Podcasts about flipbook

We're announcing AIEWF speakers this week! Take the AI Engineering Survey!Today's guest Ethan first joined us for the LS Paper Club as the lead on NVIDIA Cosmos World Model, but then joined xAI and built Grok Imagine in 3 months:He comes back on Latent Space with some nuclear hot takes: that Video Models primarily get their intelligence from LLMs, not from training on video data, and that the next frontier for truly interactive, realtime, long-horizon world models is to work on LLMs (perhaps Interaction Models as well…)Put it this way: In the near term, the next Sora won't be a better video model, but a video agent.Generative Media may more closely follow the evolution of AI coding which went from focusing on one-shot output performance and cost, to multiturn reasoning and planning models for agents and systems that can plan, edit, test, debug, and submit PRs.At a certain point, coding models got so good that the only significant next step to improve performance was handling the orchestration of these models.Now as the performance of video models increases significantly across realism, consistency, & prompt adherence while becoming more cost efficient, the next evolution of video generation may also be systems that can plan, generate, edit, critique, and iterate across an entire creative task. In this episode, Ethan joins swyx and Vibhu to unpack what it actually takes to build frontier image and video systems: data, VAEs, diffusion transformers, audio-video alignment, inference speedups, and the hidden cost of storing and moving massive video datasets. From building NVIDIA's Cosmos world model to joining xAI as Grok Imagine was being built from zero to one, Ethan He has been at the center of some of the most important work in video generation, multimodal models, and real-time world models.We go deep on Grok Imagine, how a small xAI team shipped its first multimodal video model in three months, why iteration speed matters more than almost anything in model development, and why many of the biggest gains come from fixing tiny bugs in data and training pipelines. Flipbook: The future of VideomaxxingVideo agents are almost a sure bet to be the trend in the coming year. We end with a glance at what's beyond video agents:Flipbook caused a minor sensation this year when it was released, but most treat it as a fun demo. Ethan takes it very seriously — with the speed and cost of inference coming down every year, the future of custom video JIT UI is closer than you think. We talked about why videogen models may become the front end of AI, how generative UI could replace traditional HTML/CSS, why world models need to be real-time, interactive, and long-horizon, and why the future of video generation may depend more on language models and agents than on diffusion alone.We discuss:* Why fast iteration mattered more than meetings* Why small training bugs can drive huge model quality gains* Why coding models may make compute the bottleneck again* How image and video models are trained with synthetic captions* The role of VAEs and latent space in frontier video models* Why image models are the foundation for video models* The tradeoff between temporal compression and real-time interactivity* Flipbook, Neural OS, and the future of generative UI* Why future interfaces may go from user intent to pixels* The hidden cost of training video models: storage, egress, and GPU hours* How step distillation and consistency models (like OpenAI sCM) makes video inference orders of magnitude faster* Grok Imagine 0.9 and large-scale audio-video generation* Why audio-video alignment is harder than text-video alignment* Ethan's definition of world models* Reference-to-video, video extension, and long-context video generation* Why xAI's research communication undersells Grok Imagine* How xAI culture shaped the speed of development* AI watermarking, SynthID, and detecting generated media* Why prompt rewriting matters for video models* Grok Imagine Agent and the rise of video agents* Why language models may unlock better video generation* Robotics, physical AI, and embodied world models* Why Ethan left xAI and shifted focus toward LLMs* Self-managed context, memory, and the next frontier for language modelsEthan He* LinkedIn: https://www.linkedin.com/in/ethanhe42* X: https://x.com/EthanHe_42Timestamps00:00:00 Introduction00:01:25 From NVIDIA Cosmos to xAI00:03:24 Building Grok Imagine from Zero to One00:10:07 How Image and Video Models Are Trained00:18:53 Video Compression, VAEs, and Real-Time Tradeoffs00:22:10 Generative UI, Flipbook, and Neural OS00:32:10 The Cost of Training Large Video Models00:37:04 Distillation, GANs, and Fast Video Inference00:41:21 Audio-Video Generation and Grok Imagine 0.900:48:34 What Makes a World Model?00:55:51 Reference Videos, Long Context, and Video Memory01:00:11 xAI Culture, Research, and First-Principles Building01:09:45 AI Safety, Watermarking, and Prompt Rewriting01:13:10 Video Agents and AI-Assisted Creation01:27:32 Why Language Models Unlock Better Video01:31:15 Robotics, Physical AI, and Embodied World Models01:32:38 Why Ethan Left xAI01:34:16 Self-Managed Context and the Future of LLMs01:38:43 Ethan's Career Path and Closing ThoughtsTranscriptIntroduction: Ethan He, Latent Space, and the Path to xAISwyx [00:00:00]: We're here in the studio with Ethan He, most recently of xAI. Welcome.Ethan [00:00:10]: Thank you. Glad being here.Swyx [00:00:11]: We're also here with Vibhu. you were first coming to us or joining the latent space world because you were working on Kosmos at NVIDIA, and you did a paper. We loved it. you presented it as well, so thank you for doing that.Ethan [00:00:23]: I've actually, I also presented the MoEs twice at latent space.Swyx [00:00:29]: How did you actually hear about us? Did we reach out to you? Is that how it worked?Ethan [00:00:33]: No, actually, I-- the community. Like I realized, oh, there is this online community that people talk about AI and also learn from each other through papers every week through the Paperclip. It's very nice.Ethan [00:00:49]: I learned a lot.Swyx [00:00:49]: I think three years stop. We haven't stopped even on Christmas and New Years. many weeks I want to stop but it keeps going.Vibhu [00:00:58]: No, that was good. I think you had posted that you worked on a paper, and I was “Oh, very cool. We have Paperclip. Present then.”Vibhu [00:01:04]: But I might have reached out to you after.Swyx [00:01:05]: you-- because it's an amateur club, right?Swyx [00:01:08]: so it's very unusual and but we have sometimes paper authors come by and actually explain the paper. Today we just did, the poolside paper, which was apparently very good.Vibhu [00:01:18]: Came out yesterday.Vibhu [00:01:19]: pretty interesting, right? Fully open. They talk about everything, systems. So it's a good one. We'll, we'll recommend people to read it.Swyx [00:01:25]: Bring us up to speed on your transition to xAI, ‘cause I actually don't even know when you joined. just like tell the, tell the story about the sort of transition.From NVIDIA Cosmos to xAI: Scaling Video and World ModelsEthan [00:01:34]: Before xAI, I was working on Kosmos world model as in-- at NVIDIA. So Kosmos is, it's a giant video foundation models that can-- that aims to simulate the world and for-- it serves as a foundation of-- for all of the roboticists to build on top of. There, once I built the Kosmos one, I realized as this thing also has a scaling law similar to language model, we need to scale up the video models further. that's, that's why I realized I need to move to somewhere with much more compute resources. That's how ISwyx [00:02:13]: Than NVIDIA?Vibhu [00:02:14]: The GPU rich came themselves.Vibhu [00:02:19]: And timeline-wise, when was Kosmo? It was pretty early, right? It was open world model, open paper, everything.Ethan [00:02:25]: It was end of twenty-four.Vibhu [00:02:28]: End of twenty-four.Ethan [00:02:30]: Then at mid twenty-five, I moved to xAI. At that time-- I joined about the time when xAI was about to build video models and in multi-model models. There were no infra, no data, and no model, and it just-- as a few engineers, we built it in three months and released the first model, Grok Imagine zero point nine.Ethan [00:02:55]: And since then, I keep working on video models and move more from training and to post-training of the video models. For example, like a reference to videos, kind of like the cameo feature and, video extensions. And, before I left, I worked on a world model, leading a small team to focus on the real-time long horizon video generation.Building Grok Imagine From Scratch in Three MonthsSwyx [00:03:24]: Can you give like a rough roadmap of okay, you're on a brand-new team. Grok previously was only text, or they partnered with BFL for their image gen stuff. What do you-- what are the building blocks, right? You have compute, data you can procure somewhere. Like just what are like the sequence of things that people should think about when you're setting up a new team?Vibhu [00:03:43]: actually even deeper, not just data you can procure. You guys had to go through getting the data too, right? So you shipped it pretty fast, but yeahSwyx [00:03:51]: three months is likeVibhu [00:03:52]: From everythingSwyx [00:03:52]: actually like very surprisingly fast.Ethan [00:03:55]: One thing I say like thanks to my experience at NVIDIA, ‘cause first time when we were building Kosmos together, we built it, for about a year. So this is like the second time I do it. Roughly have an idea, what to do. I say the most important thing is the talent. Everyone were very strong and clever, very close with each other towards a common goal. So that speed up things a lot. So you reduce the communication bandwidth among people, and everyone can work towards the same goal. It's, it's like every day there's not that much meetings on the calendar, like maybe like a, like a sync a day, and after that it's, it's just all building. It was pretty fun at that time.Ethan [00:04:47]: And another thing is that xAI has very strong foundations of like data inference, model inference, and the supporting there can help the model develop a lot. When I look at, training models, I don't so actually the top important thing is like how many, how many iterations can you do, per day? and the more iteration can you do, you can, you can train the model much faster. So if you have very strong infra and you have a lot of compute, you can, you can train these models in very short period of time. That can give you a much larger buffer to, for errors, and it also gives you the opportunity to spot more bugs.Iteration Speed, Compute, and Debugging Model PipelinesSwyx [00:05:46]: What is an iteration? Is it like a few hundred steps or what are youEthan [00:05:50]: Let's say just the train-training the model, like from acquire new data and maybe design new algorithms and train a new model, maybe at smaller scale orSwyx [00:06:01]: So cycle time for like any hyperparam that you're searching.Ethan [00:06:04]: Cycle time and tune to like eval this model. Is this model better than my previous iteration?Ethan [00:06:11]: SoSwyx [00:06:11]: So it's like before you, someone had already set this up that you can iterate very quickly.Ethan [00:06:15]: I think the foundation there is extremely good forDeveloping and research models.Ethan [00:06:23]: And often I find is it-- this is kind of boring, but like a lot of the improvements does not come from new algorithms. It comes from finding small bugs here and there in the data pipeline, in the, in the model training pipeline. Those give, those give the biggest boost to the model quality.Vibhu [00:06:46]: It's interesting, right? So you say it's like small team, less communication bandwidth, but also a lot of quality is like find little bugs. It seems counterintuitive, right? You have a lot of people, you can iron out more of those, but it's interesting to see the other side, right?Swyx [00:07:00]: I also wonder, have you-- do you try using LLMs to look for bugs? I don't know.Ethan [00:07:05]: I remember at that time it was mid two thousand and twenty-five, so it's the coding model wasn't quite there yet. I remem- I remember like December two thousand and twenty-five, it was extremely good. Yeah, I've been, I've been using it at that time. It's, it's helpful. sometimes it produce codes that are kind of difficult to maintain, even though like the first time it built something extremely fast. But it gave the, like a spaghetti code, thousands of lines that I couldn't maintain, and the LLM itself couldn't figure out what's, what's wrong and how to improve on top of it. But now I find it much better. Yeah, I want to bring up another point here is now coding models are much more efficient and can help us implement stuff much faster. Compute might become a bottleneck again because previously, like if you want to train a new model, say you want to generate new synthetic data and then or write a new algorithm, it might take a few weeks. And during that period of time, you don't-- you might not have experiments to run. But now you can build that thing within a few hours, then you can immediately train a model.Ethan [00:08:24]: Now you have to have enough compute to try all of the ideas. So compute might be the bottleneck of iterating speed again.Swyx [00:08:36]: yeah, I actually, honestly, I think it's like kind of a stressful job because you're “Well, I should be trying everything, and if I'm not, then I'm not doing my job well.”Vibhu [00:08:48]: there's also the stress of you're eating thousands of GPUs per hour, which is very expensive and, compute can go to other researchers.Swyx [00:08:56]: You got the daddy Elon toVibhu [00:08:57]: You got daddy Elon.Ethan [00:08:59]: It wasVibhu [00:09:00]: But there's still finite amount of compute, like you want to use it, you want to use it well, you want more of it.Ethan [00:09:06]: That was quite stressful indeed. Yeah, I think one thing is the-- with coding models now, like a lot of these jobs can be automated, which is much better. A second, it's a, it's a marathon, so you got to maintain good health and, a regular schedule.Vibhu [00:09:28]: It's, it's hard to hear that when you shift from zero to nothing in two months.Swyx [00:09:32]: and, I think obviously the culture at xAI is very famously, people work very hard. one thing I did want to dive into, in our-- in the notes that you, that you sent ahead of time, you had specific comments about the cost of Video Gen training. presumably this is on the Colossus-1, right? the two hundred megawatt cluster. Any whatever you want to just share on that.Vibhu [00:09:54]: I think there's, there's three things we're talking about, right? So there's Video Gen, there's also the Image Gen model that you put out. Do you want to like complete the, okay, so zero to one, you have a few months. Just what are the stages of create Image Gen model?Swyx [00:10:06]: Oh, yeah, maybe I got distracted.How Image and Video Models Are Trained: Synthetic Captions, Tokenizers, and VAEsVibhu [00:10:07]: Sorry. and then, from there's Video Gen, there's Audio Gen. Would love to get into those next. But what is that first few months like? So small team, a lot of bugs, iterations, but what does it look like? Do we take something off the shelf? Do we just get data compute? What's, what's the few months like? How do you go to state-art Image Gen model? How do you just start?Ethan [00:10:28]: I cannot comment specifically how xAI did, but it's, it's a quite standard process. I can draw some, examples from Cosmos. So mainly it's building a video model, you actually need to build a image model first. And building these two models, the data you need is a hundred percent synthetic pair of language and image or language to video. Because on the, on the internet, actually, the videos don't naturally associate with text. So you can say, oh, like on YouTube, you have the title and you have the description and the commentsSwyx [00:11:11]: TitleEthan [00:11:11]: of a video, but usually they're not relevant to the video itself. And say maybe like the video is a natural scene of mountains or something, and the title is, I'm so happy today.Ethan [00:11:26]: So they have they have no correlation at all. So the first step is to, you have to generate synthetic pair of language with the videos. So you gather videos from the internet, and you use a VLM to caption the videos. So that part, here's a question, like how do you, how do you gather VLM to begin with? So if there's noSwyx [00:11:55]: You, so you fuse the model, right? LikeEthan [00:11:57]: Say if there's no like VLM exists, like how do you generate the text to the beginning, right? It's, it's impossible.Swyx [00:12:04]: I see.Ethan [00:12:05]: In the beginning, it's like you ask human to describe the video as detailed as possible.For example, you ask them to describe everything, like all objects, all characters, and all interaction and dialogues in the, in the videos. So that's in the protocol of Cosmos labeling. We require the objective we give to the labelers was that you have to describe the video as detailed as possible, such that a blind person hears a blob of text can reconstruct what the video is like from their head.Swyx [00:12:43]: Video or image? You're talking about images.Ethan [00:12:44]: Video or image, either one of them.Vibhu [00:12:47]: This was pretty common when we went from clip and DALL-E, right?Vibhu [00:12:51]: It's all training on really detailed captioning of images. So same is applied to video, but insteadEthan [00:12:57]: same appliedVibhu [00:12:57]: of using multimodal model to pass in video images and write rich descriptions, you can alsoSwyx [00:13:04]: I think there's this traditional perspective of supervised, or, very highly human curated thing. I feel like there's a unlock with unsupervised, right? Where like you have enough to bootstrap that you can just throw common corpus on it or, whatever. like unsupervised vision and language pairing, right? Like where you just have, interspersed image and text and it just learns. To me, that is the VLM breakthrough that is different from the clip, different from the LM era.Ethan [00:13:36]: It's interesting to see that you kind of need both data.Ethan [00:13:41]: For example, for theSwyx [00:13:41]: You need it to bootstrap it up. YeahEthan [00:13:43]: for the generative model training, there's also usually like a small percentage of unlabeled data. So the model is instructed to generate a video without any text instruction. That can also help the model generalize. So after this stage of generative synthetic pair, so, one important common step is to train a compressor or a tokenizer of the image or videos. So because, if you train-- If you can technically, theoretically train image or video models on pure pixels, but the problem is that the, it's, it's a lot of tokens. So like one image, it's, a thousand by a thousand, it's like one million tokens, one million pixels. It's impossible to train transformer on that. So it's, you need to train a tokenizer, which can go from image to latent space and latent space back to image.Swyx [00:14:45]: That's why we named the podcast.Swyx [00:14:48]: But, basically, you're talking about vocabulary science.Ethan [00:14:50]: so vocab.Swyx [00:14:51]: And so, what is, what is imp-- like a million is impossible?Ethan [00:14:54]: In generative models, the vocab is continuous. It's a continuous space. We can think about like you map an image to a vector. It's a, it's a fixed length vector. It's sixteen or forty-eight, something like that. And then you map that vector back to the image space. And the mapping is, has-- The mapping is patch-based. So you say you haveEthan [00:15:22]: a sixteen by sixteen patch and you match, you map that patch of pixels into this latent space.Swyx [00:15:29]: We've covered thisVibhu [00:15:30]: This is like the vision transformersSwyx [00:15:32]: VAEs,Ethan [00:15:33]: VAEs.Vibhu [00:15:34]: You basically compress your input, you do your generation, you're reasoning all that generation in smaller dimension, and then you project back out.Swyx [00:15:43]: VAE is a form compression, but I think the for me, the patching thing is from VIT, right?Ethan [00:15:48]: You can make those.Swyx [00:15:49]: Literally the, yeah, the paper is titled like sixteen by sixteen is all you need. something like that. and then I think also, people make a lot of comparisons with this kind of patching with convolutions.Swyx [00:16:02]: Which is you're, you're kind of re- reconstructing the old paradigm with the new.Ethan [00:16:05]: Actually, in VAEs, there are, there are both convolution networks and transformers. You can actually do both.Ethan [00:16:14]: After this VAE, so what you've got is you've got latent space tokens and you've got the language tokens. So now the training of the diffusion transformer, usually generative models use diffusion transformers. It is actually quite standard. It's, it's very similar to how you train a language transformer models. It's not that much difference. It's just the tokens, the visual tokens in, visual tokens out. The only difference is there's a denoising process. So you train the model to unmask some of the noise. So you add, you add random noise to the visual tokens, and then you train the model to remove those noise to generate the clean tokens. Any inference, the model can iteratively remove noise from a hundred percent noise.Swyx [00:17:12]: And then there's also, to speed things along on the tech tree of diffusion, there's CFG, and then there's, there's also, latent diffusion that, there's, there's someone in there. I think, somewhere