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SpaceX priced the biggest IPO ever at $135/share, raising $75B and debuting at $1.77T. ShinyHunters exploited an unpatched Oracle PeopleSoft flaw hitting 100+ organizations, Mistral seeks €3B at €20B, MrBeast hit 500M subscribers, and SBF lost his appeal. SpaceX raises $75B in the biggest-ever IPO, pricing 555.6M shares at $135 each, giving it a market value of $1.77T (Bloomberg) Founders Fund's ~3% SpaceX stake is worth $50B+, Sequoia's ~1.5% is worth $20B+, and a16z will see its biggest return ever at $10B+ (Bloomberg) Some investors question SpaceX's valuation, citing its $4.3B loss on $4.7B in revenue in Q1, as well as concerns over space data centers (NYT) Oracle warns customers of a critical PeopleSoft flaw after ShinyHunters claimed breaches of 100+ organizations using PeopleSoft; Oracle has not issued a patch (TechCrunch) Sources: French startup Mistral AI is in talks to raise ~€3B at a ~€20B valuation; it was last valued at €11.7B during a funding round in September 2025 (Bloomberg) MrBeast hits 500M subscribers on YouTube, a record for the platform (The Wrap) Sam Bankman-Fried loses his bid to overturn his fraud conviction and 25-year prison sentence over the collapse of FTX (Reuters) Longreads As companies are hit by rising AI costs, they are increasingly using tools that tap cheaper models, including some from China, putting price pressure on OpenAI and Anthropic (WSJ) Sixteen economists weigh in on what AI will mean for the US economy, workers, and workplaces; only two expect AI to actually create more jobs (WSJ) Learn more about your ad choices. Visit megaphone.fm/adchoices

Crypto News: Michael Saylor lies saying Strategy never said it would sell its Bitcoin. Visa says it has moved $7B annually in stablecoins through its network. Stellar Development Foundation has unveiled a quantum preparedness plan to migrate all XLM accounts to quantum-resistant signatures by end of 2027. Ripple and Bitso expand their partnership, bringing Bitso's MXN-backed stablecoin MXNB to the XRP Ledger. Brought to you by

Welcome to Omni Talk's Retail Daily Minute, sponsored by Duvo and Mirakl.In today's Retail Daily Minute, Omni Talk's Chris Walton discusses:Macy's reports Q1 net sales of $4.7B, up 1.8% YoY, with comps rising 3% overall and 2.4% at its 200 reimagined stores.Ulta Beauty beats top and bottom line estimates with EPS of $7.74 vs. $6.86 expected and revenue of $3.16B, raises full-year EPS guidance, and credits its TikTok Shop launch, Rare Beauty addition, and fragrance strength for a standout fiscal Q1.Amazon expands AI-powered visual search in its shopping app with real-time generative image suggestions, "Shop by Style" shoppable collages, and visual filter capabilities.The Retail Daily Minute has been rocketing up the Feedspot charts, so stay informed with Omni Talk's Retail Daily Minute, your source for the latest and most important retail insights.

Caroline McAuliffe is Senior Vice President, Head of Corporate Finance (FP&A and Procurement) at Fannie Mae. In its Q1 2026 results, the government-owned mortgage giant boasted 33 consecutive quarters of profitability and $3.7B in net income in the quarter—delivered by a team of 7,000 employees. In this episode Caroline reveals the FP&A mindset and processes behind this success. The career progression from audit to controllership, and FP&A Combining procurement and FP&A  Shifting from an annual budget cycle to a 2-year rolling forecast How AI is transforming repetitive low value work including AI “flash reports needed supporting 50 officers at Fannie Mae Secrets to being a CTA (Challenging Trusted Advisor) at Fannie Mae 

Mokslo metams pasibaigus daugelis vaikų pirmiausia džiaugiasi, kad nereikės anksti keltis į mokyklą. FM99 studijoje viešėjo Alytaus Vidzgirio mokyklos 7B klasės mokiniai. Septintokai pasakojo apie artėjančias atostogas, vasaros planus, mokyklą ir tai, kokią miesto šventę norėtų matyti Alytuje. Vieni planuoja keliones su šeima, kiti daugiau laiko praleisti su draugais, o kai kurie tiesiog tikisi gerų orų ir galimybės pailsėti po mokslo metų.

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,

A top-5 mobile game with 60-70 million daily active users just disappeared from Google Play for 24 hours and came back. Nobody from Hungry Studios is saying anything. That's the headline.Jakub Remiar flies solo this week with nine stories from the May 23-29 news cycle. The Block Blast Android outage is the biggest shock — a game that big going dark on a major platform for an entire day with zero public explanation. The Monopoly Go licensing story is the most quietly important: Scopely paid Hasbro $41M last quarter alone, confirming the $168M/year run-rate that puts Monopoly Go in genuinely different stratosphere from everything else in social casino. And Valve raised the Steam Deck OLED 1TB from $649 to $949 — a 40% hike that prompted Tim Sweeney to publicly joke about Gabe Newell's $500M super-yacht.Plus: Playtika layoffs as social casino keeps declining, Unreal Engine 6 teased via Rocket League, NetEase posts 7% YoY growth, CD Projekt Red announces a new Witcher 3 expansion called Songs of the Past, IO Interactive's James Bond game hits 1.5M copies in 24 hours, Fortnite returns to iOS to a 3.4M download spike, and the GDC 2026 trend report confirms generative AI is the only thing anyone in the industry is talking about.━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⏱️ TIMESTAMPS00:00 Cold open — the Steam Deck mega-yacht joke00:30 Block Blast vanished from Google Play (and came back)02:00 Playtika layoffs + Monopoly Go's $41M Hasbro license fee03:30 Unreal Engine 6, NetEase Q1, Witcher 3 + James Bond05:24 Sponsor — Potensus06:32 GDC 2026 trend report — generative AI dominates07:30 Fortnite iOS return drives 3.4M downloads in 8 years08:30 Steam Deck +40% price hike + the mega-yacht punchline

Former U.S. Capitol Police officer and author of the book, “Standing My Ground: A Capitol Police Officer's Fight for Accountability and Good Trouble After January 6th,” Harry Dunn talks about his new lawsuit to block the Trump administration's $1.7B payout fund and why he believes it's “putting a retainer on a mob.”Become a supporter of this podcast: https://www.spreaker.com/podcast/tavis-smiley--6286410/support.

Trump's corruption scandals are exploding, Republicans are panicking, gas prices are surging, Congress is rebelling over Iran, and even conservative insiders are warning this could become a political disaster for the GOP.In this episode of Political Rehab, Matt Robison and Matt Wylie break down:Trump's $1.7 billion settlement slush fundThe hidden theory behind the payout schemeJeff Bezos and the collapse of media independenceWhy Republicans are privately terrified about the midtermsTrump's sinking approval ratingsThe revenge tour against Massie, Cassidy, and CornynCongress finally pushing back on Trump's Iran warThe end of Stephen Colbert and what it says about modern mediaWhy corruption may become the defining political issue of 2026PLUS:A powerful Dose of Hope segment on the FDA's breakthrough Alzheimer's blood test rollout and why government-funded science still matters.⏱️ TIMESTAMPS00:00 Intro — “Historic Butt-Kicking”00:34 Trump Dump — Congress abandons oversight03:20 Bezos, Trump, and media corruption06:10 Bye Bye Ballroom08:15 Corruption becomes central political issue09:05 Trump polling collapse10:00 Is Trump giving up on the midterms?11:15 Republicans panic over Ken Paxton endorsement12:05 Trump revenge tour backfires15:05 Senate GOP rebellion over Iran war18:05 Trump stock trades and media silence20:00 Should Democrats run on corruption?21:15 Deep Dive — The end of Colbert and late-night TV24:00 Political satire in the Trump era27:00 Why Colbert worked on Comedy Central29:15 “That's Bullshit” — Trump's $1.7B settlement fund30:30 Theory #1 — Trump chaos and greed31:40 Theory #2 — Ending the IRS audit32:50 Theory #3 — The RICO / mafia model34:10 Cassidy Hutchinson and loyalty payouts35:10 Why the settlement fund may reveal weakness35:45 Dose of Hope — Memorial Day and democracy37:10 FDA Alzheimer's blood test breakthrough38:20 Why early diagnosis matters39:00 NIH-funded science and America's future

SpaceX filed publicly for its IPO on Nasdaq, revealing $18.7B in 2025 revenue, billions in losses, and Musk's 85.1% voting control. Anthropic pays SpaceX $1.25B per month for compute. Nvidia beat estimates again, Spotify launches Reserved ticketing, and Waymo suspends service over flooding. SpaceX files publicly for its IPO, choosing Nasdaq to make its debut under the symbol SPCX; Elon Musk's shares give him 85.1% of the voting power in the company (Bloomberg) SpaceX's S-1 reveals Anthropic is paying $1.25B per month through May 2029 under their Colossus compute deal, with a 90-day termination clause (The Verge) Spotify partners with Live Nation to launch Reserved, a new feature that sets aside tickets for the most dedicated fans, starting with Premium users in the US (Hollywood Reporter) Spotify debuts a desktop app for creating personal podcasts, competing with Google's NotebookLM, with support for daily briefings based on email and calendar (TechCrunch) Nvidia reports Q1 revenue up 85% YoY to $81.62B, above $78.86B est., Data Center revenue up 92% YoY to $75.2B, and announces an $80B share repurchase program (Nvidia) Waymo suspends operations in Atlanta and San Antonio as its robotaxis struggle with flooded roads and says it has yet to develop a "final remedy" for flooding (TechCrunch) Learn more about your ad choices. Visit megaphone.fm/adchoices

Vote-a-rama could get underway in the Senate today on the Republicans' second reconciliation bill. Playbook's Jack Blanchard and Dasha Burns dig into Republican anxiety over Trump's ballroom, the $1.7B "weaponization" fund, the Iran war's rising costs, and what the CIA director's Havana trip really means. And how the Democrats could use all this for their midterm messaging. 

