chicago - 00:28:57The Blues Brothers Band - Boogie Thing - 00:33:50Steve Cropper ft Brian May - Too Much Stress - 00:37:28Led Zeppelin - Heartbreaker - 00:40:51B.B. King - Heartbreaker - 00:44:23Samantha Fish - Heartbreaker - 00:46:46Booker T & The MG's - Green Onions - 00:52:15Johnny Winter - Highway 61 Revisted - 00:55:36Mick Jagger and the Red Devils - Checkin Up On My Baby - 01:03:32Tommy Castro - This Soul Is Mine - 01:06:48My Baby - Sunroof Diesel Blues - 01:12:32Buddy Guy & Junior Wells - Boogie Chillen - 01:16:25Mark Howson - Elizia - 01:23:10Tommy Castro and the Pain Killers - Keep On Smiling - 01:26:47Eric Clapton - No Alibis - 01:31:43Left Lane Cruiser - Juice To Get Loose - 01:36:19Dusk Brothers - I Go It Alone - 01:38:25Mudlow - Sally Ruby - 01:41:38Justin Johnson - Crankin' It Up - 01:45:37Keywords:Blues From The Ouse, York Blues, Steve Cropper, Nine Below Zero, Billy Branch, Samantha Fish, Booker T & The MG's, Johnny Winter, Tommy Castro, Buddy Guy, Eric Clapton, Dusk Brothers Hosted on Acast. See acast.com/privacy for more information.

Fei-Fei Li is a Stanford professor, co-director of Stanford Institute for Human-Centered Artificial Intelligence, and co-founder of World Labs. She created ImageNet, the dataset that sparked the deep learning revolution. Justin Johnson is her former PhD student, ex-professor at Michigan, ex-Meta researcher, and now co-founder of World Labs.Together, they just launched Marble—the first model that generates explorable 3D worlds from text or images.In this episode Fei-Fei and Justin explore why spatial intelligence is fundamentally different from language, what's missing from current world models (hint: physics), and the architectural insight that transformers are actually set models, not sequence models. Resources:Follow Fei-Fei on X: https://x.com/drfeifeiFollow Justin on X: https://x.com/jcjohnssFollow Shawn on X: https://x.com/swyxFollow Alessio on X: https://x.com/fanahova Stay Updated:If you enjoyed this episode, please be sure to like, subscribe, and share with your friends.Follow a16z on X: https://x.com/a16zFollow a16z on LinkedIn:https://www.linkedin.com/company/a16zFollow the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXFollow the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details, please see http://a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Fei-Fei Li and Justin Johnson are cofounders of World Labs, who have recently launched Marble (https://marble.worldlabs.ai/), a new kind of generative “world model” that can create editable 3D environments from text, images, and other spatial inputs. Marble lets creators generate persistent 3D worlds, precisely control cameras, and interactively edit scenes, making it a powerful tool for games, film, VR, robotics simulation, and more. In this episode, Fei-Fei and Justin share how their journey from ImageNet and Stanford research led to World Labs, why spatial intelligence is the next frontier after LLMs, and how world models could change how machines see, understand, and build in 3D.We discuss:* The massive compute scaling from AlexNet to today and why world models and spatial data are the most compelling way to “soak up” modern GPU clusters compared to language alone.* What Marble actually is: a generative model of 3D worlds that turns text and images into editable scenes using Gaussian splats, supports precise camera control and recording, and runs interactively on phones, laptops, and VR headsets.* Fei-fei's essay:on spatial intelligence as a distinct form of intelligence from language: from picking up a mug to inferring the 3D structure of DNA, and why language is a lossy, low-bandwidth channel for describing the rich 3D/4D world we live in.* Whether current models “understand” physics or just fit patterns: the gap between predicting orbits and discovering F=ma, and how attaching physical properties to splats and distilling physics engines into neural networks could lead to genuine causal reasoning.* The changing role of academia in AI, why Fei-Fei worries more about under-resourced universities than “open vs closed,” and how initiatives like national AI compute clouds and open benchmarks can rebalance the ecosystem.* Why transformers are fundamentally set models, not sequence models, and how that perspective opens up new architectures for world models, especially as hardware shifts from single GPUs to massive distributed clusters.* Real use cases for Marble today: previsualization and VFX, game environments, virtual production, interior and architectural design (including kitchen remodels), and generating synthetic simulation worlds for training embodied agents and robots.* How spatial intelligence and language intelligence will work together in multimodal systems, and why the goal isn't to throw away LLMs but to complement them with rich, embodied models of the world.* Fei-Fei and Justin's long-term vision for spatial intelligence: from creative tools for artists and game devs to broader applications in science, medicine, and real-world decision-making.—Fei-Fei Li* X: https://x.com/drfeifei* LinkedIn: https://www.linkedin.com/in/fei-fei-li-4541247Justin Johnson* X: https://x.com/jcjohnss* LinkedIn: https://www.linkedin.com/in/justin-johnson-41b43664Where to find Latent Space* X: https://x.com/latentspacepodFull Video EpisodeTimestamps00:00:00 Introduction and the Fei-Fei Li & Justin Johnson Partnership00:02:00 From ImageNet to World Models: The Evolution of Computer Vision00:12:42 Dense Captioning and Early Vision-Language Work00:19:57 Spatial Intelligence: Beyond Language Models00:28:46 Introducing Marble: World Labs' First Spatial Intelligence Model00:33:21 Gaussian Splats and the Technical Architecture of Marble00:22:10 Physics, Dynamics, and the Future of World Models00:41:09 Multimodality and the Interplay of Language and Space00:37:37 Use Cases: From Creative Industries to Robotics and Embodied AI00:56:58 Hiring, Research Directions, and the Future of World Labs Get full access to Latent.Space at www.latent.space/subscribe