along the line, obviously, like stability and all these other guys, pioneered a lot of this, architecture. I don't know if you want to get into that or just, or do the video side up to you.Bootstrapping Video from Image Models and Temporal CompressionEthan [00:17:37]: After you train such model, such image model, the reason it's a, it's a foundation for video models is that image models are cheaper to train, and they have much denser connection between language and text. So, sorry, language and images. For example, you train a billion, you train on a billion images, and there's a mapping from the text to the image. And the cost to train the same, like the, a billion, a billion text to a billion videos, that's much more expensive because videosNaturally have more tokens than images. Because the diffusion models, their understanding of, language purely come from this mapping. So if you don't have enough mapping, so if you only train on like a ten million videos or something, there-- you might not see enough language tokens in your training, so your model does not understand human intention enough. So that's why you really-- you train-- you first train this image diffusion models, and then you bootstrap the video model from there.Swyx [00:18:53]: One thing I did want to ask, because I-- actually, I think you're, you're the first per-- video model person I've ever talked to, I think. we've, we've like talked to Luma and all those folks. There's all these tricks in video compression where basically frame by frame there's not that much difference, so actually you don't have to regenerate or save the whole frame, right? but I think MP4 compression or something else like that.Swyx [00:19:16]: is it tempting to use that? Or as far as I can tell, everyone just treats it as, “No, we would just generate every frame.” Is that roughly the state-art?Ethan [00:19:27]: There are a few different approaches. Let's say first, like you want to just directly use MP4 compression and use that as the tokens for the transformers to train, right? So people actually have tried that, but the main challenge is the latent space for the MP4 tokens were not, were not very comprehensible for the models. It's, it's extremely hard to train on that. And there's aEthan [00:20:01]: So that's why they created VAEs, which creates more continuous, latent space, so the models can understand that latent space and learn from it much easier. Even within the VAEs, there are different difficulties of the latent space. So you can imagine something the simplest, the most naive VAE is like you have an image, and you just shuffle all of the images into a, into a vector. So you don't need to train any VAEs, right? But that latent space is extremely hard for models to train on top of. That's why there are some debate on like how do you compress the tokens. So you mentioned like you can compress frame by frame. Also, you can compress, the temporal dimension.Ethan [00:20:52]: The difference is if you compress the temporal dimension, you get a much higher compression rate. Because there's temporal redundancy between frames, because, this frame and the last frame, likely they are mostly similar, so there's only some small difference. for example, I think in 12.1 VAE, they have like a eight by eight by four compression rate. So the four temporal tokens are compressed into one tokens. That can save a lot of, save a lot of the context length. If you do it frame by frame, you have to do maybe like eight by eight by one. Your context length will be four times larger. That being said, the benefit of the frame-- per frame compression, we might come back to this later, is, real-timeness and interactivity. ‘Cause if you, if you strain the output of the model, frame by frame, you can-- the model can respond to any user request immediately. So if you have like a temporal four compression, four times compression, thenSwyx [00:22:06]: It might be laggyEthan [00:22:07]: there's a lag there in nature.Swyx [00:22:10]: So you're very pilled on this. let's just go ahead and bring it up ‘cause we have the visual prepared anyway. There's some frontier applications of real-time video gen. So Flipbook is one of the examples that went viral recently, right? What is Flipbook?Real-Time Generative UI: Flipbook, Neural OS, and Diffusion Front EndsEthan [00:22:23]: Flipbook is kind of like a web brow- web browser. You can see like it has the web bro- browser UI on top. The difference is all of the UIs are generated by generative image model in real time, and anything here are fake. But you can, you can explore inside this wor- this imaginary world. Say like we-- here we have engineering the Great Pyramid. Like the model generates this for us to understand how it works, and if we want to navigate around and understand further, we can click on some of the, some of the description here, and the model will generate a new page, new subpage describing the details we want to know about.Swyx [00:23:14]: So it's basically kind of we're playing a video, but it's pausing for our next interaction, and then it just plays the next thing based on our interaction.Swyx [00:23:23]: Which is kind of cool.Vibhu [00:23:25]: and you kind of decide your story. So this was, how do you make a pyramid? levering technique seemed interesting, right? It shows how do you take Okay, I want to know what is thisSwyx [00:23:35]: The demo, the demo tweet had more animation between frames.Vibhu [00:23:38]: I think it's just skipping,Swyx [00:23:39]: Oh, it's just skipping a lot of frames.Ethan [00:23:40]: they also have a video modeVibhu [00:23:42]: It takes a lot. There's a lot of peopleEthan [00:23:42]: but, a lot of people are using it.Ethan [00:23:45]: So it's not available.Vibhu [00:23:46]: There's a live video stream. We can try,Swyx [00:23:50]: So this is an example of the kind of future that you see at the extreme. We don't-- we're obviously not in it today.Swyx [00:23:56]: But in a world where inference is completely free this is better than generating code and text?Ethan [00:24:02]: So this is, this is a final state of where Viva will be at for word model, I think. Imagine internet doesn't exist, and then you type in google.com. Like what should, what should, what should a model show you?the model can imagine something, and this is what the model imagine. And these web pages, they completely do not exist. So I think as the inference costs come down, we are going to have generative UI for everything. If you think about how the coding model works, so they write code for a web page, and they render the code might be con- converted into binary, and the binary render the pixels on the screen. So we in machine learning, every time we have some breakthrough, obviously it's, it's more intuit. So why don't we have like user instruction to the pixel directly? So the generative UI will be user intention to the pixels directly. And say like even if I want email, let's say everyone have the same interface, but I want, I want it slightly different. I want the email to show to me like a TikTok, so I can swipe left and right for the emails. And or maybe you want something else. We can have completely different things. Or like I have I'm looking at, Instagram stories, and I don't like the Like button. I always may click it. And, generative UI resolved it. So it's going to be a revolutionary replacement of the interface. So in the future, we might have much more powerfulEthan [00:25:50]: LLMs and coding models running behind the scene. And in the, in the front-end, the diffusion model will actually be the front-end to show stuff to you. That's how I imagine it.Swyx [00:26:02]: Diffusion front-end, deterministic back-end.Swyx [00:26:04]: Something like that. I find that very expensive, but,Vibhu [00:26:08]: I find it interesting you called LLMs writing code on the back end deterministic, but okay.Swyx [00:26:14]: you write it onceVibhu [00:26:15]: Compare it toSwyx [00:26:16]: And then you execute.Ethan [00:26:17]: If you think about the cost, say, let's say H100 costs $1 per hour, and if you use this eight hours a day and thirty days, so, every month you're paying this two forty, you'll actually not wanna pay for that. That's even more expensive than Cloud Code Max. But if you think about the compute costs come down like two times every year, and I think the future will likely arrive like within few years.Vibhu [00:26:49]: It's everything, right? compute cost comes down, compute gets faster, model gets smarterEthan [00:26:54]: More efficientVibhu [00:26:54]: model gets smaller.Swyx [00:26:55]: I don't know why you say two times, ‘cause I think it's like 100 times. In language models, it is roughly one hundred to a thousand times every twelve to eighteen months, for the same given level of LMSys, ELO.Vibhu [00:27:08]: That's a net of everything, right? That's model performance alongside compute. So different than just compute costs come down. But, a very interesting future.Swyx [00:27:19]: So the web designers will have to shout out that accessibility is an issue, right? how do you deal with screen readers or whatever. But yes, this is higher bandwidth storytelling than anything you can possibly generate with code, right? So I think that's the rough idea.Ethan [00:27:34]: And I'd like to add a little bit that so human naturally have the maximum bandwidth when we are looking at things, look at videos, and we also have maximum output bandwidth when we are talking. So in the future, it might be something like we talk to AI models, and the AI model responds back with a generative UI. So that would be the maximum input and output bandwidth to interact with AI models before neural link happens.Vibhu [00:28:06]: And it's also very custom, right? Some people are very visual, some people are not as visual, right? They prefer the text. But the best thing about generative UI, right, it can also be text.Swyx [00:28:17]: There's another project that we wanted to highlight, which is the Neural OS. Kinda similar idea, but here you're literally operating, simulating an operating system with a video model.Swyx [00:28:27]: and you can play Doom, you can do Firefox. I find this like mildly less impressive, obviously, because it's an OS that I can run.Swyx [00:28:37]: But here everything is imagined.Vibhu [00:28:40]: I was, used to the Command+W to close the Firefox tab. It didn't crash. That's why I saidSwyx [00:28:45]: It's too immersive.Vibhu [00:28:46]: It's, it's too immersive for me.Swyx [00:28:47]: Too immersive.Vibhu [00:28:48]: I wanted to close the tab.Vibhu [00:28:49]: But yes, I can play generated diffusion.Swyx [00:28:51]: this is shockingly fast.Swyx [00:28:54]: Because I remember there was a demo about like maybe one to two years ago. Someone tried to do the first-person shooter with a image model. There was no consistency. It was very slow. But here it looks like realistically it's-- this is Doom.Vibhu [00:29:07]: I think there's two sides to that, right? There's okay, what is running a game? The heavy part of it is actually the game engine, all the lighting, all that stuff, the graphics. This is just kind of video, right? Like we've solved consistency. This is still, it looks like a few years old image generation. There's some temporal consistency, but it's, it's kind of just images stitched together as frame video. But it's a good visual representation to pi- to picture the future you wanna see, right? that's, that's what I see in these more so.Ethan [00:29:38]: This reminds me of how the video models gets better and better. So Neural OS is kinda if you just look at it feels like it's just a crappy version of the, like the Windows we could have, right? And, but the difference is, so the model, this model is overfitted on the existing operating systems. It can generate nothing different than that. But it's actually also similar to video models. So when we are training these video model, image model, we train them on internet. There's no imaginary supernatural stuff on the internet. But once we train this model, you can prompt the model to generate something supernatural that have never existed in the data set. So if you train your Neural OS or neural computer on the standard screen recordings on the entire internet. The model can imagine completely new interface to interact with the computer.Swyx [00:30:43]: This is one of those things that is magical to me. usually generalizing out of distribution is bad, but somehow we have learned some kind of internal world model that you say, this plus, but it looks like rainbows and butterflies, it'll do it and it will kind of make sense.Swyx [00:31:03]: So yeah, that's kind of cool. Yeah, I don't know if there's any comment more on there. I do, I do wanted to, I did wanted to touch a little bit more on the model architecture stuff, which I think you were getting. It's, really fascinating. We don't get a chance to talk about this enough. So one of the papers that we covered, we've covered every annual, segment anything release. and I don't know if you follow-- you're a computer vision guy, so youEthan [00:31:26]: I knowSwyx [00:31:27]: . So they did memory attention, which is kind of interesting. And I always think, anything where you can, across the temporal dimension, keep some consistency, I think it's, very fascinating, and I don't know if Basically, does that-- the CV side bleeding into video gen side, I think is underexplored, right? we talk about it for labeling, but actually you can borrow the architecture itself.Ethan [00:31:50]: There's, there's also complete different approaches, right? you brought up the term world model, so we went from video model to world model. There is diffusion, but there's also other approaches that people are doing. So maybe we get into those after as well,?Swyx [00:32:03]: He has a whole definition of world models and stuff. I feel like we threw a lot at you. Whatever you want to comment on.Why Video Models Are Expensive: Storage, I/O, and Training ScaleEthan [00:32:10]: I think one thing that we should actually comment back on is okay, so we were talking about the steps to train image gen to video model. One thing we don't see as much of is okay, you brought up the delta in training data, right? SoEthan [00:32:24]: you won't have as much a video model might not generalize, but what is the cost of training a large video model? So we know for LLMs roughly, okay, even like the poolside thing that came out today, right? It's a Gemma level model trained on roughly forty trillion tokens at this many H200s over this much time, right? You can see what is the exact cost of that. So how many GPU hours over how much H200 costs? So how do we do the back-end math of, same thing for video models, image models. How do you, how do you kind of break that down? I can share some back-envelope calculation. So surprisingly, video models is-- the cost is very-- is comparable to language models and obviously the largest scale is language model, maybe like a medium scale to language models. I said just storing the videos alone, it costs a lot. You can, you can maybe look up on AWS or something.Ethan [00:33:20]: You really, say if you have a billion videos and let's say, let's just say like each video, like five megabyte, then you need five petabyte to just store those videos. And also remember we talk about you use a VAE to compress the videos, and you also need to store, typically you need to store those continuous feature, in-- also in your storage. That's also comparable size with the videos themselves. So just storing these videos and the features is tens of petabytes alone. And,Swyx [00:33:58]: I just, I just looked up the calculation. Five petabytes on S3 Standard is one hundred K per month.Ethan [00:34:05]: AndSwyx [00:34:05]: It's comparableEthan [00:34:05]: and you needSwyx [00:34:06]: AndEthan [00:34:06]: And then like tens of petabytes, two hundred K. And even more expensive is you have the ingress and egress.Swyx [00:34:13]: Oh, yeah.Ethan [00:34:14]: Like you-- through the internet. You have to just to download those videos, I believe it's, it's more expensive on AWS than just storing those videos.Swyx [00:34:25]: Storing, yeah.Ethan [00:34:25]: And each training runs, you probably need to pull them once. If you train multiple times, it's, it's even more than that. So it's like just storing the network, those costs is just, it would be a few, a few millions per month to just storing everything, not to mention the GPU cost.Ethan [00:34:45]: AndSwyx [00:34:45]: my side tangent, the compute rental, like GPU rental is very efficient. There's one side, okay, you can be XAI and build your data center. Should we not just build our, storage compute as well? LikeEthan [00:34:57]: Of courseSwyx [00:34:57]: cloud cost compared to just,Ethan [00:34:59]: You save so muchSwyx [00:35:00]: store. Yeah, exactly.Swyx [00:35:01]: Especially with like egress and stuff. So.Ethan [00:35:04]: That's a good idea, but it also comes to-- there are some of its own challenges.Swyx [00:35:09]: Of course, of course.Ethan [00:35:10]: like people who build the GPU data centers, they might not expect this much, storage. And yeah, people build storage, typically they just build it somewhere with just CPUs.Swyx [00:35:23]: I just looked it up. Five-- AWS only charges for egress, not ingress. Tier five for five petabytes is two hundred and thirty K.Ethan [00:35:32]: Even more expensive than the storage.Swyx [00:35:34]: But storing is per month, right? You check in, then you cannot check out. so it's so cool. It's okay. So there's that side.Ethan [00:35:41]: So the TLDR, my backhand mathSwyx [00:35:42]: Data is larger than you think. Yes.Ethan [00:35:44]: my backhand math of GPU hours times GPU cost is also very much, I'm missing some storage.Swyx [00:35:49]: You're also-- you're basically like also more IO bound than normal training.Swyx [00:35:55]: Yes. ‘Cause like data loading, so caching everything, it becomes super important.Ethan [00:36:00]: So in Cosmos, we did a lot of optimizations to make it not IO bound. So, speaking of the training, actually training the model, the GPU cost, if you look up like the open source model, how big these video models are, I think like LTX has nineteen B parameters. That's a dense model. And people are also exploring, MoEs, so it might be twenty B active and, like a hun- hundreds B, total. So that's, that's even-- that's similar size as medium-sized LLM models. And if you, if you look at number of tokens-Uh, we disclose that in Cosmos. It's also like tens of trillions of tokens on the visual tokens. So putting this together, the cost of, training these video models, it's actually comparable with LLMs. Not to mention, the infra is slightly different from LLM, so it might be less efficient to train these models.Inference Speedups: Step Distillation, Consistency Models, and GANsSwyx [00:37:04]: Do you get the benefits of traditional diffusion speed-up? So for, images, there's LCM, LoRAs for, fine-tuning. There's, there's a lot of stuff that's beenEthan [00:37:15]: Flow matching.Swyx [00:37:16]: there's flow matching. There's a lot of stuff that's been done. there's some overlap that applies to diffusion on the inference side and stuff or?Ethan [00:37:23]: so the difference-- the inference side is a completely different story.Ethan [00:37:28]: I think for the training side, it might be a little bit hard to reduce that cost. And for the inference side, the biggest gain is from the distillation of these models. You can-- It's called step distillation, slightly different from knowledge distillation in LLMs. So you-- Typically, for flow matching models, you need like 100 steps or something. Like a distortion model even need even more, like 1,000 steps to generate a good image or video. A step distillation is try to learn to generate fewer step from the model itself. It's kind of like now we-- you use the full model to generate in 100 steps, and then you take a model that only generate 10 steps and let that model to learn from the perfect one.Ethan [00:38:25]: why this workSwyx [00:38:27]: Strong to weak seemingly.Ethan [00:38:28]: It is. It's kind ofSwyx [00:38:29]: DistillationEthan [00:38:29]: kind of like strong to weak. the-- from the modeling perspective, the strong model, the teacher model is trying to model the image and videos of inter-internet, and that distribution is extremely complex. But the step distilled model is just trying to learn from the teacher. The teacher is a model, and the size is fixed, as the distribution is much simpler than the whole internet. That's the intuition I have why step distillation can work. So usually these models serve in productions, they only run in a few steps. In Cosmos, I believe we have, we have like four step and eight steps. If you do some simpler task, image-image translation, it can even run in fewer step, like one step in Cosmos Transfer.Swyx [00:39:22]: I think this is the same intuition that guides a lot of the consistency model work. I sent you a link for, SCM. I don't know if you covered that. To me, that was actually one of, the most impressive papers I've ever seen from OpenAI.Swyx [00:39:34]: That this is the unifying grand concept of consistency models. I don't know if you have any comments on this.Ethan [00:39:41]: So there are, there are a few different approaches,Swyx [00:39:46]: Oh, yeah. Here it is.Swyx [00:39:47]: Two steps versus twenty or 100 steps, whatever. It's already done.Ethan [00:39:52]: So there are, there are a few different approaches, for example, consistency model, and there are also Actually, we shouldn't forget GAN. So GAN, actually, that was, that was the OG ofSwyx [00:40:05]: OGEthan [00:40:05]: