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Make a Logo on Fiverr Cloner Alliance Steps Up the UHD Pro 4K The Cloner Alliance UHD Pro 4K is a standalone video capture and recording box built for creators, gamers, and anyone who needs a simple way to record HDMI video without turning the setup into a complicated production rig. After looking at the previous Cloner Alliance Pro 4K model, this newer UHD Pro 4K brings some useful upgrades, including USB-C, microSD support, USB 3.0, and more flexible recording options. This is designed for pro video workflows, game capture, screenshots, camera recording, and even scheduled recording. It can capture in 4K, supports HDMI pass-through, and records to external storage including flash drives, microSD cards, and larger hard drives. What's in the Box? Inside the box, Cloner Alliance keeps things straightforward. You get the UHD Pro 4K unit, instruction materials, a remote control, HDMI cable, power adapter, and a USB-C to USB-A cable. A Welcome USB-C Upgrade One of the first noticeable changes is the move from micro USB to USB-C. That makes the UHD Pro 4K feel more modern and more useful in current creator setups. The device also includes USB 3.0 support, which matters when you are recording larger video files at higher bitrates. Ports and Controls On the top of the unit, you get physical controls for pause, snapshot, record, and stop. There are also audio inputs, including mic, aux, and line-in options. On the side, the unit includes microSD/TF card support, USB-C, and USB-A connectivity. On the back, you get the power button, 12V power input, HDMI input, and HDMI output for pass-through monitoring. Recording Options for Video Capture The Cloner Alliance UHD Pro 4K can record in MP4 or TS file formats. Resolution options include 4K, 1080p, or auto mode. For many users, auto mode will probably be the easiest choice, but having manual resolution control is useful when you need to lock the output to a specific format. H.264 and H.265 Recording The UHD Pro 4K supports both H.264 AVC and H.265 HEVC recording. That gives users some flexibility depending on whether they want broader compatibility or more efficient compression. The video bitrate can go up to 50 Mbps, which is a nice option for higher-quality captures. Just remember that a higher bitrate also means larger files, and your storage device needs to be fast enough to keep up. Audio Settings Audio options include HDMI audio, mic input, and aux input. You can adjust mic volume, aux volume, and HDMI output volume. The audio bitrate can be set up to 320 Kbps for better sound quality. That said, this is not a multitrack audio recorder. If you combine audio sources into the unit, they are recorded together. For serious productions, it is still better to manage audio separately when possible. Storage: Flash Drive, microSD, or Hard Drive The UHD Pro 4K supports recording to multiple storage types. You can use microSD/TF cards, USB flash drives, and larger external hard drives. The device can also test writing speed, which is useful before recording at higher bitrates. File Size and Loop Recording Recording file size options include unlimited, 4GB, 16GB, or two-hour segments. This lets you decide how the device breaks up long recordings. There is also loop recording, which makes the UHD Pro 4K useful beyond gaming and creator content. You could use it with a camera for basic security-style recording, where older files are overwritten once storage fills up. HDMI Pass-Through and Latency One of the biggest questions with any video capture device is latency. The UHD Pro 4K includes HDMI pass-through so you can send video to a monitor while recording. Better Than the Previous Model Compared with the earlier Cloner Alliance Pro 4K, the latency on the UHD Pro 4K appears improved. The older model had more noticeable delay, while this new version feels closer to the 50 to 100 millisecond range during pass-through testing. That is still not zero latency. For casual gameplay, recording, screenshots, or camera capture, it may be fine. For competitive gaming, you may still want to put a splitter before the Cloner Alliance box and monitor directly from the source. On-Screen Menus and Remote Control The UHD Pro 4K includes a remote for navigating system settings, recording settings, audio settings, scheduling, playback, and storage options. Settings You Can Adjust The system menu includes time settings, time zone, HDMI output resolution, HDMI output scale, screensaver, language, factory reset, and firmware information. The recording menu lets you choose format, resolution, file size, codec, bitrate, audio bitrate, loop recording, and watermark options. Remote Control Experience The remote works without needing to be aimed perfectly at the unit, which is a plus. However, it can be a little touch-and-go at times, occasionally needing more than one button press. Scheduling and Standalone Recording A big advantage of the Cloner Alliance UHD Pro 4K is that it does not always need a computer to record. You can connect your source, attach storage, and record directly from the unit. Scheduled Recording The device also includes scheduled recording options. That could be useful for capturing a camera feed, recording a recurring video source, or setting up a simple unattended recording station. Using the UHD Pro 4K With a Computer The UHD Pro 4K can also connect to a PC using the Cloner Alliance helper software. Once connected, you can preview the video feed, record to the computer, schedule recordings, choose capture devices, and configure folders for video and photo storage. Live Video and Virtual Camera Use The software also includes options for live broadcasting and virtual camera use. That means you can bring the Cloner Alliance feed into apps such as OBS, vMix, or other streaming software. The computer preview does introduce more latency than the HDMI pass-through monitor, so it is best used for setup, checking framing, or recording control — not as your main real-time display. Video Screenshots and Pro Video Uses The UHD Pro 4K is not just for recording full videos. The snapshot button makes it useful for grabbing video screenshots, especially from gameplay, cameras, or HDMI-based devices. Good for Creators and Reviewers For content creators, this can be a useful box to keep nearby. It can capture from a camera, record a gameplay feed, document a device's HDMI output, or act as a simple single-source recorder when you need something fast. Pros and Cons Pros The Cloner Alliance UHD Pro 4K is easy to set up, works as a standalone recorder, supports 4K capture, includes HDMI pass-through, offers USB-C and USB 3.0, supports higher bitrate recording, and works with the same Cloner Alliance software ecosystem. Cons There is still some latency, especially when using the computer preview. The remote can occasionally require extra button presses. Also, while the audio input options are useful, this is not a replacement for a dedicated multitrack audio workflow. Final Thoughts on the Cloner Alliance UHD Pro 4K The Cloner Alliance UHD Pro 4K is a solid upgrade over the previous model. The move to USB-C, the addition of microSD support, better storage flexibility, and improved latency make it a more capable video capture device for creators, gamers, and anyone working with HDMI video. It is easy to set up, flexible enough for standalone recording or computer-based capture, and useful for everything from pro video workflows to video screenshots. If you need a simple HDMI video capture and recording box that can work without a full computer setup, the UHD Pro 4K is worth a look. Check it out at https://geni.us/cauhdpro4k Check out the Geekazine Merch, including "I AM AI " T-Shirt.  Thanks for reading! Don't forget to subscribe to Geekazine: RSS Feed - YouTubeTwitter - Facebook Tip Me via Paypal.me Send a Tip via Venmo RSS Bandwidth by Cachefly Get a 14 Day Trial Be a Patreon: Part of the Sconnie Geek Nation! Reviews: Geekazine gets products in to review. Opinions are of Geekazine.com. Sponsored content will be labeled as such. Read all policies on the Geekazine review page.  Reviews: Geekazine is also an affiliate of Amazon Last Updated on June 10, 2026 1:49 pm by Jeffrey PowersThe post Cloner Alliance UHD Pro 4K Unboxing & Full Review appeared first on Geekazine.

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,

In this episode, we pull back the curtain on the North Atlantic Treaty Organization (NATO)—an alliance that has been the bedrock of transatlantic security for over 75 years, and yet finds itself at a critical turning point in 2026.What is NATO?Founded in 1949, NATO began as a collective defense pact among North American and European nations. At its heart lies Article 5: the principle that an armed attack against one member is an attack against all. This "all-for-one" commitment has defined global security for decades, acting as both a deterrent against aggression and a forum for political and military cooperation. The Current LandscapeWhile the mission remains the same—safeguarding the freedom and security of its 32 member states—the environment has changed drastically. In this episode, we explore the challenges defining the current era:The Spending Shift: With the 2025 commitment to reach 5% of GDP in defense spending by 2035, we discuss what this massive investment means for national economies and the future of military readiness. Geopolitical Friction: From the fallout of the war in Ukraine to shifting relations between the U.S. and its European counterparts, we examine the complexities of maintaining consensus when political priorities diverge.A Changing Defense Posture: We look at how the alliance is modernizing its deterrence strategy to address not just traditional military threats, but also cyber warfare, supply chain vulnerabilities, and regional stability.Why It MattersWhether you're a policy buff or just trying to make sense of the headlines, this episode breaks down why NATO is more than just a treaty—it's a dynamic, evolving political machine. We move beyond the jargon to ask the big question: Can the alliance adapt fast enough to meet the security challenges of 2026 and beyond?Join us as we weigh the arguments on the future of the Atlantic bond, the debate over burden-sharing, and what it truly takes to keep the peace in an increasingly unpredictable world.NATO WEBSITE: https://www.nato.int/enSend us Fan Mail

In the Mapcreator booth at NAB in Las Vegas, Julia Schellekens provides an update on their service that delivers detailed maps for news and other organizations who want to clearly show what is happening where. With a wide array of export and animation capabilities to help drive home the information, it is almost certain that you have seen their product in use no matter where in the world you are.  Show Notes: Chapters: 00:03 MacVoices at NAB 202600:08 Chuck Joiner opens from NAB in Las Vegas00:12 Returning to the Mapcreator booth00:24 Julia joins Chuck to show what is new00:37 What Mapcreator is and how it works00:43 Creating static, interactive, and animated maps00:47 Mapping tools for journalists and reporters01:37 Helping news agencies focus on the story02:16 What's new with MapCreator this year02:26 Newsroom system and Adobe workflow integrations02:52 Keeping users in their preferred design tools03:29 Maps and visuals as storytelling tools03:41 Creating animations quickly from GPX files04:05 Matching map creation to fast-moving news04:12 Export options for interactive maps04:26 Static map exports including PNG, JPEG, PDF, and SVG04:34 Animated exports including MOV, MP4, WebM, and image sequences05:27 Why Mapcreator is more than a quick coded tool05:34 Reducing manual work and saving production time05:49 Mapcreator website: Mapcreator.io Support:      Become a MacVoices Patron on Patreon     http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect:      Web:     http://macvoices.com      Twitter:     http://www.twitter.com/chuckjoiner     http://www.twitter.com/macvoices      Mastodon:     https://mastodon.cloud/@chuckjoiner      Facebook:     http://www.facebook.com/chuck.joiner      MacVoices Page on Facebook:     http://www.facebook.com/macvoices/      MacVoices Group on Facebook:     http://www.facebook.com/groups/macvoice      LinkedIn:     https://www.linkedin.com/in/chuckjoiner/      Instagram:     https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes     Video in iTunes      Subscribe manually via iTunes or any podcatcher:      Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