Fei-Fei Li and Justin Johnson are cofounders of World Labs, who have recently launched Marble (https://marble.worldlabs.ai/), a new kind of generative “world model” that can create editable 3D environments from text, images, and other spatial inputs. Marble lets creators generate persistent 3D worlds, precisely control cameras, and interactively edit scenes, making it a powerful tool for games, film, VR, robotics simulation, and more. In this episode, Fei-Fei and Justin share how their journey from ImageNet and Stanford research led to World Labs, why spatial intelligence is the next frontier after LLMs, and how world models could change how machines see, understand, and build in 3D. We discuss: The massive compute scaling from AlexNet to today and why world models and spatial data are the most compelling way to “soak up” modern GPU clusters compared to language alone. What Marble actually is: a generative model of 3D worlds that turns text and images into editable scenes using Gaussian splats, supports precise camera control and recording, and runs interactively on phones, laptops, and VR headsets. Fei-fei's essay (https://drfeifei.substack.com/p/from-words-to-worlds-spatial-intelligence) on spatial intelligence as a distinct form of intelligence from language: from picking up a mug to inferring the 3D structure of DNA, and why language is a lossy, low-bandwidth channel for describing the rich 3D/4D world we live in. Whether current models “understand” physics or just fit patterns: the gap between predicting orbits and discovering F=ma, and how attaching physical properties to splats and distilling physics engines into neural networks could lead to genuine causal reasoning. The changing role of academia in AI, why Fei-Fei worries more about under-resourced universities than “open vs closed,” and how initiatives like national AI compute clouds and open benchmarks can rebalance the ecosystem. Why transformers are fundamentally set models, not sequence models, and how that perspective opens up new architectures for world models, especially as hardware shifts from single GPUs to massive distributed clusters. Real use cases for Marble today: previsualization and VFX, game environments, virtual production, interior and architectural design (including kitchen remodels), and generating synthetic simulation worlds for training embodied agents and robots. How spatial intelligence and language intelligence will work together in multimodal systems, and why the goal isn't to throw away LLMs but to complement them with rich, embodied models of the world. Fei-Fei and Justin's long-term vision for spatial intelligence: from creative tools for artists and game devs to broader applications in science, medicine, and real-world decision-making. — Fei-Fei Li X: https://x.com/drfeifei LinkedIn: https://www.linkedin.com/in/fei-fei-li-4541247 Justin Johnson X: https://x.com/jcjohnss LinkedIn: https://www.linkedin.com/in/justin-johnson-41b43664 Where to find Latent Space X: https://x.com/latentspacepod Substack: https://www.latent.space/ Chapters 00:00:00 Introduction and the Fei-Fei Li & Justin Johnson Partnership 00:02:00 From ImageNet to World Models: The Evolution of Computer Vision 00:12:42 Dense Captioning and Early Vision-Language Work 00:19:57 Spatial Intelligence: Beyond Language Models 00:28:46 Introducing Marble: World Labs' First Spatial Intelligence Model 00:33:21 Gaussian Splats and the Technical Architecture of Marble 00:22:10 Physics, Dynamics, and the Future of World Models 00:41:09 Multimodality and the Interplay of Language and Space 00:37:37 Use Cases: From Creative Industries to Robotics and Embodied AI 00:56:58 Hiring, Research Directions, and the Future of World Labs

The Serving Spoon is a well-loved soul-food restaurant in Inglewood, Los Angeles, known for its warm, family atmosphere and hearty Southern comfort dishes. With a cozy, diner-style setting and a menu featuring classics like chicken and waffles, grits, and catfish, it’s become a community favorite where locals gather for generous portions, friendly service, and a welcoming vibe. This is their third annual Thanksgiving breakfast where they feed the cooks. Take a listen to what you can expect. See omnystudio.com/listener for privacy information.

Fei-Fei Li and Justin Johnson are pioneers in AI. While the world has only recently witnessed a surge in consumer AI, they have long been laying the groundwork for the innovations transforming industries today.With the recent launch of Marble, the first product from their company World Labs, we are revisiting this conversation to explore the ideas that started it all. World Labs is focused on spatial intelligence, building Large World Models that can perceive, generate, and interact with the 3D world. Marble brings that vision to life, allowing anyone, from individual creators to major platforms, to generate 3D scenes directly from text or image prompts and turn complex 3D creation into a simple, creative process.In this episode, a16z general partner Martin Casado talks with Fei-Fei and Justin about the journey from early AI winters to the rise of deep learning and multimodal AI. From foundational breakthroughs like ImageNet to the cutting-edge realm of spatial intelligence, they discuss the evolution of the field and what is next for innovation at World Labs. Timecode:0:00 – The Next Decade of AI2:45 – Origins: Backgrounds of the Founders6:50 – The Rise of Deep Learning & ImageNet8:00 – Algorithmic Unlocks: Compute, Data, and Supervised Learning12:00 – From Predictive to Generative AI16:20 – The Journey to Spatial Intelligence18:35 – Defining Spatial Intelligence21:15 – 3D Data, Computer Vision, and Breakthroughs23:15 – Reconstruction vs. Generation in Computer Vision24:45 – Spatial Intelligence vs. Language Models29:00 – Applications: Virtual, Augmented, and Physical Worlds39:55 – Building World Labs: Team and Vision41:55 – The North Star: Measuring Success in Spatial Intelligence Resources:Learn more about World Labs: https://www.worldlabs.aiLearn more about Marble: https://Marble.WorldLabs.aiFind Fei-Fei on Twitter: https://x.com/drfeifeiFind Justin on Twitter: https://x.com/jcjohnssFind Martin on Twitter: https://x.com/martin_casado Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

This conversation explores the intersection of financial planning, family wealth, and Christian values. Justin Johnson of Dominion Wealth Strategists joins us to discuss the importance of understanding financial goals, the role of shared values in financial guidance, and the need for financial literacy within the church, while emphasizing the complexities of financial decisions, the significance of stewardship, and the call for Christians to engage with cultural issues responsibly.Subscribe on ⁠⁠⁠⁠⁠⁠iTunes⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Overcast⁠⁠⁠⁠⁠⁠, and ⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠.Follow us on ⁠Facebook⁠, ⁠Instagram⁠, ⁠TikTok⁠, and ⁠X⁠.Join the discussion at the Westminster Effects Green Room.Buy your guitar effects at ⁠⁠⁠⁠⁠⁠westminstereffects.com⁠⁠⁠⁠⁠⁠.