Wednesday, May 20th, 2026 Today, The Senate finally advances a War Powers Resolution after eight tries; Todd Blanche refuses to block slush fund payouts for convicted sex offenders and rioters that assaulted police on January 6th; the DOJ adds a stipulation to the slush fund that ends the IRS audits into Trump's taxes; Donald has endorsed Ken Paxton for Senate and Republicans are livid; Trump is pressuring John Thune to fire the parliamentarian over his $1B Ballroom budget provision; the top lawyer at the US Treasury has resigned after DOJ established the $1.7B slush fund; and Allison and Dana deliver your Good News. Thank You, Coyuchi Get 15% off your first order when you visit Coyuchi.com/dailybeans Thank You, HomeServe Go to HomeServe.com to find the plan that's right for you. Not available everywhere. Most plans range between $4.99 to $11.99 a month your first year. Terms apply on covered repairs. California Rising - It was a powerful night to launch the fight to win back the House! The show is over but you can still help us reach our fundraising goal! bluewavecalifornia.org/concert Guest: Oliver Larkin  Democratic Socialist running for U.S. House FL-25https://www.oliverforcongress.com/ The Latest Breakdown:Retired Judge Blasts Trump's $1.7B Slush Fund for Allies | The Breakdown StoriesThe IRS Thought it Could Fight Trump's Lawsuit, but it Struck a Deal Anyway | NYT Trump Is Pressuring John Thune to Fire the Parliamentarian Over Ballroom Funding - NOTUS | News of the United States Trump shows off White House ballroom construction as funding stalls in Congress | Washington Post Republican Senators Are Livid at Trump's Endorsement of Paxton | The New York Times Senate advances bill aimed at ending Iran war as Cassidy, after primary loss, flips to support | AP News Good Trouble ⭑ 5 Calls → Stop Trump's $1.8B Political Slush Fund   →Dump Data Centers MAY 23, UTAH STATE CAPITOL · Indivisible →Recall Gov. Jeff Landry - Louisianadeservesbetter.com →STOP the deportation proceedings against Mohsen Mahdawi - Action Network →SusanRogan - how-to-help-win-the-midterms →detentionwatchnetwork.org →FieldTeam6.org →Standwithminnesota.com →Tell Congress Ice out Now | Indivisible, Defund ICE | 5Calls →Congress: Divest From ICE and CBP | ACLU →ICE List  →iceout.org Good NewsSome Colorado Democrats seek to censure Governor Polis over Tina Peters clemency See Dana Sept 23 in Chicago →Share your Good News & Good Trouble - The Daily Beans →Beans Talk audio -beans-talk.simplecast.com →Email Dana LGBTQ Owned eating establishments in your area - hello@mswmedia.com Subject: “Dana's Project” Subscribe to the MSW YouTube Channel - MSW Media - YouTube Harry Dunn is running for CongressHarry Dunn for Maryland Our Donation Links The Daily Beans is donating $10,000 and invites you to give what you can to support their life-affirming work - Donate to It Gets Better / The Daily Beans Fundraiser The Daily beans is donating $10,000 and invites you to give what you can to support their life-affirming work - Donate to It Gets Better / The Daily Beans Fundraiser Pathways to Citizenship link to MATCH Allison's Donationhttps://crm.bloomerang.co/HostedDonation?ApiKey=pub_86ff5236-dd26-11ec-b5ee-066e3d38bc77&WidgetId=6388736 Join Dana and The Daily Beans in support of Human Rights Campaign http://onecau.se/_ekes71 More Donation LinksNational Security Counselors - Donate, ActBlue.com/donate/msw-bwc, WhistleblowerAid.org/beans Dr. Allison Gill - The Breakdown | Allison Gill, Mueller, She Wrote @muellershewrote.com - Bluesky, MSW & The Daily Beans Podcast @muellershewrote - Instagram, MSW Media - YouTube →Federal workers - email AG at fedoath@pm.me and let me know what you're going to do, or just vent. I'm always here to listen.  Dana Goldberg - Dana is on Patreon! At Dana's Dugout, @dgcomedy - Bluesky, @dgcomedy - IG, Dana Goldberg - Facebook,  DanaGoldberg.com More from MSW Media - Shows - MSW Media, Cleanup On Aisle 45 pod, The Breakdown | Allison Gill Reminder - you can see the pod pics if you become a Patron. The good news pics are at the bottom of the show notes of each Patreon episode! That's just one of the perks of subscribing! patreon.com/muellershewrote Listener Survey:http://survey.podtrac.com/start-survey.aspx?pubid=BffJOlI7qQcF&ver=shortFollow the Podcast on Apple:https://apple.co/3XNx7ckWant to support the show and get it ad-free and early?https://patreon.com/thedailybeanshttps://dailybeans.supercast.com/https://apple.co/3UKzKt0 Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

DOJ announced a $1.7B fund to pay insurrectionists using our taxpayer money.  Trump is planning to pardon 250 people on America's 250th anniversary. Jamie Raskin has proposed a bill to compensate law enforcement officers who defended the Capitol on January 6th.  And Governor Jared Polis commuted the sentence of Tina Peters in Colorado. Allison Gillhttps://muellershewrote.substack.com/https://bsky.app/profile/muellershewrote.comHarry DunnHarry Dunn | Substack@libradunn1.bsky.social on BlueskyWant to support this podcast and get it ad-free and early?Go to: https://www.patreon.com/aisle45podTell us about yourself and what you like about the show - http://survey.podtrac.com/start-survey.aspx?pubid=BffJOlI7qQcF&ver=short Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

0:30 - Massie concession: they couldn't buy my vote so they bought the seat 13:00 - Paxton endorsement 31:59 - San Diego mosque shootings 48:17 - Newly elected chair of the Illinois Republican Party, Bob Grogan, says communication is the key to reshaping the Illinois GOP - "we need to be louder and clearer with what we have to offer" 01:09:17 - President of Center of the American Experiment and contributor to Powerline, John Hinderaker, follows the Minnesota fraud money trail and asks whether it leads back to Ilhan Omar. Get John’s latest at powerlineblog.com 01:29:11 - Noted economist Stephen Moore weighs in on voter ID, calling it an “80/20 issue” and saying, “Let Democrats explain why they don’t want it.” Get more Steve @StephenMoore 01:47:41 - Jack Roth Senior Fellow in American Politics at the Claremont Institute and former director of policy planning at the Department of State, Michael Anton, looks back at "The Flight 93 Election" 10 years later. Michael has two books coming out this summer! Dispatches from the Late Republic – available 6/30 & Studies in Machiavellian Political Philosophy – available 8/18 02:02:44 - UFO files 02:09:48 - $1.7B lawfare fundSee omnystudio.com/listener for privacy information.

Tuesday, May 19th, 2026 Today, Trump has unilaterally dropped his $10B lawsuit against the IRS and has set up a $1.7B slush fund to pay his criminal co-conspirators; the district attorney in Hennepin County Minnesota has charged ICE officer Christian Castro with assault and lying in the shooting of Julio Cesar Sosa-Celis; a jury has dismissed Elon Musk's claims against Open AI CEO Sam Altman; the House Oversight Committee will interview one of the prison guards on duty when Epstein died; and Allison and Dana deliver your Good News. Thank You, IQBAR Text DAILYBEANS to 64000 to get 20% off all IQBAR products, plus FREE shipping. Message and data rates may apply.  California Rising - It was a powerful night to launch the fight to win back the House! The show is over but you can still help us reach our fundraising goal! bluewavecalifornia.org/concert Guest: Adam KlasfeldAll Rise News@allrisenews|Bluesky, @klasfeldreports.com|BlueSky, @KlasfeldReports|Twitter, @senecaprojectus - Instagram The Latest Breakdown:Retired Judge Blasts Trump's $1.7B Slush Fund for Allies | The Breakdown StoriesLive updates: Three killed, two suspects dead in shooting at San Diego mosque | NBC 7 San Diego DOJ sets up $1.8B ‘anti-weaponization' fund after Trump drops IRS lawsuit | NBC News House Oversight Committee to interview prison guard on duty when Jeffrey Epstein died | ABC7 New York Minnesota county charges ICE officer in shooting during immigration crackdown | PBS News Jury dismisses all claims in Elon Musk's lawsuit against OpenAI CEO Sam Altman | NPR Good Trouble The next protest here opposing the "deathstar" 'Stratos' data center is by Indivisible, Saturday, 23 May at the Utah State Capitol, 11 am. Dump Data Centers · Indivisible →STOP the deportation proceedings against Mohsen Mahdawi - Action Network →SusanRogan - how-to-help-win-the-midterms →detentionwatchnetwork.org →FieldTeam6.org →Standwithminnesota.com →Tell Congress Ice out Now | Indivisible, Defund ICE | 5Calls →Congress: Divest From ICE and CBP | ACLU →ICE List  →iceout.org Good NewsV Spehar (@underthedesknews) - Instagram LouisianaDeservesBetter.comgeauxvote.com/ElectionsAndVoting.html No Detention Centers in Michigan Conserve Ohio →Share your Good News & Good Trouble - The Daily Beans →Beans Talk audio -beans-talk.simplecast.com →Email Dana LGBTQ Owned eating establishments in your area - hello@mswmedia.com Subject: “Dana's Project” Subscribe to the MSW YouTube Channel - MSW Media - YouTube Harry Dunn is running for CongressHarry Dunn for Maryland Our Donation Links The Daily Beans is donating $10,000 and invites you to give what you can to support their life-affirming work - Donate to It Gets Better / The Daily Beans Fundraiser The Daily beans is donating $10,000 and invites you to give what you can to support their life-affirming work - Donate to It Gets Better / The Daily Beans Fundraiser Pathways to Citizenship link to MATCH Allison's Donationhttps://crm.bloomerang.co/HostedDonation?ApiKey=pub_86ff5236-dd26-11ec-b5ee-066e3d38bc77&WidgetId=6388736 Join Dana and The Daily Beans in support of Human Rights Campaign http://onecau.se/_ekes71 More Donation LinksNational Security Counselors - Donate, ActBlue.com/donate/msw-bwc, WhistleblowerAid.org/beans Dr. Allison Gill - The Breakdown | Allison Gill, Mueller, She Wrote @muellershewrote.com - Bluesky, MSW & The Daily Beans Podcast @muellershewrote - Instagram, MSW Media - YouTube →Federal workers - email AG at fedoath@pm.me and let me know what you're going to do, or just vent. I'm always here to listen.  Dana Goldberg - Dana is on Patreon! At Dana's Dugout, @dgcomedy - Bluesky, @dgcomedy - IG, Dana Goldberg - Facebook,  DanaGoldberg.com More from MSW Media - Shows - MSW Media, Cleanup On Aisle 45 pod, The Breakdown | Allison Gill Reminder - you can see the pod pics if you become a Patron. The good news pics are at the bottom of the show notes of each Patreon episode! That's just one of the perks of subscribing! patreon.com/muellershewrote Listener Survey:http://survey.podtrac.com/start-survey.aspx?pubid=BffJOlI7qQcF&ver=shortFollow the Podcast on Apple:https://apple.co/3XNx7ckWant to support the show and get it ad-free and early?https://patreon.com/thedailybeanshttps://dailybeans.supercast.com/https://apple.co/3UKzKt0 Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