In the Mapcreator booth at NAB in Las Vegas, Julia Schellekens provides an update on their service that delivers detailed maps for news and other organizations who want to clearly show what is happening where. With a wide array of export and animation capabilities to help drive home the information, it is almost certain that you have seen their product in use no matter where in the world you are.  Show Notes: Chapters: 00:03 MacVoices at NAB 2026 00:08 Chuck Joiner opens from NAB in Las Vegas 00:12 Returning to the Mapcreator booth 00:24 Julia joins Chuck to show what is new 00:37 What Mapcreator is and how it works00:43 Creating static, interactive, and animated maps 00:47 Mapping tools for journalists and reporters 01:37 Helping news agencies focus on the story 02:16 What's new with MapCreator this year 02:26 Newsroom system and Adobe workflow integrations 02:52 Keeping users in their preferred design tools 03:29 Maps and visuals as storytelling tools 03:41 Creating animations quickly from GPX files 04:05 Matching map creation to fast-moving news 04:12 Export options for interactive maps 04:26 Static map exports including PNG, JPEG, PDF, and SVG 04:34 Animated exports including MOV, MP4, WebM, and image sequences 05:27 Why Mapcreator is more than a quick coded tool 05:34 Reducing manual work and saving production time 05:49 Mapcreator website: Mapcreator.io Support:      Become a MacVoices Patron on Patreon      http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect:      Web:      http://macvoices.com      Twitter:      http://www.twitter.com/chuckjoiner      http://www.twitter.com/macvoices      Mastodon:      https://mastodon.cloud/@chuckjoiner      Facebook:      http://www.facebook.com/chuck.joiner      MacVoices Page on Facebook:      http://www.facebook.com/macvoices/      MacVoices Group on Facebook:      http://www.facebook.com/groups/macvoice      LinkedIn:      https://www.linkedin.com/in/chuckjoiner/      Instagram:      https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes      Video in iTunes      Subscribe manually via iTunes or any podcatcher:      Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

In this episode of The Dept. Omar breaks down the missing link to your business. Leveraging content to lead to more conversations is how you will make more money online! Creating and giving lead magnets to your viewers can build trust at a deeper level with your future clients! Make it easy for people to say yes to you.

Send James and Sam a message or voicemailAre we sinking under a sea of AI slop? How do we fix it? Sam talks with Alberto Betella to find out.• iHeartMedia and SiriusXM merger chatter and what it could mean for shareholders • Directory spam stats including AI slopcasts and SEO bait shows • Where responsibility sits across podcast hosts, Apple Podcasts, Spotify and the Podcast Index • Alberto Batella on a taxonomy for AI podcasts and why health misinformation raises the stakes • Why RSS feed AI disclosure matters plus the “substance test” at shouldidisclose.ai • EU AI Act implications for podcast transparency and compliance • Apple enforcement questions and why trust is the asset at risk • Spotify Q1 results and what declining ad revenue signals for creators • Libsyn's video distribution to Spotify and the practical costs of big MP4 files Support the showConnect With Us: Email: weekly@podnews.netFediverse: @james@bne.social and @samsethi@podcastindex.socialSupport us: www.buzzsprout.com/1538779/supportGet Podnews: podnews.net

Hey everyone, Alex here

You did the responsible thing: you froze your credit to protect your identity. But the moment you temporarily "thaw" it to buy a car, apply for a mortgage, or rent an apartment, the floodgates open. Suddenly, your mailbox is overflowing with pre-approved credit cards, shady loan offers, and an endless stream of junk mail. What gives?In this episode, we dive into the frustrating, immediate, and highly profitable link between unfreezing your credit file and the avalanche of unsolicited mail that follows. We expose how the major credit bureaus monetize your "unfrozen" status, why the junk mail industry is watching your credit report, and, most importantly, the exact steps you can take to stop the paper jam and reclaim your mailbox.Episode Resources on Junk Mail:DMAchoice (ANA): Register at DMAchoice.org to reduce mail from national brands, magazines, and charities for 10 years (approx. $5 fee).OptOutPrescreen: To stop "pre-approved" credit card and insurance offers, visit OptOutPrescreen.com or call 1-888-5-OPT-OUT (1-888-567-8688). This is free, run by major credit bureaus, and can be done for 5 years online or permanently by returning a form.Catalog Choice: Use this free service at CatalogChoice.org to cancel specific catalogs and unwanted mailings. Episode Resources on Freezing Credit Report:You must place a freeze with each bureau separately: Equifax: Equifax.com or 1-888-298-0045.Experian: Experian.com or 1-888-397-3742.TransUnion: TransUnion.com or 1-888-909-8872.Send us Fan MailSupport Everything with Everett and stay ahead of the conversation! For just $10 a month, you can join the inner circle and unlock exclusive early access to brand-new episodes five days before they are released to the public. Your support helps continue the deep dives into politics, history, and culture that make this show unique. Be the first to hear what matters most and help us keep making great content for listeners everywhere. Subscribe now and get your head start! 

April 15th – Show 1115The ChatLee shared updates about his activities, including a visit to RAF Valley and work on dismantling a kitchen, as well as discovering new features in Virtual DJ that allow recording audio tracks with synchronized lyrics as MP4 videos. T discussed her recent activities, including sales at a market and work on a consistent market stall setup. She also shared progress on her book, including fleshing out scenes and catching inconsistencies, I shared this weeks experiences with AI tools like Perplexity and Docker, including creating a Python script to organize TV shows. Emergency Questions: If you had to eat a human body part to survive, which part looks the most appetizing? Would you rather have to wear a diaper every day (and use it) or have to wear a bib every time you eat? Have you ever been attacked by a goose? Backtrax – 60's Hits 01 TV & MoviesAt Home with the Furies Taskmaster The Boys The Beauty Linktree Discord: https://discord.gg/7ndTXDhNC5 a Facebook message A blog comment below @ us on Twitter Why not surprise us with an MP3 in an email to twoguys@snugradio.co.uk Please take some time to show us your love by reviewing us on ITunes. We welcome ALL comments The Snug is an affiliate of Amazon Music   Snug StatsMusic This ShowElf Maf & Lee – Passengers Tamara Sings – Only You Tamara Writes & AI Sings – Contradictions Cover Version SandwichCarry On My Wayward Son Join us every Wednesday from 18:30 (UK time) See you then…and have a Snuggly week.

Des vidéos de vacances en 4K qui remplissent votre espace de stockage, un fichier MKV illisible sur votre téléviseur, ou encore une pièce jointe trop lourde pour être envoyée par e-mail… ces problèmes sont devenus courants. Et depuis plus de vingt ans, un logiciel gratuit y apporte une réponse : HandBrake.Son fonctionnement est volontairement simple. On importe une vidéo, on choisit un format de sortie, puis on lance la conversion. Derrière cette apparente simplicité, le logiciel est capable de gérer une grande variété de formats : MKV, AVI, MOV, MP4 ou WebM. Il peut même traiter des DVD ou Blu-ray non protégés, à condition qu'ils ne soient pas verrouillés par des systèmes de sécurité.L'intérêt principal de HandBrake, c'est la compression. Autrement dit, réduire la taille d'un fichier sans dégrader visiblement la qualité. Pour cela, il s'appuie sur différents codecs, des technologies qui permettent d'encoder et de décoder la vidéo. Parmi eux, le H.264, très répandu et compatible avec la plupart des appareils, ou le H.265, plus récent, qui permet d'obtenir des fichiers plus légers à qualité équivalente. Pour les utilisateurs les plus exigeants, le codec AV1 offre encore plus d'efficacité, au prix d'un traitement plus lourd.Le logiciel tire aussi parti de l'accélération matérielle. Concrètement, il utilise la puissance des cartes graphiques, NVIDIA, AMD ou Intel, pour accélérer le traitement. Résultat : une vidéo 4K de vingt minutes peut être compressée en quelques minutes sur un ordinateur récent. Pour les débutants, des profils prédéfinis simplifient la prise en main. Il suffit de choisir un appareil, smartphone, console ou télévision, pour obtenir un réglage optimisé. Les utilisateurs plus avancés peuvent aller plus loin : ajuster le débit, la résolution, ou appliquer des filtres pour améliorer l'image.HandBrake permet aussi de traiter plusieurs fichiers en une seule fois, grâce à un système de file d'attente. Pratique pour convertir toute une bibliothèque vidéo. Disponible sur Windows, macOS et Linux, avec une interface en français, le logiciel continue d'évoluer. Sa dernière version améliore notamment la gestion des vidéos HDR et corrige plusieurs bugs. Hébergé par Acast. Visitez acast.com/privacy pour plus d'informations.

Vi puttrar om protester, småsnackar om småkategorier, irrar om index, nystar upp nyheterna, bubblar om bottar, vurmar om video, och spanar på slutsålda stjänkonferensen. Shownotes Aktuellt från svenska Wikipedia Protestuppmaning Pyttesmå kategorier LIX Wikimediarörelsen internationellt Wikinews stängs Bot-trafiken är hög, vad görs? Omröstning för att tillåta videoformatet MP4 vid uppladdning på Wikimedia Commons Registrering för Wikimania på plats sålde slut inom 24 timmar Veckans mall Jan: Owidslider Wikifikor, meetups och träffar i närtid Måndag: Mentor me: djupdykning kampanjverktyget Måndag: Wikidata liveredigering Erkännanden Bild: Thomas Angermann from Copenhagen, Denmark, CC BY-SA 2.0 Musiken och ljudklippen är från Surf Shimmy Kevin MacLeod (incompetech.com), CC BY 3.0, samt Wikimedia Sound Logo Finalist VQ97, Thaddeus Osborne, CC BY-SA 4.0, och ljudet från Wikidata’s 10th birthday video intro animation, Lea Lacroix (WMDE), CC BY-SA 4.0. Avsnittet hittas också på Wikimedia Commons. Diskutera avsnittet på projektsidans diskussion.

In this episode of The Dept. Omar breaks down the missing link to your business. Leveraging content to lead to more conversations is how you will make more money online! Creating and giving lead magnets to your viewers can build trust at a deeper level with your future clients! Make it easy for people to say yes to you.