MATA is offering “free: transportation on all its bus routes. City Hall did not say who is paying for the “free service.” Mayor Young says removing fares is a way to open the doors for more Memphians to get jobs and access to healthcare and education. What say you, Memphis? Listen LIVE Weekdays 7AM Central on the KWAM app, or Mighty990.com See omnystudio.com/listener for privacy information.

Discover how AI-powered sales automation is transforming the distribution industry! In this episode, Justin Johnson, founder of Motivate, shares how distributors can free up 50%+ of their inside sales teams' time through intelligent order and quote automation.Watch to understand more about AI-assisted orders, multi-channel ordering via text, e-commerce drag-and-drop technology that actually works for distributors, sales intelligence that predicts customer needs before they call, why traditional e-commerce fails for B2B distributors, and more.Justin brings 25 years of distribution technology experience and shares insights from building his fourth company. Learn why AI isn't just a competitive advantage anymore—it's a necessity for wholesale distributors, plumbing suppliers, electrical distributors, HVAC companies, and building material suppliers.

Thinking about remodeling your home? Before you grab a hammer, find out which projects actually boost your home's value and which ones could drain your budget. In this week's episode, we explore where to splurge, where to save, and how to plan a remodel that works for your lifestyle and your bottom line. You'll also hear how to preserve historic character while adding modern updates, tips for finding a reliable contractor, and whether two-toned kitchen cabinets are in or out. Guests include Joshua McGrath, broker-owner of Better Homes and Garden Real Estate; Adam Pretorius, luxury real estate agent; Stacie Staub, co-founder and CEO at West + Main; and Justin Johnson, owner of The House Master.

May 2025 Dante's New SouthAlice Hong: Named one of CBC's 2018 “30 Hot Classical Musicians Under 30,” Alice is active globally as a violinist and a composer. She performs frequently with the Atlanta Symphony, Toronto Symphony, Naples Philharmonic, and more, and next weekend you can hear a premiere of Alice's orchestral work Eden performed by the Atlanta Symphony Youth Orchestra! Alice is passionate about revolutionizing the classical experience and making classical music more accessible and innovative. Classical Remix Music Festival is her biggest project yet, and she'd really love to see you at this inaugural season's concerts!Fun fact: During COVID, Alice lived in a film bubble for five weeks with Dwayne “The Rock” Johnson, Gal Gadot, and Ryan Reynolds to film a scene in the Netflix movie Red Notice. Check it out - the movie remains in Netflix's Top 10 of All Time Movies list (although Alice isn't a huge fan of the movie herself).www.aliceyhong.comwww.experienceluxardo.com/buy-tickets/p/classical-remix-gala-concertKit Cummings launched the Power of Peace Project (POPP) in 2010 with a bold mission: to bring hope, healing, and transformation to some of the most dangerous and divided spaces in the world. With deep experience resolving conflict behind prison walls and in at-risk communities, Kit has become a powerful voice for nonviolence, second chances, and real change.On MLK Day 2020, the NAACP honored Kit with the Martin Luther King Jr. “Living the Dream” Award for his civil rights work, prison reform efforts, and impact on underserved youth. In 2021, he was appointed to the Georgia House of Representatives Study Committee on Youth Gangs and Violence Prevention, playing a pivotal role in the passage of HB750, a groundbreaking anti-gang bill.From juvenile prisons to war-torn neighborhoods, Kit has taken POPP across the globe—from Tijuana's La Mesa Prison to South African townships, from U.S. high schools to Eastern European rehab centers, and from urban courts to rural churches. His tools of change? Hope, humility, courage, and compassion.www.kitcummings.comwww.powerofpeaceproject.comDenton Loving lives on a farm near the historic Cumberland Gap, where Tennessee,Kentucky, and Virginia come together. He is the author of three poetry books including Tamp which was a finalist for the Weatherford Award and recipient of the inaugural Tennessee Book Award for Poetry. He is a co-founder and editor at EastOver Press and its literary journal Cutleaf. His fiction, poetry, essays and reviews have appeared in numerous publications including The Kenyon Review, Tupelo Quarterly, Iron Horse Literary Review and Ecotone. And he's a core staff member at Table Rock Writers Workshop. He has a new book of poems coming out in August from Mercer University Press. It's called Feller.www.dentonloving.comAdditional Music Provided by: Justin Johnson: www.justinjohnsonlive.comOur Advertisers:Lucid House Press: www.lucidhousepublishing.comWhispers of the Flight: www.amazon.com/Whispers-Flight-Voyage-Cosmic-Unity-ebook/dp/B0DB3TLY43The Crown: www.thecrownbrasstown.comBright Hill Press: www.brighthillpress.orgWe Deeply Appreciate:UCLA Extension Writing Program: www.uclaextension.eduMercer University Press: www.mupress.orgAlain Johannes for the original score in this show: www.alainjohannes.comThe host, Clifford Brooks', The Draw of Broken Eyes & Whirling Metaphysics, Athena Departs, and Old Gods are available everywhere books are sold. Find them all here: www.cliffbrooks.com/how-to-orderCheck out his Teachable courses, The Working Writer and Adulting with Autism, here: brooks-sessions.teachable.com