It's News Day Tuesday on The Majority Report. On today's program: Donald Trump has secured an illegal $1.7B slush fund from the Treasury that can be used however the president chooses and comes with ZERO oversight. At a Senate Budget Hearing for the DOJ, Senator Chris Van Hollen (D-MD) gets under acting Attorney General Todd Blanche's skin simply by pointing out that he was Donald Trump's personal lawyer less than two years ago. Adam Serwer, author and staff writer at The Atlantic, joins the program to discuss the dismantling of the Voting Rights Act. In the Fun Half: More from Senator Chris Van Hollen's exchange with acting AG Todd Blanche at the Senate Budget Hearing. Carl Quintanilla mentions that Donald Trump has been day trading which sends Jim Cramer in to an apoplectic shock, I guess out of fear of reprimand from his Supreme Leader. Donald Trump claims the requested $1B for his ballroom is actually not for the ballroom, it's for the security around the ballroom. The ballroom is of course at no expense to the taxpayer, unless you count the $1B of tax dollars that are being used to build the ballroom. Zohran Mamdani takes a jab at Ronald Reagan during his speech announcing the construction of a city-run grocery store in the south Bronx. It appears that Artificial Intelligence is really doing a number on Jim Breuer's brain. Meghan McCain proves again that she is an awful person as she attacks Nicholas Kristoff's piece in the New York Times on the horrible abuse that Palestinian prisoners were subjected to at the hands of Israeli guards. All that and more. To connect and organize with your local ICE rapid response team visit ICERRT.com The Congress switchboard number is (202) 224-3121. You can use this number to connect with either the U.S. Senate or the House of Representatives. Follow us on TikTok here: https://www.tiktok.com/@majorityreportfm Check us out on Twitch here: https://www.twitch.tv/themajorityreport Find our Rumble stream here: https://rumble.com/user/majorityreport Check out our alt YouTube channel here: https://www.youtube.com/majorityreportlive Gift a Majority Report subscription here: https://fans.fm/majority/gift Subscribe to the AMQuickie newsletter here: https://am-quickie.ghost.io/ Join the Majority Report Discord! https://majoritydiscord.com/ Get all your MR merch at our store: https://shop.majorityreportradio.com/ Get the free Majority Report App!: https://majority.fm/app Go to https://JustCoffee.coop and use coupon code majority to get 10% off your purchase Check out today's sponsors: WILD GRAIN: Get $30 off your first box + free Croissants in every box. Go to Wildgrain.com/MAJORITY to start your subscription. SUNSET LAKE CBD: Starting today, you can save 35% on your favorite CBD Oil Tinctures with the coupon code Memorial26 at SunsetLakeCBD.com Follow the Majority Report crew on Twitter: @SamSeder @EmmaVigeland @MattLech On Instagram: @MrBryanVokey Check out Matt's show, Left Reckoning, on YouTube, and subscribe on Patreon! https://www.patreon.com/leftreckoning Check out Matt Binder's YouTube channel: https://www.youtube.com/mattbinder Subscribe to Brandon's show The Discourse on Patreon! https://www.patreon.com/ExpandTheDiscourse Check out Ava Raiza's music here! https://avaraiza.bandcamp.

Monday, May 18th, 2026 Today, a former judge weighs in on Trump's $1.7B slush fund for January 6th rioters in a court filing; the Senate parliamentarian has stripped the $1B ballroom provision from Republican's budget reconciliation bill; Colorado Governor Jared Polis has commuted the sentence of voter data thief Tina Peters; the Federal Aviation Administration is going to sharply cut the number of air traffic controllers; a Texas hospital will create a detransition clinic as part of a settlement with AG Ken Paxton; Senator Bill Cassidy lost his primary as Democrat Jamie Davis advances in Louisiana; and Allison Delivers your Good News. Thank You, Helix 27% Off Sitewide when you go to HelixSleep.com/dailybeans Thank You, BoxieCat For a limited time, get 30% off your order when you head to Boxiecat.com/DAILYBEANS and use code DAILYBEANS.   California Rising - It was a powerful night to launch the fight to win back the House! The show is over but you can still help us reach our fundraising goal! bluewavecalifornia.org/concert   The Latest Breakdown:Retired Judge Blasts Trump's $1.7B Slush Fund for Allies | The Breakdown StoriesTina Peters, Colorado Election Denier, Will Be Freed by Gov. Jared Polis | The New York Times FAA cuts target for air traffic control staffing | Reuters Texas Children's Hospital to develop ‘detransition clinic,' fire physicians as part of settlement, AG says | Houston Public Media Sen. Bill Cassidy loses GOP primary in Louisiana as two rivals advance to runoff | NBC News Senate parliamentarian rejects Trump's ballroom fund in budget bill | NBC News Good Trouble STOP the deportation proceedings against Mohsen Mahdawi - Action Network   →SusanRogan - how-to-help-win-the-midterms →detentionwatchnetwork.org →Deliver Mother's Day to the Moms of Dilley →Letter Carriers' “Stamp Out Hunger“ Food Drive →FieldTeam6.org →Standwithminnesota.com →Tell Congress Ice out Now | Indivisible, Defund ICE | 5Calls →Congress: Divest From ICE and CBP | ACLU →ICE List  →iceout.org Good News →Share your Good News & Good Trouble - The Daily Beans →Beans Talk audio -beans-talk.simplecast.com →Email Dana LGBTQ Owned eating establishments in your area - hello@mswmedia.com Subject: “Dana's Project” Subscribe to the MSW YouTube Channel - MSW Media - YouTube Harry Dunn is running for CongressHarry Dunn for Maryland Our Donation Links The Daily Beans is donating $10,000 and invites you to give what you can to support their life-affirming work - Donate to It Gets Better / The Daily Beans Fundraiser The Daily beans is donating $10,000 and invites you to give what you can to support their life-affirming work - Donate to It Gets Better / The Daily Beans Fundraiser Pathways to Citizenship link to MATCH Allison's Donationhttps://crm.bloomerang.co/HostedDonation?ApiKey=pub_86ff5236-dd26-11ec-b5ee-066e3d38bc77&WidgetId=6388736 Join Dana and The Daily Beans in support of Human Rights Campaign http://onecau.se/_ekes71 More Donation LinksNational Security Counselors - Donate, ActBlue.com/donate/msw-bwc, WhistleblowerAid.org/beans Dr. Allison Gill - The Breakdown | Allison Gill, Mueller, She Wrote @muellershewrote.com - Bluesky, MSW & The Daily Beans Podcast @muellershewrote - Instagram, MSW Media - YouTube →Federal workers - email AG at fedoath@pm.me and let me know what you're going to do, or just vent. I'm always here to listen.  Dana Goldberg - Dana is on Patreon! At Dana's Dugout, @dgcomedy - Bluesky, @dgcomedy - IG, Dana Goldberg - Facebook,  DanaGoldberg.com More from MSW Media - Shows - MSW Media, Cleanup On Aisle 45 pod, The Breakdown | Allison Gill Reminder - you can see the pod pics if you become a Patron. The good news pics are at the bottom of the show notes of each Patreon episode! That's just one of the perks of subscribing! patreon.com/muellershewrote Listener Survey:http://survey.podtrac.com/start-survey.aspx?pubid=BffJOlI7qQcF&ver=shortFollow the Podcast on Apple:https://apple.co/3XNx7ckWant to support the show and get it ad-free and early?https://patreon.com/thedailybeanshttps://dailybeans.supercast.com/https://apple.co/3UKzKt0 Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

On this week's Red State Update, Jackie & Dunlap yell about corruption (Trump), conmen (Trump), and d*ck doctors. Trump Goes to China, coins "Dumocrats" Trump doesn't worry about american's financial pain "not even a little bit. I don't think about americans' financial situation." Trump settled (with himself?) to drop 10 billion lawsuit against the IRS to instred launch a 1.7B fund for his buds, including January 6thers and other criminals, conmen, and reprobates. Trump's reflecting pool remodel reflects corruption, ineptitude and dumbassery.  Vance's anti-fraud task force shuts down Medicaid funding to Blue States, says there's a lot of fraud in the federal government.  "It's unbelievable how much you've been fleeced by your own government." LOL! Trump's executive assistant Natalie Harp brings in stacks of printed-out pro-Trump and racist memes for Trump to approve before she posts it all online, with no approval from staff or national security officials. Obama apes? Trump Jesus? Blame her.  Mike Johnson says congress only makes $223k a year, let 'em do some insider trading so they can buy shoes for their kids. Knoxville Bans Roots. Tennessee author Alex Haley's book Roots, cultural juggernaut and winner of the Pulitzer winner,  banned by Knox County Schools. Chud the Builder: Racist murderous online "personality" arrested in Clarksville, TN. Tennessee Speaker Cameron Sexton removed Democrats from committees and subcommittees for protesting redistricting.  Andy Ogles: My kid has nightmares that dad is going to be taken away by big bad Biden FDA Commisioner Marty Makary resigns? over flavored vapes "1 in 3 Americans is underbabied," says Dr. Oz, as he and RFK Jr. obssess over teen sperm counts.  Kash Patel watching George Strait on either your dime or some crooks' dime that the FBI won't never investigate now Plus Howard Lutnick, New ICE Leader, TUBERVILLE: "ASSIMILATE OR GO HOME;" says Muslims "here to kll us all" and  Trump official who leading Hantavirus response is a penile implant specialist. Dr. Brian Christine is an Alabama urologist and fake admiral who spouts crazy far-right talking points and hosts a YouTube show called Erection Connection.  Get 20 Extra Minutes with Jackie and Dunlap at http://www.patreon.com/redstateupdate Art by Yoni Limor Photos by Robyn von Swank Music by William Sherry Jr. Follow us on Instagram, TikTok, Facebook, YouTube, BlueSky      

