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Join Jordan, Commish, Pitt Girl, Big Sky Brigit and Beth, along with our VP of Podcast Production, Arthur. We talk Beth's adventures at the Morgantown Super Regional, the College World Series, Troy, UNC, Ole Miss, Bulldog vs Bulldog bashing homeruns, EA CFB 27 Trailer, THE MACCOON IS IN THE GAME, MASCOT MODE IS BACK, Bowl Schedule is set and it feels weird due to the movement of Christmas and New Years, ACC to Brazil is totally cancelled, NC State and UVA play back in Charlottesville, St. Francis (PA) rebrands as the Red Wolves and we try to figure out how to get the Frankie the Friar costume, Swiss team's lovely training set up complete with about 25 snakes, NO UNDER, ONLY DOGS, Sean Stellato updates and oh so much, much more!Join our Patreon for just $3 or $5 a month. https://www.patreon.com/cw/SickosCommitteeBuy some of our merch from https://thesickoscommittee-shop.fourthwall.com/Check out our Linktree for all our discount codes https://linktr.ee/sickoscommitteeSubscribe to our blog at https://sickos-newsletter.beehiiv.com/Subscribe to our YouTube at https://www.youtube.com/@sickoscommitteeSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

We dive into all the latest headlines, news stories and tea we have for you from Andy's award in Newport Beach, what OC Housewives supported, Kyle Cooke's new mystery lady, Brittany's Boyfriend goes rogue in the comments, did Amanda spend New Years with West and more news and then get into the latest Rhode Island episode that sets the stage for next week's reunion!Sleep cooler this summer with Boll & Branch and get 20% off sitewide for a limited time during their Annual Summer event. www.bollandbranch.co,/pumpers and use code Pumpers for 20% off. Exclusions apply. For bonus content, shows, giveaways and VPR trivia hangouts, please join us at www.patreon.com/vanderpumprulespartyThis podcast uses the following third-party services for analysis: Magellan AI - https://docsend.com/view/5vdvbdx7cr4tikmyClaritas - https://claritas.com/privacy-legalPodscribe - https://podscribe.com/privacy

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,

Physical media fans from the 1980s will have a lot to rejoice upon this week (if you still carry a fondness for certain films of your youth) but Erik Childress and Peter Sobczynski have plenty from various decades to add to your library this week. They include Bob Fosse's take on a free speech icon and the recent Academy Award winner for Best International Feature. Robert Wise's legendary haunted house film and a collection of classic cartoons. There is early work from Brian DePalma plus Art Carney as a private eye and Tony Randall in six roles. Plus, Peter finally caught up with Harry Hole. But for the nostalgia fans there is also the complete set of Sylvester Stallone's troubled war hero and Kevin Costner as the famed robber of the rich. John Lithgow adopts Bigfoot, Dan Aykroyd invades John Candy's vacation and Ron Howard delivers one of the quintessential comedies about family and parenting. Horror fans can take another New Years train ride with Jamie Lee Curtis or finally watch the “real” scenes of death your parents or video store may not have let you or lent you. Finally, a look at Joe Dante's Gremlins follow-up that 40+ years later still delights and still seeks a bigger audience.1:10 - Criterion (Lenny (4K), Sentimental Value (4K))13:19 - ClassicFlix (Fleischer Cartoons: Greatest Hits, Volume 1)15:20 - Shout Factory (The Haunting (1963) (4K))23:07 - Warner Archive (The 7 Faces of Dr. Lao, The Late Show)38:39 - Radiance (Hi, Mom! (4K))47:40 - Universal (Parenthood (4K))56:46 - Arrow (Robin Hood: Prince of Thieves (4K))1:07:32 - Lionsgate (Rambo (Complete Collection) 4K)1:18:35 - Kino (Brit Noir: Collection I, Terror Train (4K), The Great Outdoors (4K), Harry and the Hendersons (4K), The Snowman (4K))2:16:38 - Vinegar Syndrome (Faces of Death 4K, Explorers 4K)2:42:25 - New Theatrical Titles On Blu-ray (Nirvanna the Band the Show the Movie, If I Had Legs I'd Kick You, Heel, Anything That Moves)2:44:54 - New Blu-ray AnnouncementsCLICK ON THE FILMS TO RENT OR PURCHASE AND HELP OUT THE MOVIE MADNESS PODCAST OR BUY FROM MOVIEZYNGBe sure to check outErik's Weekly Box Office Column – At Rotten TomatoesCritics' Classics Series – At Elk Grove Cinema in Elk Grove Village, ILChicago Screening Schedule - All the films coming to theaters and streamingPhysical Media Schedule - Click & Buy upcoming titles for your library.(Direct purchases help the Movie Madness podcast with a few pennies.)Erik's Linktree - Where you can follow Erik and his work anywhere and everywhere.The Movie Madness Podcast has been recognized by Million Podcasts as one of the Top 100 Best Movie Review Podcasts as well as in the Top 60 Film Festival Podcasts and Top 100 Cinephile Podcasts. MillionPodcasts is an intelligently curated, all-in-one podcast database for discovering and contacting podcast hosts and producers in your niche perfect for PR pitches and collaborations.USE COUPON “MOVIEMADNESS” TO GET 10% OFF ALL DUBBY PRODUCTSSIGN UP FOR AUDIBLE This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit erikthemovieman.substack.com

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Tickets to the New Year’s Test between the Proteas and England were essentially sold out on the same day that they were announced and opened. They were available for purchase on Cricket South Africa’s website and new mobile app. Many local fans are angry at having missed out and there is a feeling among some that the system is unfair. Africa Melane speaks to Nqobile Ndlovu, sports business researcher and director of Cash N Sport. Good Morning Cape Town with Lester Kiewit is a podcast of the CapeTalk breakfast show. This programme is your authentic Cape Town wake-up call. Good Morning Cape Town with Lester Kiewit is informative, enlightening and accessible. The team’s ability to spot & share relevant and unusual stories make the programme inclusive and thought-provoking. Don’t miss the popular World View feature at 7:45am daily. Listen out for #LesterInYourLounge which is an outside broadcast – from the home of a listener in a different part of Cape Town - on the first Wednesday of every month. This show introduces you to interesting Capetonians as well as their favourite communities, habits, local personalities and neighbourhood news. Thank you for listening to a podcast from Good Morning Cape Town with Lester Kiewit. Listen live on Primedia+ weekdays between 06:00 and 09:00 (SA Time) to Good Morning CapeTalk with Lester Kiewit broadcast on CapeTalk https://buff.ly/NnFM3Nk For more from the show go to https://buff.ly/xGkqLbT or find all the catch-up podcasts here https://buff.ly/f9Eeb7i Subscribe to the CapeTalk Daily and Weekly Newsletters https://buff.ly/sbvVZD5 Follow us on social media CapeTalk on Facebook: https://www.facebook.com/CapeTalk CapeTalk on TikTok: https://www.tiktok.com/@capetalk CapeTalk on Instagram: https://www.instagram.com/ CapeTalk on X: https://x.com/CapeTalk CapeTalk on YouTube: https://www.youtube.com/@CapeTalkSee omnystudio.com/listener for privacy information.

Solve crimes with the great detective in "Sherlock Holmes Short Stories." Featuring classic tales by Arthur Conan Doyle, this podcast brings you the brilliant deductions and thrilling adventures of Sherlock Holmes and Dr. Watson. Whether you're a longtime fan or new to the world of Holmes, these timeless mysteries will keep you captivated.

Found it! We back!

