Podcasts about decode

As the war with Iran escalates, the United States is shifting military assets back to the Middle East — raising new questions about whether Washington can stay focused on the Indo-Pacific and China. Alice Han and James Kynge speak with Gulf Research Center chief economist Dr. John Sfakianakis about how the conflict could reshape global power dynamics and whether Beijing may gain strategic breathing room while U.S. attention is divided. Then, a new set of university rankings is fueling debate over the future of global research. Chinese universities are climbing rapidly, backed by massive state investment and a surge in scientific output. Finally, China's electric vehicle giant BYD is reportedly exploring a dramatic new move to boost its global brand: entering Formula One. We look at what it would mean for the sport — and for China's ambitions in the global auto industry. Subscribe on Substack for ad-free episodes and much more! chinadecode.profgmedia.com/ Learn more about your ad choices. Visit podcastchoices.com/adchoices

https://youtu.be/QEW0sgDkbOQ (*Watch the YouTube free feed video version Tuesday 8pm EST!)On today's episode of the Occult Symbolism and Pop Culture with Isaac Weishaupt podcast we're doing an Epstein File decode: the special Kubrick's Code edition! We'll go through some of the theories I presented in my 2014 book Kubrick's Code and how they show up in the Epstein Files! From manipulation of the news, Rothchilds, secret societies, Wayfair furniture conspiracies, Adrenochrome, frizzlefrazzledazzle, Larry Celona and even Wizard of Oz!Links:Coast to Coast AM appearance 3/15/26: https://www.coasttocoastam.com/show/2026-03-15-show/Apollo 11, Trinity Nuclear Bomb, Twin Peaks & Eyes Wide Shut: Sex Magick Symbolism of 7/16 https://illuminatiwatcher.com/apollo-11-trinity-nuclear-bomb-twin-peaks-eyes-wide-shut-sex-magick-symbolism-of-7-16/Kubrick's Lolita Film & Epstein Filthy Rich Review Mashup! MKULTRA, Pizza, Zorro Ranch, UFOs, Shapeshifters & MORE: https://www.patreon.com/posts/patreon-bonus-38023728Kubrick's Code book: https://illuminatiwatcher.com/kubricks-code-analysis-of-2001-a-clockwork-orange-the-shining-and-eyes-wide-shut/Bieber and Selena Human Cloning Conspiracy on Breaking Social Norms: https://breakingsocialnorms.com/2026/03/02/justin-bieber-selena-gomez-epstein-cloning-mkultra-handlers-hollywoods-darkest-secrets/Wizard of Oz Esoteric Analysis: L. Frank Baum, Theosophy, Occultism & Cast Tragedies PART 1! https://illuminatiwatcher.com/wizard-of-oz-esoteric-analysis-l-frank-baum-theosophy-occultism-cast-tragedies-part-1/Show sponsors- Get discounts while you support the show and do a little self improvement!*CopyMyCrypto.com/Isaac is where you can copy James McMahon's crypto holdings- listeners get access for just $1 WANT MORE?... Check out my UNCENSORED show with my wife, Breaking Social Norms: https://breakingsocialnorms.com/GRIFTER ALLEY- get bonus content AND go commercial free + other perks:*PATREON.com/IlluminatiWatcher : ad free, HUNDREDS of bonus shows, early access AND TWO OF MY BOOKS! (The Dark Path and Kubrick's Code); you can join the conversations with hundreds of other show supporters here: Patreon.com/IlluminatiWatcher (*Patreon is also NOW enabled to connect with Spotify! https://rb.gy/hcq13)*VIP SECTION: Due to the threat of censorship, I set up a Patreon-type system through MY OWN website! IIt's even setup the same: FREE ebooks, Kubrick's Code video! Sign up at: https://illuminatiwatcher.com/members-section/*APPLE PREMIUM: If you're on the Apple Podcasts app- just click the Premium button and you're in! NO more ads, Early Access, EVERY BONUS EPISODE More from Isaac- links and special offers:*BREAKING SOCIAL NORMS podcast, Index of EVERY episode (back to 2014), Signed paperbacks, shirts, & other merch, Substack, YouTube links, appearances & more: https://allmylinks.com/isaacw *STATEMENT: This show is full of Isaac's useless opinions and presented for entertainment purposes. Audio clips used in Fair Use and taken from YouTube videos.

In this episode we are exploring how the skin–gut–brain–biome axis drives chronic inflammatory skin conditions like acne, eczema, and rosacea with our guest Dr. Barbara Paldus , founder and CEO of Codex Labs and Decode.Me. Dr. Paldus' clinical data shows that 50–60% of these skin issues are rooted in gut barrier dysfunction and microbiome imbalance, meaning topical treatments alone often aren't enough. Canadian-born of Czech parents and fluent in five languages with a Ph.D. from Stanford University (U.S.), Dr. Barbara Paldus holds over 50 US patents and is a serial entrepreneur, having started companies like Picarro, involved with greenhouse gas detection for climate change and Finesse Solutions, developing biotechnology equipment for vaccines or biologics. Codex Labs was conceived with dermatologists, naturopaths, and ethnobotanists to deliver affordable, clinically proven skin-gut-brain solutions that support the microbiomes and deliver healthy skin from the inside out, without sacrificing sustainability. This episode challenges the conventional skincare model and offers a science-backed, integrated approach to healing skin from the inside out. Learning Points: The Skin Is a Signal, Not the Root Cause Gut Barrier and Microbiome Health Drive Up to 50–60% of Skin Inflammation Lasting Skin Improvement Requires an Integrated, Systems-Based Approach Social Media: https://www.instagram.com/codexlabs https://www.facebook.com/search/top?q=codex%20labs Websites: www.codexlabscorp.com www.decode-me.com

Foundations of Amateur Radio How do you make a hole? That's a pretty straightforward kind of question, and by the time this sentence is finished, there's going to be at least as many answers as people who considered it. I didn't supply any parameters to this hole, so answers could include shovels, collapsing space, fire, a drill, or any number of other interesting approaches. If I narrowed it down to, say, a hole in wood, there'd still be plenty of options. Specifying the type of wood, the diameter and other parameters would further narrow down the selection of methods. What if I asked you: "How do you decode FM?" You might wonder if there's more than one way and I can assure you, just like with making a hole, there's plenty of ways to go about achieving this, even if I limit this to software implementations only. I must confess, when I recently set out to test my Soapy SDR library notions using a GNU Radio flowgraph to listen to FM radio, I searched the documentation, found a beginners tutorial and used the information there to make my first proof of concept FM receiver. I put it on GitHub and went about my business. After finally managing to hear the decode effort and being less than impressed, I started trying to understand the tutorial flowgraph. When I started looking at what would be needed to decode stereo FM broadcast radio, I discovered that there were several tutorials, examples and videos with slightly, or significantly different solutions to the problem. That's on top of the over a dozen standard FM related blocks supplied within GNU Radio. I then set about trying to discover the canonical implementation of an FM receiver and came up short. Instead I discovered even more implementations of FM receivers, each subtly different. You should know that there's a difference between how your local hit radio station does FM and how an amateur radio repeater does FM, let alone the local CB radio channels, satellite telemetry, wireless microphones or even hearing aids, so within the implementation of an FM receiver, there's additional complexity, which explains to some extent the variety of FM related blocks within GNU Radio. I think ultimately it's safe to say that there's an unlimited supply of implementations of an FM receiver within GNU Radio. It led me to ask, what is the .. for want of a better word .. "right" way and what does that actually mean? In GNU Radio, you string together blocks that process a signal. If you're familiar with flowcharts, the process is very similar. Unlike flowcharts on a piece of paper, in GNU Radio, or should I say, GNU Radio Companion, the tool you use to actually design flowgraphs, the little blocks represent underlying software and their connections represent how data flows between these bits of software. In other words, each block represents a series of programming instructions that process data and pass it on. It means that the more blocks you have in your flowgraph, the more instructions are running to process data. The more instructions, the more computing resources required. This is significant because in a complex system like this, we're likely to be doing more than one thing at a time, so preserving resources is important, if only to ensure that there's time available to process the next sample. As a result, there's a difference between implementing an FM receiver with two blocks, or with ten blocks. You might conclude that two blocks is more efficient, but that might not be true. For example, two blocks processing 2,000 samples per second each, are processing 4,000 samples per second in total. A block that converts the 2,000 samples into 200 samples, followed by nine blocks processing 200 samples per second each, is processing 3,800 samples in total. All things being equal, the ten blocks together are handling less data per second, so overall it's potentially using less resources. I say potentially, because it might be that one of those blocks is using a massive calculation, consuming more resources than all the other blocks put together, ultimately, each block is software, so whatever it's doing is using resources. So. How would you go about choosing between two implementations or algorithms, which was the "better" one and how is "better" defined? My first pass at this, is to use standard testing files and using the algorithms under consideration to process them. Run the tests multiple times, keep a record of how long they take and then attempt to measure how much the original input signal differs from the processed output signal. At the moment I have no idea how you might compare signals, other than to invert one and combine them to see if they cancel each other out, which means they're the same, or not, which means that they're different. For my sins, in trying to think of a way to do this I realised that the way I implement this radio contraption needs to be able to deal with test files and potentially multiple different implementations of a decoder. It also means that I have some more thinking to do. Ideally, there needs to be a concept of meta information, like the radio source, the tuned frequency, the bandwidth, gain, and likely more so I can set the parameters once and re-use these across whatever else is part of the flowgraph. It should be possible to use a test file just as simply as a Soapy SDR compatible radio. It should also be possible to hear the audio, or save it to a file, or decode an embedded signal, or all at the same time. In other words, it needs to be flexible. Luckily, GNU Radio is really a collection of libraries built precisely for this task. I'd love to hear your thoughts on the matter. I'm Onno VK6FLAB

Gilbert Doctorow : The Trump–Putin Call Everyone Is Trying to DecodeSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This is a special edition of the Brainz Podcast with host Remington SteeleIn this second episode of the Brainz Magazine podcast series, Remington Steele returns as guest host alongside Tina from the Tell 'Em Tina Podcast to continue the conversation on seeing yourself through your breath as we Decode the Breath's Language. Together, they explore powerful passages from Remington's book Breathe With Me, guiding listeners through how the breath reflects our emotions, stress, and inner awareness. Through discussion and a brief interactive exercise, listeners are invited to begin recognizing what their own breathing patterns may be communicating. This episode offers a practical introduction to understanding the emotional language of the breath and how greater awareness can lead to deeper clarity, regulation, and self-understanding. Listen and enjoy!Do you like the content? Don't forget to subscribe to the Brainz Podcast. Hosted on Acast. See acast.com/privacy for more information.