Friday, May 15th, 2026 Today, Donald Trump is poised to steal $1.7B from the Treasury to pay his allies prosecuted under Biden including the January 6th insurrectionists; the Supreme Court restores mail access to mifepristone pending appeal with Thomas and Alito dissenting; Trump Border Patrol Chief Mike Banks has abruptly quit amid reports that he traveled abroad to solicit sex workers; emails show that FBI Director Kash Patel's Hawaii trip included a ‘VIP snorkel' at the USS Arizona; Trump's Reflecting Pool repairs are garbage, over budget, and behind schedule; the Trump administration has paused Medicare enrollment for hospice providers; a Trump-appointed judge says the DOJ has ‘proven unworthy' of trust in a blistering trans care case ruling; and Allison Delivers your Good News. Thank You, Fast Growing Trees Get 20% off your first purchase  FastGrowingTrees.com/dailybeans Thank You, OneSkin Get 15% off OneSkin with the code DAILYBEANS at https://www.oneskin.co/dailybeans #oneskinpod California Rising - It was a powerful night to launch the fight to win back the House! The show is over but you can still help us reach our fundraising goal! bluewavecalifornia.org/concert Guest: Ezra LevinIndivisibleBlack Voters MatterEzra Levin | Indivisible@ezralevin - Bluesky Guest: John FugelsangTell Me Everything|John Fugelsang, The John Fugelsang Podcast, John Fugelsang|Substack, @johnfugelsang|Bluesky, @JohnFugelsang|TwitterSeparation of Church and Hate by John Fugelsang The Latest Breakdown:Epstein Survivor Reveals More Docs Hidden by Trump DOJ | The Breakdown Stories Trump poised to drop IRS suit, launch $1.7B 'weaponization' fund for allies: Sources - ABC News   Emails show FBI Director Kash Patel's Hawaii trip included 'VIP snorkel' at a Pearl Harbor memorial | AP News Trump Border Patrol Chief Abruptly Quits After Report He Solicited Sex Workers Abroad | HuffPost Latest News Reflecting Pool Repairs Appear Uneven and Behind Schedule, Officials Say | The New York Times Trump administration pauses Medicare enrollments for hospice providers amid fraud investigations | CBS News Trump-appointed judge says DOJ ‘proven unworthy' of trust in blistering trans care case ruling | The Advocate Good Trouble Saturday, May 16All Roads Lead to the South Nationwide Protest 9 AM | Selma — Faith leaders gather at the Edmund Pettus Bridge for prayer  1–5 PM | Montgomery — National Mass Rally at the Alabama State Capitol Actions across the country in support of actions in Montgomery and Selma →Email Dana LGBTQ Owned eating establishments in your area - hello@mswmedia.com Subject: “Dana's Project” →SusanRogan - how-to-help-win-the-midterms →detentionwatchnetwork.org →Deliver Mother's Day to the Moms of Dilley →Letter Carriers' “Stamp Out Hunger“ Food Drive →FieldTeam6.org →Standwithminnesota.com →Tell Congress Ice out Now | Indivisible, Defund ICE | 5Calls →Congress: Divest From ICE and CBP | ACLU →ICE List  →iceout.org Good NewsTrevor Project @ruthlesslyhandmaderuthlesslyhandmade.com Minocqua Brewing Companyhttps://www.facebook.com/photo?fbid=1400373722121174&set=a.474813974677158 Cowlitz Beaver Kit Cam Live - YouTube Kern County Animal Services - Bakersfield →Share your Good News & Good Trouble - The Daily Beans →Beans Talk audio -beans-talk.simplecast.com Subscribe to the MSW YouTube Channel - MSW Media - YouTube Harry Dunn is running for CongressHarry Dunn for Maryland Our Donation Links The Daily Beans is donating $10,000 and invites you to give what you can to support their life-affirming work - Donate to It Gets Better / The Daily Beans Fundraiser The Daily beans is donating $10,000 and invites you to give what you can to support their life-affirming work - Donate to It Gets Better / The Daily Beans Fundraiser Pathways to Citizenship link to MATCH Allison's Donationhttps://crm.bloomerang.co/HostedDonation?ApiKey=pub_86ff5236-dd26-11ec-b5ee-066e3d38bc77&WidgetId=6388736 Join Dana and The Daily Beans in support of Human Rights Campaign http://onecau.se/_ekes71 More Donation LinksNational Security Counselors - Donate, ActBlue.com/donate/msw-bwc, WhistleblowerAid.org/beans Dr. Allison Gill - The Breakdown | Allison Gill, Mueller, She Wrote @muellershewrote.com - Bluesky, MSW & The Daily Beans Podcast @muellershewrote - Instagram, MSW Media - YouTube →Federal workers - email AG at fedoath@pm.me and let me know what you're going to do, or just vent. I'm always here to listen.  Dana Goldberg - Dana is on Patreon! At Dana's Dugout, @dgcomedy - Bluesky, @dgcomedy - IG, Dana Goldberg - Facebook,  DanaGoldberg.com More from MSW Media - Shows - MSW Media, Cleanup On Aisle 45 pod, The Breakdown | Allison Gill Reminder - you can see the pod pics if you become a Patron. The good news pics are at the bottom of the show notes of each Patreon episode! That's just one of the perks of subscribing! patreon.com/muellershewrote Listener Survey:http://survey.podtrac.com/start-survey.aspx?pubid=BffJOlI7qQcF&ver=shortFollow the Podcast on Apple:https://apple.co/3XNx7ckWant to support the show and get it ad-free and early?https://patreon.com/thedailybeanshttps://dailybeans.supercast.com/https://apple.co/3UKzKt0 Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The Accenture agency acquisition is still in progress. Five AI tuck-ins closed this week across fintech, crypto, process mining, hardware, and spend management. And three deals that tell you everything about where the lower middle market is heading right now.Christian and Ayelet are back for Deal Review Friday — and this one is packed.Three deals. Five AI tuck-ins. One major tease still in progress. Running a little over 15 minutes. Worth it.⏱️ TIMESTAMPS0:00 — Welcome, May 15th 2026, and what's on the agenda0:45 — Accenture update: deal still in progress, silence is golden1:42 — AI tuck-in #1: Carta acquires Avantia — AI-native legal services + UK international play3:47 — AI tuck-in #2: MoonPay acquires Dawn Labs — autonomous AI trading agents5:38 — AI tuck-in #3: Celonis acquires Ikigai Labs — MIT spin-out, AI professor joins as chief scientist7:30 — AI tuck-in #4: Nominal acquires Fid Labs — AI agents connecting to dev environments and physical hardware8:20 — AI tuck-in #5: Coupa acquires Rossum — document ingestion layer completes source-to-pay stack8:39 — Deal #1: Brands at Work acquires Chorus — two London independents bet on integrated model9:45 — Why experiential has shifted from discretionary to core marketing strategy11:53 — Two independents, no banker, no PE: why this deal is worth celebrating13:05 — Deal #2: Smartly finalizes acquisition of INCRMNTAL — LOI to close in 7 weeks13:30 — What INCRMNTAL actually does and why Smartly needed it15:26 — Smartly manages $7B in media spend — and now has the measurement layer to match16:00 — Props to the INCRMNTAL founders and Smartly's Head of Corp Dev17:16 — Deal #3: OpAd Media acquires Broad Agency — two women-owned independents join forces18:30 — How Carrie Kerpen brought the two teams together at dinner19:30 — Ayelet was at the table when it happened20:30 — Same theme as Brands at Work / Chorus: independents on their own terms21:01 — Girl dinner confirmed. Christian not invited.21:57 — Wrap + episode 60 reminder

Trump's nexus of personal corruption with UAE and Gulf states becoming increasingly clear as latest deals between his Crypto company, 'World Liberty Financial',  and UAE's sheik MGX company strike deals. How Trump personally benefits. How Trump's Iran war announcements create volatility in energy stocks sales worth $7B since war began. Update on why 'Project Freedom' collapsed in 36 hours, Trump's targeting of Cuba after Iran, US courts reject Trump's 2nd Tariff plans. Latest on US credit card debt and why AI bubble won't produce real profits for most companies.

Corning and Nvidia partnered to open three optical manufacturing plants in the US, with Nvidia investing up to $2.7B. Morgan Stanley launched crypto trading on ETrade, Google tests a personal agent called Remy, and Meta builds an OpenClaw-inspired agent called Hatch.* Corning and Nvidia partner to open three advanced manufacturing plants in North Carolina and Texas dedicated to optical tech for Nvidia, creating 3,000+ jobs (CNBC) Morgan Stanley rolls out a crypto trading pilot on E*Trade, charging less than Coinbase, Robinhood, and Charles Schwab, ahead of a wider launch later in 2026 (Bloomberg) Sources and a document: Google is testing a "personal agent" codenamed Remy in the Gemini app that integrates with Google services to take actions for users (Business Insider) Sources: Meta is building an OpenClaw-inspired agent, internally called Hatch and powered by its Muse Spark model, and an agentic shopping tool in Instagram (The Information) OpenAI partners with Microsoft, AMD, Broadcom, Nvidia, and Intel researchers to detail the Multipath Reliable Connection (MRC) protocol to help scale compute (The Deep View) Learn more about your ad choices. Visit megaphone.fm/adchoices

7B, Pink Tax & again i'm the most H8ted podcaster/livestreamer which makes me so happy! Thank you

What happens after you “make it”… and realize money was never the point?In this episode, Jyoti Bansal, Founder & CEO of Harness and founder of AppDynamics (sold for $3.7B), sits down with Alisa Cohn for a conversation that cuts deeper than typical startup playbooks.This is not just about building companies. It's about what happens when the finish line disappears… and you have to decide who you are without it.Jyoti shares the unexpected identity crisis that hit after his exit, why he chose to build again anyway, and what most founders misunderstand about success, sales, and staying relevant in a world that's changing faster than your roadmap can keep up.From the brutal reality of startup milestones to the urgency of the AI transformation, this episode is a masterclass in how to think, move, and lead when the stakes are real.You'll learn:Why a worse product can still beat you (and how to prevent it)The hidden identity crisis founders face after a big exitHow to think of entrepreneurship as a craft, not a one-time eventWhy startup growth is about milestones, not perfectionThe real reason most companies fall behind during major tech shiftsHow to operate in “founder mode” when speed is everythingThe difference between product differentiation and go-to-market dominanceHow to build a scalable sales machine (not just hire “charismatic closers”)The hiring framework Jyoti uses to spot elite sales talentHow to align a company fast during high-pressure transformationThe “startup within a startup” model that creates ownership at scaleWhy transparency in numbers builds accountability across the entire orgWe talk about:00:00 The uncomfortable truth after a billion-dollar exit02:00 Why Jyoti came back to build again05:00 The founder identity crisis no one prepares you for08:00 Entrepreneurship as a craft, not a single shot11:00 The milestone framework for building successful companies15:00 The AI transformation and why most companies will lose18:00 Founder mode, speed, and making decisions in real time22:00 Aligning teams when everything is changing fast26:00 Why revenue is the only truth in business29:00 Sales as a competitive advantage 32:00 The myth of “relationship-based” selling35:00 Building a scalable, structured go-to-market machine38:00 How to hire great sales leaders (and avoid getting sold in the interview)41:00 The onboarding mistake most founders make44:00 Transparency, numbers, and company-wide accountability47:00 The “startup within a startup” model explained52:00 Ownership, incentives, and building multiple winning productsFollow Jyoti onLinkedIn: https://www.linkedin.com/in/jyotibansalWebsite:  ​https://www.harness.io/Connect with Alisa!Follow Alisa Cohn on Instagram: @alisacohnTwitter: @alisacohnFacebook: facebook.com/alisa.cohnLinkedIn: https://www.linkedin.com/in/alisacohn/Website: http://www.alisacohn.comDownload her 5 scripts for delicate conversations (and 1 to make your life better) Grab a copy of From Start-Up to Grown-Up by Alisa Cohn from Amazon

In this episode of Molecule to Market, you'll go inside the outsourcing space of the global drug development sector with Steve Favaloro, Chairman and CEO of Genezen. Your host, Raman Sehgal, discusses the pharmaceutical and biotechnology supply chain with Steve, covering: His deep passion for operations, and how early lessons in hard work and customer service shaped his leadership Learning from Mark Bamforth and the entrepreneurial journey at Brammer Bio, culminating in a $1.7bn exit to Thermo Fisher Why gaining exposure to every seat at the table was critical in preparing him for the CEO role Building Genezen with a focus on strong values, hiring the right people and investing in differentiated capabilities How the cell and gene therapy market has evolved over the past decade, and why he remains optimistic about the future of curative medicines Why things inevitably go sideways in innovative drug development, and the importance of being prepared to navigate it Steve Favaloro is an experienced biotech executive, board member, and investor. He is currently Chairman and CEO of Genezen, a best-in-class gene and cell therapy CDMO with specialized expertise in viral vector manufacturing. Steve joined Genezen in 2023 and has built up a team of almost 300 employees, supporting gene and cell therapy innovators from early-stage, growth-oriented biotechs to established industry leaders. He is an executive advisor at Ampersand Capital Partners, a leading healthcare investor, and serves on the board of Biologos. He also serves on the board of advisors of Life Science Cares Boston. Prior to Genezen, Steve was CFO at Arbor Biotech, a next-generation gene editing therapeutic company. Steve also served as CFO at Arranta Bio, a leading CDMO for mRNA, from its founding in 2019 to its successful exit to Recipharm in February 2022.  Prior to this, Steve was a finance leader and ultimately CFO at Brammer Bio, where he oversaw a period of rapid expansion and capital deployment from 2016 to 2019 – leading up to its successful sale to Thermo Fisher Scientific in May 2019 for $1.7B. Before joining Brammer, Steve held finance roles of increasing responsibility at MilliporeSigma, Merck KGaA, and Bruker Corporation. Steve received his MBA and Master of Science from the Carroll School of Management at Boston College. Steve also received his Bachelor of Arts degree in Economics from Boston College.   Molecule to Market is also sponsored by Bora Pharmaceuticals and supported by Lead Candidate. Please subscribe, tell your industry colleagues and join us in celebrating and promoting the value and importance of the global life science outsourcing space. We'd also appreciate a positive rating!