This show has been flagged as Explicit by the host. Sauced https://www.urbandictionary.com/define.php?term=sauced Chevrolet Vega https://en.wikipedia.org/wiki/Chevrolet_Vega Chevrolet small-block engine (first- and second-generation) https://en.wikipedia.org/wiki/Chevrolet_small-block_engine_(first-_and_second-generation) https://www.chevrolet.com/performance-parts/crate-engines/small-block-engines/350-engine Straight-six engine https://en.wikipedia.org/wiki/Straight-six_engine Half marathon https://en.wikipedia.org/wiki/Half_marathon Mammoth March https://www.mammothmarch.com/ What Is Sleep Apnea? https://www.nhlbi.nih.gov/health/sleep-apnea https://en.wikipedia.org/wiki/Apnea Spaceballs https://en.wikipedia.org/wiki/Spaceballs https://www.imdb.com/title/tt0094012/ Ale 8 One Special Edition Cherry Zero Sugar https://ale8one.com/varieties/ https://www.amazon.com/Ale-One-Special-Bottles-Kentucky/dp/B09JBBDKM1 https://www.kroger.com/p/ale-8-one-zero-sugar-cherry-soda-bottles/0007227546202 Alcoholism https://en.wikipedia.org/wiki/Alcoholism https://www.cdc.gov/nchs/fastats/alcohol.htm Jitsi https://jitsi.org/ https://en.wikipedia.org/wiki/Jitsi Surface Pro 6 https://support.microsoft.com/en-us/surface/surface-pro-6-specs-and-features-ade5cfc2-e99a-6fd1-abbe-c0e8a8a3942d Xfce Desktop Environment https://www.xfce.org/ https://en.wikipedia.org/wiki/Xfce Trinity Desktop Environment https://www.trinitydesktop.org/ https://en.wikipedia.org/wiki/Trinity_Desktop_Environment Cheese https://wiki.gnome.org/Apps/Cheese Altered https://www.imdb.com/title/tt32123395/ Final fireworks sales take off with a bang as countdown begins. https://www.dutchnews.nl/2025/12/final-fireworks-sales-take-off-with-a-bang-as-countdown-begins/ https://www.theguardian.com/world/2026/jan/09/dutch-netherlands-fireworks-ban-new-years-eve Fireworks policy in the Netherlands https://en.wikipedia.org/wiki/Fireworks_policy_in_the_Netherlands Quarter of idiom https://www.merriam-webster.com/dictionary/%28a%29%20quarter%20of LinuxLugCast https://linuxlugcast.com/ Needs must idiom https://www.phrases.org.uk/meanings/needs-must.html Tech and Coffee. https://techandcoffee.info/ January 6 United States Capitol attack https://en.wikipedia.org/wiki/January_6_United_States_Capitol_attack OggCamp 2026 https://www.oggcamp.org/ List of benchmarking methods and software tools https://en.wikipedia.org/wiki/List_of_benchmarking_methods_and_software_tools Watchhouse https://watchhouseband.com/ Proper feline supervision (Just because) https://blog.catbandit.com/why-does-my-cat-always-watch-me-exploring-the-reasons-behind-feline-observation/ https://www.cats.org.uk/cats-blog/why-does-my-cat-stare-at-me https://thepurrfectguide.com/cat-supervised-introduction-guide/ https://catvets.com/clinical-resources/practice-guidelines/ WYSIWYG https://pl.wikipedia.org/wiki/WYSIWYG Pandoc a universal document converter https://pandoc.org/ Rendering on the Web https://web.dev/articles/rendering-on-the-web F-Droid https://en.wikipedia.org/wiki/F-Droid https://f-droid.org/en/ Get UTC time in seconds https://stackoverflow.com/questions/24547655/get-utc-time-in-seconds Content delivery network https://en.wikipedia.org/wiki/Content_delivery_network Audio feedback https://en.wikipedia.org/wiki/Audio_feedback Loopback https://en.wikipedia.org/wiki/Loopback List of conspiracy theories https://en.wikipedia.org/wiki/List_of_conspiracy_theories Jason Scott https://en.wikipedia.org/wiki/Jason_Scott Bug vs Feature https://devrev.ai/blog/bug-vs-feature-request-a-distinction-without-a-difference https://blog.codinghorror.com/thats-not-a-bug-its-a-feature-request/ chronic dehydration https://en.wikipedia.org/wiki/Dehydration https://www.nhs.uk/conditions/dehydration/ https://medlineplus.gov/dehydration.html https://www.healthline.com/health/chronic-dehydration Atlantic Highly Migratory Species Fishery Compliance Guides https://www.fisheries.noaa.gov/atlantic-highly-migratory-species/atlantic-highly-migratory-species-fishery-compliance-guides https://www.fisheries.noaa.gov/highly-migratory-species https://www.ecfr.gov/current/title-50/chapter-VI/part-635 Federal Bridge Gross Weight Formula https://en.wikipedia.org/wiki/Federal_Bridge_Gross_Weight_Formula https://ops.fhwa.dot.gov/FREIGHT/publications/brdg_frm_wghts/index.htm Convenience store https://en.wikipedia.org/wiki/Convenience_store Listing Linux Users and Groups: A Comprehensive Guide https://linuxvox.com/blog/list-linux-users-and-groups/ Plugable 250x Digital USB Microscope with Observation Stand https://plugable.com/products/usb2-micro-250x What's the difference between Medicare and Medicaid? https://www.hhs.gov/answers/medicare-and-medicaid/what-is-the-difference-between-medicare-medicaid/index.html https://www.medicare.gov/basics/costs/help/medicaid Provide feedback on this episode.

On this video, we talk about how Sayenne got stranded on an island, our Christmas holidays and also how we spent New Years.

A dollar short and a day late, but Richie and I are back with some outside the US wrestling. Tackle a trip down memory lane and see what WWE thinks of their foreign audience. Knees may not survive the night but we did. Enjoy the show.

Welcome to the New Year - Witamy w Nowym Roku How was your New Years Party - Jak minęła impreza noworoczna Everything was good - Wszystko było dobrze How was you New Years party? - Jak ci minęło przyjęcie noworoczne? I was at home with my son because you had a party - Byłem w domu z moim synem, ponieważ miałeś imprezę New Years Resolutions - Postanowienia noworoczne What are your New Years Resolutions? - Jakie są twoje postanowienia noworoczne? for me I always have a book that I write a list of goals that I want to do for the year - dla mnie zawsze mam książkę, w której piszę listę celów, które chcę zrobić na ten rok What is your goal No.1? - Jaki jest twój cel nr 1? Read 50 Books - Przeczytaj 50 książek No.2 to do 26 online courses - Nr 2 na 26 kursów online To do something like Polish online? - zrobić coś takiego jak polski online? No something interesting - Nic ciekawego Something that gives me energy and not take it - Coś, co daje mi energię i jej nie biorę No. 3 I don't know. I do not have my list with me - Nr 3 nie wiem. Nie mam przy sobie mojej listy Go to another country that I have never been to - Idź do innego kraju, w którym nigdy nie byłem Cook 5 new dishes - Gotuj 5 nowych potraw and you Kamila, what is your New Years Resolutions? - a wy Kamila, jakie są wasze postanowienia noworoczne? My plan for the new year is less work / more rest - Mój plan na nowy rok to mniej pracy / więcej odpoczynku To do more sport especially Yoga - Uprawiać więcej sportu, zwłaszcza jogę I plan to do a Yoga course for being a Yoga instructor - Planuję zrobić kurs jogi jako instruktor jogi More walking - Więcej chodzenia More time in Nature - Więcej czasu w naturze The most important plan - Najważniejszy plan What are our students plans for the new year? - Jakie są plany naszych studentów na nowy rok? Maybe less TV - Może mniej telewizji Maybe less work - Może mniej pracy Maybe to relax more - Może bardziej zrelaksować się Maybe more sport - Może więcej sportu Maybe less fast food - Może mniej fast foodów Earn more money - Zarób więcej pieniędzy Don't smoke cigarettes - Nie pal papierosów or don't drink alcohol - lub nie pij alkoholu or don't drink coffee - lub nie pij kawy or don't take drugs - lub nie bierz narkotyków So write what are your plans for the new year - Napisz więc, jakie masz plany na nowy rok  

New_Years_Eve_Off_the_Coast_of_Scilly_Isles

Can you de-center men and still want love? That's the question... and honestly, it's the reason this podcast exists.In this episode, we're getting into what de-centering men actually means (hint: it has nothing to do with being bitter, giving up on love, or actually hating men), why so many of us have been quietly organizing our lives around men who don't even know we exist, and how the rise of conservative Gen Z men fits into all of this.I'm sharing the story of my first real heartbreak at 20, what Mr. New Years taught me about men who want a partner but not the partnership, and the mindset shift that changed everything.If you're a lover girl who's also exhausted by the idea of shrinking yourself for someone who hasn't even shown up yet, this one's for you.Follow the podcast on all platforms & subscribe to the Tough Love Club

This week we have another doordash escapade, all the guys get sloshed, as well as two taste tests. Happy New Year! Crack into 2023 with ya bois! Drink/Smoke and Riff Responsibly! New Amsterdam Wildcard- HIGHLY RECOMMEND! Red White and Merry Cocktails- HIGHLY RECOMMEND!