step distillation ‘cause it trained just one step to begin with. So actually, a lot of, uh-- For example, there's a distribution matching distillation which use, which uses GAN, as one of the laws for distillation. It-- GAN just tells you, “Hey, generate an image,” and thenEthan [00:40:31]: it has a discriminator to tell, is this image real or not? So the model, the model just need to learn one of the distribution, not the full distribution. Because in training, the model is asked to reconstruct the ground truth image from the internet, which is extremely hard. And in-- When you're training GAN, it's a step process. It's just a, “Hey, you generate image. Does this image look as real as the image from the internet?” Which is a much simpler task. And, yeah, combining a lot of these approaches together, people typically do that, like consistency model and distribution matching and GAN, and we can get these few step models.Audio-Video Generation and Time AlignmentSwyx [00:41:21]: Then there's one step I wanted to add, which is audio and video.Ethan [00:41:26]: So, Grok Imagine zero point nine, I believe it's, it's a first audio video transmodel deployed at a large scale. SoSwyx [00:41:39]: And that was your first model?Ethan [00:41:40]: that was, Grok Imagine's first model. It's, it's audio video, joint generation. I think the hard part is, the modality alignment, ‘cause before this transmodel, we have, we have text to video alignment. We have this, correspondence between text and video. Typically, most of the VLMs, they understand images and videos. Video's very rare, and they don't understand audio mostly. And if you look at the audio generation on the LLM side, you can talk to them perfectly fine, but if you ask them to sing a song or something, it typically is not very good. Also, they don't have, they don't have music either. The hard part is thatUh, actually audio has two component. It has like a discrete component, a continuous component. The discrete component is like the language.Ethan [00:42:44]: So when we speak, it's just, someSwyx [00:42:47]: It's an ASR issue, yeah.Ethan [00:42:49]: It's, it's text token with some characteristics, I would say.Ethan [00:42:54]: But musicSwyx [00:42:56]: I think the speech guys would disagree with this.Swyx [00:42:57]: Like disfluencies and then,Vibhu [00:43:00]: There's tones you can get angry.Ethan [00:43:01]: Well, I say largely.Ethan [00:43:03]: the mu- but the music is completely different. It's, it's very continuous, and you cannot model them like discrete tokens in language models. this is like the hard part for models is, not to mention we have to align text, video, and audio together.Ethan [00:43:26]: SoVibhu [00:43:26]: How?Ethan [00:43:28]: So significant-- some significant challenges are like-- So first, like we talk about as the VLMs, they cannot understand most of them cannot understand audio.Ethan [00:43:39]: So you have to have some way to do the synthetic data generation for audio. You have to caption the model, and that involve, that involve synthetic data and human data effort a lot. And not just surprisingly, most of the LLMs are very bad at recognizing, like the beat, tone, and the details of the of music. They can, they can give some general prediction of which song is this, but it's very hard to describe the details of the music. like we mentioned in image generation, like you have to describe image as detailed as possible so that someone blind can reconstruct that. So here is like someoneVibhu [00:44:32]: DeafEthan [00:44:32]: someone deaf can reconstruct how the music sounds like without actually listening to it. Maybe you can think of it need to have the-- or they call the script.Vibhu [00:44:49]: Subtitles, yeah.Ethan [00:44:49]: You gotta have all the details of the music, and the dialogue.Vibhu [00:44:55]: So is the challenge there typically stuff like music and audio, or is it just Like is there a baseline? Okay, there's enough data where we can understand, narration, conversation, but there's nuances in audio that's where you hit all the data issues or is it just from stage zero, you just do it all right?Ethan [00:45:15]: So one important thing is like the alignment. So the model, the model has to know like the video and audio, the, uh-- it has to have a time-based alignment, like at which time step the video and the audio token correspond to each other. But we actually don't have this kind of alignment for most of the other modalities. If you think about like text and image, text and video, they are loosely aligned. So you can, you can have a description of what's going on in the video, but you don't have to exactly, You typically don't have exact description, oh, at, time step one second like what happened?Vibhu [00:46:02]: It's veryEthan [00:46:03]: At time step two second what happenedVibhu [00:46:03]: coarse. Yeah.Swyx [00:46:05]: So what was the ideal time step? You have to oblate it, and then it's like four seconds or something.Ethan [00:46:09]: So that comes down to how you design the model to, for the model to be aware of as a time, as a time modality. So the model is like a time aware. And that's something pretty unique if you think about LLMs. So if you ask LLM to complete a task, say they, uh-- you ask them and they will say, “Oh, this task will probably take twelve hours to complete,” and they come back in one hour. Say “I've already spent two days on this and I've exhausted everything.”Ethan [00:46:47]: So the LLMs them-themselves, they don't have a sense of time there.Vibhu [00:46:53]: I actually don't think that's just them not having a sense of time. I think it's somewhat based, right?Vibhu [00:46:58]: Like you tell someone, “Okay, go work on this feature. Go implement this,” there's a general understanding you would have of how long that would take without LLMs working at LLM speed, right? So you think back like two years ago, if I tell you to like build me like a new front end for latent space, have a search bar, have all this, you'll estimate that it'll take a few days, right?Vibhu [00:47:19]: So you tell an LLM, “Go build this.” It'll take me a few days. But I think it's somewhat grounded as opposed to them not having the best-- Not saying that they have a great understanding, but I think that example is like you can see where it comes from, right? You're trained on all over the text.Swyx [00:47:35]: They're, they're trying to estimate what a human would say.Vibhu [00:47:37]: because that's what the, that's what the data kind of represents. It's not themEthan [00:47:41]: It came from the corpus on the internet. People have a estimate of how much time.Vibhu [00:47:45]: And not even just in direct like training samples, right? Just your world understanding of tokens of how long stuff takes, right? Go read a book. It'll take you a while, right?Vibhu [00:47:56]: Even if you do nothing but read a book, it takes a few days. So yeah, LLM, I read it took me a few hours.Vibhu [00:48:01]: It'll take me a few hours to go through this research. But this is a tangent.Swyx [00:48:05]: Somewhat, yeah.Swyx [00:48:06]: This is a train of thought I haven't really expressed until now is, which is basically like a full world model must also be recursive, meaning that the participant in the world model must also be aware that they have a world model. which is like this whole recursive thing down the, down the line. but yes, and that the world model can be wrong and that they need to update it and blah. Yeah. We've, argued this on the, newsletter as well, that there needs to be sort of recursive or adversarial world models.World Models: Real-Time, Long-Horizon, Interactive VideoVibhu [00:48:34]: just, to ask, how do you define world model?Swyx [00:48:38]: Oh, yeah, let's go there.Ethan [00:48:40]: SoVibhu [00:48:40]: So just for context, we talked about, video generation, and then there's a-- if you say there's a distinction between world models, what's your, what's your definition? How do you see the two?Ethan [00:48:53]: So disclaimer, I'm not going to debate, what is world model. Yeah. there are many definitions, so I'll just talk about my definition. Since I came from the multi-model, multi-model domain, so mainly talking from video. So world model is like real-time interactive long horizon videos. So there are three parts. so we-- let's talk about them one by one. So the so interaction, so we just, we just look at Facebook and neural computer. So the interaction part of it, so you, world model can allow you to interact with them through keyboard, mouse, and maybe also voice. So these all is-- all is a modality. You can, you can interact with the model, and the model should respond reasonably. Second part is real time. So once you, once, say, you move your mouse, if, say, the world model generate a game, how fast can the game respond? So if you're like professional CS: GO players- -my say, oh, you have to respond- He's beginner within sub ten milliseconds or- Yeah even less. So that's not most of the- No, sixty FPS. Let's go. Oh, three hundred FPS. Oh, five hundred FPS. Wait. okay, yeah. I didn't do the math, but yeah, okay. Uh- Yeah, three hundred FPS, that's a three millisecond. So you have to respond- Oh, s**t. Okay. YeahEthan [00:50:29]: within a millisecond. Most of the video models cannot do that. Yeah. And, but if you, say, if you have a video model that is, say, like a digital human, the response time might be more generous. Maybe typically, for real-time voice interaction, it's like two hundred millisecond. So that's, that's much more generous. But even two hundred millisecond is pretty, it is pretty tricky, ‘cause remember we mentionedEthan [00:51:01]: you have this, temporal compression coming from the VAE. So if you, if you don't compress the temporal dimension, your sequence length is going to explode. So if you want to have this real-time, real-timeness in your model, you have to do is one context problem. And the third part is long horizon, ‘cause we-- if you're not going to just play with, video games just, a few seconds, most video models only a few seconds. We're going to play with minutes, hours. The model have to be able to generate long-form content.Ethan [00:51:42]: So putting these three together, it's, real-time, long horizon interactive videos. I think the final state will be, for example, like a video, a video version of Playbook, where you can, you can interact with, a neural computer. You move your mouse, and you click on the generative interface, and it will reply to you through pixels- generating in real time. But getting there, it's, it's a very long way to get there. So one of the first step, at Grok Imagine, where I led a small world model team there, was to build video extension. So, video extension- it's the first step of interactivity. Yeah. It's, it's the first step. Yeah. So it's the first step- You have it here, video editing, yeah. Yeah. Yeah. So the first step is because, this unlocks long horizon videos. Typically, for most of the video generation models, you give it a prompt or an image as an initial frame. You generate video, that's it. That's just, one time, done. And some creators would try to, use the last frame as a first frame for the second video. It can-- sometimes it works, but if you do it a few times, it says the quality would decrease. And- It doesn't have that context- Yeah over the full video, so the temporal- Yeah, exactly. Yeah, ‘cause you only gave it the last frame, of course, right? Yeah. Exactly. And- it's actually a pretty fun hack. if you've seen like- Oh, no, he's saying something better. Yeah. And for example, like Vue, I remember Vue 3 has like a second context of the last video. It is slightly better than using the last frame, but it has the same problem-- similar problem that it, the quality would decrease. if you extend a few times to, one minute, the video quality would look much worse than the first video. Second, another problem is that the model doesn't have long-range knowledge of, what's happening before. Say, if they generate some dialogue, some, two people speaking, and their voice might change, over some time, especially if the second conditioning, it does not cover the previous context. So these are the core challenges. So the Grok Imagine video extension, it has historical context of all of the previous generated videos. It can, It has, it has the context of, who is speaking and what objects have appeared and everything, having that to generate the next video. So if we naively do this, you can imagine, just, put all of the previous history video tokens into the context. The context lens will easily explode. Especially for video models, that can be like a few, a few million context, I would imagine- context lens. Yes.Yeah.Swyx [00:54:58]: Let's run with that.Ethan [00:54:59]: for example, like in Cosmos, I think just five seconds of video is like a fifty K or sixty K number of tokens. So like if you do, if you do fifty second, that's a five hundred K tokens. If you do longer than that, easily explode. This long horizon, problem was the first step we're trying to solve world model. It turns out people, yeah, people love video extension. Like a lot, a lot of the creators love using video extension to create longer form videos. This is the part I liked that you have a, you have an intermediate step toward the final goal instead of just a straight shot to the final version very much.Swyx [00:55:48]: But I can see you have a strong vision of where we want to end up.Long Context, Redundancy, and Efficient Interactive VideoVibhu [00:55:51]: Does it seem like it's an efficiency issue? okay, we're at a few million tokens context,. If you draw the parallel to language models, we had very short context, two thousand, eight thousand, then, you scale it up one million, ten million. sure, there's effective context, but at the end of the day, it's just what's it worth? sure, there's a whole training data side. In video, it might be slightly easier ‘cause we have a hundred million token video, right? Just take a movie with the full context there. Like is this efficiency from an inference standpoint that like it's expensive, but we know how to solve it? Or like why is this not the approach? So like my broader point was on your second point of world models, you say it needs to be interactive and live, right? You should be able to play a game and see the interaction live. So one thing I see with research is a lot of what you actually serve is different than what you build, right? So we talked about distillation. You train big model, you distill it, you do quantization, speculative decoding. We do all this stuff to serve it efficiently. Should we not just have a solution, like a world model that can interact well, do inference optimization, serve it, distill it secondary, so make it real time after you solve it? So like a-- another parallel is say, continual learning, right? What we need is someone to solve it and show it works inefficiently. Give it a few years, people will make it efficient. Same thing with regular attention, right? It worked. Over a few years, people have different forms of attention, and we've scaled it to be efficient at log context,? So kind of two things there, right? One is it seems like it works. You've scaled it. Can we not just scale it a lot more efficiently over time? Do we need a separate approach if this works? And same thing with interaction, right? if we can get it done, like if we can solve some way that it works, we can solve making it more efficient from an inference standpoint later.Ethan [00:57:53]: that's actually a very good point. So in videos, there's actually a lot of redundancies. So we solve a lot of the pixel redundancy from VE, but there's more redundancy in long range and long horizon videos. Say, if a character appear in the first clip and then it disappeared, it only reappear at the end of the video, you probably don't need the-- the context, like in the middle of the generation. So you only need that character, where you need. So that's why, I helped build another feature. It's a reference video.Vibhu [00:58:36]: Is it here?Swyx [00:58:36]: is it the same model release or different one?Ethan [00:58:39]: It's a different one.Ethan [00:58:41]: You probably need to search onSwyx [00:58:43]: I'll find itEthan [00:58:43]: X reference to video.Ethan [00:58:46]: So reference video allow you to like upload up to seven images as condition and generate the video. Say, if like I want-- it can, it can be characters or objects or even scenes. Say like I want, I want condition on, Sean's selfie and holding a bladeSwyx [00:59:07]: We have a dogEthan [00:59:08]: or whatever.Swyx [00:59:08]: We put the dog in the thing.Ethan [00:59:09]: you can put them there and the video models will generate the video from and copies the context over. So that can solve a lot of the problems there, like the long context problem. It doesn't need to have a very long context, but it's-- I feel like it's an intermediate solution. The modelSwyx [00:59:29]: It's cheating.Ethan [00:59:30]: the model should be able to like selectively know, where should I draw the references. So say if I want to generate a movie, I generate it autoregressive, like a ten second at a time or something. And now this character appear, I can look back to where it first appear and, bring that back. Yeah, this one, I put the references. Yeah, that's, Optimus, Einstein myself, Annie.Vibhu [01:00:02]: Oddly enough, I used Grok Search to find it, and it pulled your LinkedIn post. But yeah we found it.Ethan [01:00:08]: Interesting.Vibhu [01:00:10]: ButxAI's Underrated Work, Culture, and WatermarkingSwyx [01:00:11]: this is a problem. This is not your fault, but like XAI doesn't communicate all this work that you do very well because they just have the model release and then that's it. But actually, these details are very good.Swyx [01:00:22]: As far as I understand, everything you just described is state-art, like no one else has done it.Vibhu [01:00:30]: A lot of-- yeah, I have a lot moreSwyx [01:00:32]: And then, and then you just put this blog post with the cookies. I'm this is not enough,?Swyx [01:00:37]: but I, obviously this is like the high level numbers that people want to know. But no, okay, soVibhu [01:00:42]: And I wonder, like part of that is also some labs don't share research into what happens. And ifSwyx [01:00:50]: No, but this is literally bragging about how good they are, right?Swyx [01:00:54]: Like, why would you not say that you are capable of extending with full context? this is not a secret sauce. This is like we did the work. yeah, I don't know.Ethan [01:01:02]: different labs have slightly different communication styles.Swyx [01:01:07]: Anyway, if anyone from XAI is listening we are always happy to help you tell your story. Yeah, okay, so you did references, and I think, I think kind of the point you're, you're making is it is sort of like a kludge, right? this is-- you can do seven, but what about 100?Swyx [01:01:23]: Right? Then you need a completely different thing.Ethan [01:01:26]: So I think it's-- this is, a mechanism to, select the context from the history, and you might not put the entire history into the context. for example, there's a paper called Frame Pack, which haveEthan [01:01:41]: a heuristic that the latest history, the last one second, I put the entire history, and the history before that, I would, compress it and makes the video smaller. So they follow this pattern, this build overall pattern that the maximum sequence length is fixed. So the further you are from the current frame, you have a smaller image. So this is just a heuristic. I think it can be more automatic. The model is aware like which history part of it can be select. So this part of the research is actually being actively, worked on by a lot of people. It's also quite interesting. I feel this is actually, this part of long context is a little bit ahead of the LLM part.Ethan [01:02:31]: So for example, like in LLMs, if you-- so contexts keep growing. Let's say if you call tool and the tool call history is extremely long, that's still in context, and keep growing, keep growing. Even if you switch the topic to something else, the whole context was there. There are some agentic harnesses that help you to, say, prune the tool results and, prune Like when you, when you query a file, only show like the top 200 lines or something. Those were very heuristic-driven.Swyx [01:03:08]: For listeners, we did a write-up on the cloud code, leak where there are eight different kinds of pruning, including like you prune the tool results and all that. So you can, you can read up on that kind of thing.Ethan [01:03:17]: I think, one breakthrough in continual learning might be like a way to automatically, manage its own context.Swyx [01:03:27]: These are all heuristics, and they will be replaced by machine learning.Ethan [01:03:30]: InterestinglyVibhu [01:03:32]: TheEthan [01:03:32]: the same thing is being researched in both LLMs and video models.Vibhu [01:03:36]: The interesting thing is also like in the paper you showed, it's actually happening at the model level, right? Compared to like language models, sure, we have base attention, but we'll do our own compression, we'll do our own pruning, which is separate from model error.Vibhu [01:03:49]: Eventually, it all just boils in, hopefully.Swyx [01:03:52]: I think this is a form of like attention, but like also know sort of reasoning attention. I feel like that's different than normal attention.Swyx [01:04:03]: Does that, does that make sense?Ethan [01:04:04]: It's, it's different in the sense that attention, not to mention, set sparse attention aside,