Nepal just experienced one of Asia's most dramatic recent political upheavals. A former rapper and Kathmandu mayor, Balen Shah, swept to power in a landslide election, winning 182 of 275 parliamentary seats and wiping out every established political party. With half of Nepal's 30 million people under 25, this “Gen Z Revolution” could signal a trend for young democracies worldwide.In this episode, Sujeev Shakya - Chair of the Nepal Economic Forum and senior advisor for Nepal and Bhutan at BowerGroupAsia - explains what happened, why it matters, and what comes next for this small Himalayan country sandwiched between India and China.We explore:•⁠ ⁠How a youth-led anti-corruption movement toppled the government and formed an interim administration on Discord in just five days•⁠ ⁠Why Nepal's new PM is focused on public service delivery rather than grand promises, and whether he can actually end decades of entrenched corruption•⁠ ⁠Nepal's remarkable economic transformation: GDP growth from $7B to $44B in 20 years, fueled by $15B in annual remittances and a booming IT export sector•⁠ ⁠How Nepal navigates its position between India and China - aiming to be an economic “bridge” rather than a geopolitical buffer•⁠ ⁠The impact of the Iran war and the Strait of Hormuz closure on Nepal's fuel supply and its two million workers in the Gulf•⁠ ⁠Why thousands of Nepali soldiers are fighting for Russia in Ukraine - and the new government's challenge of bringing them home•⁠ ⁠Investment opportunities in hydropower, agriculture, technology, tourism, and infrastructureWhether you follow South Asian politics, India-China competition, or youth-led political movements, Nepal's story offers insights into how small states survive and thrive between great powers.

What does it take to go from Wall Street deals to building the future of sports?In this episode of Startup to Stock Exchange, we sit down with Ira Miller Founder of First Inning Holdings to explore how private equity is reshaping the sports industry. From youth sports and women's leagues to billion-dollar exits and media-driven growth, Ira shares what really drives success behind the scenes.This conversation goes beyond the numbers. It's about backing the right people, spotting emerging opportunities, and why passion often beats pedigree.If you're a founder, investor, or just curious about the business of sports, this episode is packed with insights you don't want to miss.Seth's CompaniesVstock Transfer – https://www.vstocktransfer.com/Share Media – https://www.sharemedia.co/Listen to the ShowApple Podcasts – https://podcasts.apple.com/us/podcast/seth-farbman-on-podcast-from-startup-to-stock-exchange/id1356667808Spotify – https://open.spotify.com/show/54i7xkWaAALAFrUvk4WZcNConnect with SethLinkedIn – https://www.linkedin.com/in/sethfarbman/Instagram – https://www.instagram.com/sethfarbmanstockTikTok – https://www.tiktok.com/@sethfarbmanTwitter (X) – https://x.com/sethfarbman1About the ShowFrom Startup to Stock Exchange, hosted by entrepreneur and investor Seth Farbman, spotlights the journey of founders and CEOs as they scale their companies from early ideas to public markets. Each episode features candid conversations with leaders across industries, offering insights on growth, fundraising, branding, and the mindset it takes to build a company that lasts.Chapters :00:00 – Introduction: Passion Over Pedigree00:55 – What First Inning Holdings Does03:06 – Turning Passion Into a Career04:02 – Ira's Wall Street Journey & $7B in Exits06:09 – Family Background & Early Influences09:03 – How to Evaluate Sports Investments17:17 – Why Soccer Could Dominate Globally25:27 – Investor vs Operator: Ira's Approach30:27 – What Makes First Inning Holdings Different36:21 – Advice for Founders Pitching Investors38:43 – The Savannah Bananas & Sports Entertainment FutureConnect with Seth LinkedIn – https://www.linkedin.com/in/sethfarbman/ Instagram – https://www.instagram.com/sethfarbmanstock TikTok – https://www.tiktok.com/@sethfarbman Twitter (X) – https://x.com/sethfarbman1

Why November 30, 2022 Created Winners and Losers (And How Parents Can Still Win Big) Episode Overview AI reshaped the side hustle landscape—but not equally. In this episode, we break down how online entrepreneurship split into two distinct paths: those leveraging AI to build sustainable, scalable income without burnout, and those caught in commodity hell. Discover which side you're on, what shifted for ai entrepreneurs, and the one strategic choice that determines your path forward. Essential listening for parents building flexible side hustles in 2025. Discover how ChatGPT's November 30, 2022 launch permanently divided the side hustle economy into winners and losers. Learn why traditional freelancers lost 5.2% of earnings overnight, while AI-savvy parents are building $5,000-$10,000 monthly income streams. Get the exact framework to transform from competing with AI to collaborating with it, plus the three new side hustle personas dominating the $214 billion AI market. https://DarkHorseEntrepreneur.com   Key Moments & Timestamps 00:00 The invisible line splitting 1.57 billion freelancers 01:45 Three key takeaways preview 02:45 The uncomfortable truth about 2021 strategies 03:10 Kitchen table scenario - The freelancer's dilemma 06:45 The New AI Side Hustle Framework begins 08:15 The three AI-era side hustler personas 10:10 The parent advantage in AI economy 11:15 New high-value skills 12:45 Essential AI tools breakdown 14:25 4-week implementation strategy 17:15 Macro-level economic transformation 19:00 Whiskered Wisdom   Key Topics Covered

Welcome to Paranormal Spectrum, where we illuminate the enigmatic corners of the supernatural world. I'm your host, Barnaby Jones, and today we have a very special guest joining us:Jack Chavez is a multifaceted author, paranormal investigator, and dedicated seeker of the unexplained who serves as a prominent voice in the Midwest's haunting scene. As the host of the Paranormal Chicago Convention and the podcast Channeling Chavez, he brings a deep-seated curiosity to everything from local legends like Resurrection Mary and the Lincoln Park ghost stories to the chilling "Great Lakes Mothman" phenomenon. Beyond his work as a tour guide and frequent convention speaker, Chavez's research extends into the unsettling world of cryptids like the Rake and Pale Crawlers, all while maintaining a profound interest in the diverse religious practices and spiritual traditions of the world. Whether he is guesting on popular podcasts or investigating regional lore, his work is defined by a tireless drive to bridge the gap between historical mystery and modern high strangeness.Chicago Paranormal Facebook Grouphttps://www.facebook.com/groups/896797017552270Paranormal Chicago Conventionhttps://www.facebook.com/events/1331820615090383/?acontext=%7B%22event_action_history%22%3A[%7B%22surface%22%3A%22group%22%7D]%7DChanneling Chavez Podcasthttps://www.youtube.com/@channelingchavezClick that play button, and let's unravel the mysteries of the UNTOLD! Remember to like, share, and subscribe to our channel to stay updated on all the latest discoveries and adventures. See you there!Join Barnaby Jones on the Paranormal Spectrum every Thursday on the Untold Radio Network Live at 12pm Central – 10am Pacific and 1pm Eastern. Come and Join the live discussion next week. Please subscribe.We have twelve different Professional Podcasts on all the things you like. New favorite shows drop each day only on the UNTOLD RADIO NETWORK.To find out more about Barnaby Jones and his team, (Cryptids, Anomalies, and the Paranormal Society) visit their website www.WisconsinCAPS.comMake sure you share and Subscribe to the CAPS YouTube Channel as wellhttps://www.youtube.com/channel/UCs7ifB9Ur7x2C3VqTzVmjNQ

What if the key to scaling your business wasn't more people, but ruthless focus combined with relentless speed?Cameron Herold teams up with Sean Kim, the former President and Chief Product Officer at Kajabi (ex-Amazon, ex-TikTok) and the current Chief Product Officer at HighLevel, to crack open the playbook that turns chaos into proven, compounding wins. Inside this conversation: why leaders who say “no” more often grow faster, how to make data the backbone of every decision, and the real story behind powering a $1.7B creator platform without burning out your team or chasing shiny objects.Listen now to dodge the trap of feature bloat, hiring sprees, and slow, clunky execution. These are unfiltered insights and backed-up frameworks from the inside that you simply won't get anywhere else, unapologetically blunt, deeply actionable, and designed for COOs and founders ready to scale, not just survive.Timestamped Highlights00:23 – Why Sean Kim said “hell no” to TikTok… at first. The surprising conversation that changed everything01:10 – “Discovery” is the real unlock… how it built TikTok's domination and sparked Sean Kim's obsession08:18 – What happens when you leave Amazon's scale for pure startup chaos… scrappy desks, no process, and surviving the LA office09:24 – The secret power of the “doc writing” culture… how writing, not slides, became TikTok and Amazon's unfair advantage12:24 – Ruthless speed… fail fast, double down faster, and outmaneuver every competitor. This is how TikTok really operates14:45 – Why Kajabi never bloats its teams… and how knowing exactly when to hire is a massive competitive edge17:13 – The impact calculator… predicting revenue, retention, and customer wins before a single feature ships25:40 – How to crush “feature creep” and avoid turning your SaaS into a Frankenstein's monsterAbout the GuestSean Kim was previously the President and Chief Product Officer of Kajabi, the all-in-one platform powering $1.7B+ in annual creator revenue. He previously led product teams at TikTok and Amazon Prime, shaping global growth strategies and a customer-obsessed culture. With a reputation for world-class execution and a bold, systems-driven mindset, Sean stands out as a top operator for scale-minded founders and COOs. He is currently the Chief Product Officer at HighLevel.