LISTEN and SUBSCRIBE on:Apple Podcasts: https://podcasts.apple.com/us/podcast/watchdog-on-wall-street-with-chris-markowski/id570687608 Spotify: https://open.spotify.com/show/2PtgPvJvqc2gkpGIkNMR5i WATCH and SUBSCRIBE on:https://www.youtube.com/@WatchdogOnWallstreet/featured  It's chaos out there. Between war headlines, deleted government tweets, shifting military goals, and political messaging, trying to follow the news cycle right now is almost impossible. One statement sends oil prices crashing. A correction sends them soaring again. And markets are moving faster than anyone can fact-check.In this episode, we break down:• How a single government tweet about escorting ships through the Strait of Hormuz briefly sent oil prices crashing• Why the tweet was later deleted — and how misinformation moves markets instantly• The constantly shifting goals behind the Iran conflict• Why talk of regime change, nuclear destruction, and deterrence keeps evolving• How the military-industrial complex and political messaging shape the narrative• Why the Strait of Hormuz remains the most critical chokepoint in global energy markets• And how Iran could attempt to drive oil prices toward $200 a barrel

In this episode of China Decode, Alice Han and James Kynge break down how the Iran war is driving oil prices above $100 a barrel, and what that means for China's energy security. They dive into China's dependence on the Strait of Hormuz, explore the country's cautious 2026 growth targets, and chat with Andy Browne, China Columnist at Semafor, about how all of this is reshaping China-U.S. relations. Check out Andy's newsletter at semafor.com/newsletters/china. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Join Kyle, Nader, Vibhu, and swyx live at NVIDIA GTC next week!Now that AIE Europe tix are ~sold out, our attention turns to Miami and World's Fair!The definitive AI Accelerator chip company has more than 10xed this AI Summer:And is now a $4.4 trillion megacorp… that is somehow still moving like a startup. We are blessed to have a unique relationship with our first ever NVIDIA guests: Kyle Kranen who gave a great inference keynote at the first World's Fair and is one of the leading architects of NVIDIA Dynamo (a Datacenter scale inference framework supporting SGLang, TRT-LLM, vLLM), and Nader Khalil, a friend of swyx from our days in Celo in The Arena, who has been drawing developers at GTC since before they were even a glimmer in the eye of NVIDIA:Nader discusses how NVIDIA Brev has drastically reduced the barriers to entry for developers to get a top of the line GPU up and running, and Kyle explains NVIDIA Dynamo as a data center scale inference engine that optimizes serving by scaling out, leveraging techniques like prefill/decode disaggregation, scheduling, and Kubernetes-based orchestration, framed around cost, latency, and quality tradeoffs. We also dive into Jensen's “SOL” (Speed of Light) first-principles urgency concept, long-context limits and model/hardware co-design, internal model APIs (https://build.nvidia.com), and upcoming Dynamo and agent sessions at GTC.Full Video pod on YouTubeTimestamps00:00 Agent Security Basics00:39 Podcast Welcome and Guests07:19 Acquisition and DevEx Shift13:48 SOL Culture and Dynamo Setup27:38 Why Scale Out Wins29:02 Scale Up Limits Explained30:24 From Laptop to Multi Node33:07 Cost Quality Latency Tradeoffs38:42 Disaggregation Prefill vs Decode41:05 Kubernetes Scaling with Grove43:20 Context Length and Co Design57:34 Security Meets Agents58:01 Agent Permissions Model59:10 Build Nvidia Inference Gateway01:01:52 Hackathons And Autonomy Dreams01:10:26 Local GPUs And Scaling Inference01:15:31 Long Running Agents And SF ReflectionsTranscriptAgent Security BasicsNader: Agents can do three things. They can access your files, they can access the internet, and then now they can write custom code and execute it. You literally only let an agent do two of those three things. If you can access your files and you can write custom code, you don't want internet access because that's one to see full vulnerability, right?If you have access to internet and your file system, you should know the full scope of what that agent's capable of doing. Otherwise, now we can get injected or something that can happen. And so that's a lot of what we've been thinking about is like, you know, how do we both enable this because it's clearly the future.But then also, you know, what, what are these enforcement points that we can start to like protect?swyx: All right.Podcast Welcome and Guestsswyx: Welcome to the Lean Space podcast in the Chromo studio. Welcome to all the guests here. Uh, we are back with our guest host Viu. Welcome. Good to have you back. And our friends, uh, Netter and Kyle from Nvidia. Welcome.Kyle: Yeah, thanks for having us.swyx: Yeah, thank you. Actually, I don't even know your titles.Uh, I know you're like architect something of Dynamo.Kyle: Yeah. I, I'm one of the engineering leaders [00:01:00] and a architects of Dynamo.swyx: And you're director of something and developers, developer tech.Nader: Yeah.swyx: You're the developers, developers, developers guy at nvidia,Nader: open source agent marketing, brev,swyx: and likeNader: Devrel tools and stuff.swyx: Yeah. BeenNader: the focus.swyx: And we're, we're kind of recording this ahead of Nvidia, GTC, which is coming to town, uh, again, uh, or taking over town, uh, which, uh, which we'll all be at. Um, and we'll talk a little bit about your sessions and stuff. Yeah.Nader: We're super excited for it.GTC Booth Stunt Storiesswyx: One of my favorite memories for Nader, like you always do like marketing stunts and like while you were at Rev, you like had this surfboard that you like, went down to GTC with and like, NA Nvidia apparently, like did so much that they bought you.Like what, what was that like? What was that?Nader: Yeah. Yeah, we, we, um. Our logo was a chaka. We, we, uh, we were always just kind of like trying to keep true to who we were. I think, you know, some stuff, startups, you're like trying to pretend that you're a bigger, more mature company than you are. And it was actually Evan Conrad from SF Compute who was just like, you guys are like previousswyx: guest.Yeah.Nader: Amazing. Oh, really? Amazing. Yeah. He was just like, guys, you're two dudes in the room. Why are you [00:02:00] pretending that you're not? Uh, and so then we were like, okay, let's make the logo a shaka. We brought surfboards to our booth to GTC and the energy was great. Yeah. Some palm trees too. They,Kyle: they actually poked out over like the, the walls so you could, you could see the bread booth.Oh, that's so funny. AndNader: no one else,Kyle: just from very far away.Nader: Oh, so you remember it backKyle: then? Yeah I remember it pre-acquisition. I was like, oh, those guys look cool,Nader: dude. That makes sense. ‘cause uh, we, so we signed up really last minute, and so we had the last booth. It was all the way in the corner. And so I was, I was worried that no one was gonna come.So that's why we had like the palm trees. We really came in with the surfboards. We even had one of our investors bring her dog and then she was just like walking the dog around to try to like, bring energy towards our booth. Yeah.swyx: Steph.Kyle: Yeah. Yeah, she's the best,swyx: you know, as a conference organizer, I love that.Right? Like, it's like everyone who sponsors a conference comes, does their booth. They're like, we are changing the future of ai or something, some generic b******t and like, no, like actually try to stand out, make it fun, right? And people still remember it after three years.Nader: Yeah. Yeah. You know what's so funny?I'll, I'll send, I'll give you this clip if you wanna, if you wanna add it [00:03:00] in, but, uh, my wife was at the time fiance, she was in medical school and she came to help us. ‘cause it was like a big moment for us. And so we, we bought this cricket, it's like a vinyl, like a vinyl, uh, printer. ‘cause like, how else are we gonna label the surfboard?So, we got a surfboard, luckily was able to purchase that on the company card. We got a cricket and it was just like fine tuning for enterprises or something like that, that we put on the. On the surfboard and it's 1:00 AM the day before we go to GTC. She's helping me put these like vinyl stickers on.And she goes, you son of, she's like, if you pull this off, you son of a b***h. And so, uh, right. Pretty much after the acquisition, I stitched that with the mag music acquisition. I sent it to our family group chat. Ohswyx: Yeah. No, well, she, she made a good choice there. Was that like basically the origin story for Launchable is that we, it was, and maybe we should explain what Brev is andNader: Yeah.Yeah. Uh, I mean, brev is just, it's a developer tool that makes it really easy to get a GPU. So we connect a bunch of different GPU sources. So the basics of it is like, how quickly can we SSH you into a G, into a GPU and whenever we would talk to users, they wanted A GPU. They wanted an A 100. And if you go to like any cloud [00:04:00] provisioning page, usually it's like three pages of forms or in the forms somewhere there's a dropdown.And in the dropdown there's some weird code that you know to translate to an A 100. And I remember just thinking like. Every time someone says they want an A 100, like the piece of text that they're telling me that they want is like, stuffed away in the corner. Yeah. And so we were like, what if the biggest piece of text was what the user's asking for?And so when you go to Brev, it's just big GPU chips with the type that you want withswyx: beautiful animations that you worked on pre, like pre you can, like, now you can just prompt it. But back in the day. Yeah. Yeah. Those were handcraft, handcrafted artisanal code.Nader: Yeah. I was actually really proud of that because, uh, it was an, i I made it in Figma.Yeah. And then I found, I was like really struggling to figure out how to turn it from like Figma to react. So what it actually is, is just an SVG and I, I have all the styles and so when you change the chip, whether it's like active or not it changes the SVG code and that somehow like renders like, looks like it's animating, but it, we just had the transition slow, but it's just like the, a JavaScript function to change the like underlying SVG.Yeah. And that was how I ended up like figuring out how to move it from from Figma. But yeah, that's Art Artisan. [00:05:00]Kyle: Speaking of marketing stunts though, he actually used those SVGs. Or kind of use those SVGs to make these cards.Nader: Oh yeah. LikeKyle: a GPU gift card Yes. That he handed out everywhere. That was actually my first impression of thatNader: one.Yeah,swyx: yeah, yeah.Nader: Yeah.swyx: I think I still have one of them.Nader: They look great.Kyle: Yeah.Nader: I have a ton of them still actually in our garage, which just, they don't have labels. We should honestly like bring, bring them back. But, um, I found this old printing press here, actually just around the corner on Ven ness. And it's a third generation San Francisco shop.And so I come in an excited startup founder trying to like, and they just have this crazy old machinery and I'm in awe. ‘cause the the whole building is so physical. Like you're seeing these machines, they have like pedals to like move these saws and whatever. I don't know what this machinery is, but I saw all three generations.Like there's like the grandpa, the father and the son, and the son was like, around my age. Well,swyx: it's like a holy, holy trinity.Nader: It's funny because we, so I just took the same SVG and we just like printed it and it's foil printing, so they make a a, a mold. That's like an inverse of like the A 100 and then they put the foil on it [00:06:00] and then they press it into the paper.And I remember once we got them, he was like, Hey, don't forget about us. You know, I guess like early Apple and Cisco's first business cards were all made there. And so he was like, yeah, we, we get like the startup businesses but then as they mature, they kind of go somewhere else. And so I actually, I think we were talking with marketing about like using them for some, we should go back and make some cards.swyx: Yeah, yeah, yeah. You know, I remember, you know, as a very, very small breadth investor, I was like, why are we spending time like, doing these like stunts for GPUs? Like, you know, I think like as a, you know, typical like cloud hard hardware person, you go into an AWS you pick like T five X xl, whatever, and it's just like from a list and you look at the specs like, why animate this GP?And, and I, I do think like it just shows the level of care that goes throughout birth and Yeah. And now, and also the, and,Nader: and Nvidia. I think that's what the, the thing that struck me most when we first came in was like the amount of passion that everyone has. Like, I think, um, you know, you talk to, you talk to Kyle, you talk to, like, every VP that I've met at Nvidia goes so close to the metal.Like, I remember it was almost a year ago, and like my VP asked me, he's like, Hey, [00:07:00] what's cursor? And like, are you using it? And if so, why? Surprised at this, and he downloaded Cursor and he was asking me to help him like, use it. And I thought that was, uh, or like, just show him what he, you know, why we were using it.And so, the amount of care that I think everyone has and the passion, appreciate, passion and appreciation for the moment. Right. This is a very unique time. So it's really cool to see everyone really like, uh, appreciate that.swyx: Yeah.Acquisition and DevEx Shiftswyx: One thing I wanted to do before we move over to sort of like research topics and, uh, the, the stuff that Kyle's working on is just tell the story of the acquisition, right?Like, not many people have been, been through an acquisition with Nvidia. What's it like? Uh, what, yeah, just anything you'd like to say.Nader: It's a crazy experience. I think, uh, you know, we were the thing that was the most exciting for us was. Our goal was just to make it easier for developers.We wanted to find access to GPUs, make it easier to do that. And then all, oh, actually your question about launchable. So launchable was just make one click exper, like one click deploys for any software on top of the GPU. Mm-hmm. And so what we really liked about Nvidia was that it felt like we just got a lot more resources to do all of that.I think, uh, you [00:08:00] know, NVIDIA's goal is to make things as easy for developers as possible. So there was a really nice like synergy there. I think that, you know, when it comes to like an acquisition, I think the amount that the soul of the products align, I think is gonna be. Is going speak to the success of the acquisition.Yeah. And so it in many ways feels like we're home. This is a really great outcome for us. Like we you know, I love brev.nvidia.com. Like you should, you should use it's, it's theKyle: front page for GPUs.Nader: Yeah. Yeah. If you want GP views,Kyle: you go there, getswyx: it there, and it's like internally is growing very quickly.I, I don't remember You said some stats there.Nader: Yeah, yeah, yeah. It's, uh, I, I wish I had the exact numbers, but like internally, externally, it's been growing really quickly. We've been working with a bunch of partners with a bunch of different customers and ISVs, if you have a solution that you want someone that runs on the GPU and you want people to use it quickly, we can bundle it up, uh, in a launchable and make it a one click run.If you're doing things and you want just like a sandbox or something to run on, right. Like open claw. Huge moment. Super exciting. Our, uh, and we'll talk into it more, but. You know, internally, people wanna run this, and you, we know we have to be really careful from the security implications. Do we let this run on the corporate network?Security's guidance was, Hey, [00:09:00] run this on breath, it's in, you know, it's, it's, it's a vm, it's sitting in the cloud, it's off the corporate network. It's isolated. And so that's been our stance internally and externally about how to even run something like open call while we figure out how to run these things securely.But yeah,swyx: I think there's also like, you almost like we're the right team at the right time when Nvidia is starting to invest a lot more in developer experience or whatever you call it. Yeah. Uh, UX or I don't know what you call it, like software. Like obviously NVIDIA is always invested in software, but like, there's like, this is like a different audience.Yeah. It's aNader: widerKyle: developer base.swyx: Yeah. Right.Nader: Yeah. Yeah. You know, it's funny, it's like, it's