Neste episódio comentamos sobre as principais atualizações e desafios no mercado de tecnologia, trazendo uma análise objetiva sobre cibersegurança e proteção de dados. Ao longo da reprodução, você irá descobrir os recentes desdobramentos éticos do uso de inteligência artificial em contextos militares, envolvendo a recusa da Anthropic em aderir aos termos do Departamento de Defesa norte-americano e os impactos disso para a privacidade global. Você também irá aprender sobre o novo marco regulatório do Conselho Federal de Medicina para ferramentas automatizadas na área da saúde, compreendendo como as exigências da LGPD se aplicam à segurança da informação na proteção de dados médicos sensíveis. Além disso, você entenderá os detalhes do recente ataque hacker que causou graves incidentes de segurança no setor financeiro, e saberá identificar as vulnerabilidades críticas na integração de modelos de linguagem via protocolo MCP, como a perigosa injeção de prompts em servidores expostos. O host Guilherme Goulart compartilha ainda sua vivência no evento SecOps Summit, refletindo sobre a importância dos profissionais de segurança na governança corporativa. Por fim, você poderá avaliar como o uso excessivo do ChatGPT pode afetar a criatividade e gerar a homogeneização do pensamento. Para continuar acompanhando nossas discussões, não se esqueça de assinar o podcast na sua plataforma preferida, seguir nossos perfis nas redes sociais e avaliar o programa para apoiar o nosso trabalho. Esta descrição foi realizada a partir do áudio do podcast com o uso de IA, com revisão humana.     Visite nossa campanha de financiamento coletivo e nos apoie!  Conheça o Blog da BrownPipe Consultoria e se inscreva no nosso mailing Acesse WhisperSafe – Transcreva áudio e grave reuniões direto no seu computador, mesmo offline. Rápido, leve e pronto para usar com qualquer IA. Use o cupom SEGLEG50 para 50% de desconto na sua assinatura. ShowNotes Episódio citado – 2013-06-18 – Episódio #28 – PRISM – Privacidade X Segurança The Pentagon formally labels Anthropic a supply-chain risk Anthropic's Claude is suddenly the most popular iPhone app following Pentagon feud Anthropic vs. U.S. Department of War The Pentagon Can't Afford This A.I. Fight Statement from Dario Amodei on our discussions with the Department of War Employees across OpenAI and Google support Anthropic's lawsuit against the Pentagon AI safety leader says ‘world is in peril’ and quits to study poetry Microsoft & Anthropic MCP Servers at Risk of RCE, Cloud Takeovers AI Conundrum: Why MCP Security Can’t Be Patched Away MCP is the backdoor your zero-trust architecture forgot to close Ministério da Educação – REFERENCIAL PARA DESENVOLVIMENTO E USO RESPONSÁVEIS DE INTELIGÊNCIA ARTIFICIAL NA EDUCAÇÃO Nova resolução de uso de IA na CFM Artigo “When ChatGPT is Gone: Creativity Reverts and Homogeneity Persists“ BTG Pactual restabelece operações via Pix após ser alvo de ataque hacker BTG Pactual sofre ataque hacker e suspende operações via Pix PF investiga participação de funcionários no ataque hacker de R$ 100 milhões ao BTG Pactual Imagem do Episódio: A Torre de Babel — Pieter Bruegel

In this episode of The Dept. Omar and Art.mp4 break down how to actually build a powerful personal brand in today's “oversaturated” content world. But instead of giving you the same recycled advice about posting more or chasing trends, they flip the script entirely… This conversation is about maximizing the opportunities you already have the calls, events, podcasts, and everyday moments most people completely overlook. You'll learn how to think differently about content, why most people are leaving attention (and money) on the table, and how to turn what you're already doing into a brand people actually want to follow. If you've ever felt behind, under-qualified, or like the market is too crowded, this episode will reset your perspective completely.

Make a Logo on Fiverr A Standalone Video Recorder Built for Flexibility If you’re looking for a dedicated video recorder that doesn't rely on a full PC setup, the Cloner Alliance 4K Pro positions itself as a flexible solution. This compact box acts as an intermediary between your source—whether that's a gaming console, OTT device, set top box, or camera—and your storage, capturing footage directly without needing a computer. It supports recording at 4K up to 30fps and 1080p at 60fps, making it a practical option for content creators focused on gameplay capture or video production workflows. The ability to work as both a standalone recorder and a PC-based capture device gives it added versatility depending on your setup. Recording Without a PC One of the biggest advantages here is the ability to record directly to external storage. Plug in a USB drive (up to 8TB) or a microSD setup, and the unit captures video in formats like MP4 using H.264 or H.265 encoding. This makes it ideal for: Capturing gameplay footage without OBS Recording camera feeds for B-roll Saving content from streaming or production sources There's no internal storage, but the plug-and-record workflow is straightforward. Insert a drive, hit record, and you're rolling. Pass-Through and Performance For gamers, pass-through is critical—and the Cloner Alliance handles that well. It supports 4K 60fps pass-through, so your gameplay still looks smooth on your display while the device records at 4K 30fps. However, there is some latency (around ~200ms) when monitoring through the device. That's not a deal-breaker for recording, but it's noticeable if you’re trying to play directly off the pass-through screen or syncing live visuals. Audio Options and Challenges Audio flexibility is solid on paper: HDMI embedded audio 3.5mm line-in Dedicated microphone input But in practice, audio routing can get tricky. You'll need to carefully manage sources—especially if your camera also has a mic—to avoid echo or distortion. Additionally, audio doesn't always pass cleanly through USB when using PC mode, which can complicate streaming setups. Controls, Interface, and Usability The device includes: Onboard buttons for recording and snapshots A remote control (basic but functional) On-screen menus for scheduling, playback, and settings You can even use it as a media playback device or loop content—handy for signage or event displays. But don't expect firmware updates or cloud connectivity—this is a fully offline system. Real-World Use Cases This is where the Cloner Alliance shines: Gaming recorder for consoles without PC overhead Backup recording device for video production Capturing camera feeds directly for editing Recording from OTT or set top box sources (non-HDCP content) It's especially useful if you want a dedicated recording pipeline separate from your main production system. The Downsides There are a few trade-offs: Slight delay before recording actually starts Noticeable monitoring latency Older micro USB connection for PC mode Audio routing quirks depending on setup None of these are deal-breakers, but they do require some workflow adjustments. Final Thoughts The Cloner Alliance 4K Pro isn't trying to replace high-end capture cards—it's carving out a niche as a simple, standalone video recorder. If your goal is to capture gameplay, camera footage, or production feeds without tying up a PC, it delivers exactly that. It's not perfect, especially when it comes to latency and audio handling, but for creators who want a plug-and-record solution, it's a solid addition to the toolkit. Check it out at https://geni.us/clonerallianceuhd Check out the Geekazine Merch, including "I AM AI " T-Shirt.  Thanks for reading! Don't forget to subscribe to Geekazine: RSS Feed - YouTubeTwitter - Facebook Tip Me via Paypal.me Send a Tip via Venmo RSS Bandwidth by Cachefly Get a 14 Day Trial Be a Patreon: Part of the Sconnie Geek Nation! Reviews: Geekazine gets products in to review. Opinions are of Geekazine.com. Sponsored content will be labeled as such. Read all policies on the Geekazine review page.  Reviews: Geekazine is also an affiliate of Amazon Last Updated on April 14, 2026 6:38 pm by Jeffrey PowersThe post Recording 4K 30fps Gameplay: ClonerAlliance 4K Pro Review appeared first on Geekazine.

When "Cloud-Only" Starts to Crack: Costs, Control, AI Risks, and Hybrid Reality The hosts discuss an AI-suggested topic: why "cloud-only" thinking is cracking, focusing on broken cost predictability from usage-based pricing, vendor lock-in and loss of control, latency and dependency on internet uptime, and growing compliance and data-residency pressures. They explore how AI increases data exposure risk while also driving demand for integrations like Copilot and Gemini, debate ethical/environmental concerns and whether banning AI would matter, and note AI may reduce support work while increasing competition. They argue hybrid setups are becoming a practical middle ground, enabled by smaller local hardware like Mac minis. They also cover new Apple Magic Mouse and keyboard purchases, announce the UniFi Cloud Gateway Industrial (high-power PoE and SIM slot features), promote ACES 2026 with code CCP, and describe difficulty playing a purchased MP4 on Apple TV due to AirPlay audio dropouts. 00:00 Show Kickoff 00:40 Cloud Costs Rising 04:57 AI Data Exposure 08:34 Ethics And Environment 13:22 Jobs And Competition 15:42 Latency And Outages 18:26 Vendor Control Drift 23:15 Hybrid Middle Ground 24:34 Compliance And Risk 27:20 How We Use AI 31:49 AI Hits Support Work 32:21 Apple AI Troubleshooting Vision 34:16 Staying Valuable Beyond AI 35:29 New Magic Mouse Setup 37:50 Fixing Accidental Gestures 40:45 UCG Industrial Gateway 41:43 Starlink Mini Power Options 45:42 Remote SIM And WiFi 7 47:09 ACEs 2026 And Discount 48:23 MP4 To Apple TV Struggles 51:47 Wrap Up And Thanks

Welcome to The Daily Wrap Up, an in-depth investigatory show dedicated to bringing you the most relevant independent news, as we see it, from the last 24 hours (3/3/26). As always, take the information discussed in the video below and research it for yourself, and come to your own conclusions. Anyone telling you what the truth is, or claiming they have the answer, is likely leading you astray, for one reason or another. Stay Vigilant. !function(r,u,m,b,l,e){r._Rumble=b,r[b]||(r[b]=function(){(r[b]._=r[b]._||[]).push(arguments);if(r[b]._.length==1){l=u.createElement(m),e=u.getElementsByTagName(m)[0],l.async=1,l.src="https://rumble.com/embedJS/u2q643"+(arguments[1].video?'.'+arguments[1].video:'')+"/?url="+encodeURIComponent(location.href)+"&args="+encodeURIComponent(JSON.stringify([].slice.apply(arguments))),e.parentNode.insertBefore(l,e)}})}(window, document, "script", "Rumble");   Rumble("play", {"video":"v74ee2a","div":"rumble_v74ee2a"}); Video Source Links (In Chronological Order): (5) Ryan Grim on X: "Don't know why I can't get over this lying https://t.co/r6FBSW1KlC" / X IMG_5413.MP4 (21) Sayer Ji on X: "'War with Iran' eclipsed ‘Epstein Files' search volume almost immediately. Distraction isn't a theory — it's measurable. https://t.co/fODBqFKFei" / X (21) The Last American Vagabond on X: "The US government is the laughing stock of the world. Now ask yourself why they would allow that to become the reality (and much of this is indeed a choice, as opposed to incompetence, which is also clearly a factor), and who would stand to benefit from that?" / X (2) The Last American Vagabond on X: "How it started: How it's going: https://t.co/VChNol7bWj" / X New Tab US/Israel Illegally Bomb Iran Killing Over 100 Schoolchildren (2) Euro-Med Monitor on X: "In southern #Iran, a girls' school became a place of unimaginable grief after at least 165 students were killed and dozens more injured in a #US-Israeli strike. Now they rest with their dreams in a mass grave. Schools are meant to nurture hope, not bear the scars of war. https://t.co/Bv64tFCIzQ" / X (2) GeoConfirmed on X: "GeoConfirmed Iran. Statement regarding our posts about the bombing of a girls' elementary school reportedly resulting in the deaths of over 100 girls. Because many readers still misunderstand our posts or how geolocation verification works, I will explain this as simply as" / X (3) MAGA Voice on X: "HOLY SH*T