Ethan Starr is a researcher and author of Billionaire Trivia, who spent years studying over 250 American billionaires, uncovering the surprising personal stories, pivotal moments, and unconventional paths behind their extraordinary wealth.Episode Sponsor: Fiscal AI is a modern data terminal that gives investors instant access to twenty years of financials, earnings transcripts, and extensive segment and KPI data—use my link for a two-week free trial plus 15% off: ⁠https://fiscal.ai/talkingbillions/⁠3:00 — Ethan's upbringing in Amherst, MA — a small college town with no super wealthy residents, shaping his careful attitude toward money.5:00 — The human side of billionaires: "Here's something that money can't fix" — Ethan on billionaires who've lost a child, showing no amount of wealth can shield from tragedy.8:00 — The self-made myth examined: Howard Schultz grew up in public housing; his father's injury and lost health insurance inspired Starbucks' employee benefits. "If you don't make mistakes, you're not trying hard enough."11:00 — Childhood traits of future billionaires: Jeff Bezos's intense focus, Michael Dell's obsession with shortcuts, Bill Gates reading books at dinner. Yet "I don't think there are any specific childhood traits that consistently predict who's going to become a billionaire."15:00 — Getting fired as a launchpad: Bernie Marcus dropped his lawsuit, co-founded Home Depot. Bloomberg's $10M severance funded Bloomberg LP. "To make billions, you have to own a business."19:00 — The power of pivoting: one billionaire switched from running an airline to leasing planes; Daniel Lubetzky created KIND Bars from a snack he wished existed.22:00 — Naming and luck: Google was originally "BackRub." Mark Cuban's broadcast.com sale to Yahoo for $5.7B at the dot-com peak.25:00 — Being unreasonable: Eli Broad's philosophy. Todd Graves limits Raising Cane's to five menu items while Michael Dell offered infinite customization — both unconventional, both successful.27:00 — Collector psychology and obsessive focus: Spielberg and Lucas collected Norman Rockwell paintings as fellow storytellers.30:00 — The space race: Bezos, Musk, Isaacman — pushing frontiers but risking everything, including their lives.38:00 — Political ambitions: Bloomberg as NYC mayor; billionaires deploying management skills in public service.42:00 — A world without billionaires: Ethan's take on wealth redistribution vs. wealth creation, and the slowing giving pledge.48:00 — Future billionaires: high-margin businesses, software, consumer products. "Start a business that can serve a lot of customers."52:00 — Defining success beyond money: "Success is making a positive difference" — Ethan's tribute to his fifth-grade teacher who left a lasting legacy.

Major shifts in mobile gaming, UA, and investmentsThis week's Two and a Half Gamers Breaking News covers three massive trends shaping the industry right now:

Send us Fan MailPrivate credit is the crisis everyone's watching, but the real story -- and the one no one has been focused on -- is what private equity is doing behind the scenes.In Part 1 of our 3-part series, Kristen and Jen break down the $30 billion leveraged buyout of Caesars by Apollo and TPG, the deal that became the blueprint for what we now call "creditor-on-creditor violence" and flipped everything everyone thought they knew about the relationship between debt and equity investors on its head.This also happens to be the ultimate Private Equity & LBO deep dive as we start with the basics: what an LBO actually is, how it works, why private equity firms started to do club deals back in 2006/7 (hint...size) and how capital structures work at a high level.From there, Jen and Kristen walk through the actual structure of the Caesars deal — $6B in equity from Apollo, TPG, and 30+ co-investors (everyone from Goldman Sachs to the Michael J. Fox Foundation to Bob Kraft), $7B in bank loans, $6B in bridge-to-high-yield bonds, and $6.5B in commercial mortgage-backed securities sitting at the PropCo level. They explain what an OpCo/PropCo mean in laymen's terms, why it let Apollo juice leverage, why club deals fell out of favor in favor of co-invest structures, and how today's mega-LBOs (Electronic Arts, the Ellison family's Warner Bros. Discovery play) stack up against what was historic in 2007.This series is based on The Caesars Palace Coup by Sujeet Indap and Max Frumes — not sponsored, just genuinely one of the best case studies out there on LBOs and distressed debt investing. Stay tuned for Part 2, where Jen and Kristen get into everything that went wrong, the asset-transfer shenanigans, and the birth of creditor-on-creditor violence and how Britney Spears was the linchpin that kept it all together...until it all unraveled with the biggest names in investing, Apaloosa, Eliott, Oak Tree, Oak Hill, Paulson and more got in the ring. In Part 3, we sit down with Sujeet Indap of the Financial Times to talk about what the Caesars deal means for the private credit market today, and what exactly is going on with Caesars who is back in the news with Carl Icahn and billionaire Tilman Fertitta out with competing offers.For a 14 day FREE Trial of Macabacus, click HEREShop our Self Paced Courses:Investment Banking & Private Equity Fundamentals HEREFixed Income Sales & Trading HEREWealthfront.com/wss. This is a paid endorsement for Wealthfront. May not reflect others' experiences. Similar outcomes not guaranteed. Wealthfront Brokerage is not a bank. Rate subject to change. Promo terms apply. If eligible for the boosted rate of 4.15% offered in connection with this promo, the boosted rate is also subject to change if base rate decreases during the 3 month promo period.The Cash Account, which is not a deposit account, is offered by Wealthfront Brokerage LLC ("Wealthfront Brokerage"), Member FINRA/SIPC. Wealthfront Brokerage is not a bank. The Annual Percentage Yield ("APY") on cash deposits as of 11/7/25, is representative, requires no minimum, and may change at any time. The APY reflects the weighted average of deposit balances at participating Program Banks, which are not allocated equally. Wealthfront Brokerage sweeps cash balances to Program Banks, where they earn the variable APY. Sources HERE. 

With Wen Nottebohm—Managing Director, Wealth Advisor at Cresset Overview Wen Nottebohm of Cresset joins Mindy Diamond to share the next gen perspective: how advisors can design their own growth path, earn credibility among UHNW clients, the value of mentors, the influence of AI, and much more. Listen in… > Download a transcript of this episode… NOTE: The views and opinions expressed by the guests on this podcast are their own and do not necessarily reflect the views and opinions of Diamond Consultants. Neither Diamond Consultants nor the guests on this podcast are compensated in any way for their participation. Watch… https://youtu.be/jmtqqBQ9C80 About this episode… There's a fairly well-defined career path for most financial advisors. You spend the early years learning the business, supporting senior advisors, and gradually taking on more responsibility. When it comes to ultra-high net worth clients, that timeline tends to stretch even longer, given the complexity and expectations that come with those relationships. But the path isn't always linear. And in some cases, it moves faster than people expect—especially when the focus shifts from simply accumulating experience to developing real expertise and “a seat at the table” early on. That's part of what makes Wen Nottebohm's perspective so compelling. Wen is part of the Atlanta team at Cresset, a $230B+ multi-family office. The team manages roughly $7B in assets, and Wen herself is advising on $1.6B for UHNW families and entrepreneurs. What stands out is not just the scale, but how early in her career Wen stepped into that level of responsibility—and what it actually required to make that work. In this conversation with Mindy Diamond, Wen offers a very real look at the next gen perspective, including: The wirehouse environment—and what made it a successful training ground. The value of a mentor—and how working with Justin Berman helped her move to the next level. Building a book to over $1B—and how she did so in a much shorter timeline than many of her peers. Earning credibility—and what it really takes to build a business and client trust with less of a track record. Working with a sophisticated client base—and how to manage expectations and identify what they really value. The benefit of a firm like Cresset—and how the more personalized culture and boutique feel creates a foundation for growth. The influence of AI—and how it's both changing the dynamic and raising the level of the advisor-client conversation. This episode is a masterclass for next gen and seasoned advisors alike, identifying what it really takes to build a billion-dollar business in a rapidly changing environment and questioning whether the traditional timeline for building an advisory practice is being rewritten in real time. Want to learn more about where, why, and how advisors like you are moving? Click to contact us or call 908-879-1002. Related Resources Finding the Shortest Path to Excellence Can Be a Game Changer for AdvisorsDoing everything you can to deliver better service, drive growth, and achieve your goals faster can result in extraordinary benefits. The 4th Annual Advisor Transition ReportA data-driven look at where advisors are moving, why they're making changes, and what it means for your business in 2026. Life After Goldman Sachs: A Story of Extraordinary SuccessEx-Goldman Sachs advisor Justin Berman shares how he found the courage to leave the Goldman imprimatur, brave Garden Leave, and build the $3B Berman Capital Advisors. Wen NottebohmManaging Director and Wealth Advisor Wen Nottebohm is a Managing Director, Wealth Advisor at Cresset. She works with clients to help protect and grow their legacy in order to have a bigger impact on what is most important to them. Wen was named to the 2024 Barron's Top 100 Independent Advisors, 2025 Barron's Top Independent Financial Advisors, 2025 Barron's Top Financial Advisors By State, 2025 Barron's Top Women Financial Advisors, 2025 Forbes Top Women Wealth Advisors Best-In-State, 2025 Forbes Best-In-State Wealth Advisors, 2025 Forbes Top Next-Gen Wealth Advisors Best-In-State, and 2025 Forbes America's Top Next-Gen Wealth Advisors lists. Prior to Cresset, Wen worked as a Wealth Advisor for Berman Capital Advisors, and before that was with AQR Capital Management, where she was a Client Strategies and Portfolio Solutions Analyst. Wen started out her career in the Private Wealth Management division at Morgan Stanley Smith Barney, where she specialized in risk and discretionary account management for the firm's ultra-high-net-worth clients. Wen graduated from MIT with Bachelor of Science degrees in Economics and Management Science. She also holds an MBA from The Wharton School, University of Pennsylvania. She obtained the CERTIFIED FINANCIAL PLANNER® designation in 2019. Wen and her husband live in Atlanta with their son and daughter. She serves on the Board of the YWCA of Greater Atlanta and is involved with the Atlanta Regional Commission Global Advisory Panel, the MIT Alumni Association, the Wharton Club of Atlanta, and the Young Women Leadership Forum. Wen is also a member of the LEAD Atlanta Class of 2016.