Well, here's a film that is near the bottom of many lists of all the Oscar winners for Best Picture. Why do people have such an affinity towards Cavalcade (1933)? It's a film that is very disappointing as the storyline about a British family and their servants go through 32 years full of major events, including war, the death of the queen, and the sinking of the Titanic.  Looking back, was it deserving of the Best Picture Oscar from all the films that were eligible from the 6th Annual Academy Awards? Many critics and fans don't thinks so. Listen and find out what film critic Jack Ferdman thinks, and which film he chooses for his Rewatch Oscar of that year.Download, listen, and share ALL Rewatching Oscar episodes.SUBSCRIBE and FOLLOW Rewatching Oscar:Website: https://rewatchingoscar.buzzsprout.comApple Podcasts/iTunesSpotifyGoogle PodcastsiHeart RadioPodchaserPodcast AddictTuneInAlexaAmazon Overcasts Podcast Addict Player FMRSS Feed: https://feeds.buzzsprout.com/1815964.rssWebsite: https://rewatchingoscar.buzzsprout.comSocial Media Links: Facebook, Twitter, LinkedIn, Instagram, BlueSkyShare your thoughts and suggestions with us through:Facebook Messenger or email us atjack@rewatchingoscar.com or jackferdman@gmail.comMusic by TurpacShow Producer: Jack FerdmanPodcast Logo Design: Jack FerdmanMovie (audio) trailer courtesy of MovieClips Classic TrailersMovie (audio) clips courtesy of YouTubeSupport us by downloading, sharing, and giving us a 5-star Rating.  It helps our podcast continue to reach many people and make it available to share more episodes with everyone.Send us Fan Mail

Catch up with Ansen, Isaac and Zoe this week to hear about why asking for help is so hard, renewed New Years resolutions, and what to do when life keeps sending new opportunities to grow.

This show has been flagged as Explicit by the host. Aldi https://www.aldi.us/ https://en.wikipedia.org/wiki/Aldi Does Aldi's Summit Diet Cola Contain Aspartame? https://www.thedailymeal.com/1465489/does-aldi-cola-contain-aspartame/ Aspartame and Other Sweeteners in Food https://en.wikipedia.org/wiki/Aspartame https://www.fda.gov/food/food-additives-petitions/aspartame-and-other-sweeteners-food https://pmc.ncbi.nlm.nih.gov/articles/PMC8227014/ Sugar: THE BITTER TRUTH https://www.youtube.com/watch?v=dBnniua6-oM How to Make Up Comebacks when Somebody Calls You Fat https://www.wikihow.com/Make-Up-Comebacks-when-Somebody-Calls-You-Fat Swimming With Men - You Calling Me Fat? https://www.youtube.com/watch?v=JbD_sk0ih0g "Weird Al" Yankovic - Fat (Official Video) https://www.youtube.com/watch?v=t2mU6USTBRE Sam's Club https://www.samsclub.com/ 3rd Rock from the Sun https://en.wikipedia.org/wiki/3rd_Rock_from_the_Sun Interstate Highway System https://en.wikipedia.org/wiki/Interstate_Highway_System History of the Interstate Highway System https://highways.dot.gov/highway-history/interstate-system/50th-anniversary/history-interstate-highway-system https://www.gbcnet.com/ushighways/history.html https://www.history.com/articles/interstate-highway-system https://www.historicushighways.com/history-of-us-highways https://vividmaps.com/evolution-interstate-highway-system/ https://www.youtube.com/watch?v=SF16uDPGi14 99% Invisible https://99percentinvisible.org/ https://en.wikipedia.org/wiki/99%25_Invisible Devhack is a Queer-focused hackerspace https://wiki.hackerspaces.org/%E2%88%95dev/hack https://devhack.net/ Beyond The Exit https://www.youtube.com/@BTE4172/videos Amtrak https://www.amtrak.com/home Palmer Raids https://en.wikipedia.org/wiki/Palmer_Raids Mumble project https://www.mumble.info/ LinuxLugCast https://linuxlugcast.com/ n scale piedmont northern boxcar https://www.worthpoint.com/worthopedia/scale-kadee-piedmont-northern-40-1840448079 N scale https://en.wikipedia.org/wiki/N_scale HO scale https://en.wikipedia.org/wiki/HO_scale Rail transport modelling scales https://en.wikipedia.org/wiki/Rail_transport_modelling_scales Navy Pier https://en.wikipedia.org/wiki/Navy_Pier https://navypier.org/ The IT Crowd https://en.wikipedia.org/wiki/The_IT_Crowd https://www.imdb.com/title/tt0487831/ A Christmas Story https://en.wikipedia.org/wiki/A_Christmas_Story Die Hard https://www.imdb.com/title/tt0095016/ https://theconversation.com/nine-reasons-why-die-hard-really-is-a-christmas-film-173801 The Fifth Element https://en.wikipedia.org/wiki/The_Fifth_Element Footloose https://en.wikipedia.org/wiki/Footloose Tom Cruise's Couch Jump https://people.com/tom-cruise-couch-jump-on-oprah-is-20-years-old-11737728 Cruise control https://en.wikipedia.org/wiki/Cruise_control Blind spot monitor https://en.wikipedia.org/wiki/Blind_spot_monitor Kenworth T680 https://www.kenworth.com/trucks/T680/ https://www.youtube.com/watch?v=Ze05NW6UJOE Knight Rider https://en.wikipedia.org/wiki/Knight_Rider_(1982_TV_series) https://en.wikipedia.org/wiki/KITT Christine (King novel) https://en.wikipedia.org/wiki/Christine_(King_novel) SWAT https://en.wikipedia.org/wiki/SWAT The Blues Brothers (film) https://en.wikipedia.org/wiki/The_Blues_Brothers_(film) https://www.imdb.com/title/tt0080455 Speed limits in the United States https://en.wikipedia.org/wiki/Speed_limits_in_the_United_States Provide feedback on this episode.

EMERGENCY EARLY POD RELEASE! Our first BIG look at the Harry Potter TV show is here, and it's way earlier AND bigger than expected! The first season of the upcoming TV show is now titled Harry Potter and the Philosopher's Stone, and Holy Dumbledore do we have thoughts. Heads up! For one week only: Celebrate the TV show coming out THIS YEAR by using code '2026' from now through April 1 to receive 26% off your first month of our Patreon! Visit Patreon.com/mugglecast and pledge now! Your support helps us cover the TV show. Before we can even analyze the trailer, we have to talk about that title (RIP "Sorcerer"), and the equally surprising release date: Christmas 2026! How many episodes will they release at the launch, and do we expect more episodes on New Years? I guess we won't be taking a break over the holidays... After discussing those developments, we go scene-by-scene through the trailer. One of our big takeaways is that this TV adaptation is being more loyal than the movies ever were! From Petunia cutting Harry's hair to Hagrid knocking three times on the entry doors to Hogwarts, no detail seems to be overlooked. We also discuss the slew of character reveals (Laura thirsts over the new Snape, Eric celebrates the confirmation of Peeves), discuss the familiar-yet-different changes to the look and feel of the Wizarding World,  and point out the little things you may have missed. For example, WTH are Ron and Harry doing running on tables!? Heads up! For one week only: Celebrate the TV show coming out THIS YEAR by using code '2026' from now through April 1 to receive 26% off your first month of our Patreon! Visit Patreon.com/mugglecast and pledge now! Your support helps us cover the TV show. Learn more about your ad choices. Visit megaphone.fm/adchoices

Why are months dated from the Exodus and why did we subsequently absorb the names of the months of the Persians? Why is New Year celebrated in Tishrei if the world was created in Nissan?