not, uh,swyx: so like, what, what is it called internally? What, what is this that people should be aware that is going on there?Nader: Uh, what, like developer experienceswyx: or, yeah, yeah. Is it's called just developer experience or is there like a broader strategy hereNader: in Nvidia?Um, Nvidia always wants to make a good developer experience. The thing is and a lot of the technology is just really complicated. Like, it's not, it's uh, you know, I think, um. The thing that's been really growing or the AI's growing is having a huge moment, not [00:10:00] because like, let's say data scientists in 2018, were quiet then and are much louder now.The pie is com, right? There's a whole bunch of new audiences. My mom's wondering what she's doing. My sister's learned, like taught herself how to code. Like the, um, you know, I, I actually think just generally AI's a big equalizer and you're seeing a more like technologically literate society, I guess.Like everyone's, everyone's learning how to code. Uh, there isn't really an excuse for that. And so building a good UX means that you really understand who your end user is. And when your end user becomes such a wide, uh, variety of people, then you have to almost like reinvent the practice, right? Yeah. You haveKyle: to, and actually build more developer ux, right?Because the, there are tiers of developer base that were added. You know, the, the hackers that are building on top of open claw, right? For example, have never used gpu. They don't know what kuda is. They, they, they just want to run something.Nader: Yeah.Kyle: You need new UX that is not just. Hey, you know, how do you program something in Cuda and run it?And then, and then we built, you know, like when Deep Learning was getting big, we built, we built Torch and, and, but so recently the amount of like [00:11:00] layers that are added to that developer stack has just exploded because AI has become ubiquitous. Everyone's using it in different ways. Yeah. It'sNader: moving fast in every direction.Vertical, horizontal.Vibhu: Yeah. You guys, you even take it down to hardware, like the DGX Spark, you know, it's, it's basically the same system as just throwing it up on big GPU cluster.Nader: Yeah, yeah, yeah. It's amazing. Blackwell.swyx: Yeah. Uh, we saw the preview at the last year's GTC and that was one of the better performing, uh, videos so far, and video coverage so far.Awesome. This will beat it. Um,Nader: that wasswyx: actually, we have fingersNader: crossed. Yeah.DGX Spark and Remote AccessNader: Even when Grace Blackwell or when, um, uh, DGX Spark was first coming out getting to be involved in that from the beginning of the developer experience. And it just comes back to what youswyx: were involved.Nader: Yeah. St. St.swyx: Mars.Nader: Yeah. Yeah. I mean from, it was just like, I, I got an email, we just got thrown into the loop and suddenly yeah, I, it was actually really funny ‘cause I'm still pretty fresh from the acquisition and I'm, I'm getting an email from a bunch of the engineering VPs about like, the new hardware, GPU chip, like we're, or not chip, but just GPU system that we're putting out.And I'm like, okay, cool. Matters. Now involved with this for the ux, I'm like. What am I gonna do [00:12:00] here? So, I remember the first meeting, I was just like kind of quiet as I was hearing engineering VPs talk about what this box could be, what it could do, how we should use it. And I remember, uh, one of the first ideas that people were idea was like, oh, the first thing that it was like, I think a quote was like, the first thing someone's gonna wanna do with this is get two of them and run a Kubernetes cluster on top of them.And I was like, oh, I think I know why I'm here. I was like, the first thing we're doing is easy. SSH into the machine. And then, and you know, just kind of like scoping it down of like, once you can do that every, you, like the person who wants to run a Kubernetes cluster onto Sparks has a higher propensity for pain, then, then you know someone who buys it and wants to run open Claw right now, right?If you can make sure that that's as effortless as possible, then the rest becomes easy. So there's a tool called Nvidia Sync. It just makes the SSH connection really simple. So, you know, if you think about it like. If you have a Mac, uh, or a PC or whatever, if you have a laptop and you buy this GPU and you want to use it, you should be able to use it like it's A-A-G-P-U in the cloud, right?Um, but there's all this friction of like, how do you actually get into that? That's part of [00:13:00] Revs value proposition is just, you know, there's a CLI that wraps SSH and makes it simple. And so our goal is just get you into that machine really easily. And one thing we just launched at CES, it's in, it's still in like early access.We're ironing out some kinks, but it should be ready by GTC. You can register your spark on Brev. And so now if youswyx: like remote managed yeah, local hardware. Single pane of glass. Yeah. Yeah. Because Brev can already manage other clouds anyway, right?Vibhu: Yeah, yeah. And you use the spark on Brev as well, right?Nader: Yeah. But yeah, exactly. So, so you, you, so you, you set it up at home you can run the command on it, and then it gets it's essentially it'll appear in your Brev account, and then you can take your laptop to a Starbucks or to a cafe, and you'll continue to use your, you can continue use your spark just like any other cloud node on Brev.Yeah. Yeah. And it's just like a pre-provisioned centerswyx: in yourNader: home. Yeah, exactly.swyx: Yeah. Yeah.Vibhu: Tiny little data center.Nader: Tiny little, the size ofVibhu: your phone.SOL Culture and Dynamo Setupswyx: One more thing before we move on to Kyle. Just have so many Jensen stories and I just love, love mining Jensen stories. Uh, my favorite so far is SOL. Uh, what is, yeah, what is S-O-L-S-O-LNader: is actually, i, I think [00:14:00] of all the lessons I've learned, that one's definitely my favorite.Kyle: It'll always stick with you.Nader: Yeah. Yeah. I, you know, in your startup, everything's existential, right? Like we've, we've run out of money. We were like, on the risk of, of losing payroll, we've had to contract our team because we l ran outta money. And so like, um, because of that you're really always forcing yourself to I to like understand the root cause of everything.If you get a date, if you get a timeline, you know exactly why that date or timeline is there. You're, you're pushing every boundary and like, you're not just say, you're not just accepting like a, a no. Just because. And so as you start to introduce more layers, as you start to become a much larger organization, SOL is is essentially like what is the physics, right?The speed of light moves at a certain speed. So if flight's moving some slower, then you know something's in the way. So before trying to like layer reality back in of like, why can't this be delivered at some date? Let's just understand the physics. What is the theoretical limit to like, uh, how fast this can go?And then start to tell me why. ‘cause otherwise people will start telling you why something can't be done. But actually I think any great leader's goal is just to create urgency. Yeah. [00:15:00] There's an infiniteKyle: create compelling events, right?Nader: Yeah.Kyle: Yeah. So l is a term video is used to instigate a compelling event.You say this is done. How do we get there? What is the minimum? As much as necessary, as little as possible thing that it takes for us to get exactly here and. It helps you just break through a bunch of noise.swyx: Yeah.Kyle: Instantly.swyx: One thing I'm unclear about is, can only Jensen use the SOL card? Like, oh, no, no, no.Not everyone get the b******t out because obviously it's Jensen, but like, can someone else be like, no, likeKyle: frontline engineers use it.Nader: Yeah. Every, I think it's not so much about like, get the b******t out. It's like, it's like, give me the root understanding, right? Like, if you tell me something takes three weeks, it like, well, what's the first principles?Yeah, the first principles. It's like, what's the, what? Like why is it three weeks? What is the actual yeah. What's the actual limit of why this is gonna take three weeks? If you're gonna, if you, if let's say you wanted to buy a new computer and someone told you it's gonna be here in five days, what's the SOL?Well, like the SOL is like, I could walk into a Best Buy and pick it up for you. Right? So then anything that's like beyond that is, and is that practical? Is that how we're gonna, you know, let's say give everyone in the [00:16:00] company a laptop, like obviously not. So then like that's the SOL and then it's like, okay, well if we have to get more than 10, suddenly there might be some, right?And so now we can kind of piece the reality back.swyx: So, so this is the. Paul Graham do things that don't scale. Yeah. And this is also the, what people would now call behi agency. Yeah.Kyle: It's actually really interesting because there's a, there's a second hardware angle to SOL that like doesn't come up for all the org sol is used like culturally at aswyx: media for everything.I'm also mining for like, I think that can be annoying sometimes. And like someone keeps going IOO you and you're like, guys, like we have to be stable. We have to, we to f*****g plan. Yeah.Kyle: It's an interesting balance.Nader: Yeah. I encounter that with like, actually just with, with Alec, right? ‘cause we, we have a new conference so we need to launch, we have, we have goals of what we wanna launch by, uh, by the conference and like, yeah.At the end of the day, where isswyx: this GTC?Nader: Um, well this is like, so we, I mean we did it for CES, we did for GT CDC before that we're doing it for GTC San Jose. So I mean, like every, you know, we have a new moment. Um, and we want to launch something. Yeah. And we want to do so at SOL and that does mean that some, there's some level of prioritization that needs [00:17:00] to happen.And so it, it is difficult, right? I think, um, you have to be careful with what you're pushing. You know, stability is important and that should be factored into S-O-L-S-O-L isn't just like, build everything and let it break, you know, that, that's part of the conversation. So as you're laying, layering in all the details, one of them might be, Hey, we could build this, but then it's not gonna be stable for X, y, z reasons.And so that was like, one of our conversations for CES was, you know, hey, like we, we can get this into early access registering your spark with brev. But there are a lot of things that we need to do in order to feel really comfortable from a security perspective, right? There's a lot of networking involved before we deliver that to users.So it's like, okay. Let's get this to a point where we can at least let people experiment with it. We had it in a booth, we had it in Jensen's keynote, and then let's go iron out all the networking kinks. And that's not easy. And so, uh, that can come later. And so that was the way that we layered that back in.Yeah. ButKyle: It's not really about saying like, you don't have to do the, the maintenance or operational work. It's more about saying, you know, it's kind of like [00:18:00] highlights how progress is incremental, right? Like, what is the minimum thing that we can get to. And then there's SOL for like every component after that.But there's the SOL to get you, get you to the, the starting line. And that, that's usually how it's asked. Yeah. On the other side, you know, like SOL came out of like hardware at Nvidia. Right. So SOL is like literally if we ran the accelerator or the GPU with like at basically full speed with like no other constraints, like how FAST would be able to make a program go.swyx: Yeah. Yeah. Right.Kyle: Soswyx: in, in training that like, you know, then you work back to like some percentage of like MFU for example.Kyle: Yeah, that's a, that's a great example. So like, there's an, there's an S-O-L-M-F-U, and then there's like, you know, what's practically achievable.swyx: Cool. Should we move on to sort of, uh, Kyle's side?Uh, Kyle, you're coming more from the data science world. And, uh, I, I mean I always, whenever, whenever I meet someone who's done working in tabular stuff, graph neural networks, time series, these are basically when I go to new reps, I go to ICML, I walk the back halls. There's always like a small group of graph people.Yes. Absolute small group of tabular people. [00:19:00] And like, there's no one there. And like, it's very like, you know what I mean? Like, yeah, no, like it's, it's important interesting work if you care about solving the problems that they solve.Kyle: Yeah.swyx: But everyone else is just LMS all the time.Kyle: Yeah. I mean it's like, it's like the black hole, right?Has the event horizon reached this yet in nerves? Um,swyx: but like, you know, those are, those are transformers too. Yeah. And, and those are also like interesting things. Anyway, uh, I just wanted to spend a little bit of time on, on those, that background before we go into Dynamo, uh, proper.Kyle: Yeah, sure. I took a different path to Nvidia than that, or I joined six years ago, seven, if you count, when I was an intern.So I joined Nvidia, like right outta college. And the first thing I jumped into was not what I'd done in, during internship, which was like, you know, like some stuff for autonomous vehicles, like heavyweight object detection. I jumped into like, you know, something, I'm like, recommenders, this is popular. Andswyx: yeah, he did RexiKyle: as well.Yeah, Rexi. Yeah. I mean that, that was the taboo data at the time, right? You have tables of like, audience qualities and item qualities, and you're trying to figure out like which member of [00:20:00] the audience matches which item or, or more practically which item matches which member of the audience. And at the time, really it was like we were trying to enable.Uh, recommender, which had historically been like a little bit of a CP based workflow into something that like, ran really well in GPUs. And it's since been done. Like there are a bunch of libraries for Axis that run on GPUs. Uh, the common models like Deeplearning recommendation model, which came outta meta and the wide and deep model, which was used or was released by Google were very accelerated by GPUs using, you know, the fast HBM on the chips, especially to do, you know, vector lookups.But it was very interesting at the time and super, super relevant because like we were starting to get like. This explosion of feeds and things that required rec recommenders to just actively be on all the time. And sort of transitioned that a little bit towards graph neural networks when I discovered them because I was like, okay, you can actually use graphical neural networks to represent like, relationships between people, items, concepts, and that, that interested me.So I jumped into that at [00:21:00] Nvidia and, and got really involved for like two-ish years.swyx: Yeah. Uh, and something I learned from Brian Zaro Yeah. Is that you can just kind of choose your own path in Nvidia.Kyle: Oh my God. Yeah.swyx: Which is not a normal big Corp thing. Yeah. Like you, you have a lane, you stay in your lane.Nader: I think probably the reason why I enjoy being in a, a big company, the mission is the boss probably from a startup guy. Yeah. The missionswyx: is the boss.Nader: Yeah. Uh, it feels like a big game of pickup basketball. Like, you know, if you play one, if you wanna play basketball, you just go up to the court and you're like, Hey look, we're gonna play this game and we need three.Yeah. And you just like find your three. That's honestly for every new initiative that's what it feels like. Yeah.Vibhu: It also like shows, right? Like Nvidia. Just releasing state-of-the-art stuff in every domain. Yeah. Like, okay, you expect foundation models with Nemo tron voice just randomly parakeet.Call parakeet just comes out another one, uh, voice. TheKyle: video voice team has always been producing.Vibhu: Yeah. There's always just every other domain of paper that comes out, dataset that comes out. It's like, I mean, it also stems back to what Nvidia has to do, right? You have to make chips years before they're actually produced.Right? So you need to know, you need to really [00:22:00] focus. TheKyle: design process starts likeVibhu: exactlyKyle: three to five years before the chip gets to the market.Vibhu: Yeah. I, I'm curious more about what that's like, right? So like, you have specialist teams. Is it just like, you know, people find an interest, you go in, you go deep on whatever, and that kind of feeds