#271 GTM Engineering | In this episode, Dave is joined by John Short, CEO of Compound Growth Marketing, along with Cammy Keiler, Justin Johnson, and Dan Guenet. Together, they break down the rise of GTM engineering, what it is, how it differs from RevOps, and why B2B teams are investing in it.Dave and the crew cover:The core difference between RevOps and GTM engineering (and why the latter is more focused on building than just integrating)Real GTM engineering use cases, from AI-powered sales tools to mid-funnel campaigns that go way beyond ebooksHow GTM engineers are driving higher revenue per employee and why this role should be one of your first five marketing hiresWhether you're hiring or just GTM-curious, you'll leave this episode with a clear definition of the role, real-world examples, and tactical ways GTM engineers drive impact.Timestamps(00:00) - – Intro (03:33) - – Why this topic resonated with 1,200+ registrants (05:48) - – What even is **GTM engineering? (08:03) - – GTM engineering vs. RevOps vs. Marketing Ops (11:18) - – How AI is driving this role forward (14:28) - – Real examples: ABM campaigns, mid-funnel tools, sales call analysis (19:38) - – Tools GTM engineers are using today (Clay, Unify, GPTs) (23:03) - – Role of GTM engineering in revenue per employee (27:18) - – How GTM engineers enable sales + reduce headcount (31:33) - – What Dan actually does all day as a GTM engineer (36:23) - – Custom GPTs for sales and marketing teams (39:38) - – What MCP servers are (and why they matter) (44:08) - – Claude, Gamma, and AI-powered content systems (46:53) - – Why this isn't just PLG (or ABM, or RevOps) (50:43) - – When to hire a GTM engineer (53:23) - – Big feelings about the role (and why they exist) (55:33) - – Closing thoughts + what to take away Send guest pitches and ideas to hi@exitfive.comJoin the Exit Five Newsletter here: https://www.exitfive.com/newsletterCheck out the Exit Five job board: https://jobs.exitfive.com/Become an Exit Five member: https://community.exitfive.com/checkout/exit-five-membership***Today's episode is brought to you by Walnut.Why are we pouring all this effort into marketing just to push buyers to a “request a demo” or “contact sales” button?Come on, today's buyers don't want to talk to sales right away. They want to explore your product themselves, see how it works, and understand its value before booking a meeting.That's where Walnut comes in.Walnut empowers marketers and GTM teams to create interactive, self-guided product experiences in minutes. Embed these experiences on your site, in emails, or anywhere in your funnel to let buyers engage on their terms, from awareness to close and beyond. That's the beauty of Walnut - you're getting a platform that your sales and CS colleagues can use to showcase the product too.And the best part? You get real intent data—see which features prospects love, where they drop off, and what's actually driving pipeline. Demo Qualified Leads are the new MQL.Over 500 companies, like Adobe and NetApp, use Walnut to drive 2-3x higher website conversion rates and 7 figures in pipeline on a yearly basis. So do you want to drive more leads, shorten sales cycles, and actually show your product instead of hiding it behind another typical B2B CTA? Go check out Walnut.io. And if you tell them Dave from Exit 5 sent you, they'll build out your first demo for free!

Thanks to our Partners, NAPA TRACS, and Today's Class This episode features Brakes for Breasts co-founders Leigh Anne Best and Laura Frank, along with Cleveland Clinic researcher Dr. Justin Johnson, as they celebrate the automotive industry's role in raising over $2 million for breast cancer vaccine research. They share the initiative's grassroots beginnings, its 100% donation to research model, and provide an update on the vaccine's progress, highlighting the completion of Phase One trials and the upcoming launch of Phase Two. A key highlight of the campaign: During October, independent auto repair shops across the U.S. offer free brake pads to customers. For every brake service performed, the customer receives their brake pads at no cost and only pays for labor and other parts. In turn, each participating shop donates 10% of the brake service total to the Cleveland Clinic Breast Cancer Vaccine Research Fund. The episode also shares the inspiring story of Jennifer Davis, the first vaccine recipient, and encourages more shops to get involved in this unique, community driven fundraising effort that's helping fuel groundbreaking research. Show Notes: Watch Full Video Episode The First Breast Cancer Vaccine Trial Recipient: Jennifer Davis [CC 111]: https://remarkableresults.biz/remarkable-results-radio-podcast/cc111/ Introduction (00:00:00) Celebrating the $2 Million Milestone (00:03:08) Origin Story of Breaks for Breasts (00:03:46) Connection to Cleveland Clinic and Dr. Tuohy (00:06:01) Personal Motivations for Founding (00:06:55) Industry Call to Action and Broader Impact (00:07:31) Expanding Research Beyond Breast Cancer (00:10:09) Clinical Trials Overview: Phase One (00:12:14) Clinical Trials: Phase Two and Three Plans (00:14:08) How Research Funding Works at Cleveland Clinic (00:19:42) 2024 Check Presentation and Fundraising Impact (00:21:03) Jennifer Davis: The First Clinical Trial Patient (00:23:38) Hope and Realistic Expectations...

Justin Johnson Cortez, known for his roles in The CW's Walker and Walker: Independence, returned to the screen earlier this year in Netflix's Western drama Ransom Canyon. In the latest episode of Actors With Issues, Cortez opens up about navigating life as a working actor and devoted father. From his early days in modeling to writing scripts inspired by family, Cortez shares how authenticity, vulnerability, and adaptability have shaped his life both on and off screen.Thanks for watching! If you enjoyed the episode, please subscribe to the channel, give us a thumbs up and leave a comment!