Apple turns on HLS video in Apple Podcasts and rewrites the business rules while keeping files with hosts. We unpack the listener experience, creator workflows, dynamic ads, costs, open standards, and what Spotify and YouTube might do next, with insights from Justin Jackson.• HLS explained and why it matters for control• What listeners get on iOS and when it ships• MP4 feeds versus HLS delivery trade-offs• Supported hosts at launch and why ad-tech drives it• Delivery metrics vs true attribution for advertisers• Apple's per-ad tech fee and billing model• Rising CDN request costs and host pricing changes• Audio switching, manifests, and separate audio renders• Alternate enclosure for wider app distribution• Tags that should be next: person, location, live• Industry reactions from publishers and ad leaders• Live video, platforms, and monetisation experimentsStart podcasting, keep podcasting with BuzzSprout.comSend James & Sam a messageSupport the showConnect With Us: Email: weekly@podnews.net Fediverse: @james@bne.social and @samsethi@podcastindex.social Support us: www.buzzsprout.com/1538779/support Get Podnews: podnews.net

On Weds, February 18th Live Episode #651 of the New Media Show, Rob Greenlee, Host, 2017 Podcast Hall of Famer and CEO of Trust Factor Lab at https://RobGreenlee.com, and James Cridland, Editor, https://Podnews.net and 2026 Podcast Hall of Famer discuss Apple's announcement of a new and improved video podcast experience in the Apple Podcasts app and what it changes technically and strategically heading into 2026.  They explain how video was previously active in Apple Podcasts but was hidden and poorly presented in the iOS apps, and how this new updated experience makes video playback front and center, with a “turn video off” option that keeps the audio track playing.  The episode breaks down Apple's preferred move to HLS-based on-demand video delivery (via a separate, proprietary API HLS video streaming pass-through submission from approved hosting partners) while still supporting legacy MP4 video via RSS.  They cover HLS basics (chunked delivery, adaptive quality, reduced bandwidth, and hosting costs), improved seeking/scrubbing versus progressive MP4 playback, and new measurement implications (better insight into drop-off and ad viewing). A major focus is monetization: Apple plans to enable dynamic ad insertion for HLS video and charge a per-impression fee, positioning Apple to take revenue without operating an ad business.  The conversation notes early launch partners (Acast, Art19, Omny Studio, Simplecast), questions about specs and rollout timing (an app update is likely by the end of March; dynamic ad features later in the year), and the risk of platform fragmentation as distribution shifts from open RSS to proprietary APIs.  James and Rob discuss alternate enclosures (Podcasting 2.0) as an open path to wider app support, reference iHeart's stated support for video via RSS alternate enclosures, and highlight creator concerns about losing separate audio edits when video replaces the audio feed during playback.  They also touch on device support (not initially on Apple TV; CarPlay doesn't show video; Vision Pro support) and briefly discuss future RSS innovation ideas like comments, payments, transcripts, and location tags, plus a short note on upcoming podcast events (Podcast Show London, Podcast Movement New York, Podcast Movement at SXSW). Chapter Topics: 00:00 Welcome + Why Apple's Video Podcast Update Matters 01:31 Apple Brings Video Front-and-Center (and Why Now) 06:00 The New Playback Experience: Full-Screen Video & One Feed 10:49 How Apple's HLS Video Works (and Why It's Better) 11:36 The Money Shift: Dynamic Video Ads & Apple's Per-Impression Fee 17:59 Rollout Timeline, Unknown Specs, and Early Partner Shows 23:54 Partners, Two Ingestion Paths, and the RSS vs HLS Debate 34:47 Hands-On Demo: Video Icons, Turn Video Off, and MP4 vs HLS 39:47 Bandwidth, Scrubbing, and What HLS Enables for Measurement 44:16 Quality/Resolution Questions + Missing Apple TV (for Now) 46:26 CarPlay & Vision Pro: Where Apple Podcasts Video Actually Plays 47:09 Will HLS Replace MP3 for Audio? Monetization, Costs, and Reality Check 49:51 Apple vs Spotify: Open Hosting, Dynamic Ads, and Why This Helps Creators 52:30 Audio Isn't ‘Video Without Pictures': Why Separate Edits Matter 55:21 Will It Work With Spotify for Creators? Partners, Megaphone, and Pressure 01:00:02 How HLS Interstitials Work: Client-Side Ad Breaks and Spec Unknowns 01:07:48 Keeping RSS Relevant: Alternate Enclosures, Comments, Payments, and New Tags 01:13:48 Local Podcasting & Specialized Apps: Location Tag, TuneIn, and the Future 01:20:20 Wrap-Up: Conferences, Cold Weather, and Final Goodbyes What you will learn in this episode – How Apple's HLS video differs from RSS MP4 enclosures in real-world creator workflows  – Why HLS segment-based delivery enables adaptive streaming and modern video ad insertion – What Apple's limited launch partner list means for hosting competition and creator choice  (Podnews) – https://podnews.net/article/video-apple-podcasts-details – How Apple Podcasts Connect API keys work, and what they do and do not grant to hosting providers – https://podcasters.apple.com/support/5593-how-to-publish-video – How creators should decide between RSS video, Apple HLS video, and other platform video strategies in 2026 – https://www.theverge.com/tech/879749/apple-podcasts-video-swap-hls-live-streaming Links for show notes Watch live or On Demand https://newmediashow.com Apple announcement https://www.apple.com/newsroom/2026/02/apple-introduces-a-new-video-podcast-experience-on-apple-podcasts/ Apple creator documentation https://podcasters.apple.com/video-apple-podcasts  https://podcasters.apple.com/support/5593-how-to-publish-video https://podcasters.apple.com/support/3684-video-podcasts  Podnews analysis https://podnews.net/article/video-apple-podcasts-details  https://podnews.net/update/apple-podcasts-hero  Guest James Cridland, Editor, https://Podnews.net https://james.cridland.net/biography/  Host Rob Greenlee, 2017 Podcast Hall of Fame Inductee https://robgreenlee.com https://www.linkedin.com/in/robgreenlee https://www.youtube.com/@RobGreenlee https://x.com/robgreenlee https://PodcastHall.comThe post Apple's New Video Podcast Deep Dive | James Cridland #651 first appeared on New Media Show.

-X is facing yet another investigation into Grok's reported creation of nonconsensual sexual images on the platform. Ireland's Data Protection Commission has announced an inquiry into X regarding the harmful, intimate images and processing of EU and EEA individuals' personal data — including children. -The European Commission has opened an investigation into low-cost fast fashion retailer Shein. EC officials are concerned about the sale of illegal products, including child sexual abuse material, as well as the potentially addictive design of its shopping experience. -Apple is planning a major update for its Podcasts app. The app now supports the company's HTTP Live Streaming video technology. Previously, it only streamed video in various formats like MOV, MP4 and M4V. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Reuploading as an earrlier version was accidently uploaded as a MP4. I apologize if anyone sees this twice History of Djibouti  Munaty cooking: https://www.munatycooking.com/skoudehkaris/ Email: whydocountriesexist@gmail.com Website: https://whydocountriesexist.libsyn.com/sources-for-djibouti-episode Patreon: patreon.com/Whydocountriesexist797 Paypal: paypal.me/whydocountriesexist Feedback and request forum: https://forms.gle/H5hG9zcZbFPBAz8t7 Intro 0:00 Country profile 1:30 Early history 4:22 Early modern history 6:39 French Somaliland 8:03 Independence and civil war 14:59 Current history and politics 19:45 Conclusion, outro and sources 25:12

In this episode of The Dept. Omar is joined by Brandon Flakes and Art.mp4 to break down one of the most powerful (and overlooked) ways to build a personal brand today: stop trying to make content and start being the content. They unpack how trust is built by simply showing your real work, conversations, and process without scripts, hacks, or perfection. From filming everyday moments and meetings, to why consistency beats polish, to how this approach has directly led to millions in business, this episode gives a practical, freeing framework for creators, entrepreneurs, and leaders who want visibility without burnout. If you want to build a brand people trust, grow your influence organically, and turn your life and work into leverage, this conversation will completely change how you think about content.

In this episode of The Dept. Omar is joined by Neel Dhingra and ART.MP4 to break down how creators and entrepreneurs can actually use AI to grow a real business, not just create more noise. They walk through how to use AI for content ideation, packaging, editing, distribution, and automation, while staying authentic to your voice and vision. From building a personal brand faster to saving time, increasing leverage, and even driving millions in revenue, this conversation shows how AI becomes a multiplier when paired with clarity, strategy, and action. If you've felt late to AI, overwhelmed by tools, or unsure how to turn content into income, this episode gives you a practical, grounded path forward.

¿Alguna vez habéis pensado que vuestro coche es, en realidad, un organismo vivo? Tiene corazón, el motor; tiene cerebro, la centralita; y tiene extremidades, la suspensión. Pero nada de eso serviría sin un esqueleto que lo mantenga todo unido: el Chasis. Un buen chasis define si un coche es una maravilla o un desastre, porque la rigidez lo es todo. Si la estructura flexa o se retuerce como un flan al tomar una curva, la geometría de la suspensión se pierde, el coche no gira y, lo peor de todo, el coche miente al conductor. Hoy hacemos un viaje técnico, pero con lenguaje "asequible", a través de la historia y la ingeniería de los chasis. Desde los primeros "hierros" hasta la fibra de carbono. 1. El origen: Largueros y travesaños (Ladder Frame) Es la lógica pura heredada de los carruajes de caballos. Se trata de dos vigas gruesas de acero unidas por travesaños, pareciendo una escalera de mano tumbada. Aunque es una tecnología antigua, sigue viva en los todoterrenos puros como el Jeep Wrangler o el Toyota Land Cruiser por una razón: su robustez absoluta. La carrocería es solo una caja que "flota" encima, aislada con silentblocks. Es pesado y tiene un centro de gravedad alto, pero es indestructible. 2. La revolución: El chasis tubular La competición buscaba ligereza, así que sustituyeron las vigas macizas por jaulas de tubos finos soldados formando triángulos (la forma indeformable por excelencia). Aquí encontramos historias fascinantes: -Mercedes 300 SL: Sus puertas de "Alas de Gaviota" no son postureo, son una necesidad técnica. Su chasis tubular era tan alto en los laterales para garantizar rigidez que no podían poner puertas normales. -Porsche 917: Ferdinand Piëch llevó esto al límite usando magnesio. El chasis de este monstruo de 1000 CV pesaba solo 42 kilos. El problema es que el magnesio es altamente inflamable e imposible de apagar. Para detectar fisuras, los tubos estaban llenos de gas a presión y el piloto tenía un manómetro en el salpicadero. Si la aguja bajaba en plena recta de Le Mans, sabían que el chasis se estaba rompiendo. 3. La rareza genial: El chasis de viga central Una solución técnica preciosa popularizada por Colin Chapman en sus Lotus y usada en el Alpine A110 original o el DeLorean. Consiste en una columna vertebral central muy rígida que conecta ambos ejes. Es ligero y permite una transmisión central limpia, pero tiene un gran defecto: la nula protección en impactos laterales, motivo por el que cayó en desuso con las normativas modernas. 4. El estándar moderno: Monocasco autoportante Popularizado por el Citroën Traction Avant en 1934, es lo que conducimos hoy. No hay diferencia entre chasis y carrocería, todo es una estructura de chapa estampada y soldada. Permite más espacio interior y bajar el coche al suelo. Hoy en día se usan aceros al boro de ultra-alta resistencia para proteger a los ocupantes en caso de vuelco. 5. Nuevos materiales: Aluminio y el "pegamento" Muchos creen que el Audi A8 fue el primer monocasco de aluminio, pero el honor es del Honda NSX en 1990. Sin embargo, la revolución llegó con el Lotus Elise en 1996. Sus ingenieros descubrieron que soldar aluminio lo debilita por el calor, así que decidieron pegarlo con adhesivo epoxi aeroespacial. El resultado fue un chasis de extrusiones de aluminio de solo 68 kilos, una técnica que hoy usa Aston Martin. 6. La era espacial: Fibra de Carbono Introducida en la F1 por McLaren en 1981 con el MP4/1. Al principio se temía que se hiciera añicos como el cristal en un accidente, pero John Watson demostró en Monza (saliendo ileso de un accidente brutal) que era el material más seguro del mundo. Hoy en día, coches como el Alfa 4C o el Bugatti Chiron usan "bañeras" de carbono cocinadas en autoclave. Comparativa de Rigidez (Nm/grado): Para que veáis la evolución, la rigidez se mide en la fuerza necesaria para torcer el coche un grado: -Lotus Elan (Viga central): ~4.500 Nm/grado. -McLaren F1 (Carbono de los 90): 13.500 Nm/grado. -Ferrari 360 (Aluminio): 23.000 Nm/grado. -Bugatti Chiron (Carbono moderno): 50.000 Nm/grado. El chasis es el héroe silencioso de tu coche. La próxima vez que tomes una curva y sientas que el coche apoya plano, recuerda que es mérito de esos ingenieros que pelearon con soldaduras, pegamentos y fibras.