back into, you know, okay, we, we expect predictions.Like the internals at Nvidia must be crazy. Right? You know? Yeah. Yeah. You know, you, you must. Not even without selling to people, you have your own predictions of where things are going. Yeah. And they're very based, very grounded. Right?Kyle: Yeah. It, it, it's really interesting. So there's like two things that I think that Amed does, which are quite interesting.Uh, one is like, we really index into passion. There's a big. Sort of organizational top sound push to like ensure that people are working on the things that they're passionate about. So if someone proposes something that's interesting, many times they can just email someone like way up the chain that they would find this relevant and say like, Hey, can I go work on this?Nader: It's actually like I worked at a, a big company for a couple years before, uh, starting on my startup journey and like, it felt very weird if you were to like email out of chain, if that makes [00:23:00] sense. Yeah. The emails at Nvidia are like mosh pitsswyx: shoot,Nader: and it's just like 60 people, just whatever. And like they're, there's this,swyx: they got messy like, reply all you,Nader: oh, it's in, it's insane.It's insane. They justKyle: help. You know, Maxim,Nader: the context. But, but that's actually like, I've actually, so this is a weird thing where I used to be like, why would we send emails? We have Slack. I am the entire, I'm the exact opposite. I feel so bad for anyone who's like messaging me on Slack ‘cause I'm so unresponsive.swyx: Your emailNader: Maxi, email Maxim. I'm email maxing Now email is a different, email is perfect because man, we can't work together. I'm email is great, right? Because important threads get bumped back up, right? Yeah, yeah. Um, and so Slack doesn't do that. So I just have like this casino going off on the right or on the left and like, I don't know which thread was from where or what, but like the threads get And then also just like the subject, so you can have like working threads.I think what's difficult is like when you're small, if you're just not 40,000 people I think Slack will work fine, but there's, I don't know what the inflection point is. There is gonna be a point where that becomes really messy and you'll actually prefer having email. ‘cause you can have working threads.You can cc more than nine people in a thread.Kyle: You can fork stuff.Nader: You can [00:24:00] fork stuff, which is super nice and just like y Yeah. And so, but that is part of where you can propose a plan. You can also just. Start, honestly, momentum's the only authority, right? So like, if you can just start, start to make a little bit of progress and show someone something, and then they can try it.That's, I think what's been, you know, I think the most effective way to push anything for forward. And that's both at Nvidia and I think just generally.Kyle: Yeah, there's, there's the other concept that like is explored a lot at Nvidia, which is this idea of a zero billion dollar business. Like market creation is a big thing at Nvidia.Like,swyx: oh, you want to go and start a zero billion dollar business?Kyle: Jensen says, we are completely happy investing in zero billion dollar markets. We don't care if this creates revenue. It's important for us to know about this market. We think it will be important in the future. It can be zero billion dollars for a while.I'm probably minging as words here for, but like, you know, like, I'll give an example. NVIDIA's been working on autonomous driving for a a long time,swyx: like an Nvidia car.Kyle: No, they, they'veVibhu: used the Mercedes, right? They're around the HQ and I think it finally just got licensed out. Now they're starting to be used quite a [00:25:00] bit.For 10 years you've been seeing Mercedes with Nvidia logos driving.Kyle: If you're in like the South San Santa Clara, it's, it's actually from South. Yeah. So, um. Zero billion dollar markets are, are a thing like, you know, Jensen,swyx: I mean, okay, look, cars are not a zero billion dollar market. But yeah, that's a bad example.Nader: I think, I think he's, he's messaging, uh, zero today, but, or even like internally, right? Like, like it's like, uh, an org doesn't have to ruthlessly find revenue very quickly to justify their existence. Right. Like a lot of the important research, a lot of the important technology being developed that, that's kind ofKyle: where research, research is very ide ideologically free at Nvidia.Yeah. Like they can pursue things that they wereswyx: Were you research officially?Kyle: I was never in research. Officially. I was always in engineering. Yeah. We in, I'm in an org called Deep Warning Algorithms, which is basically just how do we make things that are relevant to deep warning go fast.swyx: That sounds freaking cool.Vibhu: And I think a lot of that is underappreciated, right? Like time series. This week Google put out time. FF paper. Yeah. A new time series, paper res. Uh, Symantec, ID [00:26:00] started applying Transformers LMS to Yes. Rec system. Yes. And when you think the scale of companies deploying these right. Amazon recommendations, Google web search, it's like, it's huge scale andKyle: Yeah.Vibhu: You want fast?Kyle: Yeah. Yeah. Yeah. Actually it's, it, I, there's a fun moment that brought me like full circle. Like, uh, Amazon Ads recently gave a talk where they talked about using Dynamo for generative recommendation, which was like super, like weirdly cathartic for me. I'm like, oh my God. I've, I've supplanted what I was working on.Like, I, you're using LMS now to do what I was doing five years ago.swyx: Yeah. Amazing. And let's go right into Dynamo. Uh, maybe introduce Yeah, sure. To the top down and Yeah.Kyle: I think at this point a lot of people are familiar with the term of inference. Like funnily enough, like I went from, you know, inference being like a really niche topic to being something that's like discussed on like normal people's Twitter feeds.It's,Nader: it's on billboardsKyle: here now. Yeah. Very, very strange. Driving, driving, seeing just an inference ad on 1 0 1 inference at scale is becoming a lot more important. Uh, we have these moments like, you know, open claw where you have these [00:27:00] agents that take lots and lots of tokens, but produce, incredible results.There are many different aspects of test time scaling so that, you know, you can use more inference to generate a better result than if you were to use like a short amount of inference. There's reasoning, there's quiring, there's, adding agency to the model, allowing it to call tools and use skills.Dyno sort came about at Nvidia. Because myself and a couple others were, were sort of talking about the, these concepts that like, you know, you have inference engines like VLMS, shelan, tenor, TLM and they have like one single copy. They, they, they sort of think about like things as like one single copy, like one replica, right?Why Scale Out WinsKyle: Like one version of the model. But when you're actually serving things at scale, you can't just scale up that replica because you end up with like performance problems. There's a scaling limit to scaling up replicas. So you actually have to scale out to use a, maybe some Kubernetes type terminology.We kind of realized that there was like. A lot of potential optimization that we could do in scaling out and building systems for data [00:28:00] center scale inference. So Dynamo is this data center scale inference engine that sits on top of the frameworks like VLM Shilling and 10 T lm and just makes things go faster because you can leverage the economy of scale.The fact that you have KV cash, which we can define a little bit later, uh, in all these machines that is like unique and you wanna figure out like the ways to maximize your cash hits or you want to employ new techniques in inference like disaggregation, which Dynamo had introduced to the world in, in, in March, not introduced, it was a academic talk, but beforehand.But we are, you know, one of the first frameworks to start, supporting it. And we wanna like, sort of combine all these techniques into sort of a modular framework that allows you to. Accelerate your inference at scale.Nader: By the way, Kyle and I became friends on my first date, Nvidia, and I always loved, ‘cause like he always teaches meswyx: new things.Yeah. By the way, this is why I wanted to put two of you together. I was like, yeah, this is, this is gonna beKyle: good. It's very, it's very different, you know, like we've, we, we've, we've talked to each other a bunch [00:29:00] actually, you asked like, why, why can't we scale up?Nader: Yeah.Scale Up Limits ExplainedNader: model, you said model replicas.Kyle: Yeah. So you, so scale up means assigning moreswyx: heavier?Kyle: Yeah, heavier. Like making things heavier. Yeah, adding more GPUs. Adding more CPUs. Scale out is just like having a barrier saying, I'm gonna duplicate my representation of the model or a representation of this microservice or something, and I'm gonna like, replicate it Many times.Handle, load. And the reason that you can't scale, scale up, uh, past some points is like, you know, there, there, there are sort of hardware bounds and algorithmic bounds on, on that type of scaling. So I'll give you a good example that's like very trivial. Let's say you're on an H 100. The Maxim ENV link domain for H 100, for most Ds H one hundreds is heus, right?So if you scaled up past that, you're gonna have to figure out ways to handle the fact that now for the GPUs to communicate, you have to do it over Infin band, which is still very fast, but is not as fast as ENV link.swyx: Is it like one order of magnitude, like hundreds or,Kyle: it's about an order of magnitude?Yeah. Okay. Um, soswyx: not terrible.Kyle: [00:30:00] Yeah. I, I need to, I need to remember the, the data sheet here, like, I think it's like about 500 gigabytes. Uh, a second unidirectional for ENV link, and about 50 gigabytes a second unidirectional for Infin Band. I, it, it depends on the, the generation.swyx: I just wanna set this up for people who are not familiar with these kinds of like layers and the trash speedVibhu: and all that.Of course.From Laptop to Multi NodeVibhu: Also, maybe even just going like a few steps back before that, like most people are very familiar with. You see a, you know, you can use on your laptop, whatever these steel viol, lm you can just run inference there. All, there's all, you can, youcan run it on thatVibhu: laptop. You can run on laptop.Then you get to, okay, uh, models got pretty big, right? JLM five, they doubled the size, so mm-hmm. Uh, what do you do when you have to go from, okay, I can get 128 gigs of memory. I can run it on a spark. Then you have to go multi GPU. Yeah. Okay. Multi GPU, there's some support there. Now, if I'm a company and I don't have like.I'm not hiring the best researchers for this. Right. But I need to go [00:31:00] multi-node, right? I have a lot of servers. Okay, now there's efficiency problems, right? You can have multiple eight H 100 nodes, but, you know, is that as a, like, how do you do that efficiently?Kyle: Yeah. How do you like represent them? How do you choose how to represent the model?Yeah, exactly right. That's a, that's like a hard question. Everyone asks, how do you size oh, I wanna run GLM five, which just came out new model. There have been like four of them in the past week, by the way, like a bunch of new models.swyx: You know why? Right? Deep seek.Kyle: No comment. Oh. Yeah, but Ggl, LM five, right?We, we have this, new model. It's, it's like a large size, and you have to figure out how to both scale up and scale out, right? Because you have to find the right representation that you care about. Everyone does this differently. Let's be very clear. Everyone figures this out in their own path.Nader: I feel like a lot of AI or ML even is like, is like this. I think people think, you know, I, I was, there was some tweet a few months ago that was like, why hasn't fine tuning as a service taken off? You know, that might be me. It might have been you. Yeah. But people want it to be such an easy recipe to follow.But even like if you look at an ML model and specificKyle: to you Yeah,Nader: yeah.Kyle: And the [00:32:00] model,Nader: the situation, and there's just so much tinkering, right? Like when you see a model that has however many experts in the ME model, it's like, why that many experts? I don't, they, you know, they tried a bunch of things and that one seemed to do better.I think when it comes to how you're serving inference, you know, you have a bunch of decisions to make and there you can always argue that you can take something and make it more optimal. But I think it's this internal calibration and appetite for continued calibration.Vibhu: Yeah. And that doesn't mean like, you know, people aren't taking a shot at this, like tinker from thinking machines, you know?Yeah. RL as a service. Yeah, totally. It's, it also gets even harder when you try to do big model training, right? We're not the best at training Moes, uh, when they're pre-trained. Like we saw this with LAMA three, right? They're trained in such a sparse way that meta knows there's gonna be a bunch of inference done on these, right?They'll open source it, but it's very trained for what meta infrastructure wants, right? They wanna, they wanna inference it a lot. Now the question to basically think about is, okay, say you wanna serve a chat application, a coding copilot, right? You're doing a layer of rl, you're serving a model for X amount of people.Is it a chat model, a coding model? Dynamo, you know, back to that,Kyle: it's [00:33:00] like, yeah, sorry. So you we, we sort of like jumped off of, you know, jumped, uh, on that topic. Everyone has like, their own, own journey.Cost Quality Latency TradeoffsKyle: And I, I like to think of it as defined by like, what is the model you need? What is the accuracy you need?Actually I talked to NA about this earlier. There's three axes you care about. What is the quality that you're able to produce? So like, are you accurate enough or can you complete the task with enough, performance, high enough performance. Yeah, yeah. Uh, there's cost. Can you serve the model or serve your workflow?Because it's not just the model anymore, it's the workflow. It's the multi turn with an agent cheaply enough. And then can you serve it fast enough? And we're seeing all three of these, like, play out, like we saw, we saw new models from OpenAI that you know, are faster. You have like these new fast versions of models.You can change the amount of thinking to change the amount of quality, right? Produce more tokens, but at a higher cost in a, in a higher latency. And really like when you start this journey of like trying to figure out how you wanna host a model, you, you, you think about three things. What is the model I need to serve?How many times do I need to call it? What is the input sequence link was [00:34:00] the, what does the workflow look like on top of it? What is the SLA, what is the latency SLA that I need to achieve? Because there's usually some, this is usually like a constant, you, you know, the SLA that you need to hit and then like you try and find the lowest cost version that hits all of these constraints.Usually, you know, you, you start with those things and you say you, you kind of do like a bit of experimentation across some common configurations. You change the tensor parallel size, which is a form of parallelismVibhu: I take, it goes even deeper first. Gotta think what model.Kyle: Yes, course,ofKyle: course. It's like, it's like a multi-step design process because as you said, you can, you can choose a smaller model and then do more test time scaling and it'll equate the quality of a larger model because you're doing the test time scaling or you're adding a harness or something.So yes, it, it goes way deeper than that. But from the performance perspective, like once you get to the model you need, you need to host, you look at that and you say, Hey. I have this model, I need to serve it at the speed. What is the right configuration for that?Nader: You guys see the recent, uh, there was a paper I just saw like a few days ago that, uh, if you run [00:35:00] the same prompt twice, you're getting like double Just try itagain.Nader: Yeah, exactly.Vibhu: And you get a lot. Yeah. But the, the key thing there is you give the context of the failed try, right? Yeah. So it takes a shot. And this has been like, you know, basic guidance for quite a while. Just try again. ‘cause you know, trying, just try again. Did you try again? All adviceNader: in life.Vibhu: Just, it's a paper from Google, if I'm not mistaken, right?Yeah,Vibhu: yeah. I think it, it's like a seven bas little short paper. Yeah. Yeah. The title's very cute. And it's just like, yeah, just try again. Give it ask context,Kyle: multi-shot. You just like, say like, hey, like, you know, like take, take a little bit more, take a little bit more information, try and fail. Fail.Vibhu: And that basic concept has gone pretty deep.There's like, um, self distillation, rl where you, you do self distillation, you do rl and you have past failure and you know, that gives some signal so people take, try it again. Not strong enough.swyx: Uh, for, for listeners, uh, who listen to here, uh, vivo actually, and I, and we run a second YouTube channel for our paper club where, oh, that's awesome.Vivo just covered this. Yeah. Awesome. Self desolation and all that's, that's why he, to speed [00:36:00] on it.Nader: I'll to check it out.swyx: Yeah. It, it's just a good practice, like everyone needs, like a paper club where like you just read papers together and the social pressure just kind of forces you to just,Nader: we, we,there'sNader: like a big inference.Kyle: ReadingNader: group at a video. I feel so bad every time. I I, he put it on like, on our, he shared it.swyx: One, one ofNader: your guys,swyx: uh, is, is big in that, I forget es han Yeah, yeah,Kyle: es Han's on my team. Actually. Funny. There's a, there's a, there's a employee transfer between us. Han worked for Nater at Brev, and now he, he's on my team.He wasNader: our head of ai. And then, yeah, once we got in, andswyx: because I'm always looking for like, okay, can, can I start at another podcast that only does that thing? Yeah. And, uh, Esan was like, I was trying to like nudge Esan into like, is there something here? I mean, I don't think there's, there's new infant techniques every day.So it's like, it's likeKyle: you would, you would actually be surprised, um, the amount of blog posts you see. And ifswyx: there's a period where it was like, Medusa hydra, what Eagle, like, youKyle: know, now we have new forms of decode, uh, we have new forms of specula, of decoding or new,swyx: what,Kyle: what are youVibhu: excited? And it's exciting when you guys put out something like Tron.