Artemis II is reigniting America's fascination with space... As the Orion astronauts return to Earth, a new generation is being inspired to boldly go and explore the universe (at 15:18) --- A closer look at the proposed $7B+ settlement in the Monstanto-Roundup case, and what it means for farm workers, landscapers and backyard gardeners (at 26:39) --- Salute to Service: This week's National Disabled Veterans Winter Sports Clinic is one of several events through the adaptive sports and therapeutic programs offered by the VA (at 32:25) --- Another collection of yummy and easy-to-make recipes from Kyra's Kitchen (at 50:15)

Host David Shiple covers major cybersecurity news: investigators attribute a record $285 million April 1 hack of crypto platform Drift Protocol to North Korea, describing a three-week setup involving a fake "Carbon Vote Token," wash trading to inflate value, social engineering to pre-approve backdoored transactions, Drift's removal of a timelock, and rapid collateralized withdrawals that crashed Drift's token and are now tracked by TRM Labs; the report notes North Korea's 2025 crypto theft total of $2.5B and lifetime total surpassing $7B after this incident, alongside mention of a North Korea-linked supply-chain compromise of the widely used Axios package. Stryker Medical says it has fully recovered from a March 11 Iran-linked wiper attack that used a compromised admin account and Microsoft Intune, prompting Microsoft guidance on multi-admin approval for wipes. The FBI labels a suspected China-linked breach of a U.S. surveillance system a "major incident," likening it to the 2024 Salt Typhoon campaign, while Sen. Mark Warner cites staffing cuts and leadership turmoil at CISA. TechCrunch reports embattled compliance startup Delve faces new claims it repackaged an open-source tool (Sim Studio) as its own "Pathways," as Delve denies broader fraud allegations, says it was targeted by a malicious actor, and Y Combinator cuts ties. Cybersecurity Today  would like to thank Meter for their support in bringing you this podcast. Meter delivers a complete networking stack, wired, wireless and cellular in one integrated solution that's built for performance and scale.  You can find them at Meter.com/cst 00:00 Headlines And Sponsor 00:54 North Korea Crypto Heist 01:16 How The Drift Hack Worked 03:20 Bigger DPRK Crypto Trend 04:24 Stryker Wiper Recovery 06:39 China Breach Major Incident 08:38 Policy And Staffing Fallout 09:37 Delve Startup In Crisis 10:29 Stolen Software Allegations 13:12 Delve Fights Back YC Cuts Ties 14:35 Wrap Up And Thanks 15:12 Sponsor Message Meter 00:00 Headlines And Sponsor 00:54 North Korea Crypto Heist 01:16 How The Drift Hack Worked 03:20 Bigger DPRK Crypto Trend 04:24 Stryker Wiper Recovery 06:39 China Breach Major Incident 08:38 Policy And Staffing Fallout 09:37 Delve Startup In Crisis 10:29 Stolen Software Allegations 13:12 Delve Fights Back YC Cuts Ties 14:35 Wrap Up And Thanks 15:12 Sponsor Message Meter

In this episode, we're joined by Summer Liu, CMO of SocialPeta, one of the leading ad intelligence platforms used by top app developers and marketers worldwide.Summer will break down the latest data from 90K+ advertisers and 1.7B+ ad creatives, revealing what's actually driving installs, revenue, and scale in 2026. She'll also share the trends from AI apps and short drama apps to the top-performing ad creatives and strategies across different markets.Must watch, if you're building, growing an app, or finding what to build next.You will discover:✅ Why micro-drama apps grew 126% YoY and how to replicate their success✅ The rise of AI apps (Chat, Companions) and winning growth angles✅ How to find winning creatives and spy on competitors using SocialPeta✅ Top-performing ad creatives across regions (and why they work)Learn More:Planning to scale your app or game globally?SocialPeta provides deep insights into global advertising trends, localized creatives, and competitive strategies, helping growth teams expand into new markets with confidence.Start your data-driven expansion at https://www.socialpeta.com/.You can also watch this video here: ⁠⁠https://youtube.com/live/_ELbpz39hzE*********************************************SPONSORSStill designing, resizing, and uploading screenshots manually? AppScreens lets you pick from hundreds of high-converting templates, generate for every device size and language in minutes, and upload automatically to directly to App Store Connect and Google Play Console. Trusted by more than 100K developers and ASO experts worldwide.Try it free: https://appscreens.com/?via=am*********************************************Got tons of freemium users who won't upgrade? Encore turns free users into paying customers and reduces churn by adding smart, curated affiliate offers at key user moments. Everyone wins with Encore.Learn more at ⁠https://encorekit.com/*********************************************Ready to take action? Start exploring AppsFlyer's deep linking suite -  coming soon as a standalone solution, independent of their measurement packages → https://bit.ly/46O7Wgd*********************************************Follow us:YouTube: ⁠AppMasters.com/YouTube⁠Instagram: ⁠@App MastersTwitter: ⁠@App MastersTikTok: ⁠@stevepyoung⁠Facebook: ⁠App Masters⁠*********************************************

Apple (NASDAQ:AAPL) just dropped a bombshell product lineup — including the all-new MacBook Neo at just $600, the iPhone 17E, and the MacBook Air M5 — and they're doing it while raising gross margins. How is that possible in an inflationary, tariff-heavy environment? In this episode, Simon Erickson breaks down Apple's bold pricing strategy, its asset-light business model, and why this could be a major long-term win for investors.We dig into Apple's record-breaking Q1 results: $143.8B in revenue (up 16% YoY), an all-time high gross margin of 48.2%, and $54B in operating cash flow — including $24.7B in share buybacks. We also explore how Apple's reliance on Taiwan Semiconductor (NYSE:TSM) and Broadcom (NASDAQ:AVGO) for chip manufacturing lets it avoid the massive CapEx spending that rivals like Amazon (NASDAQ:AMZN), Alphabet (NASDAQ:GOOGL), Microsoft (NASDAQ:MSFT), and Meta (NASDAQ:META) are racing to deploy.Plus, a preview of our upcoming Friday show: the Novo Nordisk (NYSE:NVO) vs. Hims & Hers (NYSE:HIMS) feud over GLP-1 weight loss drugs — and a future special episode on quantum computing.Don't miss out on our free investing newsletter with show recaps delivered straight to your inbox: 7investing.com/newsletter#Apple #AAPL #MacBookNeo #iPhone17E #MacBookAirM5 #StockMarket #InvestingNews #TechStocks #AppleInvestor #Tariffs #Inflation #GrossMargin #ShareBuybacks #TaiwanSemiconductor #Broadcom #GLP1 #NovoNordisk #HimsAndHers #QuantumComputing #7investing #SimonErickson

AI is moving fast, and for a lot of leaders that creates both pressure and possibility. In this episode of Leader Generation, Tessa Burg talks with Rohit Prabhakar, Global Head of Digital Experiences and Capabilities at Visa, about what it really takes to lead transformation when the rules keep changing. They dig into why strong foundations still matter, why connected data is more important than ever and why leaders need to balance quick wins with bigger reimagining. If you're trying to make sense of AI beyond the hype, this conversation is worth your time. Rohit shares practical ways to think about adoption, experimentation and change management without getting stuck in overplanning or unrealistic ROI expectations. It's a thoughtful listen for anyone leading teams, modernizing operations or figuring out how to move forward while bringing people along with them. Leader Generation is hosted by Tessa Burg and brought to you by Mod Op. About Rohit Prabhakar: Rohit Prabhakar is a Fortune 50 CMO and Chief Digital Officer who has generated $1.7B+ in business value by turning customer obsession into revenue growth. Currently leading global digital experiences at Visa, he has transformed marketing, data, AI, and CX across McKesson, Thomson Reuters, and FIS. Rohit's superpower: making customers love the most powerful growth engine. You can reach him at Rohitprabharkar.com or on LinkedIn. About Tessa Burg: Tessa is the Chief Technology Officer at Mod Op and Host of the Leader Generation podcast. She has led both technology and marketing teams for 15+ years. Tessa initiated and now leads Mod Op's AI/ML Pilot Team, AI Council and Innovation Pipeline. She started her career in IT and development before following her love for data and strategy into digital marketing. Tessa has held roles on both the consulting and client sides of the business for domestic and international brands, including American Greetings, Amazon, Nestlé, Anlene, Moen and many more. Tessa can be reached on LinkedIn or at Tessa.Burg@ModOp.com.  

DescriptionBhaskar was employee #1 at AppDynamics, which was sold to Cisco for $3.7B. He and co-founder Jyoti found a way to change how enterprise monitoring tools worked. From tracking low-level code metrics that ops teams didn't understand to monitoring what the business actually cares about.In this episode, Bhaskar breaks down how that one insight won them Netflix and Priceline as early customers, why they ran production POCs that no competitor would dare try, and how a free download called AppDynamics Lite generated over 60% of their leads—in an industry where getting started normally took weeks of professional services and six-figure contracts.Why You Should ListenWhy selling to developers is operating on hard mode.How one-day POCs became the killer enterprise sales weapon.Why freemium disrupted an industry that required weeks of professional services to get started.How they grew from $2M to $12M in revenue in just one year post launch.Keywords startup podcast, startup podcast for founders, product market fit, AppDynamics, application monitoring, enterprise SaaS, B2B sales, finding pmf, freemium strategy, Cisco acquisition, production POCChapters00:00:00 Intro00:11:33 Choosing the ICP00:20:37 Landing Netflix with Freemium00:28:44 Growing from $2M to $12M in Year Two00:30:10 The Free Download Strategy That Generated 60% of Leads00:32:04 Days from the NASDAQ Bell—Then Cisco Offered $3.7B00:41:28 The Moment of True Product Market FitSend me a message to let me know what you think!

For most of the week, lines snaked stubbornly around Philadelphia International Airport, a frustrating reminder of the government's inability to secure funding for the Department of Homeland Security. But days after ICE agents arrived with orders to ease the load on TSA workers, the Senate sent a bill to the House to get DHS back up and running. Find out how this development impacted the scene at PHL, while catching up on the past week's other big headlines from the Delaware Valley, including Phillies' Opening Day and state lawmakers' efforts to give Pennsylvania's minimum wage a boost.  00:00 Intro 02:07 How long until PHL gets back to normal? 06:52 City Council scrutinizes Mayor Parker's $7B budget 12:54 Could raising Pennsylvania's minimum wage really happen? 18:30 Breaking down Big, Beautiful Bill's local impact on Philly 24:26 With new season underway, Phillies again face World Series-or-bust expectations 30:37 Stolen pitbull found after 10 years Listen to The Week in Philly with Matt Leon and our team of reporters on KYW Newsradio every Saturday at 5am and 3pm, and Sunday at 3pm 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

Here's the podcast description for March 27, 2026: March 27, 2026: Your daily rundown of health and wellness news, in under 5 minutes. Today's top stories: WSJ reports consumers now take 20+ supplements daily spending $1K+ monthly, with SuppCo data showing average user spends $168/month but half of 500+ products fail label claims Longevity hotel market expected to grow from $7.6B in 2026 to $11.7B by 2030 as properties shift from wellness amenities to core health platforms eMed raises $200M at $2B+ valuation with Tom Brady as investor and Chief Wellness Officer, helping employers manage GLP-1 use through supervised platform Today's episode is brought to you by AIIR — a modern communications and experiential agency for health, wellness, fitness, and performance brands. From earned media to events and creator-led campaigns, AIIR helps companies sharpen their story, earn attention, and build trust that compounds. Visit https://aiir.agency to learn more. More from Fitt: Fitt Insider breaks down the convergence of fitness, wellness, and healthcare — and what it means for business, culture, and capital. Subscribe to our newsletter → insider.fitt.co/subscribe Work with our recruiting firm → https://talent.fitt.co/ Follow us on Instagram → https://www.instagram.com/fittinsider/ Follow us on LinkedIn → linkedin.com/company/fittinsider Reach out → insider@fitt.co