In this episode of The Dept. Omar breaks down his Online Business Operation Blueprint. A simple, repeatable framework for turning your knowledge into your first $10,000 a month online. He walks through the three core moves every creator, coach, or entrepreneur needs to master: unlocking infinite content, guiding people into intimate conversion events, and building one irresistible core offer. Along the way, Omar explains why most people overlook what they're already great at, how content really drives trust and sales, and why the buying experience matters more than “selling tactics.” If you want to monetize your expertise without overcomplicating it and build a business that actually lasts this episode will completely reshape how you think about content, offers, and income online.

What if working LESS is the smartest business growth strategy for 2026? Michael Walsh went three years without a vacation—grinding relentlessly, believing scaling required personal sacrifice. Then his wife forced him to take time off. The result? He generated $10,000 in new sales—more than any previous week. He tested further, taking the last week of every month off. His income kept growing. After 30+ years helping $2M-$20M companies scale, Michael has proven that people-first business growth outperforms systems-first approaches every time. What You'll Discover: ✅ The $10,000 vacation discovery - Why strategic time off accelerates revenue instead of slowing it down ✅ The relationship complexity math - Why 100 people = 4,950 relationships, explaining why your systems break as you scale from $1M to $10M ✅ Survive, Thrive, Connect, Adapt framework - Practical roadmap for understanding human behavior structures that support your people to be at their best ✅ Why your people are your #1 brand story customer - How training influencers (even janitors and cafeteria workers) instead of just executives creates authentic brand ambassadors ✅ The social contract that works - Why professional growth takes pressure off top dollar, and how two-minute weekly conversations replace twice-yearly performance theater ✅ Intelligent ecosystems vs. machines - Why "I'm the boss, you do what I say" fails in service businesses, and how to build adaptive capacity ✅ AI and the Age of Creativity - How AI is eliminating junior jobs and what the shift from Information Age to Age of Creativity means for your business About Michael Walsh: Michael Walsh is founder of Walsh Business Growth Institute and author of Freedom by Design: The Established Business Owner's Guide to Grow, Make an Impact, and Find the Joy Again. His myth-busting methodologies liberate owners from operational dependency through contrarian, people-first strategies. FREE BOOK: Get Freedom by Design free (print, PDF, or MP4) at WalshBusinessGrowth.com Key Topics: business growth strategies, scaling $2M-$20M companies, employee relationship management, leadership development, burnout recovery, work-life balance, organizational culture, brand storytelling, people-first leadership, service business optimization, AI impact on business, future of work Connect with Michael:

In this episode of The Dept. Omar breaks down what people are actually buying online and why most creators and entrepreneurs are stuck trying to sell the wrong thing. Joined by ART.MP4 and Brandon Flakes, the conversation unpacks the real drivers behind high-converting offers, from speed and transformation to identity, proximity, and community. Omar introduces a powerful framework that explains why courses, communities, and products don't sell on their own and how to reposition what you offer so it actually resonates and makes money. If you're trying to monetize your knowledge, build better offers, or finally understand why some businesses scale while others stall, this episode will completely change how you think about selling online.

Website Marketing vs. SEO Marketing: The Complete Business Essentials Guide with Favour Obasi-Ike | Sign up for exclusive SEO insights.This episode demystifies the relationship between website marketing and Search Engine Optimization (SEO), clarifying the critical distinction between the two. The discussion frames website marketing as the broad, all-encompassing "ecosystem" of a brand's online presence, including email, social media, and advertising. In contrast, SEO is presented as the tactical, high-performance "engine" that powers a website's visibility and drives targeted traffic within that ecosystem. Through foundational principles, practical strategies, and live consultations with business owners, this guide provides a comprehensive framework for building a powerful and effective digital identity.--------------------------------------------------------------------------------Next Steps for Digital Marketing + SEO Services:>> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Need SEO Services? Book a Complimentary SEO Discovery Call with Favour Obasi-Ike⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠>> Visit our Work and PLAY Entertainment website to learn about our digital marketing services.>> Visit our Official website for the best digital marketing, SEO, and AI strategies today!>> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Join our exclusive SEO Marketing community⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠>> Read SEO Articles>> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Need SEO Services? Book a Complimentary SEO Discovery Call with Favour Obasi-Ike⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠>> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Subscribe to the We Don't PLAY Podcast⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠--------------------------------------------------------------------------------Key Takeaways• Website Marketing is the Ecosystem, SEO is the Engine: Website marketing is the entire universe of your online activities, from email campaigns to social media posts. SEO is the specific, technical practice of optimizing your website to be found by search engines, giving your marketing efforts direction and power.• Your Website is Your Digital Identity: A website is more than a link or a digital storefront; it is the central hub for establishing your brand's credibility, trustworthiness, and authority, creating a lasting experience for both new and returning visitors.• Messaging Precedes Marketing: The effectiveness of any marketing tactic hinges on compelling messaging that connects with customer psychology. As demonstrated with the "strawberry" example, great marketing shifts a customer's mindset from a simple "need" to an emotional "want."• Storytelling Sells, Facts Only Tell: To convert visitors into customers, product descriptions must go beyond listing features and instead create an emotional connection. As speaker Mo advises:• Technical Health is Non-Negotiable: A website's foundational health depends on more than just load speed and hosting. Consistently publishing fresh content is critical because every update creates a new "tokenized" copy for search engines to crawl. A dormant site gives search engines no reason to return, while an active site signals relevance and forces re-evaluation, directly impacting rankings.--------------------------------------------------------------------------------Detailed Episode Notes1. Defining the Landscape: Website Marketing vs. SEOTo build a successful online presence, it is vital to distinguish between the overarching platform of website marketing and the specific tactics of SEO. Website marketing represents your brand's total visibility and communication channels online. SEO, a critical component within that framework, is the deliberate set of actions taken to ensure your website is discovered by the right audience at the right time. Understanding this difference is the first step toward a coherent and effective digital strategy.Contrasting Key ConceptsWebsite Marketing (The Ecosystem)The Truck and Engine AnalogyThe relationship between these two concepts can be understood through a simple yet powerful analogy presented during the episode:"Think of your website like a truck. Website marketing is the truck itself—it exists, it's present, and it's visible. SEO is the engine that actually moves the truck forward, giving it the power, speed, and direction it needs to reach its destination."With these foundational definitions established, it's clear that the website itself serves as the strategic center of all marketing efforts.2. The Strategic Hub: Your Website's Core FunctionYour website is your most critical digital asset. It is the definitive online destination where you control the narrative and build direct relationships with your audience. Far more than just a place for transactions, it is the central hub for establishing trust, demonstrating expertise, and solidifying a brand identity that resonates with visitors long after they leave.The Four Pillars of a Trustworthy WebsiteFor a website to be effective, it must embody four key qualities for every visitor:1. Credible: The information is accurate, professional, and demonstrates authority.2. Resourceful: It provides value and answers the questions your audience is asking.3. Trustworthy: The site is secure, transparent, and operates with integrity.4. Accessible: It is easy to navigate and available to all users.Analyzing Visitor BehaviorEvery website serves two primary types of visitors: new visitors and returning visitors. Understanding their distinct behaviors through analytics is crucial for optimization. With over 1.1 billion websites online, simply existing is not enough; your site must be engineered to effectively engage both audiences and guide them toward a desired action.Key Website ComponentsA modern website is a multimedia platform composed of various elements that search engines index and users engage with:• Text (including body copy, headlines, and policies)• Images (with descriptive alt text for accessibility and SEO)• Audio (e.g., MP3 files for podcasts or sound clips)• Video (e.g., MP4 files for tutorials or product showcases)• Documents (e.g., PDFs for white papers or downloadable guides)A well-structured website, rich with these components, provides the perfect foundation for the tactical work of SEO to drive qualified traffic.3. Tactical Deep Dive: Activating Your SEOSEO is the disciplined practice of aligning your website's structure and content with the specific words and phrases your target audience uses in search engines like Google. It is not about tricking algorithms but about creating a valuable and relevant experience that naturally earns high visibility. This requires a consistent content engine, especially since blogs have a shelf life of 24 months. A single post can provide SEO value for up to two years, demonstrating the long-term ROI of a strategic content plan.The Content Creation EngineGenerating traffic starts with a simple question-and-answer flow. How do you generate traffic? By kickstarting the engine. How do you kickstart the engine? By creating content. How do you create effective content? By building links through publishing valuable posts like blogs, landing pages, and product pages.Uncovering SEO OpportunitiesA live demonstration in the episode revealed how to find high-intent keywords directly from Google's search suggestions—a reflection of real, frequent user queries.The strategic takeaway is clear: each of these suggestions represents a distinct user need. A single list of 10 terms can be transformed into 10 to 50 unique media assets, including blog posts, email newsletters, social media updates, and even podcast episodes. This moves SEO from theory to a practical, content-driven reality.4. Marketing in Action: Live Business ConsultationsApplying marketing theory to real-world businesses is the fastest path to clarity. This section analyzes the specific, actionable advice given to two entrepreneurs, providing a blueprint for any product-based business seeking to translate online presence into measurable results.5. Tools & Resources MentionedThe selection of a tool, particularly for email marketing, is not just a matter of features but also of technical performance. As discussed in the episode, platforms with strong server infrastructure (like Flodesk's partnership with Amazon SES) can significantly impact email deliverability, a key component of the overall marketing ecosystem.• AI Idea Generation: ChatGPT, Perplexity, Claude, DeepSeek, Grok• Email Marketing Platforms: Constant Contact, Mailchimp, Flodesk (preferred), Aweber, Kit, Brevo• Website Hosting: GoDaddy, BlueHost, Hostinger, SiteGround• Website Builders: Webador• Social & Content Platforms: Instagram, Pinterest, YouTube, Clubhouse• E-commerce: AmazonSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Working and Breastfeeding Made Simple? Nancy and Barbara discuss this important topic and how their new book group, Working and Breastfeeding Made Simple, can help make you an expert on this topic. Here are just five topics that will be covered in depth during the book group! Yes, it is possible to support working parents in achieving their infant feeding goals. Several critical factors for supporting breastfeeding/chestfeeding among employed parents have been identified in the literature and clinical practice. Despite the dire statistics, families in Barbara’s private practice actually do well. None of them discontinued breastfeeding during the first month of returning to work. Providing accurate information about how breast milk supply works and how to express breast milk, along with social and emotional support, appeared to help clients maintain breastfeeding despite occasional difficulties. Here are five critical factors that help families meet their breastfeeding goals. 1. Breastfeeding Is Going Well Before Returning to Work One critical factor for success is having the parent be good at breastfeeding before they return to work. It is well established that breastfeeding becomes less labor-intensive (and generally easier) for most mothers at approximately 6–7 weeks (Mohrbacher & Kendall-Tackett, 2010). If breastfeeding isn't going well or a mother goes back to work before 6–7 weeks, she is more likely to be unsuccessful with this transition. If a mother is struggling with pain, has a baby who doesn't feed well at the breast, or her milk supply is low when she returns to work, she is doubly challenged from the get-go! Providing a plan to address these issues along with hope, accurate information, and support can help mothers continue breastfeeding even as they return to work. 2. Support From an International Board Certified Lactation Consultant The support and information that an International Board Certified Lactation Consultant (IBCLC) can provide are critical for success. Many parents don't have anyone in their lives who understands or cares about why they are even trying to continue to breastfeed and work. IBCLCs do care. They want them to achieve their breastfeeding/chestfeeding goals. Together, IBCLCs can help improve the low statistics on working and breastfeeding success. 3. Success at Milk Removals Another critical factor for success is how effectively the parent expresses their milk when separated from their baby. Most clients use a standard, personal-use, double-electric breast pump. However, not all pumps are created equal. Some work well, and some don't work as well. Using a pump with adequate vacuum, different-sized breast shields (as necessary), and variable speeds will increase her chances of success. At the same time, if a pump has all these things and they is still not getting out their milk, IBCLCs have to get creative. Perhaps they need to try a different pump brand, rent a hospital-grade pump, use a hand pump, or hand express. Watching a parent pump is essential. Test the vacuum. Make sure their shields fit well. Many families are unaware that different-sized breast shields even exist. Positive associations to help them “Feel the Love” for their pump. Without an oxytocin release, parents are trying to pull the breast milk out of their bodies. With an oxytocin release, they are working in sync with their body. Their body is pushing the milk out of their breasts. This is much more effective. If the parent is having trouble “feeling the love,” suggest warm compresses, warm breast shields (Kent, Geddes, Hepworth, & Hartmann, 2011), and/or massage before pumping (Bolman & Witt, 2013; Bowles, 2011). They can also use “hands-on” pumping techniques to help get the breast if the milk is flowing (Morton, n.d.). Additionally, hand expression for a minute or two on each breast after pumping can support milk production (Morton et al., 2012). Some mothers find that visualizing their baby or their milk flowing helps. Others find that playing Candy Crush helps! There are some hypno-pumping visualization MP4 products out there. Have them practice pumping while getting a massage, eating chocolate, or watching their favorite comedy. It's straight classical conditioning. Pair a condition with a response (think Pavlov's dog). Clients can help train their bodies to have an oxytocin surge in response to their pumps. If a mother is having difficulties with her milk production, encourage her to blame her pump for lack of breast milk, not her body! If breast milk is not being removed effectively while she is separated from her baby, her supply will go down. 4. Supportive Child Care Working and breastfeeding success can also be at risk if the family's child care provider does not value breast milk or the breastfeeding relationship with the baby. Overfeeding the baby while the parent is away is a common problem. The child care provider needs to understand that not all crying or fussiness is about food. They also need to know how to care for expressed breast/chest milk and how to bottle-feed a baby in a breastfeeding-friendly manner by pacing the bottle feed. It is now recommended that all infants be fed in this manner, not just breastfed infants, even when there is breast milk in the bottle. Pacing the feed helps the baby control his or her intake and prevents overeating, which may help prevent obesity in later life. 5. Avoid Overfeeding at Child Care The final stumbling block concerns overfeeding and subsequent reduced breastfeeding when families are reunited. When a baby has been overfed at child care, not only is it almost impossible to keep providing enough pumped breast milk for the baby, but the baby also doesn't need to breastfeed as often from mom when they get back together. It is as if the baby is saying, “No thanks; I'm good! I had all my needed calories for day from my caregiver.” This does not hold true for all babies, but it does for many. Additionally, being away from one’s mother can be stressful and tiring. Babies can sometimes sleep longer at night because of this. Between not needing to nurse because of the calorie overload during child care and sleeping longer at night, mothers can end up breastfeeding far less than they were before returning to work. Suggesting that mothers pump before going to bed if their baby is scheduled to sleep at 8:00 p.m. and will not feed much during the night can help. This strategy appears to help improve their breast milk supply. Summary In Barbara’s clinical practice, she has found that these five factors can undermine a parent's ability to continue breastfeeding/chestfeeding after they return to work. Again, breastfeeding not working well, the lack of information and support, milk removals not working well, lack of paced bottle feeding, and a parent's daily milk removals reducing over time are the most common culprits that have been found to sabotage a mother's success in meeting her breastfeeding goals when returning to work. Providing information about these issues may help families anticipate problems before they arise, or at least help them quickly identify when they are moving down a slippery slope, and can significantly increase their odds of having the breastfeeding/chestfeeding relationship they dreamed of before returning to work. The post All Things Breastfeeding Episode 104: Working and Breastfeeding Made Simple appeared first on The Breastfeeding Center of Ann Arbor.