‘cause I remember the paper on this Tron three, [00:37:00] uh, the amount of like post train, the on tokens that the GPU rich can just train on. And it, it was a hybrid state space model, right? Yeah.Kyle: It's co-designed for the hardware.Vibhu: Yeah, go design for the hardware. And one of the things was always, you know, the state space models don't scale as well when you do a conversion or whatever the performance.And you guys are like, no, just keep draining. And Nitron shows a lot of that. Yeah.Nader: Also, something cool about Nitron it was released in layers, if you will, very similar to Dynamo. It's, it's, it's essentially it was released as you can, the pre-training, post-training data sets are released. Yeah. The recipes on how to do it are released.The model itself is released. It's full model. You just benefit from us turning on the GPUs. But there are companies like, uh, ServiceNow took the dataset and they trained their own model and we were super excited and like, you know, celebrated that work.ZoomVibhu: different. Zoom is, zoom is CGI, I think, uh, you know, also just to add like a lot of models don't put out based models and if there's that, why is fine tuning not taken off?You know, you can do your own training. Yeah,Kyle: sure.Vibhu: You guys put out based model, I think you put out everything.Nader: I believe I know [00:38:00]swyx: about base. BasicallyVibhu: without baseswyx: basic can be cancelable.Vibhu: Yeah. Base can be cancelable.swyx: Yeah.Vibhu: Safety training.swyx: Did we get a full picture of dymo? I, I don't know if we, what,Nader: what I'd love is you, you mentioned the three axes like break it down of like, you know, what's prefilled decode and like what are the optimizations that we can get with Dynamo?Kyle: Yeah. That, that's, that's, that's a great point. So to summarize on that three axis problem, right, there are three things that determine whether or not something can be done with inference, cost, quality, latency, right? Dynamo is supposed to be there to provide you like the runtime that allows you to pull levers to, you know, mix it up and move around the parade of frontier or the preto surface that determines is this actually possible with inference And AI todayNader: gives you the knobs.Kyle: Yeah, exactly. It gives you the knobs.Disaggregation Prefill vs DecodeKyle: Uh, and one thing that like we, we use a lot in contemporary inference and is, you know, starting to like pick up from, you know, in, in general knowledge is this co concept of disaggregation. So historically. Models would be hosted with a single inference engine. And that inference engine [00:39:00] would ping pong between two phases.There's prefill where you're reading the sequence generating KV cache, which is basically just a set of vectors that represent the sequence. And then using that KV cache to generate new tokens, which is called Decode. And some brilliant researchers across multiple different papers essentially made the realization that if you separate these two phases, you actually gain some benefits.Those benefits are basically a you don't have to worry about step synchronous scheduling. So the way that an inference engine works is you do one step and then you finish it, and then you schedule, you start scheduling the next step there. It's not like fully asynchronous. And the problem with that is you would have, uh, essentially pre-fill and decode are, are actually very different in terms of both their resource requirements and their sometimes their runtime.So you would have like prefill that would like block decode steps because you, you'd still be pre-filing and you couldn't schedule because you know the step has to end. So you remove that scheduling issue and then you also allow you, or you yourself, to like [00:40:00] split the work into two different ki types of pools.So pre-fill typically, and, and this changes as, as model architecture changes. Pre-fill is, right now, compute bound most of the time with the sequence is sufficiently long. It's compute bound. On the decode side because you're doing a full Passover, all the weights and the entire sequence, every time you do a decode step and you're, you don't have the quadratic computation of KV cache, it's usually memory bound because you're retrieving a linear amount of memory and you're doing a linear amount of compute as opposed to prefill where you retrieve a linear amount of memory and then use a quadratic.You know,Nader: it's funny, someone exo Labs did a really cool demo where for the DGX Spark, which has a lot more compute, you can do the pre the compute hungry prefill on a DG X spark and then do the decode on a, on a Mac. Yeah. And soVibhu: that's faster.Nader: Yeah. Yeah.Kyle: So you could, you can do that. You can do machine strat stratification.Nader: Yeah.Kyle: And like with our future generation generations of hardware, we actually announced, like with Reuben, this [00:41:00] new accelerator that is prefilled specific. It's called Reuben, CPX. SoKubernetes Scaling with GroveNader: I have a question when you do the scale out. Yeah. Is scaling out easier with Dynamo? Because when you need a new node, you can dedicate it to either the Prefill or, uh, decode.Kyle: Yeah. So Dynamo actually has like a, a Kubernetes component in it called Grove that allows you to, to do this like crazy scaling specialization. It has like this hot, it's a representation that, I don't wanna go too deep into Kubernetes here, but there was a previous way that you would like launch multi-node work.Uh, it's called Leader Worker Set. It's in the Kubernetes standard, and Leader worker set is great. It served a lot of people super well for a long period of time. But one of the things that it's struggles with is representing a set of cases where you have a multi-node replica that has a pair, right?You know, prefill and decode, or it's not paired, but it has like a second stage that has a ratio that changes over time. And prefill and decode are like two different things as your workload changes, right? The amount of prefill you'll need to do may change. [00:42:00] The amount of decode that you, you'll need to do might change, right?Like, let's say you start getting like insanely long queries, right? That probably means that your prefill scales like harder because you're hitting these, this quadratic scaling growth.swyx: Yeah.And then for listeners, like prefill will be long input. Decode would be long output, for example, right?Kyle: Yeah. So like decode, decode scale. I mean, decode is funny because the amount of tokens that you produce scales with the output length, but the amount of work that you do per step scales with the amount of tokens in the context.swyx: Yes.Kyle: So both scales with the input and the output.swyx: That's true.Kyle: But on the pre-fold view code side, like if.Suddenly, like the amount of work you're doing on the decode side stays about the same or like scales a little bit, and then the prefilled side like jumps up a lot. You actually don't want that ratio to be the same. You want it to change over time. So Dynamo has a set of components that A, tell you how to scale.It tells you how many prefilled workers and decoded workers you, it thinks you should have, and also provides a scheduling API for Kubernetes that allows you to actually represent and affect this scheduling on, on, on your actual [00:43:00] hardware, on your compute infrastructure.Nader: Not gonna lie. I feel a little embarrassed for being proud of my SVG function earlier.swyx: No, itNader: wasreallyKyle: cute. I, Iswyx: likeNader: it's all,swyx: it's all engineering. It's all engineering. Um, that's where I'mKyle: technical.swyx: One thing I'm, I'm kind of just curious about with all with you see at a systems level, everything going on here. Mm-hmm. And we, you know, we're scaling it up in, in multi, in distributed systems.Context Length and Co Designswyx: Um, I think one thing that's like kind of, of the moment right now is people are asking, is there any SOL sort of upper bounds. In terms of like, let's call, just call it context length for one for of a better word, but you can break it down however you like.Nader: Yeah.swyx: I just think like, well, yeah, I mean, like clearly you can engage in hybrid architectures and throw in some state space models in there.All, all you want, but it looks, still looks very attention heavy.Kyle: Yes. Uh, yeah. Long context is attention heavy. I mean, we have these hybrid models, um,swyx: to take and most, most models like cap out at a million contexts and that's it. Yeah. Like for the last two years has been it.Kyle: Yeah. The model hardware context co-design thing that we're seeing these days is actually super [00:44:00] interesting.It's like my, my passion, like my secret side passion. We see models like Kimmy or G-P-T-O-S-S. I'm use these because I, I know specific things about these models. So Kimmy two comes out, right? And it's an interesting model. It's like, like a deep seek style architecture is MLA. It's basically deep seek, scaled like a little bit differently, um, and obviously trained differently as well.But they, they talked about, why they made the design choices for context. Kimmy has more experts, but fewer attention heads, and I believe a slightly smaller attention, uh, like dimension. But I need to remember, I need to check that. Uh, it doesn't matter. But they discussed this actually at length in a blog post on ji, which is like our pu which is like credit puswyx: Yeah.Kyle: Um, in, in China. Chinese red.swyx: Yeah.Kyle: It's, yeah. So it, it's, it's actually an incredible blog post. Uh, like all the mls people in, in, in that, I've seen that on GPU are like very brilliant, but they, they talk about like the creators of Kimi K two [00:45:00] actually like, talked about it on, on, on there in the blog post.And they say, we, we actually did an experiment, right? Attention scales with the number of heads, obviously. Like if you have 64 heads versus 32 heads, you do half the work of attention. You still scale quadratic, but you do half the work. And they made a, a very specific like. Sort of barter in their system, in their architecture, they basically said, Hey, what if we gave it more experts, so we're gonna use more memory capacity.But we keep the amount of activated experts the same. We increase the expert sparsity, so we have fewer experts act. The ratio to of experts activated to number of experts is smaller, and we decrease the number of attention heads.Vibhu: And kind of for context, what the, what we had been seeing was you make models sparser instead.So no one was really touching heads. You're just having, uh,Kyle: well, they, they did, they implicitly made it sparser.Vibhu: Yeah, yeah. For, for Kimmy. They did,Kyle: yes.Vibhu: They also made it sparser. But basically what we were seeing was people were at the level of, okay, there's a sparsity ratio. You want more total parameters, less active, and that's sparsity.[00:46:00]But what you see from papers, like, the labs like moonshot deep seek, they go to the level of, okay, outside of just number of experts, you can also change how many attention heads and less attention layers. More attention. Layers. Layers, yeah. Yes, yes. So, and that's all basically coming back to, just tied together is like hardware model, co-design, which isKyle: hardware model, co model, context, co-design.Vibhu: Yeah.Kyle: Right. Like if you were training a, a model that was like. Really, really short context, uh, or like really is good at super short context tasks. You may like design it in a way such that like you don't care about attention scaling because it hasn't hit that, like the turning point where like the quadratic curve takes over.Nader: How do you consider attention or context as a separate part of the co-design? Like I would imagine hardware or just how I would've thought of it is like hardware model. Co-design would be hardware model context co-designKyle: because the harness and the context that is produced by the harness is a part of the model.Once it's trained in,Vibhu: like even though towards the end you'll do long context, you're not changing architecture through I see. Training. Yeah.Kyle: I mean you can try.swyx: You're saying [00:47:00] everyone's training the harness into the model.Kyle: I would say to some degree, orswyx: there's co-design for harness. I know there's a small amount, but I feel like not everyone has like gone full send on this.Kyle: I think, I think I think it's important to internalize the harness that you think the model will be running. Running into the model.swyx: Yeah. Interesting. Okay. Bash is like the universal harness,Kyle: right? Like I'll, I'll give. An example here, right? I mean, or just like a, like a, it's easy proof, right? If you can train against a harness and you're using that harness for everything, wouldn't you just train with the harness to ensure that you get the best possible quality out of,swyx: Well, the, uh, I, I can provide a counter argument.Yeah, sure. Which is what you wanna provide a generally useful model for other people to plug into their harnesses, right? So if youKyle: Yeah. Harnesses can be open, open source, right?swyx: Yeah. So I mean, that's, that's effectively what's happening with Codex.Kyle: Yeah.swyx: And, but like you may want like a different search tool and then you may have to name it differently or,Nader: I don't know how much people have pushed on this, but can you.Train a model, would it be, have you have people compared training a model for the for the harness versus [00:48:00] like post training forswyx: I think it's the same thing. It's the same thing. It's okay. Just extra post training. INader: see.swyx: And so, I mean, cognition does this course, it does this where you, you just have to like, if your tool is slightly different, um, either force your tool to be like the tool that they train for.Hmm. Or undo their training for their tool and then Oh, that's re retrain. Yeah. It's, it's really annoying and like,Kyle: I would hope that eventually we hit like a certain level of generality with respect to training newswyx: tools. This is not a GI like, it's, this is a really stupid like. Learn my tool b***h.Like, I don't know if, I don't know if I can say that, but like, you know, um, I think what my point kind of is, is that there's, like, I look at slopes of the scaling laws and like, this slope is not working, man. We, we are at a million token con