On this episode of the Kaya Cast Podcast, Tommy Truong sits down with Justin Johnson, founder of BudsFeed and Managing Partner at Dyspensr, to explore the evolving cannabis accessories market and how dispensaries can leverage it for growth. Justin shares the origin story of BudsFeed—a user-generated platform designed to connect the tight-knit cannabis community—and reveals how it led to the launch of Dispenser, a game-changing wholesale and consignment service that offers dispensaries a turnkey “head shop in a box” with thousands of SKUs, dropshipping, and seamless POS integration.Discover actionable strategies for dispensaries to increase accessory sales from the typical 1.5% of revenue up to 5% or more, with smart stocking tips like prioritizing vape batteries and basic essentials that keep customers coming back. Justin also dives into the challenges and future of the cannabis industry, including thoughts on federal legalization, market regulation, and how dispensaries can survive and thrive amid shifting landscapes.Whether you're launching a new store, looking to expand your product mix, or aiming to boost profit margins, this candid conversation is packed with insider insights and practical advice to help you scale your cannabis business. Plus, don't miss details on how dispensaries can get started with a $2,000 consignment package and free consultation with Justin's team.Tune in to learn how to unlock accessories as a key revenue driver and get connected with the tools that will elevate your dispensary's success! Find out more about BudsFeed at:https://budsfeed.com/https://www.linkedin.com/company/dyspensr/https://www.linkedin.com/in/justinmichaeljohnson/https://www.linkedin.com/company/budsfeed/ 00:00 Introduction and Initial Connections00:22 The Vision Behind BudsFeed01:05 Building the BudsFeed Community02:54 Challenges and Successes05:21 Transition to Elevated Accessories05:56 Strategies for Dispensary Accessories11:24 Introducing Dispenser: A Wholesale Platform13:07 Supporting Dispensaries with Consignment20:22 Data-Driven Decisions for Dispensaries23:10 Challenges of High-End Dispensaries23:46 Replenishment Strategies for Dispensaries24:42 Wholesale and Distribution Insights25:45 Personalization and Large Orders29:23 Loyalty Programs and Customer Service30:13 Innovations in Dispensary Operations34:40 The Future of Cannabis Legalization36:06 Economic Realities of the Cannabis Market38:08 California's Cannabis Market Struggles41:05 Final Thoughts and Contact Information #kayacast #cannabis #tips #dispensaries #business #podcast

There is so much happening in this week's show! recaps of an unbelievable week out at the St. Lawrence River with the Fish Or Die Pro Staff. Plus a look back at the 4th Slot Tourney of 2025 and how did your host fare? Just Johnson of Chill Steel Pipes discusses an amazing product for the "fish whistle" crowd. And AJ Beaudoin from Battlefish Charters joins us to discuss an amazing opportunity for Veterans to take the first step to starting a guide business with Battlefish Academy in conjunction with Paul Smith's College!Save $20 off your own Double Walled Insulated Water Bong at https://chill.store/jigsandbigs - just use JIGSANDBIGS at checkout!Take advantage of our new ambassador roll with Ark! Use Code JIGSANDBIGS to save 10% on Rods, Reels, and Baits too! https://arkrods.com/JIGSANDBIGSWant to support the show?BECOME A JIGHEAD HERE:https://rebrand.ly/bf8612And/OrBuy me a coffee here: https://buymeacoffee.com/jigsandbigsSubscribe to J&B on YouTube: https://www.youtube.com/channel/UCQgjclBaAYEl0Xrw9JKYNQgSubscribe to American Vet Fishing on YouTube:https://www.youtube.com/@american_vet_fishing8741BUY HEAT YOUR MEAT: https://heatyourmeat.net/Call the J+B Hotline! 1+ (413) 324-8519Or email jigsandbigs413@gmail.com(Questions, comments, FTG, Stories from the bait shop, Broke on the Boat submissions, and more)Check out our LINKTREE: https://linktr.ee/jigsandbigsThanks to our Show Partners!- Hookset Hoodlums - https://www.hooksethoodlums.com - Use code JIGSANDBIGS10 for 10% off at checkout!!!- Dark Horse Tackle - https://darkhorsetackle.com?sca_ref=4963595.Ulm8078KDd [Save 15% off your first box in a Weekend Warrior or Dabble Pack month-month subscription using code JIGSANDBIGS15 at checkout or put together a BYOB and use the code JANDBBYOB25! - Omnia Fishing - https://omnia.direct/OmniaE-GiftCard [Save 15% off your FIRST order at Omnia Fishing!]- A-Bay Lure - https://abaylure.com [Use code Jigsandbigs to save 20% on your entire order]- Bay House Apartment - https://shorturl.at/fpRX8- The Ship Motel - https://theshipmotel.com/- Reaction Tackle - https://www.reactiontackle.com/JIGSANDBIGS- Three Belles Outfitters - https://rebrand.ly/zsdnchi- Torege Polarized Sunglasses - https://rebrand.ly/i2cqymx [Use code jigsandbigs10 to save 10% at checkout!]

Remember when eCommerce was going to revolutionize B2B sales? Twenty years in, only a handful of channels have capitalized on the initial promise. But distributors aren't to blame for the operational failure, says Justin Johnson, Founder of Motivate. He maintains that the major e-commerce platforms should bear the blame. They failed to grasp that most orders are placed from the job site via mobile, a recurring purchase order, or a list scribbled on a piece of drywall.  Jason spoke with Justin about his company's innovative plug-and-play order processing solution, a PO-to-cart widget that works with the software distributors already own. It can even convert images into orders with incredible accuracy. CONNECT WITH JASON LinkedIn CONNECT WITH JUSTIN LinkedIn Motivate *** For full show notes and services visit: https://www.distributionteam.com Distribution Talk is produced by The Distribution Team, a consulting services firm dedicated to helping wholesale distribution clients remove barriers to profitability, generate wealth, and achieve personal goals.    This episode was edited by The Creative Impostor Studios  Special thanks to our sponsors for this episode: Connected Peers, providing virtual communities for wholesale distributors; and INxSQL Distribution Software, an integrated distribution ERP software designed for the wholesale and distribution industry.