This show has been flagged as Explicit by the host. 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https://www.rottentomatoes.com/celebrity/771821133 Villians https://www.rottentomatoes.com/m/villains Becky (movie series) https://www.rottentomatoes.com/m/becky_2020 https://www.rottentomatoes.com/m/the_wrath_of_becky Kevin James https://www.rottentomatoes.com/celebrity/1148922-kevin_james Krampus https://www.rottentomatoes.com/m/krampus Bruce Campbell https://www.rottentomatoes.com/celebrity/bruce_campbell The Perfect Host https://www.rottentomatoes.com/m/the-perfect-host David Hyde Pierce https://www.rottentomatoes.com/celebrity/david_hyde_pierce John Dies At The End https://www.rottentomatoes.com/m/john_dies_at_the_end This Book Is Full of Spiders https://www.goodreads.com/book/show/12924261-this-book-is-full-of-spiders The Owners https://www.rottentomatoes.com/m/the_owners_2020 Games of Thrones https://www.rottentomatoes.com/tv/game_of_thrones Maisy Williams https://www.rottentomatoes.com/celebrity/maisie_williams Sylvester McCoy 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https://thedreamstress.com/2024/04/making-18th-century-buckram-gum-arabica-vs-tragacanth-vs-xantham/ Gnu Wolrd Order https://gnuworldorder.info/ Drawing Fluid (screen printing) https://www.melissadettloff.com/blog/2023/5/10/drawing-with-drawing-fluid-for-screen-printing-paint-pen-squeeze-bottle-four-tools-tested Screen Filler https://thediningtablestudio.uk/blog/screen-printing-with-screen-filler-and-drawing-fluid/ Photo Emullsion https://www.instructables.com/Photo-emulsion-Screen-Printing/ PHP https://www.php.net/ Proton Drive https://proton.me/drive GRUB https://www.gnu.org/software/grub/ Arch Linux https://archlinux.org/ Proxmox https://www.proxmox.com/en/ Allen Americans Hockey Team https://allenamericans.com/ Dallas Stars Hockey https://www.nhl.com/stars/ Arlington, Texas https://www.arlingtontx.gov/Home Dallas, Texas https://dallascityhall.com/Pages/default.aspx Knoxville Ice Bears https://knoxvilleicebears.com/ Skrewball Whiskey https://www.skrewballwhiskey.com/en/ Fireball https://www.fireballwhisky.com/ Dr. McGillicuddys https://drmcgillicuddy.com/ Guacamole https://www.allrecipes.com/recipe/14064/easy-guacamole/ Inkscape https://inkscape.org/ Cricut Cutting Machine https://inkscape.org/ South East Linux Fest https://southeastlinuxfest.org/ Seinfeld https://www.rottentomatoes.com/tv/seinfeld Simpsons https://www.rottentomatoes.com/tv/the_simpsons 24 (TV Show) https://www.rottentomatoes.com/tv/24 Eveangelion https://www.rottentomatoes.com/m/evangelion_111_you_are_not_alone Robotech https://www.rottentomatoes.com/tv/robotech StarGate https://www.rottentomatoes.com/m/stargate MakeMKV https://www.makemkv.com/ Handbrake https://handbrake.fr/ The IT Crowd https://www.rottentomatoes.com/tv/the_it_crowd_2006 Jimmy Carr https://www.jimmycarr.com/ IT Crowd (American version) https://www.asteroidg.com/index.php?section=articles&page=20240327_it_crowd_2007_pilot IT Crowd (German version) https://www.imdb.com/title/tt1101236/ Red Bull https://www.redbull.com/us-en 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Sheryl Glick host of Healing From Within Interviews Sue Elliott, founder and Editor-in-Chief of Law of Attraction Magazine and originator of Heartfelt Holidays', an audio program which provides the shifts necessary to find more peace, ease, and joy at the Holiday times when many people may be feeling depressed, anxious, fearful, irritated, or upset during the time of Thanksgiving to New Years. Sue is also a leading personal executive transformation coach. https://www.myangelcoach.com/ Learn more about Sheryl here: http://www.sherylglick.com/

Ben's got one (and a day off!) Max doesn't. Why some of us celebrate New Years in the middle of winter. Awaken My Love. The Orange Lantern. And Greek Mythology for dessert.  *** Submit Your Topic - Get A Free Shirt - ignorantanduninformed@gmail.com

In this episode, Dennis is joined by the director and cast of the new play Foursome, which is currently running at the Atwater Village Theatre in Los Angeles. The play is about two couples who head to a mountain cabin for a New Years getaway and let's just say...the play isn't called Foursome for nothing. The show's director Tom DeTrinis as well as the cast, which includes Matthew Scott Montgomery (who is also the show's playwright), Jimin Moon, Adrián Javier and Calvin Seabrooks join Dennis for a game of You Don't Know My Life! featuring these two Foursome-inspired questions: You're writing an article called "A Weekend Getaway I'll Never Forget" based on an experience from your life. What happens in it? and What kiss from your life felt like something out of a movie? The gang also talk about what they love about the show and playing their respective characters, the audience reactions so far and the show's unique mix of laugh-out-loud comedy and lump-in-the-throat drama. https://www.iamatheatre.com/  

Kourtney is joined by special guest, Jacqui Saldana, content creator, mom, and close friend of hers.  They chat about how they're celebrating Lunar New Year and discuss their thoughts on New Years resolutions. Kourtney pulls out a vision board from 2022 and reflects on how many of the goals she accomplished.  Jacqui talks about her journey into content creation and how the landscape of social media has changed in over a decade.  She explains how she used her online community after the loss of her son to provide a space for others to grieve and process her own feelings with the support of others online.  Jacqui explains how she handles criticism online and why she ultimately would never give up social media despite any negativity.  Jacqui gives Kourtney the rundown on camping outside in order to get a front row barricade spot at her favorite concerts and why she thinks it is all worth it. The two wrap up the episode with a fun round of Rapid Fire questions. Follow Jacqui: @jacquisaldana Follow Holding Kourt: @holdingkourt Follow Kourt: @court_with_a_K

With a very late recap on the Holidays, Brandon Sanderson and Dan Wells are back to chat about all things during Christmas and New Years. From gifts that they have been given, that they gave, and what its like having the family back home!Want to send me something to open?Dragonsteel EntertainmentATTN: AdamP.O Box 698American Fork, UT 84003Get your Wheel of Time updates here with the Bound and Woven newsletter: https://mailchi.mp/brandonsanderson/eye-of-the-world-campaignStay up to date by following my newsletter: https://brandonsanderson.us10.list-manage.com/subscribe?u=7d056bb7596a3e617f82004b2&id=fa68f14db0Interested in signed books and swag? Check here: https://www.dragonsteelbooks.com/You can also follow me on:Tiktok: https://www.tiktok.com/@authorbrandonsandersonFacebook: https://www.facebook.com/BrandSandersonTwitter: https://twitter.com/BrandSandersonInstagram: https://www.instagram.com/brandsanderson/?hl=enTwitch: https://www.twitch.tv/mistbornbrandonFrequently asked questions: https://faq.brandonsanderson.com

New year, new us! Come listen as Raggedy and Emiry share their new years resolutions. Intro music is "Shonen Showdown Opening" by Syn Strain In The Pentane and the ending music is "Chiptunes" by Liborio Conti (https://www.no-copyright-music.com/) You can support the podcast in the following ways: Merchandise Store: www.AAAShop.info Discord: www.AAADiscord.com Subscribe: www.aaapodcast.com/join Donations: www.aaapodcast.com/donate Patreon: www.patreon.com/AAAPodcast Thank you for your generosity and kindness