“Mastering the gray areas is to doing business in China what political correctness is to corporate America: MANDATORY.”Westerners often parachute into China assuming strength, clarity, and leverage translate cleanly across cultures. They don't.China operates in a gray zone—where ambiguity is tactical, patience is power, and absolutist, black-and-white thinking quietly destroys influence.In this video, I explain why:Guānxì (关系) explains HOW relationships operateLìyì (利益) explains WHAT people considerYīnyáng (阴阳) explains WHERE decisions actually liveChina's “maddening vagueness” isn't incompetence or evasion. It's a pragmatic system designed to preserve Face, share risk, and keep future options open.If you're frustrated by indirect answers, shifting commitments, or a lack of accountability, the problem usually isn't them—it's the questions you're asking.This episode reframes Yīnyáng not as an ancient philosophy but as a modern psychological operating system that governs leadership, negotiation, ethics, and survival in China's business landscape.If you want to lead, negotiate, or build teams in China, mastering the shades of gray isn't optional.

Out of Collective Podcast – E27 – FLIPBOOK w/ Parkin Costain Big lines, bigger vision — Parkin Costain is back with Flipbook, a new ski film stitched together from a winter of pure momentum. Known for his explosive style and down-to-earth creativity, Parkin opens up about the process behind his [...] The post Out of Collective Podcast – E28 – FLIPBOOK w/ Parkin Costain appeared first on Out Of Collective.