The Tim Conway Jr. Show Hour 1 (3.6) Tim Conway Jr. battles real-time computer chaos on the air, and—like any proper Conway spiral—the tech trouble somehow detours into the Apostles’ Creed and a laugh-out-loud breakdown of The Lion King opening: “Look, there is a lion… OMG! It’s a lion.” The crew also hits a modern-life curiosity: the upside-down pineapple and its discreet reputation as a symbol tied to swinging/consensual non-monogamy—because of course that ends up in the mix. Plus, Stephanie Lydecker, host of the iHeart hit “True Crime Tonight,” joins to talk about the show’s success and its new home on KFI every Sunday night (7–9pm). Then Tom Quigley, Santa Anita Park’s VIP Player Concierge and respected handicapper, breaks down what to watch for at the track and how his daily seminars help bettors think smarter. And to wrap it up: the L.A. Marathon is here, the forecast looks fantastic, and the weekend vibes are officially locked in. See omnystudio.com/listener for privacy information.

China will set up a national-level mergers and acquisitions fund to help venture capital investors find an exit. How urgent is the need? And with cumulative dividends and share buybacks hitting a record high, what does that signal about the reshaping of China's securities market? Host TU Yun joins Yao Shujie, Chueng Kong Professor of Economics, Chongqing University, John Gong, Professor of Economics, University of International Business and Economics, and Einar Tangen, a senior fellow of the Canadian think tank, the Center for International Governance Innovation, and the Chairman at Asia Narratives for a close look.