Comedian, actress, and musician Kerri Kenney-Silver (Reno 911! The Four Seasons! The State!) joins The Andy Richter Call-In Show this week to hear your NEW YEAR FAIL STORIES!  Want to be a part of the Andy Richter Call-In Show? Tell us your favorite dinner party story or ask Andy a question! Fill out our Google Form at BIT.LY/CALLANDYRICHTER or dial 855-266-2604. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Jackie is sticking with her New Years resolution and sets the financial record straight, does a deep dive into Ashley Tisdale's toxic mom group, and explains why you shouldn't trust people with fake plants and accent walls.Thanks for supporting my sponsors:Leesa Mattress: Get 25% off mattresses, plus an extra $50 off with promo code BIBLE at www.Leesa.comHero Bread: Use code BIBLE to get 10% off your order at www.Hero.coMerit Beauty: Get Merit's Signature Makeup Bag with your first order at www.MeritBeauty.comRevolve: Shop my edit, and take 15% off your first order with code BITCH at www.Revolve.com/BITCHRitual: For a limited time, save 40% on your first month at www.Ritual.com/BIBLESee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

January brings two things in Vergecast-land: CES, and New Years' Resolutions. We start this episode with a dive into the story of this year's biggest tech show, the Lego Smart Brick, which is either a clever way of thinking about creativity or the end of creativity as we know it. Sean Hollister explains how the Smart Brick works, and how Lego can make sure it ends the right way. Then, Platformer's Casey Newton discusses his productivity system, his adventures in Claude Code, and how you too can make yourself a little more productive this year — with or without AI. Further reading: Lego announces Smart Brick, the ‘most significant evolution' in 50 years Lego's Smart Bricks aren't just an experiment I played with the Lego Smart Brick From Platformer: The project that turned me into a Claude Code believer From Platformer: What I learned about productivity this year Subscribe to The Verge for unlimited access to theverge.com, subscriber-exclusive newsletters, and our ad-free podcast feed.We love hearing from you! Email your questions and thoughts to vergecast@theverge.com or call us at 866-VERGE11. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Andy Cohen may finally have gone too far this time as rumors, and nastiness, of his alleged looming termination surface, this time stronger than ever.  Kyle Mauricio got hot and heavy during New Years, but this newfound PDA seems to be continuing much past the ski slopes of Aspen. Last, but not least, Denise Richards' ex Aaron makes a desperate move for all sorts of reasons none of which seem to be working.  @behindvelvetrope @davidyontef BONUS & AD FREE EPISODES Available at - www.patreon.com/behindthevelvetrope  BROUGHT TO YOU BY: MOMENTOUS - livemomentous.com (Use Code VELVET For 35% Off Your First Order on Creatine, Protein, Omega-3 Or Any Momentous Products) MOOD - www.mood.com/velvet (20% Off With Code Velvet on Federally Legal THC Shipped Right To Your Door) WERE YOU RAISED BY WOLVES? - https://podcasts.apple.com/us/podcast/were-you-raised-by-wolves/id1478026758(A Fast-paced, Delightful Podcast About Etiquette & Social Norms) PROGRESSIVE - www.progressive.com (Visit Progressive.com To See If You Could Save On Car Insurance) ADVERTISING INQUIRIES - Please contact David@advertising-execs.com MERCH Available at - https://www.teepublic.com/stores/behind-the-velvet-rope?ref_id=13198 Learn more about your ad choices. Visit megaphone.fm/adchoices

With the arrival of 2026, Anney and Samantha chat about how their holidays went, and the new year.See omnystudio.com/listener for privacy information.

He was one of the bestselling Christian comedians on the touring circuit, with millions in revenue, a dedicated staff, and followers willing to fund his lifestyle with “love offerings.” But soon, two journalists - a pair of fellow Christians, no less - shed a less-than-flattering light on the self-proclaimed Bishop, and the whole empire came tumbling down. This week's episode is Mike Warnke, Fake Satanist – Part 2.Click here for this week's show notes.Click here to sign up for our Patreon and receive hundreds of hours of bonus content.Please click here to leave a review and tell us what you think of the show.Please consider supporting the companies that support us!-Go to Quince.com/creepy for free shipping on your order and 365-day returns. Now available in Canada, too.-Head to tryfum.com and use code CREEPY to claim your Double Cores and your free gift before this New Years offer closes for good.-This episode is sponsored by BetterHelp. Sign up and get 10% off at BetterHelp.com/SINISTER-Hero Bread is offering 10% off your order. Go to hero.co and use code CREEPY at checkout. -For a limited time, Nutrafol is offering our listeners $10 off your first month's subscription and free shipping when you go to Nutrafol.com and enter the promo code CREEPY.

It's a new year and we're resolving to make and not make some resolutions! This week we're talking about some steamy couples like Alix Earle and Tom Brady, we're talking about the curious case of John Travolta's youngest son, and how to make New Years resolutions.  18 min: Couples Updates  30 min: Riley Keough, John Travolta, and Scientology 36 min: Venezuela 46 min: Zohran's New York  52 min: New Year's Resolutions  1 hour 8 min: Caps Off ___________________________________ Keep up with all the latest: https://www.goodnoticings.com/ Read our many musings on Substack: https://cmbc.substack.com/?utm_source=global-search Join the Patreon for new, exclusive episodes every Friday! https://www.patreon.com/c/goodnoticings Follow us on: TikTok- @goodnoticingspod Instagram- @goodnoticingspod Theme song by: Bri Connelly  ___________________________________ Tom Brady and Alix Earle:  https://www.eonline.com/news/1426828/tom-brady-at-nhl-event-after-nye-with-alix-earle Riley Keough and John Travolta:  https://pagesix.com/2025/12/17/celebrity-news/riley-keough-is-john-travoltas-youngest-sons-biological-mother-new-lawsuit-claims/?utm_source=twitter&utm_social_handle_id=182107650&utm_medium=social&utm_social_post_id=626152596&utm_campaign=pagesix Venezuela:  https://www.newyorker.com/news/q-and-a/the-brazen-illegality-of-trumps-venezuela-operation Zohran's First Days:  https://nymag.com/intelligencer/article/what-zohran-mamdani-has-done-since-becoming-mayor.html Friction Maxing:  https://www.thecut.com/article/brooding-friction-maxxing-new-years-2026-resolution.html Decision Fatigue:  https://www.nytimes.com/2011/08/21/magazine/do-you-suffer-from-decision-fatigue.html Willpower:  https://www.nytimes.com/2025/12/28/opinion/willpower-doesnt-work-this-does.html Learn more about your ad choices. Visit podcastchoices.com/adchoices

Today, this is what's important: Traveling, January 6th, Blake's mustache, gifts, New Years plans, Bruno Mars, billionaires, pets, & more. Click here for more information about the This Is Important Cruise Feb 22nd-26th!See omnystudio.com/listener for privacy information.

We are back baby! Hope all the baby gurls and rock truckers had a good New Years! We give Alan Ginn 2 truths 1 lie! ☎️ 442-777-3331 (Advice/Confess/Anything)

The first episode of 2026 from the JBP begins with a recap of New Years for each member (15:59) as well as their resolutions and predictions (29:52). Drake & Adin Ross have been hit with a RICO lawsuit over alleged gambling scheme with Stake (40:15), Joe shares his thoughts about the recent stories involving NFL brothers Stefon Diggs & Trevon Diggs (1:01:00), and Doechii & SZA have a new single 'girl, get up.' (1:19:28). Uncle Murda and Skillz drop their 2025 Wrap Up songs (1:27:56), the room discusses lies you tell as a couple (1:48:23) which leads to a conversation about pet owners (1:58:45). Also, the JBP learns of Chevy Chase's history through a new documentary (2:17:42), Will Smith is being sued by a former employee (2:24:45), Part of the Show (2:57:45), and much more!  Become a Patron of The Joe Budden Podcast for additional bonus episodes and visual content for all things JBP! Join our Patreon here: http://www.patreon.com/joebudden 

One more TCB Classic before the dangerous duo return to start an all new season of streaming and recorded episodes This one his a 12 Days of TCB Classic starting Chuck Wolery and a Love Connection favorite. Hold on to your knee caps. They may mention their nether regions! New streaming episodes start January 6th, 2026 around 1pm ET. new recorded episodes release here on January 7th! To learn more about listener data and our privacy practices visit: https://www.audacyinc.com/privacy-policy Learn more about your ad choices. Visit https://podcastchoices.com/adchoices Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