Ankle Foot Orthoses (AFOs) are essential in neuro rehab yet can be an area clinicians feel a lack of knowledge. This episode is for the clinician who is both - super knowledgeable about AFOs, AND the clinician who could use more education. Hosts Erin Gallardo, PT, DPT, NCS and Claire McLean, PT, DPT, NCS interview Dr. Jennifaye Brown, PT, MSPT, PhD, NCS, CAPS about her work transforming the way we think about ankle-foot orthoses (AFOs) for stroke survivors. Her approach goes far beyond traditional medical practice, focusing on personalization, functionality, and patient empowerment. Her level of understanding on the topic will leave even seasoned therapists with insightful takeaways. Dr. Brown doesn't just see AFOs as medical devices, but as tools that can dramatically improve a stroke survivor's quality of life. Her book, "Brace Yourself: Everything You Need to Know About AFOs After Stroke," was written to empower stroke survivors and their caregivers with comprehensive, accessible information about AFO selection and use. Yet there are important sections for healthcare professionals as well. It is an essential tool for the clinic.   With a PhD in exercise science and decades of clinical experience, Dr. Brown continues to push the boundaries of stroke rehabilitation. Her work reminds us that true healing goes beyond medical interventions - it's about understanding, adapting, and empowering individuals to live their best lives. jvb physical therapy services, llc Order ebook (Flipbook or PDF): jvbneuropt.com/book Website: jvbneuropt.com LinkedIn: https://www.linkedin.com/in/jennifaye-brown-pt-mspt-phd-ncs-caps/ YouTube: https://www.youtube.com/channel/UC-0M-apffkZl4vqjAqomd8g

In dieser Folge des ESG-Talk-Podcasts spreche ich, Stella Ureta-Dombrowsky mit Karina Forchtmann und Lina Weigel, zwei engagierten Projektmanagerinnen beim SDG-Scouts-Programm. Ein Programm, das junge Menschen in Unternehmen dazu befähigt, die Nachhaltigkeitsziele der Vereinten Nationen (SDGs) konkret umzusetzen – und dabei echte Veränderung im Arbeitsalltag zu bewirken. Gemeinsam werfen wir einen Blick hinter die Kulissen dieses besonderen Weiterbildungsformats, das über einen Zeitraum von sechs bis acht Monaten läuft und mittlerweile über 400 Teilnehmenden aus unterschiedlichen Branchen und Unternehmensgrößen ausgebildet hat. Karina und Lina erklären, wie die Workshops, Praxisphasen und das Train-the-Trainer-Konzept aufgebaut sind, welche Themen die Teilnehmenden besonders bewegen – und wie wichtig Selbstwirksamkeit, Teamarbeit und Motivation sind, um Nachhaltigkeit im Unternehmen wirklich zu verankern.   Wir sprechen über: die Herausforderungen junger Menschen im Angesicht globaler Krisen das Gefühl von Ohnmacht – und warum konstruktive Ansätze so entscheidend sind die Rolle von Empathie, Sinn und gemeinsamer Verantwortung im Arbeitskontext  

Chime In, Send Us a Text Message!In this episode, Dr. Jennifaye V. Brown shares her journey into neuro-physical therapy, emphasizing the importance of personalized care and the role of movement in recovery. She discusses her specialization in AFOs (ankle-foot orthoses) and how they can be tailored to individual needs. Dr. Brown highlights the significance of empowering patients through education and the benefits of aquatic therapy for stroke survivors. She also addresses the balance between using AFOs and maintaining muscle recovery, and shares her vision for future innovations in therapy, including the development of an app to enhance patient engagement and education.TakeawaysDr. Brown's journey into neuro-PT was inspired by her family background.Walking is a fundamental and accessible form of exercise.AFOs should be customized to fit individual needs and lifestyles.Patient empowerment is crucial in the recovery process.Aquatic therapy offers unique benefits for stroke survivors.Communication between therapists and patients is essential for effective care.Therapists should focus on teaching patients how to maintain their health long-term.Regular assessments and adjustments to AFOs are necessary as patients progress.Dr. Brown emphasizes the importance of movement science in therapy.Future innovations in therapy could include technology to enhance patient education.Author: Brace Yourself: Everything You Need to Know About AFOs After StrokeOrder Book From: AmazonOrder ebook (Flipbook or PDF): jvbneuropt.com/bookWebsite: jvbneuropt.comBusiness: jvb physical therapy services, llc.Cell: 843.364.5089Email: info@jvbneuropt.comLinkedIn: Support Our Show! Thank you for helping us to continue to make great content. We appreciate your generosity! Support the showShow credits:Music intro credit to Jake Dansereau. Our intro welcome is the voice of Caroline Goggin, a stroke survivor and our first podcast guest! Please listen to her inspiring story on Episode 2 of the podcast.Connect with Us and Share our Show on Social:Website | Linkedin | Twitter | YouTube | Facebook | SubstackKnow Stroke Podcast Disclaimer: Our podcast and media advertising services are for informational purposes only and do not constitute the practice of medical advice, diagnosis or treatment. Get Our Podcast News Updates on Substack

In this special episode of the ESG Talk Podcast, things get personal, physical – and hormonal! Stella Ureta-Dombrowsky dives into a topic that's rarely linked to finance but has a powerful impact: the female cycle. You'll discover how our hormones – depending on the phase of our cycle – influence our risk-taking, spending behavior, and financial planning. And how this knowledge can help you make smarter money moves. It's not a taboo – it's a total gamechanger.   Here's what to expect: Why your cycle phases are more connected to your investments than you might think When it's the best time for budget reviews, financial decisions, or salary negotiations How to build new money routines with cycle-tracking apps, journaling, and a money-mood tracker Tips for more clarity, fewer impulse buys – and a stronger money mindset Quick and powerful takeaways: Your cycle directly impacts your financial decisions Menstrual phase = time for reflection and planning Ovulation phase = energy for negotiation and big ideas Luteal phase = financial hygiene, slowing down, and clarity Cycle awareness = decision-making power Combine cycle apps with finance tools – your rhythm matters Journaling and mood tracking reveal your money patterns Your cycle is not a weakness – it's your superpower   Let's talk money – cyclical, conscious, empowered. If you loved this episode, feel free to share it with a friend, colleague, or money buddy. And if you'd like to support this podcast: leave a rating or hit subscribe – it helps our community grow.   ESG-Talk-Podcast: Social Media: Linkedin: https://www.linkedin.com/showcase/esgtalkpodcast Instagram: https://www.instagram.com/esg_talk_podcast/   Podcast - Links: Spotify: https://open.spotify.com/show/0NUvvcweDOrPFQFaWTtMEl Apple: https://podcasts.apple.com/ch/podcast/esg-talk-podcast/id1682453395 Youtube:  https://www.youtube.com/@ESG-Talk-Podcast-Start-2023   Female Finance (Deutsch) - WhatsApp-Gruppe: https://chat.whatsapp.com/KL7yiAlWs092N6Iw4ICmnl   Female Finance (English) - WhatsApp-Gruppe: https://chat.whatsapp.com/BQ5UyixvQHBGv4PGZNcKRC   Female Finance (Español) - WhatsApp-Gruppe: https://chat.whatsapp.com/KntWHL7LyEuAluXl8RWn8H   ESG-Talk-Booklet - German (free download) Flipbook; 1. Ausgabe: https://online.publuu.com/637375/1437254 Flipbook; 2. Ausgabe: https://publuu.com/flip-book/637375/1813017 Download: https://www.trimpact.net/esg-talk-booklet/   ESG-Education  - German (free download) Themen wie CSRD, ESRS, ESG-Reporting, Planetare Grenzen, Nachhaltige Investieren und Frauen und Finanzen, Empfehlungslisten 2023 & 2024 Download: https://www.trimpact.net/esg-education/   Contact: Stella Ureta-Dombrowsky https://www.linkedin.com/in/stella-ureta-dombrowsky/ sd@trimpact.net www.trimpact.net

Stella Ureta-Dombrowsky takes you on a journey to discover your personal values compass. Because your finances shouldn't just work – they should reflect who you are and what truly matters to you. What if investing could smell like freedom, taste like justice, or sound like the future? This episode dives into exactly that: how to identify your values and bring them to life in your financial decisions. With clear insights, honest questions, and hands-on tips, Stella shows that sustainable investing isn't just a trend – it's a powerful statement. For women. For everyone who wants to align their money with meaning. Takeaways: Your core values have a powerful impact on your financial strategy. Money is neutral – but how we use it is not. Ethical banks matter when it comes to responsible investing. Small steps in investing make a big difference. Values like social justice and independence are key. Promoting women in business is essential. Microfinance can create real social and economic change. Reviewing your current bank is a crucial first step. Diversification is essential for successful investing. Awareness of your values is the first step toward financial empowerment. Chapters 00:00 Introduction to Female Finance 02:30 The Values Compass and Why It Matters for Your Finances 07:31 Sustainable Investing: The How and the Why 10:47 Practical Steps to Align Your Money with Your Values ESG-Talk-Podcast: Social Media: Linkedin: https://www.linkedin.com/showcase/esgtalkpodcast Instagram: https://www.instagram.com/esg_talk_podcast/   Podcast - Links: Spotify: https://open.spotify.com/show/0NUvvcweDOrPFQFaWTtMEl Apple: https://podcasts.apple.com/ch/podcast/esg-talk-podcast/id1682453395 Youtube:  https://www.youtube.com/@ESG-Talk-Podcast-Start-2023   Female Finance (Deutsch) - WhatsApp-Gruppe: https://chat.whatsapp.com/KL7yiAlWs092N6Iw4ICmnl   Female Finance (English) - WhatsApp-Gruppe: https://chat.whatsapp.com/BQ5UyixvQHBGv4PGZNcKRC   Female Finance (Español) - WhatsApp-Gruppe: https://chat.whatsapp.com/KntWHL7LyEuAluXl8RWn8H   ESG-Talk-Booklet - German (free download) Flipbook; 1. Ausgabe: https://online.publuu.com/637375/1437254 Flipbook; 2. Ausgabe: https://publuu.com/flip-book/637375/1813017 Download: https://www.trimpact.net/esg-talk-booklet/   ESG-Education  - German (free download) Themen wie CSRD, ESRS, ESG-Reporting, Planetare Grenzen, Nachhaltige Investieren und Frauen und Finanzen, Empfehlungslisten 2023 & 2024 Download: https://www.trimpact.net/esg-education/   Contact: Stella Ureta-Dombrowsky https://www.linkedin.com/in/stella-ureta-dombrowsky/ sd@trimpact.net www.trimpact.net

In this opening episode of the summer series "Emotions and Money – sustainable, secure, free!", Stella Ureta-Dombrowsky talks about an often underestimated topic: the menopause - and what it has to do with your financial future. With personal insight and well-founded facts, she shows why financial self-determination is essential, especially in this phase of life. It's about pension gaps, emotional upheaval, care work and the big question: How free am I actually - financially too?

Get the book, RIGOR Unveiled: A Video-Enhanced Flipbook to Promote Teacher Expertise in Relationship Building, Instruction, Goals, Organization, and Relevance About The Author   Douglas Fisher, PhD is professor and chair of educational leadership at San Diego State University and a teacher leader at Health Sciences High and Middle College. He has published numerous articles on reading and literacy, differentiated instruction, and curriculum design, as well as books such as The Teacher Clarity Playbook 2/e, Your Introduction to PLC+, The Illustrated Guide to Teacher Credibility, The Teaching Reading Playbook, and Welcome to Teaching!. In 2022, he was inducted into the Reading Hall of Fame by the Literacy Research Association.   This episode of Principal Center Radio is sponsored by IXL, the most widely used online learning and teaching platform for K-12. Discover the power of data-driven instruction in your school with IXL—it gives you everything you need to maximize learning, from a comprehensive curriculum to meaningful school-wide data. Visit IXL.com/center to lead your school towards data-driven excellence today.   

This week the boays are joined by comedian Liam Farrelly. Liam discusses how he had to commit "a small act of fraud" in order to get married in Wales, his experience gigging in (and nightmare flight to) Saudi Arabia, and recounts losing his virginity at a house party.Liam is performing his show "Flipbook" at Oran Mor on 30th March as part of the Glasgow Comedy Festival. Tickets here: https://www.glasgowcomedyfestival.com/performances/liam-farrelly-flipbook/Sign up to our Patreon for extra episodes and bonus content including access to all our live shows here:⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.patreon.com/somelaugh⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Marc is going on his first UK & Ireland tour in the summer of 2025 (now with added shows in Glasgow & Bristol) Tickets are on sale here now: ⁠⁠⁠⁠⁠⁠⁠⁠https://tour.marcjenningscomedy.com/⁠⁠⁠⁠⁠⁠⁠⁠Stuart is currently on a UK tour.  All dates & tickets here: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.stuartmcpherson.co.uk/live-gigs⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠You can watch Stu, Marc & Steve's stand-up specials on the Some Laugh YouTube channel here: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://youtube.com/playlist?list=PLM6lKn8dnMK5bOtlX-3XlCpZSf-B_qweQ&si=JjKknRTZvvza5l55⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Stand-Up Tickets:Marc: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://linktr.ee/MarcJenko⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Stu: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://linktr.ee/StuartMcP⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Steve: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://linktr.ee/stephenbuchanan⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠You can follow Some Laugh on ⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠⁠Twitter⁠⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠⁠TikTok⁠⁠⁠⁠⁠⁠⁠⁠ - and please remember to leave a 5 star review!

In dieser Episode erfährst du, wie du die kraftvolle Energie des Neumonds im Schützen nutzen kannst, um deine großen Visionen zu entfesseln – und das ganz ohne Stress oder Überforderung. Ich teile mit dir: Warum der Schütze-Neumond ideal ist, um langfristige Ziele zu setzen Wie du deine Visionen mit Leichtigkeit und Klarheit angehst Eine persönliche Geschichte darüber, wie ich selbst von „hart“ auf „smart“ umgestiegen bin Praktische Übungen und Inspirationen, die dir helfen, den ersten Schritt zu gehen Lass uns gemeinsam die Pfeile unserer Träume abschießen – entspannt, fokussiert und voller Vertrauen! Highlights der Episode: Was die Energie des Neumonds im Schützen ausmacht Meine persönliche Erfahrung mit „smart statt hart“ im Business Wie du deine Vision in kleine, smarte Schritte unterteilst Praktische Übungen für den Neumond – von Vision-Boarding bis zur Ausrichtung Erwähnte Ressourcen: Folge mir auf Instagram und LinkedIn: https://www.linkedin.com/in/deniseantoinettesonderegger/  https://www.instagram.com/astrologie_business/ um noch mehr Inspiration zu erhalten Welche Vision möchtest du mit der Schütze-Energie verwirklichen? Schreib mir auf Instagram oder LinkedIn – ich freue mich, von dir zu hören! Hast du schon dein Jahr 2025 geplant? Mit meinem Angebot unterstütze ich dich dabei, mit astrologischen und energetischen Tools deine Ziele zu definieren und smart zu erreichen. Blättere gerne durch mein Flipbook: https://www.denisesonderegger.com/mein-angebot-2025-detailliert/ Bleib inspiriert und denk daran: Großes entsteht durch Klarheit, Leichtigkeit und den smart statt hart-Ansatz. Bis zur nächsten Episode!