Research from Barna and C12 Business Forums shows that 51% of "Faith-Forward" CEOs consider faith a major motivation in leadership. A survey by Houston Christian University found that 74% of Christian business leaders rely on spiritual practice for decision-making and 63% look to scripture for guidance. Carl Grant III is an experienced leader in professional services business development, having worked with AM Law 50 firms and a Big Four accounting firm. He led Cooley LLP's business development team for 20 years, contributing to $1.7B in annual revenue growth, and drove a 33% market share increase at PricewaterhouseCoopers. Grant also doubled venture funds as part of Fairfax County Economic Development Authority and currently serves as Chairman and CEO of Cyrulion, Inc. He is a founding board member of the Austin Venture Association, an Army veteran, best-selling author, and has degrees from Indiana University and Harvard Business School. As a Christian business leader and founder of Bridges of Faith, Carl helps integrate faith, purpose, and leadership, advising executives on building trust and results without sacrificing values. His work includes promoting respectful Muslim–Christian dialogue, peacemaking, and living out faith with integrity. Married for 31 years with five adult children, he brings practical insights on faith both at home and in leadership roles. -- Follow: @carl.grant.iii Get the book: https://www.amazon.com/Live-Abundant-Life-Carl-Grant/dp/1637351941#:~:text=%22How%20to%20Live%20the%20Abundant,to%20live%20their%20best%20life.%22&text=%22Thoughtful%2C%20accessible%2C%20and%20compelling Learn more about your ad choices. Visit megaphone.fm/adchoices

What happens to an artist's reputation the moment they admit they used AI? Does admitting how they used AI make a difference? New research suggests the stakes are higher than most realize, and the answer is far from simple.  This week on the podcast, Dr. Joel Carnevale, assistant professor of Management at Florida International University, joins Dmitri to break down the findings from his recent article in The Conversation that put that question to the test. Using a music composition scenario with Hans Zimmer asa stand-in for established reputation, Joel and his co-authors designed experiments to find out how disclosure affects the way listeners evaluate a creator's competence and credibility. The conversation covers why authenticity is at the heart of the debate, what different types of AI disclosure actually signal to audiences, and why how you disclose may matter more than whether you disclose  Dmitri and Joel also explore what all of this means for a music industry where nearly every working producer is already using AI in some part of their process.    The news Global recorded music revenues hit $31.7B in 2025, up 6.4% YoY; users of paid music subscriptions reach 837M Why Mark Cuban Thinks Music Is (Basically) 'the Worst Industry Ever' for Investors Live Nation Employees Bragged About 'Gouging' Customers and 'Robbing Them Blind' In Dozens of Leaked Exchanges—Here's a Look at the Unsealed Documents   The Music Tectonics podcast goes beneath the surface of the music industry to explore how technology is changing the way business gets done. Visit musictectonics.com to find shownotes and a transcript for this episode, and find us on LinkedIn, Twitter, and Instagram. Let us know what you think!  Get Dmitri's Rock Paper Scanner newsletter.

A new resource center for trans, nonbinary and gender-diverse communities is opening soon in Ashland. The nonprofit Rogue Trans will offer a free clothing closet, activities, classes and more at the center. An open house was held March 14, and a grand opening celebration is planned for May. Maeve Woulfe is the executive director of Rogue Trans. She joins us to talk about the importance of creating safe spaces for queer communities in Southern Oregon.

AlabamaSen. Katie Britt pushing for passage of the SAVE American Act State senate passes a $3.7B general fund budget for FY 2027Governor Ivey signs bill into law requiring English proficiency for CDLsCentral Alabama Water release report on past operations under prior leadershipTroy to see expansion of Lockheed Martin facility over course of 5 yearsNationalWH corrects ABC News for alarmist news about Iranian drone attacks in CAA refueling tanker goes down into waters in Middle East, 6 on boardDriver in MI plows into a synagogue and is shot by security guardSen. Cornyn of TX gets snippy with a reporter for bringing up his RINO recordFL governor to sign bill on voter ID and citizenship verification for electionsWY governor signs bill that prohibits abortions after fetal heartbeat foundElection attorney Peter Tiktin says Dems plan to steal the midterms, impeach Trump and Vance and entrench establishment control once again

The news of Texas covered today includes:Our Lone Star story of the day: John Cornyn has defended support from Texas pastors directly linked to a major recipient of Soros money that has lobbied massively for near complete amnesty for illegal aliens in the U.S.I told you that Paxton was clever in his offer to withdraw. Cornyn and his swamp buddies just can't bring themselves to pass something as simple as nationwide Voter ID in elections with federal offices on the ballot: Cornyn Flip-Flops Again on Filibuster After Promising ‘Whatever It Takes'.Our Lone Star story of the day is sponsored by Allied Compliance Services providing the best service in DOT, business and personal drug and alcohol testing since 1995.Tilman Fertitta's Houston company aims to buy Caesar's in $7B deal. “Caesars, headquartered in Reno, operates more than 50 resorts, including Harrah's and Circus Circus, as well as properties branded as Caesars.”Lubbock County Expo Center project comes with [more] strings attached before county borrows money, as approved by oversight board. Boren changes vote to “yes.”Everything you need to know about this weekend's IndyCar race in Arlington: When it starts, what tickets cost and free events surrounding the race.Listen on the radio, or station stream, at 5pm Central. Click for our radio and streaming affiliates.www.PrattonTexas.com

For years, we've heard about AI transforming software development. But what if that same level of agentic, AI-driven collaboration could be applied not just to writing code, but to writing your entire go-to-market playbook?Agility requires that your go-to-market teams operate at the speed of insight, not at the speed of manual data entry and fragmented workflows. This means empowering them with tools that don't just provide data, but automate action based on strategic intent.Today, we're going to talk about the concept of an 'agentic' go-to-market platform, where AI doesn't just assist, but actively collaborates with sales and marketing teams to automate entire workflows, from strategy to execution.To help me discuss this topic, I'd like to welcome, Marcio Arnecke, Chief Marketing Officer at Apollo.io. About Marcio Arnecke As Apollo.io's Chief Marketing Officer, Marcio Arnecke brings a visionary approach to scaling high-growth B2B SaaS marketing in the AI-driven sales landscape. With over two decades of experience driving revenue acceleration across global markets, he has consistently transformed early-stage technology companies into market-defining brands. His expertise in AI-powered go-to-market strategies uniquely positions him to accelerate Apollo's mission of empowering sales teams through intelligent data and automation. Previously, he played a pivotal role in scaling marketing functions at SaaS giants like Intercom and Zendesk, where he drove remarkable growth from $40M to $1.7B, culminating in a successful IPO that raised $100 million in 2014. Leveraging his comprehensive background in demand generation, product marketing, and strategic storytelling, Marcio is focused on positioning Apollo as the go-to AI sales platform for SMB and mid-market teams. His approach combines data-driven insights with targeted narrative strategies, translating Apollo's technological capabilities into practical business value. Drawing from his global experience across Silicon Valley and international markets, Marcio aims to expand Apollo's brand and demonstrate how AI can meaningfully improve sales engagement for growing businesses. Marcio holds advanced degrees from Stanford University's Graduate School of Business and Golden Gate University, complemented by a BS in Business Administration from Universidade Feevale in Brazil. Marcio Arnecke on LinkedIn: https://www.linkedin.com/in/marcioarnecke/ Resources Apollo.io: https://www.apollo.io Take your personal data back with Incogni! Use code AGILE at the link below and get 60% off an annual plan: https://incogni.com/agile  The Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://www.teksystems.com/versionnextnow Catch the future of e-commerce at eTail Palm Springs, Feb 23-26 in Palm Springs, CA. Go here for more details: https://etailwest.wbresearch.com/Drive your customers to new horizons at the premier retail event of the year for Retail and Brand marketers. Learn more at CRMC 2026, June 1-3. https://www.thecrmc.com/ Enjoyed the show? Tell us more at and give us a rating so others can find the show at: https://ratethispodcast.com/agileConnect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter and more: https://www.theagilebrand.showCheck out The Agile Brand Guide website with articles, insights, andMartechipedia, the wiki for marketing technology: https://www.agilebrandguide.com The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company Hosted on Acast. See acast.com/privacy for more information.

For years, we've heard about AI transforming software development. But what if that same level of agentic, AI-driven collaboration could be applied not just to writing code, but to writing your entire go-to-market playbook? Agility requires that your go-to-market teams operate at the speed of insight, not at the speed of manual data entry and fragmented workflows. This means empowering them with tools that don't just provide data, but automate action based on strategic intent. Today, we're going to talk about the concept of an 'agentic' go-to-market platform, where AI doesn't just assist, but actively collaborates with sales and marketing teams to automate entire workflows, from strategy to execution. To help me discuss this topic, I'd like to welcome, Marcio Arnecke, Chief Marketing Officer at Apollo.io. About Marcio Arnecke As Apollo.io's Chief Marketing Officer, Marcio Arnecke brings a visionary approach to scaling high-growth B2B SaaS marketing in the AI-driven sales landscape. With over two decades of experience driving revenue acceleration across global markets, he has consistently transformed early-stage technology companies into market-defining brands. Hisexpertise in AI-powered go-to-market strategies uniquely positions him to accelerate Apollo's mission of empowering sales teams through intelligent data and automation. Previously, he played a pivotal role in scaling marketing functions at SaaS giants like Intercom and Zendesk, where he drove remarkable growth from $40M to $1.7B, culminating in a successful IPO that raised $100 million in 2014. Leveraging his comprehensive background in demand generation, product marketing, and strategic storytelling, Marcio is focused on positioning Apollo as the go-to AI sales platform for SMB and mid-market teams. His approach combines data-driven insights with targeted narrative strategies, translating Apollo's technological capabilities into practical business value. Drawing from his global experience across Silicon Valley and international markets, Marcio aims to expand Apollo's brand and demonstrate how AI can meaningfully improve sales engagement for growing businesses. Marcio holds advanced degrees from Stanford University's Graduate School of Business and Golden Gate University, complemented by a BS in Business Administration from Universidade Feevale in Brazil. Marcio Arnecke on LinkedIn: https://www.linkedin.com/in/marcioarnecke/ Resources Apollo.io: https://www.apollo.io Take your personal data back with Incogni! Use code AGILE at the link below and get 60% off an annual plan: https://incogni.com/agile  The Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://www.teksystems.com/versionnextnow Catch the future of e-commerce at eTail Palm Springs, Feb 23-26 in Palm Springs, CA. Go here for more details: https://etailwest.wbresearch.com/ Drive your customers to new horizons at the premier retail event of the year for Retail and Brand marketers. Learn more at CRMC 2026, June 1-3. https://www.thecrmc.com/ Enjoyed the show? Tell us more at and give us a rating so others can find the show at: https://ratethispodcast.com/agile Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstrom Don't miss a thing: get the latest episodes, sign up for our newsletter and more: https://www.theagilebrand.show Check out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company