In this episode of The Dept. Omar celebrates 100 weeks of uploading and breaks down the ONE habit that can completely change your life and business: showing up consistently with one long-form video every week. From building unshakable trust with your audience, to transforming your personal brand, to unlocking indirect opportunities you could never predict, Omar shares the five pillars that have fueled his growth establishing your reason, assembling the right relationships, dialing in your weekly routine, refining your craft, and making clear invitations that move people. This live episode is packed with real stories, mindset shifts, and practical frameworks to help you build a brand people trust, keep your word, and step into the person your business requires you to become. If you want to grow online and finally stay consistent, this conversation will change the way you create forever.

In this episode: Martin has been learning Go and created: Jivedrop - Drop the mix, ship the show-metadata, cover art, and all

In this episode: Martin has been learning Go and created: Jivedrop - Drop the mix, ship the show-metadata, cover art, and all

What are you really waiting for this December? Not the polished answer—the honest one. What's keeping you up at night? What's making your spouse anxious? In this first episode of our 4-part seasonal series, we explore the three types of hope that show up in marriages during the holidays: Security (Will we be okay? Will we have enough?), Connection (Will everyone get along? Will anyone feel left out?), and Intimacy (Will we stay close intimately or sexually)? Will we lose each other in the chaos?). You'll discover why you and your spouse are often "waiting" for completely different things this season, and why that difference creates so much tension. More importantly, you'll learn how to honor both longings without making either one wrong, so you can actually experience renewal together instead of just surviving until January. Whether you're the one watching the budget, managing family dynamics, or protecting your marriage connection, this episode will help you name what you need and understand what your spouse needs too. Watch on YouTube, tooz1 Get your "Me-Time Coaching Session" package here!⁠ https://www.enneagramandmarriage.com/coachingpackages-2 Use code BLACKFRIDAY for 55% off here! www.EnneagramandMarriage.com Get on our Advent adventure together too where we'll discuss hope, love, and joy starting December 1st at ⁠⁠⁠www.EnneagramandMarriage.com⁠⁠⁠. Mark your calendars for Dec 9 as we meet over Zoom 1PM EST to discuss how to keep you from fighting all season long, too! Sign up for emails to get your link. Find more about your type, the pod, freebies, and SO much more at our website right here! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.EnneagramandMarriage.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Leave Christa a podcast question anonymously by sending an MP4 recording to enneagramandmarriage@gmail.com. Love what you're learning on E + M? Make sure you leave us a podcast review so others can find us, too⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ here!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Learn more about your ad choices. Visit podcastchoices.com/adchoices

The third episode in our family systems series explores triangulation, the pattern where a two-person relationship becomes unstable so you pull in a third person to stabilize it. Instead of dealing with issues directly with your spouse, you complain to your mom, get your best friend to tell them they're wrong, focus all your energy on the kids, or text your sister about your marriage. Triangulation feels safer than direct conflict because it gives you validation and emotional support without vulnerability, but it doesn't actually solve anything. Christa breaks down how each Enneagram type triangulates and also gives general tips in this quick, must-listen holiday prep episode! But here's the nuance: sometimes you need to triangulate for a moment. Listen for how to do both! www.EnneagramandMarriage.com if you're not on the email list yet. Watch on YouTube! Get your "Me-Time Coaching Session" package here! https://www.enneagramandmarriage.com/coachingpackages-2 Use code BLACKFRIDAY for 50% off here! www.EnneagramandMarriage.com Get on our Advent adventure together too where we'll discuss hope, love, and joy starting December 1st at ⁠⁠www.EnneagramandMarriage.com⁠⁠. Find more about your type, the pod, freebies, and SO much more at our website right here! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.EnneagramandMarriage.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Leave Christa a podcast question anonymously by sending an MP4 recording to enneagramandmarriage@gmail.com. Love what you're learning on E + M? Make sure you leave us a podcast review so others can find us, too⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ here!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Learn more about your ad choices. Visit podcastchoices.com/adchoices

As we head into Thanksgiving week, fears are high and tensions are real and you and your family need both wisdom and peace for the wild cultural times and questions of faith in dark moments. Alexandra Hudson, leading world leader and founder of Civic Renaissance (with 50,000 subscribers and the praise of the Wall Street Journal) is timely on the pod, both in our convo here with Christa in also what she has written "The Soul of Civility" as she revived what the ancient Greeks called "the Great Conversation" about politics, beauty, goodness, and truth. On the must-listen pod here, Alexandra (Lexie) makes a crucial distinction: true civility is deeper than politeness, understanding the substance behind people's words and practicing robust discourse with love while respecting personhood. This conversation explores the "libido dominandi," the desire to dominate that shows up in marriages, families, and our cultural discourse, as human group effect takes us farther away from what we really need - each other. Whether you're navigating a tense marriage, a divided family gathering, or just trying to stay sane in our current moment, this listener-requested episode is a gem as you prep for differing voices over the holiday. Remember, respectful discourse doesn't mean avoiding disagreement, it means engaging it well and with love and grace so good is done in the world - we are all learning this together. Watch on YouTube! Get the book: "The Soul of Civility: Timeless Principles to Heal Society and Ourselves" by Alexandra Hudson https://a.co/d/dzJN8Zs Get on her website to get her beautiful newsletter: https://alexandraohudson.com/ Get on our Advent adventure together too where we'll discuss hope, love, and joy starting December 1st at ⁠www.EnneagramandMarriage.com⁠. Find more about your type, the pod, freebies, and SO much more at our website right here! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.EnneagramandMarriage.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Leave Christa a podcast question anonymously by sending an MP4 recording to enneagramandmarriage@gmail.com. Love what you're learning on E + M? Make sure you leave us a podcast review so others can find us, too⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ here!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Learn more about your ad choices. Visit podcastchoices.com/adchoices

In this episode of The Dept. Omar breaks down the five video formats that every creator and entrepreneur should be using to grow on YouTube in 2026 without relying on hacks, luck, or the algorithm. After 15+ years on the platform and over 70M views, he reveals why most people don't grow: they aren't making bulletproof videos. Omar walks through the exact types of videos YouTube is pushing right now, from compilation content, course-style long-form videos, and content marathons, to conversation-based videos and crowd content. If you want to grow your YouTube channel this year, build trust faster, create content that stands out above the noise, and develop a personal brand people actually want to follow, this episode is a full masterclass on creating videos that work.