In this conversation, Jeffrey Bradbury and Diane Manser explore the transformative power of digital tools in education, particularly focusing on Google animations. They discuss how these tools can enhance creativity, engagement, and learning across various subjects, while also addressing the emotional challenges teachers face and the importance of resilience and empowerment in the profession. If you are a new listener to TeacherCast, we would love to hear from you.  Please visit our Contact Page and let us know how we can help you today! [convertkit form=7230980] Conversation Takeaways Google Slides can be used creatively to make animations. Students can engage with animation concepts through familiar movies. Creating flipbook animations helps students understand the animation process. Using Google Slides allows for unique features not found in other presentation tools. The lesson plan for animations is available on TeacherCast. Students can express their creativity through animation projects. Animation festivals in classrooms can be a fun learning experience. Technical challenges can arise, but they can be managed effectively. Understanding the history of animation can enhance student interest. Collaboration and sharing ideas among educators can improve teaching strategies. The transition from physical to digital learning opens new avenues for creativity. Digital tools can be integrated into various subjects, enhancing student engagement. Teaching digital citizenship is essential in today's technology-driven classrooms. Students can take ownership of their learning through creative projects. Using animations in lessons can make complex topics more accessible and fun. Empowering students leads to better learning outcomes and classroom dynamics. Teachers can alleviate stress by incorporating engaging digital projects. Collaboration and sharing among educators can lead to innovative teaching practices. Resilience is key for teachers to navigate the challenges of the profession. Connecting with aspiring educators can inspire and motivate current teachers. Follow Our Podcast And Subscribe View All Episodes Apple Podcasts Spotify Follow Our Host Jeff Bradbury | @JeffBradbury TeacherCast | @TeacherCast Join Our PLN Are you enjoying the TeacherCast Network, please share your thoughts with the world by commenting on Apple Podcasts today? I enjoy reading and sharing your comments on the podcast each week. Let's Work Together Host: Jeff Bradbury @TeacherCast | @JeffBradbury Email: info@teachercast.net Voice Mail: **http://www.TeacherCast.net/voicemail** YouTube: **

Originally recorded at youtube.com/comicpop and uploaded to youtube.com/comicpopreturns!

The bois get together and shoot the breeze with some familiar gents. Amish folks make the best erotica, and rimshots make bad jokes even better!Check out all episodes @ filthyfox.buzzsprout.comEmail us @ filthyfoxpodcast@gmail.com

She's a business leader, a Grammy-nominated musician and is trying to transform education. Chadrika Tandon joins Vasant Dhar in episode 69 of Brave New World to discuss her life, her learning, and why she is still so driven. Useful resources 1. Chandrika Tandon on Spotify, Facebook, Instagram, Twitter, YouTube, TikTok, LinkedIn, Tandon School of Engineering and her own website. 2. Ammu's Treasures on YouTube, Flipbook and other streaming platforms. 3. Rick Smolan on a Life in Photography -- Episode 65 of Brave New World. 4. Lust for Life -- Norman Corwin. 5. The Complete Works of William Shakespeare. 6. Elegy Written in a Country Churchyard -- Thomas Gray. 7. A Psalm of Life -- Henry Wadsworth Longfellow. 8. The Shadow Lines -- Amitav Ghosh. 9. Sri Venkateswara Suprabhatham -- MS Subbulakshmi. 10. Binaca Geetmala, 1953-2000. 11. The Beatles and Carpenters on Spotify. 12. Quiet Fire -- Roberta Flack. 13. The Pyramid Principle -- Barbara Minto. 14. The Paradigm Shifts in Artificial Intelligence -- Vasant Dhar. Check out Vasant Dhar's newsletter on Substack. Subscription is free!

Heute geht es bei Money Matters um die Finanzmärkte. Mit Prof. Dr. Erwin Heri von Fintool spreche ich über den starken Schweizer Franken, die Möglichkeiten für Anleger:innen im aktuellen Markt und ob die Situation wirklich so schlimm ist, wie wir es gerade in den Medien lesen. Ganz generell, ohne Bezug zur Credit Suisse und UBS, weil die Folge vorher aufgenommen wurde. Weniger aktuell ist die Sicht auf den Gesamtmarkt aber nicht! Prof. Dr. Erwin Heri ist Finanzprofessor und war als Anlagemanager verantwortlich für die Verwaltung von weit über CHF 100 Mrd. Er ist der Gründer von Fintool, einer videobasierten Internetplattform für Finanzausbildung. Wenn dich folgende Antworten interessieren, dann unbedingt in die Folge reinhören: Sind Obligationen nun die Lösung? Wie gehe ich mit den Währungsrisiken um und welche gibt es überhaupt? Was es mit dem zielorientierten Anlegen auf sich hat Was ist der Unterschied zwischen ETFs und Indexfonds? Mehr Infos zu Fintool: https://fintool.ch/ FlipBook "Die Inflation ist zurückWas heisst das?": https://fintool.ch/books/inflation Erwähnte Podcastepisoden: 024 - So investierst du in ETFs 008 - Was sind ETFs? Werbung: Sponsorin dieser Staffel ist die ⁠Bank Cler⁠. Vielen Dank! Die Bank Cler redet mit dir über Geld – offen und ehrlich. Egal, wie viel du davon hast. Und zwar so, wie's ihr Name verspricht: «Cler» bedeutet im Rätoromanischen «klar, einfach, deutlich». Die Bank Cler macht also deine Bankgeschäfte so unkompliziert und angenehm wie möglich. Dies ist keine Finanz- oder Anlageberatung und stellt keine Aufforderung zum Kauf oder Verkauf von Produkten dar! Alle Informationen wurden sorgfältig recherchiert. Ich übernehme keinerlei Haftung für die Richtigkeit der Informationen im Podcast. Das Handeln von Wertpapieren an der Börse ist ein Risiko und du trägst die Verantwortung für deine Finanzen! Ich übernehme keine Haftung für deine Entscheidungen. Ich berichte hier lediglich von meinen persönlichen Erfahrungen. Dies ist keine Finanz- oder Anlageberatung und stellt keine Aufforderung zum Kauf oder Verkauf von Produkten dar! Alle Informationen wurden sorgfältig recherchiert. Ich übernehme keinerlei Haftung für die Richtigkeit der Informationen im Podcast. Das Handeln von Wertpapieren an der Börse ist ein Risiko und du trägst die Verantwortung für deine Finanzen! Ich übernehme keine Haftung für deine Entscheidungen. Ich berichte hier lediglich von meinen persönlichen Erfahrungen.

Adam's visiting London's Cartoon Museum to find out about the history of cartoons, Dennis the Menace, plus a bit of Thunderbirds. And Georgia's helping us make a flipbook!Join Fun Kids Podcasts+: https://funkidslive.com/plusSee omnystudio.com/listener for privacy information.

What's SHE Up To Now Day 1852? Out Of Sight, Best Emotional Well Being Tools? Drop in to get the real scoop--the good, the bad, the ugly, the truth (well my truth anyway). https://facebook.com/beme2thrive #documentthejourney #shareyourexperience #outofsightoutofmind

R.S.S. # 2-C: "Dale's Flipbook" (Side 3) #CP-66 by Spoken Word with Electronics

R.S.S. # 2-C: "Dale's Flipbook" (Side 3) #CP-66 by Spoken Word with Electronics

Voilà, c'est lancé. La version digitale de Podcast Magazine est quasiment finalisée. Il reste encore quelques ajustements et les sélections de podcast à ajouter. A tous ceux qui ont participé au Kisskissbankbank, vous pouvez accéder à la version digitale du magazine en vous identifiant sur le site. Votre login est votre mail et votre mot de passe, faites simplement mot de passe oublié : Voici le lien direct vers la liseuse ) attention il faut être identifié pour y accéder (Flipbook et version audio) : https://podcastmagazine.fr/espace-abonnes/ Pour ceux qui n'ont pas pas contribué au Kisskiss, vous pouvez souscrire à un abonnement papier ou un digital ou cumuler les deux pour accéder aux contenus exclusifs que nous aurons au fur et à mesure des semaines en plus des articles du magazine. Voici le lien vers l'abonnement Premium Papier + Digital : Abonnement premium Je remercie Vialife Digital au passage qui nous permet d'avoir tous les articles en version audio Text2Speech. La voix est loin d'être aussi naturelle qu'une voix féminine, même si c'est pas trop mal. Ce qui est important c'est de pouvoir écouter les articles pour ceux qui ne peuvent pas lire. D'être accessible à tous. Je reprends cette OANI que vous recevrez désormais tous les jeudis matin avec une newsletter envoyée directement depuis COOL. Elle permet selon les espaces auxquels vous êtes abonnés de suivre les actualités de la plateforme. Le site lepod.fr est quant à lui en arrêt et nous alimentons maintenant au fur et à mesure le site de Podcast magazine qui va évoluer aussi avec les retours que vous aurez j'espère la gentillesse de nous faire. Car le site est aussi un projet collaboratif et tous ceux qui veulent nous aider à le rendre plus agréable sont les bienvenus. Merci au plus de 1000 abonnés au magazine. Les commandes quotidiennes nous font chaud au coeur et prouve que le bouche à oreille fonctionne et que le magazine plaît.

»Zwischen Verschwörungstheorien und der bitteren Realität«, so heißt die neue Folge von »DuMont auf Sendung – Der Podcast mit Büchern«. Diesmal hat Martin Becker mit Pia Frey und Peter Wittkamp gesprochen. Die beiden haben mit »Der Desinformator« ein Flipbook kreiert, das – dem Kombinationsprinzip sei Dank – ganze 125.000 Verschwörungstheorien zum Selbermachen ermöglicht. Keine Sorge: das Ganze ist natürlich mit einem Augenzwinkern zu verstehen. Was genau es damit auf sich hat, wie es zu dieser Idee kam und welche Anwendungszwecke es hierfür gibt, führen Pia Frey und Peter Wittkamp im Podcast-Gespräch aus. Außerdem hat Tabea Soergel sich mit Julius Hendricks unterhalten, der bei DuMont als Sachbuch- und Belletristik-Lektor beschäftigt ist. Mit »Looking for Trouble – Bericht einer unerschrockenen Kriegsreporterin« von Virginia Cowles (Übersetzung: Monika Köpfer) ist gerade eine ganz besondere literarische Wiederentdeckung aus dem Umfeld von Martha Gellhorn und Ernest Hemingway erschienen, die von Julius Hendricks als Lektor betreut wurde. Was die Hintergründe dieses Titels sind und inwiefern dieser erschreckend aktuell und relevant ist, erläutert Julius Hendricks im Interview. Außerdem gibt er Einblicke in seinen Arbeitsalltag als Lektor bei DuMont.

Subscribe to the World's First One and Only Digital Marketing Legend Srinidhi Ranganathan's YouTube Channel. Click this link - https://www.youtube.com/channel/UCXP3bY7BbMt1pXK0tPp8G4Q?sub_confirmation=1World's First Secretive Videos of Digital Marketing Legend. Click this link to access:https://www.youtube.com/watch?v=czPAGS3kfaU&list=PL7iVMyVUvArbgxihjoJ3bEkPyjFmuO1TV&index=1World's First Digital Marketing New Videos and Tutorials (2022-23). Click this link to access:https://www.youtube.com/watch?v=Wawd4Zh5RRw&list=PL7iVMyVUvArbOCLFtyv_sv74cM9FaNDYw&index=1World's First Digital Marketing Free Full Complete Tutorials and Courses. Click this link to access:https://www.youtube.com/watch?v=Z3rf5_k_Ag0&list=PL7iVMyVUvArYtwaZR4R41SPop58PmUbVD&index=1&t=1sWorld's First Favorite Videos of Digital Marketing Legend. Click this link to access:https://www.youtube.com/watch?v=-qJWb-Vtbhs&list=PL7iVMyVUvArY1j1v7j0b2JTGWPrpmoHyV&index=1&t=2156sWorld's First Growth Hacking Courses from the One & Only Digital Marketing Legend "Srinidhi Ranganathan. Click this link to access:https://www.youtube.com/watch?v=wveq63n0ZBk&list=PL7iVMyVUvAra2egy90W498ItgO3UUc-Tr&index=1&t=2sWorld's First Trending Digital Marketing Legend's (Shorts) Videos. Click this link to access:https://www.youtube.com/watch?v=czPAGS3kfaU&list=PL7iVMyVUvAra5Ij3f8ABX9XJZUrL98B7-&index=1World's First Digital Marketing Educative Videos with Tips. Click this link to access:https://www.youtube.com/watch?v=WcyCa9hvwN4&list=PL7iVMyVUvArbYIQ-yeJMlmsoDDsYa6e-K&index=1World's First Digital Marketing Legend's Trending Music Playlist. Click this link to access:https://www.youtube.com/watch?v=u7ermncH_so&list=PL7iVMyVUvArZfnrx8LfZ4u9V8vNFmtw3i&index=1World's First Free Digital Marketing Full Free Online Training. Click this link to access:https://www.youtube.com/watch?v=tHRu7Ch8IvA&list=PL7iVMyVUvArbQ5PW739-pbAwFwBHHFFbo&index=2&t=59sWorld's First Videos on Cave 101 - Hyperphantasia Demo. Click this link to access:https://www.youtube.com/watch?v=Ha0imob1f3A&list=PL7iVMyVUvAraYU4Hr97qFpibr_KasE5MU&index=1World's First Amazing Animated Films. Click this link to access:https://www.youtube.com/watch?v=6wpfx-u8eUg&list=PL7iVMyVUvArbnVKcrpJY5jz5z4kaERAwz&index=1&t=4sWorld's First Videos on the Hidden Research of Digital Marketing Legend "Srinidhi Ranganathan". Click this link to access:https://www.youtube.com/watch?v=jZi-JaXpy_g&list=PL7iVMyVUvAraBHYskDvHDkj1Psxa821cN&index=1&t=7sWorld's First Videos of Legend Playing AI Cricket. Click this link to access:https://www.youtube.com/watch?v=vbvFpFqsdWQ&list=PL7iVMyVUvArZjoDHFk3-g5qNRx0Z7f3Hi&index=1&t=374sWorld's First Videos on How to Make Money Online with Tips. Click this link to access: https://www.youtube.com/watch?v=QI6ey9ra3kY&list=PL7iVMyVUvAraJkLm9EqXH0I8B6N5vmIa_&index=1&t=4531sWorld's First RoboAuthor Content Writing & SEO AI Educative Video. Click this link to access:https://www.youtube.com/watch?v=1acNL394z-g&list=PL7iVMyVUvArafIGsOM7xlJgmDZ69VdJ4Z&index=1&t=121sWorld's First Virtual Human-Like Robot Girl Videos. Click this link to access:https://www.youtube.com/watch?v=G7I-6QorpgI&list=PL7iVMyVUvAra3wz8cigH3_e6sOZ5pvA3h&index=1World's First Digital Marketing Training Playlist. Click this link to access:https://www.youtube.com/watch?v=FqsQLO-3h_k&list=PL7iVMyVUvArbLTjfea7LhkJShYZdl6T-L&index=1