In this explosive episode of The SOVEREIGN SOUL Show, Gene Decode joins our host Brad Wozny to drop additional, major intel on the war for the ancient Golden Dome: a Celestial Defense and 8th Dimensional Ascension system tied to humanity's mass awakening.  . We dive deep into the Galactic Federation's role, Bigfoot sightings as hybrid evidence, vampire nests from New Mexico throughout South America, a 1 billion strong Robot Army under the Giza Pyramids, hybrid vampire bloodlines controlling from the shadows, Khazarian Mafioso, and Iran's escalating battles as flashpoints in the global timeline shift.  Follow Gene Decode at http://www.GeneDecode.org  On Rumble https://rumble.com/user/RealGeneDecode .

Why anxiety spirals happen — and a step-by-step strategy to interrupt them Anxiety often feels like it comes out of nowhere. One moment you're fine. Next, your chest is tight, your thoughts are racing, and you feel like you're spiralling. But anxiety spikes are rarely random. Your body is constantly scanning for safety and threat and when something triggers that system, your nervous system can react before your mind even understands what's happening. In this episode, we slow that moment down. You'll learn how to decode an anxiety spike in real time so you can understand what's actually happening in your body and interrupt the spiral before it takes over. In this episode, you'll learn: Why anxiety spikes feel sudden (even though they aren't) How your nervous system detects threat before conscious thought What actually happens inside an anxiety spiral The hidden sequence behind panic and emotional overwhelm A 5-step framework to decode anxiety in real time When you understand the sequence of an anxiety spike, you stop fighting your body and start working with it. Because anxiety is a body response trying to protect you. And once you know how to read those signals, you can meet them with clarity instead of fear. If you've ever thought: “I don't even know what just happened.” “Why did I spiral so fast?” “Why can't I stop it once it starts?” This episode will help you understand what's happening beneath the surface. Want deeper support? Inside EASE Mentorship, I teach you how to understand the language of your nervous system and interrupt anxiety spirals from the inside out — before they take over. Learn more here: https://www.theunstuckinitiative.com/easementorship 