We return with a special episode - The Coaches Panel, featuring Alex Adams, Head WSOC Coach of Timber Creek, Justin Johnson, Head WSOC Coach of San Antonio Churchill, and Alexi Upton, Head MSOC Coach of Royse City. Our 6A coaches join us to discuss their new roles and why they made the change. They also give us great insight into the interview and hiring process. We also discuss the state of TXHSSOC and the many changes that have taken place in the last year, along with a look at the Club game and College Soccer. Don't miss this exciting episode!    [Originally Recorded 6-9-2025]

Two Major ALM Conferences back-to-back … they said it couldn't be done.  Legal Speak believed it … and went there to see it for themselves. For over 20 years, the General Counsel Conference Midwest has been the premier event in the industry.  Delivering key insights and practical solutions that today's general counsel need to manage and better leverage C-Suite relationships, successfully overcome a litigation crisis and do more with fewer resources just to name a few.  For the 2nd year, Legal Speak was there live to bring you you interviews with interesting attendees as well as moderators and speakers from various panels from this year's event in Chicago.   In this episode, host Patrick Smith is joined by Justin Johnson, the Chicago President & Partner of Latitude Legal.   Host: Patrick Smith Guest: Justin Johnson Producer: Charles Garnar  

In this episode of the Westminster Effects Doxology Podcast, we dive into the complex world of President Donald Trump's tariffs with Justin Johnson and Josiah Stowe from Dominion Wealth Strategists. Join us for a thoughtful and nuanced conversation exploring the economic, cultural, and theological implications of tariffs on everyday Americans and the broader market. How do these policies align with biblical principles of stewardship and justice? What can Christians take away from this economic debate? Justin and Josiah bring their expertise as Reformed wealth strategists to offer practical insights and a fresh perspective. Recorded on April 8, 2025.Subscribe on ⁠⁠⁠⁠⁠⁠iTunes⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Overcast⁠⁠⁠⁠⁠⁠, and ⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠.Follow us on ⁠Facebook⁠, ⁠Instagram⁠, ⁠TikTok⁠, and ⁠X⁠.Join the discussion at the Westminster Effects Green Room.Buy your guitar effects at ⁠⁠⁠⁠⁠⁠westminstereffects.com⁠⁠⁠⁠⁠⁠.

February 2025 Dante's Old SouthDr. Fubbs: Singer, songwriter, multi-instrumentalist, composer, master engineer, cinematographer, editor, actor, designer, recording engineer, Death Row Record-signed artist: linktr.ee/drfubbsKelly J Nelson Founder / Chief Creative Officer / Director:30+ Year entertainment and event industry veteran and award-winning live experience designer, conceptual artist, and theatrical marketing expert.  Previous clients include AMC Network Coca-Cola, Accenture, Cartoon Network, CNN, The Atlanta Hawks, Ponce City Market, City of Atlanta.  BA In Communications and Visual Art from Florida State University.  Previous work: Jack Morton Worldwide then 3 of my own agencies: The Maverick Group (19 Years), LED Experience (15 years) and Oracle Experience Enterprises (1 Year)www.mirthandmischief.liveCoach Lee Wilson has over 20 years in the relationship recovery service and his website is www.MyExBackCoach.comAdditional Music by:Justin Johnson: https: www.justinjohnsonlive.comOur Sponsors:Taco Cat Goat Cheese Pizza & the Case of the Missing Hat: www.dolphinhat.com/product/taco-cat-goat-cheese-pizza-graphic-novelLucid House Press: www.lucidhousepublishing.comWhispers of the Flight: www.amazon.com/Whispers-Flight-Voyage-Cosmic-Unity-ebook/dp/B0DB3TLY43The Crown: www.thecrownbrasstown.comThe Red Phone Booth: www.redphonebooth.comBright Hill Press: www.brighthillpress.orgWe Deeply Appreciate:UCLA Extension Writing Program: www.uclaextension.eduMercer University Press: www.mupress.orgNPR: https: www.npr.orgWUTC: www.wutc.orgAlain Johannes for the original score in this show: www.alainjohannes.comThe host, Clifford Brooks', The Draw of Broken Eyes & Whirling Metaphysics, Athena Departs, and Old Gods are available everywhere books are sold. Find them all here: www.cliffbrooks.com/how-to-orderCheck out his Teachable courses, The Working Writer and Adulting with Autism, here: brooks-sessions.teachable.com