One more TCB Classic before the dangerous duo return to start an all new season of streaming and recorded episodes This one his a 12 Days of TCB Classic starting Chuck Wolery and a Love Connection favorite. Hold on to your knee caps. They may mention their nether regions! New streaming episodes start January 6th, 2026 around 1pm ET. new recorded episodes release here on January 7th! To learn more about listener data and our privacy practices visit: https://www.audacyinc.com/privacy-policy Learn more about your ad choices. Visit https://podcastchoices.com/adchoices

(SPOILER) Your Daily Roundup covers tonight's live re-watch on the Patreon, New Years Eve programming thoughts, a new A-list celebrity couple seen in St. Barts, & a re-boot of one my favorite classic shows coming to Disney + next month.    Music written by Jimmer Podrasky (B'Jingo Songs/Machia Music/Bug Music BMI) Learn more about your ad choices. Visit megaphone.fm/adchoicesSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

(SPOILER) Your Daily Roundup covers tonight's live re-watch on the Patreon, New Years Eve programming thoughts, a new A-list celebrity couple seen in St. Barts, & a re-boot of one my favorite classic shows coming to Disney + next month.    Music written by Jimmer Podrasky (B'Jingo Songs/Machia Music/Bug Music BMI) Learn more about your ad choices. Visit megaphone.fm/adchoices

Watch The X22 Report On Video No videos found (function(w,d,s,i){w.ldAdInit=w.ldAdInit||[];w.ldAdInit.push({slot:17532056201798502,size:[0, 0],id:"ld-9437-3289"});if(!d.getElementById(i)){var j=d.createElement(s),p=d.getElementsByTagName(s)[0];j.async=true;j.src="https://cdn2.decide.dev/_js/ajs.js";j.id=i;p.parentNode.insertBefore(j,p);}})(window,document,"script","ld-ajs");pt> Click On Picture To See Larger Picture Trump is showing the world how green energy doesn’t work, plus it also shows the environmentalist really don’t care about the environment. The people are waking up to the fact that the [CB] have been robbing us of our money. Trump’s economy is taking off. The [DS] is being exposed, the people are now seeing the criminal syndicate system, it is one tyrannical money laundering system. The people have been funding our destruction. The [DS] hunted Trump and now Trump is hunting them. The difference is that the [DS] have committed the crimes and the investigations will show their criminal acts. We are in the process of fighting the 2nd American revolution. Economy  (function(w,d,s,i){w.ldAdInit=w.ldAdInit||[];w.ldAdInit.push({slot:18510697282300316,size:[0, 0],id:"ld-8599-9832"});if(!d.getElementById(i)){var j=d.createElement(s),p=d.getElementsByTagName(s)[0];j.async=true;j.src="https://cdn2.decide.dev/_js/ajs.js";j.id=i;p.parentNode.insertBefore(j,p);}})(window,document,"script","ld-ajs"); https://twitter.com/KobeissiLetter/status/2006870301041467482?s=20   improved across every US region last month to their highest levels of 2025. The West posted the largest increase, followed by the South, the nation's largest home-selling region. As a result, the Pending Home Sales Index is up to 79.2 points, the highest since February 2023. Homebuyer activity is regaining traction. https://twitter.com/elonmusk/status/2006832536257966286?s=20   need to cut fraud https://twitter.com/CynicalPublius/status/2006750062844534872?s=20  greatly eliminates fraud, waste and abuse; -or- (ii) Middle-class taxpayers decide enough is enough and they too stop following the rules. Door (i) = prosperity. Door (ii) = anarchy. https://twitter.com/elonmusk/status/2006833536335327501?s=20 https://twitter.com/QuantusInsights/status/2006036670680912007?s=20   overseas buying. This is strong, confidence-driven allocation by sophisticated investors looking 12–24 months ahead. When stocks, Treasuries and corporate bonds all see heavy inflows together, the data quietly signals: • U.S. growth looks resilient (no recession on the horizon) • American institutions remain solid • Global alternatives don't measure up A rare combination that points to a strong setup for the U.S. economy. https://twitter.com/howardlutnick/status/2006867104272961854?s=20  positions across industries and our nation. This new growth will employ millions of workers in great, high-paying jobs. The era of non-productive jobs fueled by DEI bureaucracy and corporate performative politics is over. Those who want to work and build America will be rewarded. Great positions and opportunities will be plentiful. The time is now to Make America Great Again. To the amazing success of America and the American worker in 2026!! Political/Rights   the Country, including Tim Waltz, Gavin Newscum, for who is going to lead the Democrats to their future defeat. Clooney got more publicity for politics than he did for his very few, and totally mediocre, movies. He wasn't a movie star at all, he was just an average guy who complained, constantly, about common sense in politics. MAKE AMERICA GREAT AGAIN! https://twitter.com/RichardGrenell/status/2006739373346226506?s=20  quickly. It's unverified gossip that is embraced by News Editors. I see it everyday with the Trump Kennedy Center. Fake news repeated over and over without a single reporter calling to verify the information they are repeating. DOGE https://twitter.com/EricLDaugh/status/2006843983016960428?s=20 “This is deeply morally WRONG.” “Why is it right for someone who escaped tyranny in other countries and happens to live in SF to pay ‘reparations’ for something they had nothing to do with?”  “California didn’t even have slaves!” Geopolitical More Than 1,000 Cars Burned in France, as New Years' Eve ‘Celebrations' in Europe Turn Into a ‘Fireworks War' Between Migrants and Police (VIDEOS)  Cars burning on NYE: Macron is presiding over the destruction of France. The suicidal policy of unchecked mass migration is takings its toll on the European nations. Among the multiple problems, there's the fact that the New Years ‘celebrations' have turned into an excuse for violent migrants to attack police, firefighters and commons citizens with fireworks, turning it into a war. https://twitter.com/visegrad24/status/2006763220258926726?ref_src=twsrc%5Etfw%7Ctwcamp%5Etweetembed%7Ctwterm%5E2006763220258926726%7Ctwgr%5E6f5fbf697d1dedb8ea125a1a961ff7b248f5d362%7Ctwcon%5Es1_c10&ref_url=https%3A%2F%2Fwww.thegatewaypundit.com%2F2026%2F01%2Fmore-than-1000-cars-burned-france-as-new%2F https://twitter.com/RMXnews/status/2006884531585024201?ref_src=twsrc%5Etfw%7Ctwcamp%5Etweetembed%7Ctwterm%5E2006884531585024201%7Ctwgr%5E6f5fbf697d1dedb8ea125a1a961ff7b248f5d362%7Ctwcon%5Es1_c10&ref_url=https%3A%2F%2Fwww.thegatewaypundit.com%2F2026%2F01%2Fmore-than-1000-cars-burned-france-as-new%2F Source: thegatewaypundit.com https://twitter.com/visegrad24/status/2006843568816796153?s=20  Maduro Says He’s Ready to Play ‘Let’s Make a Deal’ Venezuela’s Nicolas Maduro says that he’s willing to come to terms with President Trump if the U.S. ends its military pressure campaign in an interview with socialist academic and journalist (but I repeat myself) Ignacio Ramonet. Trump has made multiple demands that Maduro depart, going back to the beginning of the pressure campaign in November, for instance, on December 23: “We want it back,” he added. “They took our oil rights — we had a lot of oil there. As you know they threw our companies out, and we want it back.” The list includes, but is not limited to: Exxon Mobil—2007—oil extraction. Conoco Phillips—2007—oil extraction. Halliburton—2009—oil operations. Cargill—2009—rice processing. Owens Illinois—2010—glass. Clorox—2014—consumer goods.  General Motors—2017—auto manufacturing.  Kellogg's—2018)—cereals. Goodyear—2018—tires. Source: redstate.com War/Peace Anonymous U.S. Officials Say Ukraine Didn't Target Putin with Drone Attack – Russian Officials Say They Have Drone Flight Plan From Navigation Unit  The Wall Street Journal is reporting that Ukraine did not target the personal residence of Russian Federation President Vladimir Putin, “according to U.S. officials.”   However, Russia captured one of the drones intact and have said they were able to “extract a file containing a flight plan from the navigation unit” which they plan to share with the Trump administration through established channels. {LINK}   Who are we going to believe, Russian “special service” operations or anonymous “U.S. Intelligence Officials”?  U.S. media have said the attack on Putin may be a lie; however, with physical evidence from the defense operation, it is less likely Russia just made up the attack.  At this moment in the conflict, Putin doesn't need domestic propaganda.    Source: theconservativetreehouse.com [DS] Agenda https://twitter.com/KanekoaTheGreat/status/2006842440968450361?s=20 https://twitter.com/MrAndyNgo/status/2006830735626301488?s=20   up to dozens of times for safety violations. Four facilities had prepared themselves for liberal journalists by having Somali children inside. https://twitter.com/MrAndyNgo/status/2006877951376154782?s=20  extreme, with little girls usually required to wear both head and body coverings. Female genital mutation is also endemic to their cultural practices. In June 2025, Mayor @Jacob_Frey released an official video in Somali condemning the U.S. government’s efforts to restrict incoming migration from Somalia. This is the same mayor who oversaw (managed) the burning of Minneapolis during the 2020 BLM-Antifa riots. http://ngocomment.com https://twitter.com/MrAndyNgo/status/2006849302002544832?s=20 https://twitter.com/AAGDhillon/status/2006887697743302932?s=20 Report Alleges Somalia's Foreign Minister, Whose Ohio Healthcare Company Receives U.S. Tax Dollars, Also Controls LLC at SAME ADDRESS as Somali Money Transfer Firm Accused of Terror Financing  A new report alleges that Somalia's Foreign Minister Abdisalam Abdi Ali, a U.S. citizen whose Ohio-based healthcare company has raked in millions from American taxpayers, also controls an LLC operating out of the same address as a Somali money transfer firm previously accused of funneling funds to terrorist organizations. Abdisalam Abdi Ali was appointed Minister of Foreign Affairs and International Cooperation of Somalia in May 2025. Born in Somalia but building a life in the U.S., Ali established Ritechoice Healthcare Services LLC in Toledo, Ohio, over a decade ago. Shockingly, two additional healthcare companies operate out of the same office suite. https://twitter.com/libsoftiktok/status/2006872203921600958?s=20 In that role, he: Oversees Security Council meetings Sets the Council's agenda Manages resolutions and presidential statements Speaks for the A3+ bloc (African nations plus Caribbean representation) on issues like Afghanistan and Yemen But before assuming global authority in New York, Osman spent years embedded inside Ohio's public welfare system. Osman relocated to the United States in the late 1980s and built his career in Ohio's taxpayer-funded social services apparatus. From 1999 to 2012, he worked at the Franklin County Department of Job and Family Services, serving as: Case Manager Social Program Specialist Source: thegatewaypudit.com  https://twitter.com/JoeLang51440671/status/2006726416168079799?s=20   democrats by the same corrupt Somali's. Stolen elections violate the Constitutional rights of citizens. That will play a HUGE part in FORCING our election system to be completely transformed. Fraud vitiates everything and everything is connected. Source: thegatewyapundit.com President Trump's Plan https://twitter.com/ScottAdamsSays/status/2007077071684780275?s=20 https://twitter.com/elonmusk/status/2007076187760366005?s=20 President Trump Issues the First Vetoes of His Second Term  It took about 11 months, but President Donald Trump has finally issued the first vetoes of his second term. And like most things involving the president, the moves aren't without their critics — including some you might not normally expect pushback from. Trump's rapid response team highlighted the two vetoes: https://twitter.com/RapidResponse47/status/2006153283996381333?ref_src=twsrc%5Etfw%7Ctwcamp%5Etweetembed%7Ctwterm%5E2006153283996381333%7Ctwgr%5E79e6ef2350ae826bc802e9e5d82d5c97bad630de%7Ctwcon%5Es1_c10&ref_url=https%3A%2F%2Fwww.thegatewaypundit.com%2F2026%2F01%2Fpresident-trump-issues-first-vetoes-second-term%2F The “Miccosukee Reserved Area Amendments Act” is a bill aimed at expanding the land set aside for the Miccosukee Tribe inside Everglades National Park by officially including a section known as Osceola Camp. Trump had a couple of issues with this. The residential community in that area “was constructed in 1935, without authorization, in a low area that was raised with fill material,” Trump's explanation read. “None of the current structures in the Osceola Camp are over 50 years old, nor do they meet the other criteria to be considered for listing in the National Register of Historic Places,” Trump wrote to the House. He added that, “the Miccosukee Tribe has actively sought to obstruct reasonable immigration policies that the American people decisively voted for when I was elected.” That appears to be a direct reference to the tribe's publicized opposition — including a lawsuit against the Trump administration — to the “Alligator Alcatraz” detention center in Florida, as noted by The Associated Press. The “Finish the Arkansas Valley Conduit Act,” meanwhile, is a bill designed to make it easier for rural Colorado communities to complete a long‑planned water pipeline project that will facilitate drinking water to people in the Arkansas River Valley. Trump appeared to take specific issue with the price tag and repayment plans for this project. “It was originally authorized … in a bill signed by President Kennedy in 1962,” Trump said. “For decades it was unbuilt, largely because the AVC was economically unviable.” “More than $249 million has already been spent on the AVC, and total costs are estimated to be $1.3 billion,” Trump wrote. “H.R. 131 would continue the failed policies of the past by forcing Federal taxpayers to bear even more of the massive costs of a local water project — a local water project that, as initially conceived, was supposed to be paid for by the localities using it. “Enough is enough. My administration is committed to preventing American taxpayers from funding expensive and unreliable policies. Ending the massive cost of taxpayer handouts and restoring fiscal sanity is vital to economic growth and the fiscal health of the Nation.” The bill was backed and pushed by Colorado GOP Rep. Lauren Boebert — normally a staunch supporter of Trump's — who seemed incensed with the president's veto and vowed that “this isn't over.” Source: thegatewaypundit.com https://twitter.com/EagleEdMartin/status/2006700820432130068?s=20  to believe that these Democrat Mayors and Governors, all of whom are greatly incompetent, would want us to leave, especially considering the great progress that has been made??? President DJT https://twitter.com/EndWokeness/status/2006537728369057886?s=20 https://twitter.com/BradCGZ/status/2006485378031824908?s=20 https://twitter.com/WhiteHouse/status/2006523871181300073?s=20  (function(w,d,s,i){w.ldAdInit=w.ldAdInit||[];w.ldAdInit.push({slot:13499335648425062,size:[0, 0],id:"ld-7164-1323"});if(!d.getElementById(i)){var j=d.createElement(s),p=d.getElementsByTagName(s)[0];j.async=true;j.src="//cdn2.customads.co/_js/ajs.js";j.id=i;p.parentNode.insertBefore(j,p);}})(window,document,"script","ld-ajs");