The second episode in our family systems series explores the overfunctioning and underfunctioning dynamic, the exhausting pattern where one partner takes on too much responsibility while the other does less than their share. The more one overfunctions (making decisions, remembering everything, managing household and parenting), the more the other underfunctions (waiting to be told, checking out, not initiating). This isn't about laziness or control, it's a reciprocal dance where you're creating each other's behavior. Christa breaks down how certain Enneagram types are more prone to overfunctioning (2s, 1s, 3s, 6s) or underfunctioning (9s, 5s, 7s, 4s), though any type can fall into either role. The way out? Overfunctioners must stop doing so much and create space. Underfunctioners must start doing without being asked. Both must recognize they're creating the pattern together. We talk about all of that right here! This episode is part of the ongoing family systems series also running on Instagram. For a deeper dive, tune in to Apple or join our E+M Collective here! You'll get insider info, be part of an encouraging community, and get video trainings and access at https://www.enneagramandmarriage.com/membership. Get on our Advent adventure together too where we'll discuss hope, love, and joy starting December 1st at www.EnneagramandMarriage.com. Find more about your type, the pod, freebies, and SO much more at our website right here! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.EnneagramandMarriage.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Leave Christa a podcast question anonymously by sending an MP4 recording to enneagramandmarriage@gmail.com. Love what you're learning on E + M? Make sure you leave us a podcast review so others can find us, too⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ here!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Learn more about your ad choices. Visit podcastchoices.com/adchoices

As the days get shorter and the holidays approach, many of us feel that familiar darkness creeping in, doubt about our gifts, questions about our worth, uncertainty about whether we're enough. Pastor Ed Newton, Lead Pastor of the 27,000 member Community Bible Church in San Antonio and author of Why Not You?: Believing What God Believes About You, sits down with Christa for a conversation about finding faith, truth, and doing the deep personal work required to believe you're worthy, even in your weakest moments. Ed shares his own journey of therapy and spiritual work, unpacking how he learned he was loved despite his weaknesses (not because of his strengths). Drawing from Moses' story, Eminem's famous rap battle where he humbled himself by exposing his own flaws first, and his own experience with imposter syndrome and almost total darkness, Ed explores how we prove, please, and pacify others when we don't believe we're enough. Whether you're a person of faith or just someone searching for truth about your own worthiness, this conversation meets you where you are. Ed and Christa discuss how this shows up in marriage (one spouse overperforming to earn love, the other hiding their true self), how to break these exhausting patterns even for men who often want to display competency or machismo, and why ordinary people are exactly who get chosen for extraordinary things. As we head into the holidays, a season that can bring both light and strain, this episode offers the spiritual and emotional replenishment we all need to shore ourselves up for what's coming. Watch on YouTube! Follow Ed here at his church: https://www.communitybible.com/ Get the new book here: https://a.co/d/5RJTLGm Find the personality test here: www.5voices.com Find more about your type, the pod, freebies, and SO much more at our website right here! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.EnneagramandMarriage.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Leave Christa a podcast question anonymously by sending an MP4 recording to enneagramandmarriage@gmail.com. Love what you're learning on E + M? Make sure you leave us a podcast review so others can find us, too⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ here!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Learn more about your ad choices. Visit podcastchoices.com/adchoices

In this episode of The Dept. Omar breaks down the five content ideas that every entrepreneur, creator, and personal brand needs to be using in today's “anti-AI revolution.” While everyone is obsessing over AI-generated posts, Omar explains why the real opportunity is in content that only you can create your stories, your behind-the-scenes process, your voice, your perspective. He walks through the 5 C's: Classified Content, Candid Content, Conversion Content, Captured Content, and Cutless Content, and shows how each one builds authenticity, connection, and demand. If you've been stuck, overthinking, or inconsistent online, this episode gives you a clear roadmap to show up in a way that is unique, human, and impossible for AI to replicate. This conversation will give you your creative spark back.

Ever feel like the more you try to connect with your spouse, the more they pull away? Or maybe you're the one who needs space while your partner wants to talk everything through? This is the pursuer-distancer dance, and it's one of the most common patterns in marriage. In this episode, we'll explore how your Enneagram type influences which role you naturally fall into. Heart types (2, 3, 4) often become pursuers, seeking connection and reassurance. Head types (5, 6, 7) frequently take the distancer role, needing space to process. Body types (8, 9, 1) can go either way depending on their specific type and stress level. But here's the key: when you understand YOUR type's fear and your PARTNER's type's fear, you can break this exhausting cycle. We'll give you one simple practice to try this week that interrupts the pattern—and it starts with doing the opposite of what feels natural. Whether you're a Type 2 who pursues when anxious or a Type 5 who distances when overwhelmed, you'll learn how to create connection without the chase. Find more about your type, the pod, freebies, and SO much more at our website right here! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.EnneagramandMarriage.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Leave Christa a podcast question anonymously by sending an MP4 recording to enneagramandmarriage@gmail.com. Love what you're learning on E + M? Make sure you leave us a podcast review so others can find us, too⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ here!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Learn more about your ad choices. Visit podcastchoices.com/adchoices

How do busy couples maintain marriage goals without becoming rigid? Christa sits down with Colton Simmons, 1w9, creator of the popular You've Got a Type YouTube channel and podcast, to explore staying flexible without losing standards. As a Type 1w9 married to a Type 3w4, Colton shares practical insights about his own 1-3 pairing dynamics, navigating the tension between "doing it right" and "getting it done efficiently," managing extreme productivity without burnout, and thriving as a high-achiever couple who are also navigating parenthood. They discuss how both partners can be driven without perfectionism killing connection, and Colton also shares about his creative but also uniquely-paced process for thorough Enneagram content (including typing Lord of the Rings characters) and his current series on each type in relationships. The conversation explores teaching without becoming rigid and also learning how many type 1s inner critics really work from the inside out as Colton so graciously and vulnerably shares. Whether you're a busy couple trying to balance goals and flexibility in a high-achiever pairing, wants to find your own balanced rhythm for creating content or teaching or leading others, (or just love deep Enneagram work), this episode offers you an interesting dive! Find Colton's website here: https://www.youvegotatype.com/ Find Colton's YouTube here: https://www.youvegotatype.com/ Find more about your type, the pod, freebies, and SO much more at our website right here! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.EnneagramandMarriage.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Leave Christa a podcast question anonymously by sending an MP4 recording to enneagramandmarriage@gmail.com. Love what you're learning on E + M? Make sure you leave us a podcast review so others can find us, too⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ here!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Learn more about your ad choices. Visit podcastchoices.com/adchoices

Communication in marriage breaks down when one partner can't open up - and often, it's the men who struggle most with vulnerability. In this practical, tool-filled conversation, Christa sits down with couples therapist Shane Birkel, a Type 7 and certified Relational Life Therapist who worked closely with Terry Real as his mentor. Shane is the host of Couples Therapy for Parents podcast and has been featured in Men's Health, Cosmopolitan, USA Today, and The New York Times. In this 7-7 pairing conversation, they do a deep dive into how men can actually open up in marriage and what their partners can do to help. Shane breaks down the speaker-listener technique - a research-backed communication tool that creates safety for hard conversations and helps men access and articulate their emotions. Learn why men shut down emotionally, how to explore patterns you may not even be aware of, and practical steps to help your husband (or yourself) begin to have more control of emotions and feel excited about the relationship again with the speaker-listener technique. Whether you're a man who knows you need to open up more or a partner exhausted from trying to connect, this episode delivers actionable marriage tips you can use tonight. Shane's RLT training and practical wisdom make this a must-listen for anyone who wants better communication in their marriage. Watch on YouTube! Find and follow Shane on his website here: https://www.couplestherapistcouch.com/ Listen to the Couples Therapist Couch pod w/Shane right here: https://podcasts.apple.com/mu/podcast/the-couples-therapist-couch/id1281853816 Follow Shane on Instagram here: https://www.instagram.com/shanebirkel/?hl=en Follow Shane on TikTok here: https://www.tiktok.com/@shanebirkel?lang=en Find more about your type, the pod, freebies, and SO much more at our website right here! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.EnneagramandMarriage.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Leave Christa a podcast question anonymously by sending an MP4 recording to enneagramandmarriage@gmail.com. Love what you're learning on E + M? Make sure you leave us a podcast review so others can find us, too⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ here!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Learn more about your ad choices. Visit podcastchoices.com/adchoices

What was wounded in relationship needs to heal in relationship. In this powerful conversation, Christa sits down with licensed psychotherapist and attachment expert Jessica Baum, author of the new book "Safe: An Attachment-Informed Guide to Building Secure Relationships," to explore why anxious attachment can't be healed in isolationm and what to do instead. Jessica reveals how implicit memories from childhood live in our bodies and change our felt sense in the world. Maybe a parent, teacher, or friend made you feel a certain way, and your body created protective spaces to keep you safe. Now, when your partner echoes that old wound, your nervous system reacts before your mind can catch up. Learn how healing happens through empathy, co-regulation, and anchoring relationships with safe people who can help you hold what you've been carrying alone. Discover what co-regulation actually looks like, why the earlier the wound the more relational support you need, and how to create secure attachment in your marriage even if you didn't have it growing up. Jessica's book includes exercises that help you regulate as you read, making it a healing companion for anyone ready to move from anxious patterns to secure connection. You can't do this work alone, and you don't have to. Get the book here! https://www.amazon.com/Safe-Attachment-Informed-Building-Secure-Relationships/dp/0593850815 Get the somatic meditation and other gifts along with your purchase! https://jessicabaumlmhc.com/interview More show links: ⁠Use this brief form to tell us more of what you'd like to hear and see on the pod in our E + M Pod survey!⁠ https://docs.google.com/forms/d/e/1FAIpQLSc3QManM8zj6ODWSOAM3BdDLoLh-A4AzUO3zXu5xGq6bjUgsg/viewform?usp=header Find more about your type, the pod, freebies, and SO much more at our website right here! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.EnneagramandMarriage.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Leave Christa a podcast question anonymously by sending an MP4 recording to enneagramandmarriage@gmail.com. Love what you're learning on E + M? Make sure you leave us a podcast review so others can find us, too⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ here!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Learn more about your ad choices. Visit podcastchoices.com/adchoices