In this episode, we explore the innovative strategies employed by Justin Johnson, the founder of BMP Creative, a thriving social media agency that has seen significant growth in recent years. Justin shares insights into his journey of scaling the company from a small team to nearly 30 employees while emphasizing the importance of innovation as a driving force behind their success. At the heart of BMP Creative's growth lies a unique internal tool called the Busy-O-Meter, designed to foster transparency and understanding of employee workloads within a remote work environment. Every day at 11 a.m., the Busy-O-Meter prompts team members to rate their busyness on a scale from 1 to 10, encouraging open communication about capacity and creating a cohesive company culture. This innovative approach allows the team to efficiently allocate resources and support one another, effectively eliminating any guesswork regarding who may need assistance. The discussion further delves into the vital role of core values in building a culture of innovation. Justin explains that BMP Creative actively hires individuals who demonstrate a natural affinity for creative problem-solving, often evidenced through their side projects and personal passions. He recounts an enlightening interview with a candidate who not only worked in strategy but also engineered custom video distortion tools as a hobby. This propensity for innovation, Justin argues, is essential for maintaining a dynamic and forward-thinking organization. The conversation also highlights the rapid evolution of video production tools, particularly in the realm of AI, which Justin integrates into his company's workflows to enhance creativity and efficiency. He discusses the importance of staying ahead of trends and experimenting with new tools, like the Submachine platform that his team developed to streamline the creation of dynamic subtitles for Netflix content. By leveraging technology, BMP Creative boosts its output while ensuring high-quality results, allowing the agency to handle substantial client demands more effectively. Justin's excitement for storytelling comes to the forefront as he shares his endeavors in film, including his latest documentary about his parents' unconventional business. Drawing parallels between filmmaking and corporate innovation, he emphasizes the necessity of human emotion and compelling narratives in driving impactful content creation. Closing the episode, Justin invites listeners to think about how they can harness their unique stories and experiences to illustrate their professional journeys. He offers to collaborate on creating innovative sizzle reels that encapsulate personal and professional milestones, showcasing how narrative can be intertwined with corporate growth and innovation. Overall, this episode serves as a wealth of knowledge for those looking to implement creative strategies in their organizations, urging leaders to embrace innovation, prioritize transparency, and recognize the importance of storytelling in both their work and personal lives. 00:00:10 Introduction to Scaling by Innovation 00:09:46 Tools for Scaling in Remote Work 00:12:12 The Busy-O-Meter: A Transparency Tool 00:14:24 Hiring for Innovation: The Secret Sauce 00:16:39 Core Values That Drive Innovation 00:18:58 Innovation as a Way of Working 00:22:58 Personal Projects and Career Stories

Join us as Justin Johnson shares his inspiring journey from healthcare entrepreneur to real estate wholesaler. Discover the key insights and strategies that helped him hit the ground running, close multiple deals in his first months, and build a thriving business. Whether you're new to wholesaling or looking to level up, this episode is packed with actionable advice. KEY TALKING POINTS:0:00 - Introduction0:37 - How Justin Johnson Got His Start In Real Estate1:49 - His Previous Business3:22 - Using Door Knocking As A Lead Channel5:09 - Justin's First Deal6:57 - What He Did After Getting His First Assignment Fee10:35 - What His Business Looks Like Today14:29 - How He Got His Business To Become More Profitable15:55 - How Much Justin Spends To Get A Deal18:22 - Moving From Wholesaling To Flipping21:46 - His First Hire In His Business23:39 - How His Marketing Strategy Evolved25:06 - Where He Wants To Take His Business26:48 - How To Find Justin On Social Media27:02 - Outro LINKS:Instagram: Justin Johnsonhttps://www.instagram.com/j3_companies/ Website: Justin Johnsonhttps://www.facebook.com/justin.johnson.100483/ Instagram: David Leckohttps://www.instagram.com/dlecko Website: DealMachinehttps://www.dealmachine.com/pod Instagram: Ryan Haywoodhttps://www.instagram.com/heritage_home_investments Website: Heritage Home Investmentshttps://www.heritagehomeinvestments.com/

In this episode of the EntrePastors Podcast, Jon has an awesome conversation with Justin Johnson, founder of Dominion Wealth Strategists, a company that was founded with the sole mission of putting more money into the hands of God's people.  Justin discusses the flawed ideology that exists among some believers that celebrates poverty and avoids even the appearance of abundant wealth.  Justin believes when God's people embrace the dominion for which they were created, they will find success in all arenas of life, including their financial well being. Guest Info/Links:Website: https://www.dominionwealthstrategists.com/  Call to Action:Take advantage of our 50% off Black Friday - Cyber Monday sale on all our courses!https://www.entrepastors.com/courses 

Michael concludes this series on quit immaturity as he is joined by Justin Jefferson, to discuss quit immaturity in faith and purity. Visit our linktree: https://linktr.ee/scatteredabroadnetwork Visit our website, www.scatteredabroad.org, and subscribe to our email list. "Like" and "share" our Facebook page: https:// www.facebook.com/sapodcastnetwork Follow us on Instagram: https://www.instagram.com/ the_scattered_abroad_network/ Subscribe to our Substack: https://scatteredabroad.substack.com/Subscribe to our YouTube channel: The Scattered Abroad Network Contact us through email at san@msop.org. If you would like to consider supporting us in any way, don't hesitate to contact us through this email.

Michael concludes this series on quit immaturity as he is joined by Justin Jefferson, to discuss quit immaturity in faith and purity. Visit our linktree: https://linktr.ee/scatteredabroadnetwork Visit our website, www.scatteredabroad.org, and subscribe to our email list. "Like" and "share" our Facebook page: https:// www.facebook.com/sapodcastnetwork Follow us on Instagram: https://www.instagram.com/ the_scattered_abroad_network/ Subscribe to our Substack: https://scatteredabroad.substack.com/Subscribe to our YouTube channel: The Scattered Abroad Network Contact us through email at san@msop.org. If you would like to consider supporting us in any way, don't hesitate to contact us through this email.