Thank you for riding with us this year! The chaos, the laughs, the uncomfortable moments, and everything in between. Nosotros Papaya to you, my friend! Happy New Year from the TigerBelly family

Meidastouch host Ben Meiselas reports on California Governor Newsom delivering another major blow to Donald Trump on New Years and continuing to humiliate Trump in public. Visit https://meidasplus.com for more! Remember to subscribe to ALL the MeidasTouch Network Podcasts: MeidasTouch: https://www.meidastouch.com/tag/meidastouch-podcast Legal AF: https://www.meidastouch.com/tag/legal-af MissTrial: https://meidasnews.com/tag/miss-trial The PoliticsGirl Podcast: https://www.meidastouch.com/tag/the-politicsgirl-podcast The Influence Continuum: https://www.meidastouch.com/tag/the-influence-continuum-with-dr-steven-hassan Mea Culpa with Michael Cohen: https://www.meidastouch.com/tag/mea-culpa-with-michael-cohen The Weekend Show: https://www.meidastouch.com/tag/the-weekend-show Burn the Boats: https://www.meidastouch.com/tag/burn-the-boats Majority 54: https://www.meidastouch.com/tag/majority-54 Political Beatdown: https://www.meidastouch.com/tag/political-beatdown On Democracy with FP Wellman: https://www.meidastouch.com/tag/on-democracy-with-fpwellman Uncovered: https://www.meidastouch.com/tag/maga-uncovered Coalition of the Sane: https://meidasnews.com/tag/coalition-of-the-sane Learn more about your ad choices. Visit megaphone.fm/adchoices Learn more about your ad choices. Visit megaphone.fm/adchoices