Lernen mit WOW-Effekt. Dies klappt auch in Online-Kursen, wenn Du eben keinen 08/15 Kurs anbieten möchtest. One-Size-fits all, passt halt nicht immer für alle, vor allem dann nicht, wenn Du Deinen Lernenden dabei auch im Kopf und Blick hast.   Es reicht aus meiner Sicht eben nicht mehr aus noch ein paar hübsche PDFs zusätzlich in den Kurs zu packen. Iris Komarek von mindSystems zum Beispiel erstellt statt eines PDFs ein Flipbook, wo die Teilnehmenden virtuell durchblättern können und sogar ein Ton beim Umblättern abgespielt wird.   Warum nicht auch mal einen QR-Code einbinden mit einer Verlinkung zu weiteren Material (Video, Podcast oder Artikel). Einem gemeinsamen Event, so wie ich es jetzt bei der LernOS erlebt habe. Im Vorfeld habe ich ein Päckchen bekommen mit zwei Suppen und einem Becher sowie Getränken. Nicht nur liebevoll verpackt, sondern auch noch nachhaltig.    Versuche alle Sinne Deiner Teilnehmenden einzubinden, vielleicht etwas haptisches, schmackhaftes oder duftendes. Geht nicht, dann befindest Du Dich gerade in Deiner Komfortzone. Du kannst Deinen Teilnehmenden auch gerne eine Kleinigkeit mit regionalen Bezug im Vorfeld schicken, so gibt es auch einen weiteren Grund sich über Dich und Dein Produkt auszutauschen.    Deine Liebe und die Energie zu Deinem Produkt, zu Deiner Region und Deinen Teilnehmenden sollte spürbar werden.   Inhalt:

Před týdnem byla oficiální světová premiéra obalu s označením PITAKA FlipBook Case for iPad Pro. Nejde tak úplně o obal, spíš uši, které přiděláte na iPad Pro či iPad Air, který je založený v Apple Magic Keyboard.

To suggest poems for Season 3 of the Litpoetry Podcast, email: jamesdlaidler@gmail.com To download a free digital copy of ‘The Taste of Apple' (with embedded audio) follow the following instructions: For PC users: Download 'The Taste of Apple' Flipbook for PC (select 'download' file and open the .exe file to run – ignore virus warnings; it is safe!)https://drive.google.com/file/d/1QALtqEQlkPPmkeMAWnNrvuAiIQPV5e_s/view  For Apple iOS users:  Click below link, press ‘download file', and then extract the file to a folder. Next, navigate to your new folder and open the 'web' folder to run and double click the 'index.html' file to read the book. https://drive.google.com/file/d/1DUOaZpy2ikVTWVqyeKcoS5Ytag3GzY5k/view?usp=sharing   ‘The Taste of Apple' (written by James Laidler with music by Don Stewart), published in 2010 by Interactive Publishers after winning their ‘Best First Book Award' for that year. The Litpoetry Podcast (season 2, Episode 20) features 5 Tracks from ‘The Taste of Apple' and can be listened to on all major podcasting platforms, including: Spotify, Apple, Google and here on YouTube. Otherwise, it can be found in the Podcasts section of the Litpoetry website at: https://www.litpoetry.com/home/litpoetry-podcasts This audio adaptation and podcast is copyrighted, © James Laidler (Litpoetry) Music  for the poems featured was composed by Don Stewart in consultation with James Laidler at Unmuzzled Music. http://www.unmuzzledmusic.com.au    

Comment la machine inventée par les frères Lumière fonctionne-t-elle ? “Qui a inventé ?” t'explique tout et te propose un petit atelier pour mieux comprendre. Il te faut : un carnet de notes ou un cahier, de quoi dessiner (un stylo, un crayon papier), un peu de patience et d'imagination… “Qui a inventé ?”, c'est un podcast qui raconte les petites et les grandes histoires des inventions qui ont changé nos vies : l'électricité, le cinéma, les fusées, les vaccins… Sous forme de jeux, d'histoires, d'interviews, avec la participation d'enfants, “Qui a inventé ?” éclaire chaque semaine ta curiosité avec un nouvel épisode ! Crédits : Ce podcast est préparé et animé par le magazine Images Doc (Bayard Jeunesse). Réalisation : Billy the Cast. Direction éditoriale : Bertrand Fichou. Création visuelle : Mathieu Carron de la Carrière et Jérôme Anfré. Production : Hélène Devannes. Musique : Emmanuel Viau. Un podcast de Bayard Jeunesse 2021- Droits réservés. 

* Mark Armitage back on RSR: Real Science Radio host Bob Enyart interviews long-time friend Mark Armitage on his latest soft tissue discoveries published in a Cambridge University Press science journal, Microscopy Today. Bob welcomes Mark back to RSR after seven years during which time Armitage founded DSTRI, the Dinosaur Soft Tissue Research Institute. Here are three brief quotes from his paper on autofluorescence microscopy of dinosaur bones revealing blood clots. "dinosaur neurovascular bundles travel as a triad of veins, vessels, and nerve fibers, as in other vertebrates." And regarding the Schweitzer iron rescue device, "free iron was unavailable, at least in these... bones." And see all of our RSR programs with Mark listed at rsr.org/armitage. And you may want to listen to the second of our two 2021 Armitage interviews... Paleontology Breakthrough! Now, dinosaur nerve bundles! * 29 Journals, 57 Papers: Mark Armitage is on back-to-back RSR episodes! To date, 29 peer-reviewed science journals have published a total of 57 dinosaur biomaterial discoveries including Nature, Science, Cretaceous Research, Current Biology, Geology, Paleontology, Vertebrate Paleontology, Nature Communications, Scientific Reports, PLoS ONE, Proceedings of the Royal Society B, and PNAS. The many dinosaur and other Mesozoic creatures yielding their original still-soft biological material include hadrosaur, titanosaur, the [ostrich-like] ornithomimosaur, Nodosaur, mosasaur, [bird-like] Anchiornis huxleyi, Triceratops, Lufengosaur, Archaeopteryx, and T. rex. Powerful Google Creation Tool!  Multiple Creation Site Search! In fossils from dinosaur-layer and "deeper", i.e. believed older, strata, researchers have discovered flexible and transparent blood vessels and cartilage, red blood cells, starch, many various proteins including beta-keratin, the microtubule building block tubulin, collagen, mollusk shell glycoprotein and dino eggshell peptides and chelating ligands, chitin, the cytoskeleton components actin, tropomyosin, and the related motor protein myosin, and hemoglobin, bone maintenance osteocyte cells, pigment including melanosomes, clearly-seen chromosome-like structures within cell nucleus, DNA-related histone proteins, and powerful evidence for DNA including positive results from multiple double-helix tests including IP and DAPI on fossils from various dinosaurs. And now, thanks to microscopist Mark Armitage, dinosaur nerve bundles! So we invite you to enjoy today's interview with Mark, see his cover story paper in the latest issue of Microscopy Today, a Cambridge University Press journal, and check out all our related programs at rsr.org/armitage! Thx Cary, Illinois!* Walt Brown's In the Beginning: For PDF, HTML, and Flipbook versions of the 9th Edition of Walt Brown's In the Beginning, just click on over to hpt.rsr.org! Walt Brown's In the Beginning 8th Edition is OUT OF PRINT! Do you have a used copy you don't need? Here at Real Science Radio/BEL we've long been a source of information about the rsr.org/hydroplate theory and a great place to purchase Walt Brown resources. But now we're out. If you have a copy that you've already read, or that you know that you're not going to read, and would like to help us, we ask you to consider mailing your copy to BEL, 6126 Braun Court, Arvada CO 80004. (As of April 2021 new copies of Walt's book online are going for $300 to $370 each and used one for well over $100. But for our RSR listeners, and to keep ITB available for as reasonable a price as we can, around $120 each, we track sales of pre-owned books and offer them at our rsr.org/store.) RSR listener from Alaska: "You can have my In the Beginning book... when you pry it out of my cold, dead hands. ;)" -Russ Holmes, Wasilla, Alaska, 12/6/19

* Mark Armitage back on RSR: Real Science Radio host Bob Enyart interviews long-time friend Mark Armitage on his latest soft tissue discoveries published in a Cambridge University Press science journal, Microscopy Today. Bob welcomes Mark back to RSR after seven years during which time Armitage founded DSTRI, the Dinosaur Soft Tissue Research Institute. Here are three brief quotes from his paper on autofluorescence microscopy of dinosaur bones revealing blood clots. "dinosaur neurovascular bundles travel as a triad of veins, vessels, and nerve fibers, as in other vertebrates." And regarding the Schweitzer iron rescue device, "free iron was unavailable, at least in these... bones." And see all of our RSR programs with Mark listed at rsr.org/armitage. And you may want to listen to the second of our two 2021 Armitage interviews... Paleontology Breakthrough! Now, dinosaur nerve bundles! * 29 Journals, 57 Papers: Mark Armitage is on back-to-back RSR episodes! To date, 29 peer-reviewed science journals have published a total of 57 dinosaur biomaterial discoveries including Nature, Science, Cretaceous Research, Current Biology, Geology, Paleontology, Vertebrate Paleontology, Nature Communications, Scientific Reports, PLoS ONE, Proceedings of the Royal Society B, and PNAS. The many dinosaur and other Mesozoic creatures yielding their original still-soft biological material include hadrosaur, titanosaur, the [ostrich-like] ornithomimosaur, Nodosaur, mosasaur, [bird-like] Anchiornis huxleyi, Triceratops, Lufengosaur, Archaeopteryx, and T. rex. Powerful Google Creation Tool!  Multiple Creation Site Search! In fossils from dinosaur-layer and "deeper", i.e. believed older, strata, researchers have discovered flexible and transparent blood vessels and cartilage, red blood cells, starch, many various proteins including beta-keratin, the microtubule building block tubulin, collagen, mollusk shell glycoprotein and dino eggshell peptides and chelating ligands, chitin, the cytoskeleton components actin, tropomyosin, and the related motor protein myosin, and hemoglobin, bone maintenance osteocyte cells, pigment including melanosomes, clearly-seen chromosome-like structures within cell nucleus, DNA-related histone proteins, and powerful evidence for DNA including positive results from multiple double-helix tests including IP and DAPI on fossils from various dinosaurs. And now, thanks to microscopist Mark Armitage, dinosaur nerve bundles! So we invite you to enjoy today's interview with Mark, see his cover story paper in the latest issue of Microscopy Today, a Cambridge University Press journal, and check out all our related programs at rsr.org/armitage! Thx Cary, Illinois!* Walt Brown's In the Beginning: For PDF, HTML, and Flipbook versions of the 9th Edition of Walt Brown's In the Beginning, just click on over to hpt.rsr.org! Walt Brown's In the Beginning 8th Edition is OUT OF PRINT! Do you have a used copy you don't need? Here at Real Science Radio/BEL we've long been a source of information about the rsr.org/hydroplate theory and a great place to purchase Walt Brown resources. But now we're out. If you have a copy that you've already read, or that you know that you're not going to read, and would like to help us, we ask you to consider mailing your copy to BEL, 6126 Braun Court, Arvada CO 80004. (As of April 2021 new copies of Walt's book online are going for $300 to $370 each and used one for well over $100. But for our RSR listeners, and to keep ITB available for as reasonable a price as we can, around $120 each, we track sales of pre-owned books and offer them at our rsr.org/store.) RSR listener from Alaska: "You can have my In the Beginning book... when you pry it out of my cold, dead hands. ;)" -Russ Holmes, Wasilla, Alaska, 12/6/19

Listen to this super long string of syllable samples that, in sequence, sound like actual language! Andy, Vito, John, Greg, and Flask vocalize just how non-canon Shadow of War is, WandaVision season 1's ending, Attack on Titan, Nioh 2, Rogue Heroes, Star Wars movies, 90-Day Fiancée, Valheim, The Outer Wilds, Pokemon announcements, Mediatonic's epic future, The Sinking City contract clusterfrick, Elden Ring leaks, Marvel's Avengers (get your levels in now), Bethesda's soft microfuture, and more. Find out more at https://broken-campfire.pinecast.co

This is an evangelistic book to use for witnessing to your friends. It is an evangelistic flipbook! It shows a couple growing up, falling in love, dying, then asking if there's an afterlife. This book is only available through the Living Waters Book site or YOUTH ACTION MINISTRIES WEB SITE. It is not yet on Amazon yet. You Can also order this book through our Website Youth Action Ministries. We will order the book for you and send it out. A small commission will be given to our ministry Youth Action Ministries. Thank you Please click on the link and donate to Youth Action Ministries secure server. The book will be sent out to you to the address you put in the secure server. Thank You. Price for the book and shipping is $ 30.00. https://www.youth-action.com/support-us --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app Support this podcast: https://anchor.fm/anthony-rizzo3/support

www.RussellCorey.com www.FlipbookGame.com Youtube channel: https://www.youtube.com/channel/UC5jNWYvGacyUw2qp_2lkeCw Flipbook Game Books on Amazon: https://www.amazon.com/gp/product/B08WZ3VKB6 In this episode I talk about getting my Flipbook Game shows on YouTube starting with the 48 Team Carolina Card Tournament and the show Cybertruck vs The World.