Send us a text We brought you all of the live coverage from the Fight Laugh Feast Prodigal America conference held 10/31-11/2/24! This episode includes interviews with (in order) Kyle Hessler & Parker Brown, Keith Foskey & Andrew Rappaport, Will Spencer & Tate Taylor, Chance Summers & Andrew Rappaport, Steve Cruz & TC Cook, George Grant, Justin Johnson, & Nathan Anderson! Enjoy! Are you a Christian startup or company looking to partner with a low-cost, high-return service that shares like-minded principles? Then AdventDS is for you!Are you ready for your church conference? Contact Striving For Eternity at "speaker@strivingforeternity.com" or click HERE! Covenant Real Estate: "Confidence from Contract to Close" Facebook: Dead Men Walking PodcastYoutube: Dead Men Walking PodcastInstagram: @DeadMenWalkingPodcastTwitter X: @RealDMWPodcastExclusive Content: PubTV AppCheck out our snarky merch HERE

Send us a textWe brought you all of the live coverage from the Fight Laugh Feast Prodigal America conference held 10/31-11/2/24! This episode includes interviews with (in order) Kyle Hessler & Parker Brown, Keith Foskey & Andrew Rappaport, Will Spencer & Tate Taylor, Chance Summers & Andrew Rappaport, Steve Cruz & TC Cook, George Grant, Justin Johnson, & Nathan Anderson! Enjoy! Are you a Christian company looking to partner with a low-cost, high-return service that shares like-minded principles? Then AdventDS is for you!Are you ready for your church conference? Contact Striving For Eternity HERE!Dominion Wealth: "All of Christ for all of life, All of Finance for Christendom!" Covenant Real Estate: "Confidence from Contract to Close" Facebook: Dead Men Walking PodcastYoutube: Dead Men Walking PodcastInstagram: @DeadMenWalkingPodcastTwitter X: @RealDMWPodcastExclusive Content: PubTV App

If your C-suite isn't entertaining conversations about artificial intelligence, is it interested in profitability? Perhaps that's not a fair assessment. Maybe the C-Suite just needs a crash course in what the technology can do for distribution.  Justin J. Johnson, founder and CEO of Motivate AI, is the perfect spokesperson for the job. Jason caught up with Justin to learn more about Motivate AI's purpose-built automated solutions for distribution and how they boost sales team performance, enhance customer engagement, and streamline the quote and order process. CONNECT WITH JASON LinkedIn CONNECT WITH JUSTIN Website Email LinkedIn *** For full show notes and services visit: https://www.distributionteam.com Distribution Talk is produced by The Distribution Team, a consulting services firm dedicated to helping wholesale distribution clients remove barriers to profitability, generate wealth, and achieve personal goals.    This episode was edited by The Creative Impostor Studios  Special thanks to our sponsors for this episode: Connected Peers, providing virtual communities for wholesale distributors, and INxSQL Distribution Software, an integrated distribution ERP software designed for the wholesale and distribution industry.

The podcast reports that Justin Johnson has been found guilty of all charges related to the murder of the rapper Young Dolph, resulting in a life sentence, marking a pivotal moment in this high-profile case. See omnystudio.com/listener for privacy information.

In this episode, attorney Marc Agnifilo defends Sean “Diddy” Combs, claiming that the recent TMZ documentary, The Downfall of Diddy, represents a concerted effort to take down a successful Black man. The discussion sheds light on the challenges faced by prominent figures in the spotlight and the impact of public scrutiny.  The show also covers some lively celebrity news, including Nicki Minaj's outrage directed at an Outback worker who added her name to a food order bag, leading to an online outburst where she criticized both the restaurant and the employee. Additionally, Cardi B expresses her frustrations about her estranged husband Offset during an IG Live session, revealing her decision to date other men after years of his infidelity. In a significant legal update, the podcast reports that Justin Johnson has been found guilty of all charges related to the murder of Young Dolph, resulting in a life sentence, marking a pivotal moment in this high-profile case.  Website: https://www.urban1podcasts.com/rickey-smiley-morning-show  See omnystudio.com/listener for privacy information.

Fei-Fei Li and Justin Johnson are pioneers in AI. While the world has only recently witnessed a surge in consumer AI, our guests have long been laying the groundwork for innovations that are transforming industries today.In this episode, a16z General Partner Martin Casado joins Fei-Fei and Justin to explore the journey from early AI winters to the rise of deep learning and the rapid expansion of multimodal AI. From foundational advancements like ImageNet to the cutting-edge realm of spatial intelligence, Fei-Fei and Justin share the breakthroughs that have shaped the AI landscape and reveal what's next for innovation at World Labs.If you're curious about how AI is evolving beyond language models and into a new realm of 3D, generative worlds, this episode is a must-listen.Resources: Learn more about World Labs: https://www.worldlabs.aiFind Fei-Fei on Twitter: https://x.com/drfeifeiFind Justin on Twitter: https://x.com/jcjohnss Stay Updated: Let us know what you think: https://ratethispodcast.com/a16zFind a16z on Twitter: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zSubscribe on your favorite podcast app: https://a16z.simplecast.com/Follow our host: https://twitter.com/stephsmithioPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

Justin Johnson from Dominion Wealth wants to help guide Christians to fight against the Anti-Christian theologies that leave them as poor stewards of their money. This results in many families being hamstrung and unable to pass along generational wealth to their offspring. Fear not! Bring your worries to the table and reason (using God’s Word)! There are very real strategies that you can start implementing NOW to get on the right track of good stewardship and generational wealth. “(The difficulty) is more the shift in perspective instead of the actual work that it takes to do it” Consider a complimentary consultation w/ Dominion Wealth: Reformed.Money Don’t forget to Sign up for The FLF Conference 2024 (Prodigal America) https://flfnetwork.com/prodigal-america/

Justin Johnson from Dominion Wealth wants to help guide Christians to fight against the Anti-Christian theologies that leave them as poor stewards of their money. This results in many families being hamstrung and unable to pass along generational wealth to their offspring. Fear not! Bring your worries to the table and reason (using God’s Word)! There are very real strategies that you can start implementing NOW to get on the right track of good stewardship and generational wealth. “(The difficulty) is more the shift in perspective instead of the actual work that it takes to do it” Consider a complimentary consultation w/ Dominion Wealth: Reformed.Money Don’t forget to Sign up for The FLF Conference 2024 (Prodigal America) https://flfnetwork.com/prodigal-america/