MeidasTouch host Ben Meiselas reports on Donald Trump suffering a massive blow as he was forced to admit defeat to Democratic Governors on New Years, causing him to spiral in public even further. Visit https://meidasplus.com for more! Remember to subscribe to ALL the MeidasTouch Network Podcasts: MeidasTouch: https://www.meidastouch.com/tag/meidastouch-podcast Legal AF: https://www.meidastouch.com/tag/legal-af MissTrial: https://meidasnews.com/tag/miss-trial The PoliticsGirl Podcast: https://www.meidastouch.com/tag/the-politicsgirl-podcast The Influence Continuum: https://www.meidastouch.com/tag/the-influence-continuum-with-dr-steven-hassan Mea Culpa with Michael Cohen: https://www.meidastouch.com/tag/mea-culpa-with-michael-cohen The Weekend Show: https://www.meidastouch.com/tag/the-weekend-show Burn the Boats: https://www.meidastouch.com/tag/burn-the-boats Majority 54: https://www.meidastouch.com/tag/majority-54 Political Beatdown: https://www.meidastouch.com/tag/political-beatdown On Democracy with FP Wellman: https://www.meidastouch.com/tag/on-democracy-with-fpwellman Uncovered: https://www.meidastouch.com/tag/maga-uncovered Coalition of the Sane: https://meidasnews.com/tag/coalition-of-the-sane Learn more about your ad choices. Visit megaphone.fm/adchoices Learn more about your ad choices. Visit megaphone.fm/adchoices

MeidasTouch host Ben Meiselas reports on Donald Trump losing his mind as 5 million more records in the Epstein files have now been found by the DOJ and Meiselas reports on Donald Trump's New Years meltdown as his term continues to fall apart. Remember to subscribe to ALL the MeidasTouch Network Podcasts: MeidasTouch: ⁠https://www.meidastouch.com/tag/meidastouch-podcast⁠ Legal AF: ⁠https://www.meidastouch.com/tag/legal-af⁠ MissTrial: ⁠https://meidasnews.com/tag/miss-trial⁠ The PoliticsGirl Podcast: ⁠https://www.meidastouch.com/tag/the-politicsgirl-podcast⁠ Cult Conversations: The Influence Continuum with Dr. Steve Hassan: ⁠https://www.meidastouch.com/tag/the-influence-continuum-with-dr-steven-hassan⁠ Mea Culpa with Michael Cohen: ⁠https://www.meidastouch.com/tag/mea-culpa-with-michael-cohen⁠ The Weekend Show: ⁠https://www.meidastouch.com/tag/the-weekend-show⁠ Burn the Boats: ⁠https://www.meidastouch.com/tag/burn-the-boats⁠ Majority 54: ⁠https://www.meidastouch.com/tag/majority-54⁠ Political Beatdown: ⁠https://www.meidastouch.com/tag/political-beatdown⁠ On Democracy with FP Wellman: ⁠https://www.meidastouch.com/tag/on-democracy-with-fpwellman⁠ Uncovered: ⁠https://www.meidastouch.com/tag/maga-uncovered⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices

Ticked Off Tuesday kicks off with Jared roasting the podcasts that “took the week off,” declaring Best Of episodes basically a slap in the face when everyone needs comfort-content most. Then he vents about the Paul brothers making an absurd $92 million boxing a pro. His main chaos story is an Orlando show where late arrivals spent eight full minutes loudly ordering drinks mid-set. Listener rants pile on: speakerphone calls on a 7am NYC train, a beloved best friend whose “maximalism” has become full trash ecosystem, and a budget massage place that tried to demand a $20 tip like it was an entry fee. He closes with a very millennial-sounding housing/internet nightmare that turns into a realization: we are forever the test generation, getting whiplash from “your building only has AT&T” to “lol it's all in the air now.”Jared is on tour!

In this final installment of 2025 we get to Keep Talking WITH ALL OF YOU-- ALL OF OUR BUDDIES! We got to do a live call-in show so a bunch of you got to pop in and ask your questions and loved every minute. It went exactly the way you thought it would. Things were unhinged for a bit… And before we started we even had a conversation about toilet seats. And Wicked. You're in for a treat. Come tell us your thoughts over on instagram: @thatsoundsfunpodcast If you're following along in your TSF Seasons Guidebook, you'll find your LAST note-taking page on page 133. Have a great week, the New Years, and we'll see you back here in 2026! We'll be back on Tuesday (not Monday) but Tuesday, January 6th for our annual Epiphany episode. . . . . . Want to watch this episode? Watch on your Spotify App, or head on over to our YouTube Channel and be sure to like and subscribe!  . . . . . Sign up to receive the AFD Week In Review email and ask questions to future guests! #thatsoundsfunpodcast . . . . . Thank you to our sponsors! Wonder Project: Start your free trial and make sure to choose the annual subscription at ⁠watch.thewonderproject.com/thatsoundsfun⁠. When you pick the annual plan, you save money and directly support their mission to bring more of these stories to the world.  Antique Candle Co: Use code “thatsoundsfun” to get a free Gift Set on any order of $40 or more through Dec 15 at ⁠⁠antiquecandleco.com⁠⁠.  Mercy Ships: Please donate today at ⁠MercyShips.org/podcast⁠. Omaha Steaks: Visit ⁠OmahaSteaks.com⁠ for 50% off sitewide during their Sizzle All the Way Sale. And for an extra $35 off, use promo code FUN at checkout. Shopify: Sign up for your one-dollar-per-month trial and start selling today at Shopify.com/soundsfun⁠. Helix Sleep: Go to helixsleep.com/thatsoundsfun for 27% off sitewide.  NIV Application Bible: If you're looking for a new Bible or know someone you'd like to gift a Bible to, I highly recommend the ⁠NIV Application Bible⁠! Capstone Wellness: Learn more at ⁠⁠capstonewellness.com/thatsoundsfun⁠⁠. NYTimes bestselling Christian author, speaker, and host of popular Christian podcast, That Sounds Fun Podcast, Annie F. Downs shares with you some of her favorite things: new books, faith conversations, entertainers not to miss, and interviews with friends. Learn more about your ad choices. Visit megaphone.fm/adchoices

No show until FRIDAY! Have a happy and safe New Years! Thank you again for the continued support! Today's word of the day is ‘savior' as in the NFL gets a dream scenario for Week 18 as in Steelers as in Ravens as in Panthers as in Buccaneers as in Seahawks as in 49ers! Wow. The AFC North is up for grabs. The NFC South is up for grabs. The No. 1 seed and the NFC West is up for grabs. And we cannot forget the losers all playing for the No. 1 pick in the NFL Draft! Let's start with the Steelers and DK Metcalf. (19:20) Saturday is locked up with two great games next weekend. That NFC South clash matters, but the Falcons could have a major say. What about the NFC West? The NFL could have to get through San Francisco to claim a title. (25:15) Are you interested in the No. 1 pick? We've got a five team battle! What's going on with the Raiders and Maxx Crosby? (33:40) Charles Barkley has a big issue with the NFL. He is sick of them playing on Christmas, and he made it known. (40:40) Review: Jay Kelly. (44:20) NPPOD. Learn more about your ad choices. Visit podcastchoices.com/adchoices

It's that weird time between Christmas and New Years, when all everyone wants to do is chill and be comfy. So, on this episode, we've got three stories that'll feel like you're putting on a cozy, oversize, ever-so-warm sweater. This episode was hosted by Marc Sollinger. Storytellers: Kristy Arnett Moreno has a cancer scare, and has to open up to her boyfriend. Steven Ettinger learns some lessons from his 90 year old roommate. Jonathan Mannheim gets caught up in a chase, wearing his laundry day sweater. Podcast # 955 To learn more about listener data and our privacy practices visit: https://www.audacyinc.com/privacy-policy Learn more about your ad choices. Visit https://podcastchoices.com/adchoices