www.RussellCorey.com Watch the first FLIPBOOK GAME on Youtube: https://www.youtube.com/watch?v=m0ohMlq2mbU You can buy the first FLIPBOOK GAME book on Amazon at: https://www.amazon.com/dp/B08WZBXRLZ And the new Series 2 Carolina Cards are available on Amazon as well: https://www.amazon.com/dp/B08X65PL88 On this episode I give an update on FLIPBOOK GAME with the Original Five Flipbook Teams and the Carolina Card Flipbook Game Tournament. I also talk about my mystery invention that will change the way we live. (hopefully)

www.RussellCorey.com Watch the first FLIPBOOK GAME on Youtube: https://www.youtube.com/watch?v=m0ohMlq2mbU You can buy the first FLIPBOOK GAME book on Amazon at: https://www.amazon.com/dp/B08WZBXRLZ On this episode I give an update on FLIPBOOK GAME with the Original Five Flipbook Teams and the Carolina Card Flipbook Game Tournament. I also talk about my mystery invention that will change the way we live. (hopefully)

www.RussellCorey.com Watch the first FLIPBOOK GAME on Youtube: https://www.youtube.com/watch?v=m0ohMlq2mbU You can buy the first FLIPBOOK GAME book on Amazon at: https://www.amazon.com/dp/B08WZBXRLZ On this episode I talk about the start of FLIPBOOK GAME with the Original Five Flipbook Teams: New York Business Boston Blue Decks Chicago Card Sharks Los Angeles Shuffle Miami Wild Cards

J. Gonzo joins me to talk about the trade paperback edition of "La Mano del Destino". It is currently running on Kickstarter for another 47 days as of the day of this post. "La Mano del Destino" will be collecting issues #1-6 and is going to include a translated Spanish version of the complete story along with the English Version in a Flipbook format (that way neither language seems like an addendum or afterthought to the other).  "La Mano del Destino," tells the tale of a once-champion Luchador – who, after being betrayed by his friends and unmasked in the ring, agrees to a Faustian bargain with a mysterious promoter. He gains a new power and the identity of La Mano del Destino in order to exact revenge upon his betrayers. Set in a swanky, 1960's Mexico where Lucha Libre is intrinsically woven into all aspects of society and are the most important events that happen within this world, this tale winds its way through the machinations and motivations of all types who inhabit this unique setting. Watch the trailer below or click here to head over to the Kickstarter page.  Get our Merch:bit.ly/NerdsMerch Follow us on social media:https://twitter.com/NerdsFTChttps://www.instagram.com/nerdsftchttps://ww.facebook.com/NerdsFTC Saul:https://twitter.com/Better_CallMe Greg:https://twitter.com/ThatAmazingTwithttps://www.instagram.com/thatamazingtwit David:https://twitter.com/DaveyDave503https://www.instagram.com/daveydave Theme by: Jake Lionharthttps://twitter.com/Jake_Lionheart

In this week's MakeCode Minute: Pixel Flipbook @adafruit @johnedgarpark #adafruit @MSMakeCode. Make a flipbook of pixel images on the micro:bit using MakeCode. To learn about MakeCode: makecode.adafruit.com This clip is from the full John Park's Workshop livestream: https://youtu.be/mOZExFdiHvo?t=788 MakeCode @adafruit @johnedgarpark #adafruit @MSMakeCode @adafruit @johnedgarpark #adafruit @MSMakeCode Music by John Park -- https://johnpark.bandcamp.com/

Sam Sethi and Cary Marsh have been friends for over a decade. We first met when Cary was CEO of Mydeo and online video hosting company. In this podcast we talked about Cary's two successful kickstarter projects - Bootclaw and My Flipping World. Cary explains why she prefers to raise funds via crowdfunding instead of through more traditional Angel or VC routes having had such a harrowing time raising funds for Mydeo.Cary also talks us through how she had the idea and more importantly how she went about getting the product to market.Cary's degree in engineering from Nottingham University was 20 years ago, however there are still so few women engineers. We discussed why that is and what can be done to encourage more women.In the future Cary would like to launch more tangible products through Punchfront Innovation via kickstarter.

La Sélection Comics de ce dimanche 03 décembre 2018, c'est un flipbook gratuit avec un histoire de Faith et une de Giant Days, c'est publié à la fois par Bliss Comics et par Akileos.

Que el ritmo no pare!! Eso es, el ritmo no para porque somos unos podcasters de culto. Volvemos con nuevos plugins publicados en el repositorio de WordPress y esta semana si que traemos algunos plugins interesantes. Venga, calla y escucha!! Los plugins de esta semana son: – Good & Bad Comments: https://es.wordpress.org/plugins/good-bad-comments/  –>  7 estrellas. – […]

Siding, patios, load-bearing walls, and beams are on the menu for this episode of the FHB Podcast, with our regulars Justin Fink, Rob Yagid, and Brian Pontolilo. The guys talk about the state of residential construction in California, and specifically San Francisco. Also in this episode ... gable roofs, painting, scribing, Victorian homes, and Shaker style.

We got two newbies ready to have their Creepypasta virginities plucked from that tree of knowledge, so let's be sure to show 'em around, eh, Frowns? Today we read a bunch of TOST and if you don't know what that is, you haven't been paying attention. The Watchers Among Us(19:16)Her Side of the Bed(21:31)Picture Day(22:52)Childhood Superstitions(24:49)Roulette(27:06)Sleepover(28:58)Missed Calls(30:33)Peripheral Vision(32:00)Baby Doll(33:33)Copies(35:48)The Railroad(37:13)The Amityville Incident(40:10)A Pile of Photographs(42:39)Flipbook(46:52)Operation Wandering Soul: TRUE(49:33)A Wonderful Place(51:44)Check out our episodes on Youtube!www.youtube.com/channel/UCxoqIN-fkfdlmGEjWujypxwFeaturing wonderful ambient music from our fam in Sweden: CryoChamber, givin' us all the ooky-spooky tunage. Follow: @cryo-chamberThank you!"Are You Afraid of the Dark Theme Song," "Spooky Skeletons REMIX," and "You Reposted in the Wrong Neighborhood" are not my songs. Credit and All rights are reserved by the owners

We got two newbies ready to have their Creepypasta virginities plucked from that tree of knowledge, so let's be sure to show 'em around, eh, Frowns? Today we read a bunch of TOST and if you don't know what that is, you haven't been paying attention. The Watchers Among Us(19:16)Her Side of the Bed(21:31)Picture Day(22:52)Childhood Superstitions(24:49)Roulette(27:06)Sleepover(28:58)Missed Calls(30:33)Peripheral Vision(32:00)Baby Doll(33:33)Copies(35:48)The Railroad(37:13)The Amityville Incident(40:10)A Pile of Photographs(42:39)Flipbook(46:52)Operation Wandering Soul: TRUE(49:33)A Wonderful Place(51:44)Check out our episodes on Youtube!www.youtube.com/channel/UCxoqIN-fkfdlmGEjWujypxwFeaturing wonderful ambient music from our fam in Sweden: CryoChamber, givin' us all the ooky-spooky tunage. Follow: @cryo-chamberThank you!"Are You Afraid of the Dark Theme Song," "Spooky Skeletons REMIX," and "You Reposted in the Wrong Neighborhood" are not my songs. Credit and All rights are reserved by the owners

Flip Book finally delves into the world of anime! Kay and Aby walk down memory lane to recall how they got into anime, what keeps them coming back for more, and even what they don't find so good about the format. They go through some of their favourite series and movies to give beginners a sort of amateur guide into what they can do to test the anime waters. See acast.com/privacy for privacy and opt-out information.

In episode 20 of twohundredby200’s podcast, Creative Director, Sean Makin is back to talk about the latest news from the studio, the magazine and it’s shop. Sean talks about the reason the twohundredby200 magazine is no longer available on the website in a Flipbook-type format but lets listeners know that it can still be experienced in that format through online publisher portal Issuu. The portal hosts the magazine in different viewing formats through it's website and through it’s own free iOS and Android apps. Sean moves on to cover the coming enhancements to the magazine and talks about the studio’s plans to expand it presence on Youtube and how it will integrate with the magazine and podcast. This something the studio team have been experimenting with over the past few months and the first content will be coming online with a regularly "Show and Tell" feature starting soon. Sean answers a few questions from listeners including the plan for coverage of the Edinburgh festival period this year and one asking how to part company with a client you can no longer work with. Sean talks about a recent experience the studio had when they reached the decision to stop working for a client they had been involved with for nearly 11 years. Sean covers the different aspects that people have to be aware of and talks about how to do it with the minimum impact on client and studio. A tricky topic but one Sean thought worth covering in this episode of the podcast.

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Save the Date & New Location! Don't miss this one-of-a-kind, 3-in-1 conference that brings the pharmacy profession together in paradise. The American College of Apothecaries (ACA), the International Academy of Compounding Pharmacists (IACP) and the American College of Veterinary Pharmacists (ACVP) are joining forces again to bring you an extraordinary Educational Conference, February 5-8, 2014 at the ocean front property, the Harbor Beach Marriott Resort & Spa in Fort Lauderdale, Florida.  What you can expect in 2014: •Benefit from multiple education tracks; practice-based, compounding, and veterinary clinical and compounding. •Learn the fundamental steps to successfully work with your local media. •Earn up to 14.0 contact hours (1.4 CEUs) of continuing education credit including 4.0 contact hours (.4 CEUs) of LIVE Pharmacy Law.•Hear what your peers are doing in the  sessions. •Visit with companies showcasing services that can improve your business.Special one-day registration rate is available for Saturday, February 8 at $195!The Educational Conference is proud to partner with the . All Florida-area pharmacists, technicians, and marketing reps are invited to attend the ACA, IACP, ACVP Educational Conference.  A special one-day registration rate is available for Saturday, February 8 at $195! Join your fellow colleagues and meet new friends while taking part in the Continuing Education programs and networking opportunities among three leading pharmacy organizations. To register for the Special Day Only rate, click here.This Works for Me!Florida Pharmacy Association For more information about Educational Conference 2014, click here to view the meeting press release.   The ACA, IACP, ACVP Educational Conference e-brochure is now available.  Learn what's new in 2014, review the complete meeting agenda with in-depth Continuing Education sessions by leading experts in pharmacy; understand why pharmacy students should attend, and much more! Click here to download the 2014 Educational Conference e-brochure, sponsored by ACA & IACP Corporate Partner Humco Compounding.  The Flipbook technology for the e-brochure was generously provided by RXinsider.Sponsored by the - Educational Conference 2014 See omnystudio.com/listener for privacy information.

I'm conducting a month long blitz on using various forms of animation with my dozen or so classes.Part of my teaching assignment is to introduce new ways to "show what you know". And from my days 5 years ago taking photographs with a tripod and using Windows Movie Maker to try to animate the photos we have come a long way since then.  I continue to find this type of storytelling interesting, innovative and a very good way to motivate students.I have collected a number of resources along the way and tried to find ways to bring animation closer to the students. In the photo above, you'll see my 6 year old Mac Mini, a 5 year old school owned Canon Mini DV camera and a school owned monitor. I used this set-up this week as a demonstration animation station. I have it on a metal cart on wheels which allows me to move from classroom to classroom.National Film Board - Canada (NFB) ResourcesStopMo - Great site. 18 minute segmented step-by-step process for animation. Includes a detailed series of lesson plans which can be adapted to different grade levels.SoftwareWe're very fortunate to have an agreement with Tech4Learning to have Frames animation software installed on each academic image among publicly funded schools in Ontario.Mobile Animation Apps. for iOSFor iPhone and iPod Touch I have had success with (free) LEGO® Super Heroes Movie MakerAnd just last week a student in grade 8 showed me a terrific app. for iPhone and iPod Touch called iMotion HD. Unlike the LEGO® app., which saves to the Camera Roll, iMotion HD does not save unless you purchase the full version for $1.99. We also use the animation instructional videos included with NFB's free (in Canada) PixStop Animation App. for iOS.  Three short tutorial films are included with the app. and are very good: "Three Principles of Animation",  "Flipbook" , and "Storyboarding".Steps in the ProcessI encouraged students to keep a few things in mind when creating their animations:a) Create a 3 panel storyboard which shows: beginning, middle, and end.b) Write next to your sketch the Action Sequence in each panel.b) Select no more than 3 characters to be the 'talent' in the animation.c) Tell your story in 10 seconds or less.d) Decide ahead of time whether you'll be creating your animation as a Pixilation with classmates, with toy characters, or with clay.Note: There are other animation options but these are three good ones with which to start.Teacher Created Resources:York Region teacher Dan Grant uses animation in his junior classroom and penned an article a while back for ETFO's Voice magazine on Stop Motion in the classroom. The best collection of templates and instructional videos around is by teacher Kevin Hodgson. His animation website is terrific.Update: This week we started storyboarding and creating backgrounds. A trip to No-Frills was necessary. Came back with about 40 cardboard boxes!

The NMC Horizon Report > 2011 K-12 Edition is the third report in the K-12 series. In this edition, the New Media Consortium, the Consortium for School Networking (CoSN), and the International Society for Technology in Education (ISTE) collaborate on identifying the emerging technologies and key trends and challenges that will impact teaching, learning, and creative inquiry in the K-12 sector over the next five years. View the work that produced the report here. Read the Flipbook version for your laptop, desktop, iPhone, and iPad. Download the presentation, which gives a visual overview of the contents of The NMC Horizon Report > 2011 K-12 Edition. The presentation was shared at conferences all over the world in conjunction with the release of the accompanying report.

Itâ??s episode nine of the AwesomeCast! Our hosts Rob de la Cretaz and Mike Sorg are online, and are joined by Chris Maverick of Cosmic Hellcatsand ElseWorld to talk about Photography in a world where we all have access to it on our cellphones and pocket devices. We also have a chance to talk about Apple's new hardware, the Flipbook controversy, Samsung's Galaxy givaway, legalized Jailbreaking, and the secret tethering app. Join the AwesomeCast on Twitter, Facebook, Delicious, and be sure to follow us on iTunes in both videoand audio formats, as well as YouTube and Blip.tv! This weekâ??s Audible Pick: FREE: The Future of a Radical Price by Chris Anderson Get this book free at www.audiblepodcast.com/sorgatronmedia

Itâ??s episode nine of the AwesomeCast! Our hosts Rob de la Cretaz and Mike Sorg are online, and are joined by Chris Maverick of Cosmic Hellcatsand ElseWorld to talk about Photography in a world where we all have access to it on our cellphones and pocket devices. We also have a chance to talk about Apple's new hardware, the Flipbook controversy, Samsung's Galaxy givaway, legalized Jailbreaking, and the secret tethering app. Join the AwesomeCast on Twitter, Facebook, Delicious, and be sure to follow us on iTunes in both videoand audio formats, as well as YouTube and Blip.tv! This weekâ??s Audible Pick: FREE: The Future of a Radical Price by Chris Anderson Get this book free at www.audiblepodcast.com/sorgatronmedia