You don't just marry your spouse, you marry into their family. And if you've ever felt trapped in a toxic cycle with your mother-in-law or other family members, doomed to feel like either a victim or a villain no matter what you do, this episode is for you. Join Christa as she sits down with Type 3 clinical psychologist and couples therapist Dr. Tracy Dalgleish, author of the brand new book already heralded a best seller even before official launch tomorrow, "You, Your Husband, and His Mother: Create a Healthy Relationship with Your Mother-in-Law – and Your Spouse – in Five Simple Steps." Dr. Tracy introduces the most comprehensive method to date, her tried-and-true VAULT method to help couples break unhealthy patterns, set boundaries, and resolve conflicts with their mothers-in-law for a stronger marriage and happier life. Learn how to identify what type of MIL you have, develop mutual respect for boundaries, and most importantly, feel like you're on the same team with your partner and the larger family. Women, if your mother-in-law is overbearing, critical, or emotionally distant, this conversation will help you reclaim your power, strengthen your relationship, and solve your in-law problems once and for all. While Dr. Tracy's book focuses on women and their mothers-in-law, these principles apply to all in-law relationships. Men - listen to understand your spouse's experience AND to apply these boundary-setting strategies to your own in-law dynamics as well as you too find peace in the home and with those you love so dearly. Watch on YouTube! Get Dr. Tracy's brand new book just for you here! https://a.co/d/9K7h1jB Follow Dr. Tracy's practical tips (and she and her type 9 hubby model it for us) here: https://www.instagram.com/drtracyd/?hl=en Get on Dr. Tracy's mailing list on her website here! https://drtracyd.com/ More show links: Use this brief form to tell us more of what you'd like to hear and see on the pod in our E + M Pod survey! https://docs.google.com/forms/d/e/1FAIpQLSc3QManM8zj6ODWSOAM3BdDLoLh-A4AzUO3zXu5xGq6bjUgsg/viewform?usp=header Find more about your type, the pod, freebies, and SO much more at our website right here! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.EnneagramandMarriage.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Leave Christa a podcast question anonymously by sending an MP4 recording to enneagramandmarriage@gmail.com. Love what you're learning on E + M? Make sure you leave us a podcast review so others can find us, too⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ here!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Learn more about your ad choices. Visit podcastchoices.com/adchoices

Get ready for a 1980s blast from the past twist on The Enneagram and Marriage Podcast this spooky season! In this family-friendly special episode, Christa welcomes two very special guests making their podcast debut: her nephew Lucas Wilson and son Jack Hardin, representing Gen Alpha, along with Gen Z E+M Certified Coaches Melody Hardin, 9 and Gen X Abigail Perry, 3. Together, they dive into typing beloved Stranger Things characters, predictors for the next season, and fave characters including Lucas Sinclair, Dustin Henderson, Joyce Byers, Jim Hopper, and more, just in time for the final season. This fun, intergenerational conversation explores how personality shapes heroism, friendship, courageous parenting, and love in the Upside Down,. Whether you're a die-hard Stranger Things fan eagerly awaiting the final season or just love a good fun-hearted family convo, this E+M Spooky Season Special brings the laughs, the insights, and maybe even a few jump scares. Perfect for a lighthearted listen! Watch on YouTube! More show links: Our Boo Sale: Use code BOO30 here for 30% off pairing guides, the 52-week planner, and more ⁠here!⁠ www.EnneagramandMarriage.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Find more about your type, the pod, freebies, and SO much more at our website right here! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.EnneagramandMarriage.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Leave Christa a podcast question anonymously by sending an MP4 recording to enneagramandmarriage@gmail.com. Love what you're learning on E + M? Make sure you leave us a podcast review so others can find us, too⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ here!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Learn more about your ad choices. Visit podcastchoices.com/adchoices

Jim Hodges is an old friend from way back. I'm talking so far back that MP3 and MP4 weren't the dominant digital file type in those olden days when dinosaurs roamed the Earth. Jim Hodges is a retired Navy vet who crashed into the audiobook and recording market in a huge way. You gotta listen if you want to find out how, but I'll say that he dominated an entire niche market in the book recording industry. Not only that, but Jim has found ways to create multiple streams of income from his one thing.   Find Jim at https://jimhodgesaudiobooks.com/    Things mentioned in the show: Dan Miller https://amzn.to/3JbFgF7  Shark Tank https://amzn.to/4oCay7p    --- Click here to change your life- http://eepurl.com/gy5T3T   Hit me up for a one-on-one brainstorming session- https://militaryimagesproject.com/products/brainstorming-session-1-hour    Check out my Linktree for different ways to rock your world! https://linktr.ee/ruggeddad    Check out the sweet Hyper X mic I'm using. https://amzn.to/41AF4px    Check out my best-selling books: Rapid Skill Development 101- https://amzn.to/3J0oDJ0 Streams of Income with Ryan Reger- https://amzn.to/3SDhDHg Strangest Secret Challenge- https://amzn.to/3xiJmVO This page contains affiliate links. This means that if you click a link and buy one of the products on this page, I may receive a commission (at no extra cost to you!) This doesn't affect our opinions or our reviews. Everything we do is to benefit you as the reader, so all of our reviews are as honest and unbiased as possible. #passiveincome #sidehustle #cryptocurrency #richlife

Join Christa and author Erica Liganza Gwynn (3-8 pairing) for an honest conversation about the lies we believe and how they affect us and our marriages. Erica, author of "That's Just Not True: How to Replace the Lies You Didn't Know You Believed with God's Unchanging Truth" (brand new release!) and host of the Thrive Podcast, shares practical wisdom for those of us hustling and juggling multiple roles without losing ourselves in the process. This episode tackles the most common lies we can believe about themselves and how these lies show up in work, parenting, life, and of course, marriage, plus we learn about Erica's best hacks for showing up when your heart is heavy but life still demands your presence. Pay close attention to how, as a pragmatic Type 3, she has learned to not overly expect from herself or others in the middle marriage season, this insight alone is worth the listen, but there's so much more! Learn how to detect God's truth in the middle of chaos, navigate rest and ambition without becoming a "human doing," and discover practical tools for replacing lies with truth. Perfect for anyone who needs encouragement to keep going when emotions are hard and the demands are high. Listen here! Watch on YouTube! Erica's new book, "That's Just Not True: How to Replace the Lies You Didn't Know You Believed with God's Unchanging Truth" is right here! https://a.co/d/6Gujfnz Erica's Instagram is here! https://www.instagram.com/ericaligenza/?hl=en Erica's Thrive podcast is here! https://podcasts.apple.com/us/podcast/thrive-podcast/id1480400869 More show links: Our Boo Sale: Use code BOO30 here for 30% off pairing guides, the 52-week planner, and more here! www.EnneagramandMarriage.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Find more about your type, the pod, freebies, and SO much more at our website right here! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.EnneagramandMarriage.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Leave Christa a podcast question anonymously by sending an MP4 recording to enneagramandmarriage@gmail.com. Love what you're learning on E + M? Make sure you leave us a podcast review so others can find us, too⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ here!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Learn more about your ad choices. Visit podcastchoices.com/adchoices

In this October special, Christa sits down with Type 4 author Sarah Skilton (pen name Hadley Hartwell) to explore the intersection of the Enneagram and motives, namely using the Enneagram to solve a mystery. Sarah has been studying the Enneagram since 1998 and brings that depth and careful study to her debut novel "One Is the Deadliest Number," which kicks off a nine-book series - one for each type. They discuss what it's like for a Four to write from a Type One perspective, how Sarah's 4-6 marriage informs her understanding of different personality dynamics, and why Miss Marple's knowledge of human nature is essentially Enneagram wisdom in action. Most importantly, they explore what happens when people don't do their inner work - and how recognizing the warning signs in ourselves and our loved ones can prevent our worst from coming out. Whether you're a mystery lover, an Enneagram enthusiast, or simply curious about human nature, this episode offers fresh insights into why understanding personality types matters for relationships and life. GIVEAWAY: Sarah is giving away 9 copies of her book "One Is the Loneliest Number" - one for each Enneagram type! The first person to email from each type wins. Plus, the very first person to write in will be our grand prize winner and receive the book, a Supper Sleuths mystery dinner game, AND a couples Enneagram pairing guide. ❤️❤️❤️ To Enter the Contest: Email melody@enneagramandmarriage.com (or reply if you're on our newsletter) with your Enneagram type and your favorite mystery book, movie, or show! Link to Sarah's book "One Is the Deadliest Number: A Personality Types Mystery" - https://a.co/d/2uX8oFV CONTEST: SHARE YOUR TYPE AND FAVORITE MYSTERY SHOW OR MOVIE HERE! https://www.enneagramandmarriage.com/contact-us Link to Sarah's website here: https://www.purrsandpersonalitytypes.com/ Another way to enter contest: melody@enneagramandmarriage.com Supper Sleuths mystery dinner games: suppersleuths.com Use code HALLOWEEN30 for 30% off any game this week through Oct 29 More show links: The EnneaSummit on MidLife and Beyond is here! Sign up free ⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠ or for ⁠⁠⁠⁠⁠the upgraded plan here⁠⁠⁠⁠⁠: https://www.tylerzach.com/midlife/enneasummit?ref=https%3A%2F%2Fwww.tylerzach.com%2Fa%2F2148178305%2FLS2nNmzL Find more about your type, the pod, freebies, and SO much more at our website right here! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.EnneagramandMarriage.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Leave Christa a podcast question anonymously by sending an MP4 recording to enneagramandmarriage@gmail.com. Love what you're learning on E + M? Make sure you leave us a podcast review so others can find us, too⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ here!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Learn more about your ad choices. Visit podcastchoices.com/adchoices

In this episode of The Dept. Omar sits down with Neel Dhingra and ART.MP4 to break down the art of framing. How you present yourself, your content, and your offers. Together, they dive deep into how perception shapes opportunity and why great framing can make an average product look exceptional. They talk about storytelling, positioning, and the subtle psychology that drives trust, status, and sales. If you want to stand out in your industry and package your ideas in a way that commands attention and premium value, this conversation will shift how you think about content and communication.