Oil markets are rattled, Trump is escalating, and China is speaking out. In this episode of China Decode, Alice Han and James Kynge break down how China is responding after Trump's strikes on Iran — and what soaring oil prices mean for Beijing's energy security and global strategy. Is this about principle, protecting its oil lifeline, or quietly capitalizing on U.S. distraction? Then they turn to China's next Five-Year Plan and its aggressive push into AI and advanced manufacturing. Is Beijing accelerating economic decoupling for good? And finally, a fatal crash involving a Chinese EV sparks a nationwide safety rethink. Does this dent China's global EV ambitions — or make them stronger? Learn more about your ad choices. Visit podcastchoices.com/adchoices

If your students can decode CVC words but completely shut down when they see fantastic or instruction, this episode is for you. In today's conversation, we dig into what really helps students read multisyllabic words — and it's not just memorizing syllable types. CLICK HERE FOR FULL SHOW NOTES

Fertility isn't just about reproduction; it's a powerful indicator of overall health, hormonal balance, and resilience.In this episode of A Voice and Beyond, I'm joined by Dr Marina Straszak-Suri, a highly respected OBGYN and an assistant professor at the Faculty of Medicine at the University of Ottawa for over 30 years, providing care to women during all stages of life. Drawing on both modern reproductive medicine and holistic, evidence-based lifestyle strategies, Dr Marina offers clarity and empowerment in an area where many feel overwhelmed or unheard.In this deeply informative and reassuring conversation, we explore how to:Decode your cycle and understand your body's signalsImprove egg and sperm quality through proven lifestyle shiftsNavigate stress, sleep, nutrition, and environmental toxinsExplore natural supplements that actually make a differenceRestore your sense of agency and hope, no matter your age or diagnosisWhether you're planning for pregnancy, preserving your options, or simply wanting to understand your body on a deeper level, this episode offers clarity, compassion, and practical insight.Find Marina Here:Website: https://drmarinaobgyn.com/linkedin: https://www.linkedin.com/in/marina-straszak-suri-md-frcsc-9b32351a/?originalSubdomain=caFB: https://www.facebook.com/profile.php?id=100064823585003Insta: https://www.instagram.com/dr.marina.obgyn?igsh=MTJ4ZHJjbXp0OWU1Resources:Free report – "Seven Tips to Optimize Your Chance of a Healthy Pregnancy" at https://drmarinaobgyn.com/freereportFind Marisa online: Website: https://drmarisaleenaismith.com/ LinkedIn: https://www.linkedin.com/in/drmarisaleenaismith/ Instagram: https://www.instagram.com/drmarisaleenaismith/ Facebook: https://www.facebook.com/marisa.lee.12 YouTube: https://www.youtube.com/@avoiceandbeyond3519/videos Resources: MLN Coaching Program: https://drmarisaleenaismith.com/mentoring/ Schedule a Free Clarity Call: https://calendly.com/info-56015/discovery Gratitude Journal: https://drmarisaleenaismith.com/product/in-gratitude-my-daily-self-journal/ Download your eBook: Thriving in a Creative Industry: https://drmarisaleenaismith.com/product/ebook-thriving-in-a-creative-industry-dr-marisa-lee-naismith/ Like this episode? Please leave a review here - even ...

En este episodio te traemos varias noticias de actualidad, desde los datos de adopción de IA, pasando por el Informe Citrini, noticias de salseo relacionadas con OpenClaw y los nuevos competidores de PicoClaw y Computer de Perplexity. Además te explicamos la nueva versión de Nano Banana 2. No te lo pierdas si quieres estar al día de las novedades en inteligencia artificial y tecnología. Vídeo de Decode: https://youtu.be/okxUb455s5M?si=qbQx4eX3dOkkcCXB Vídeo de AiCandy: https://www.instagram.com/reels/DVLE-QJEf0n/

This actually was just slop.Buddy Links

In this episode of China Decode, Alice Han and James Kynge unpack the International Monetary Fund's blunt warning that China's export-led growth model is nearing its limits — just as the Supreme Court of the United States rolls back sweeping Trump-era emergency tariffs, reshaping the trade war at a pivotal moment. Then, China's hospitals are going viral. From Beijing to Hainan, foreign patients are seeking faster, cheaper treatment as part of Beijing's “Healthy China 2030” push to turn healthcare into a new growth engine — but could that spark domestic backlash? And finally, Seedance 2.0, the powerful new AI video model from ByteDance, is generating hyper-realistic celebrity deepfakes and rattling Hollywood. Is this the future of filmmaking — or the start of a new AI arms race? Learn more about your ad choices. Visit podcastchoices.com/adchoices

In this conversation, Sathiya and Jay Stringer explore the concept of desire, challenging the common belief that it is a problem. They discuss how desire can be a source of healing, intimacy, and personal growth. Jay introduces his framework of five core desires—wholeness, personal growth, intimacy, pleasure, and meaning—and emphasizes the importance of navigating critical periods in life with intention and support from community and elders. The discussion highlights the diagnostic nature of desire and its role in revealing areas of personal development, ultimately advocating for a healthier relationship with desire as a means to flourish in life.  

In today's episode, we are exploring what resistance really is — mentally, physically, and spiritually — and why it's not a flaw, but a message. Instead of pushing through resistance with force and discipline, I am sharing a compassionate, neuroscience-informed and spiritually grounded framework for working with resistance to create sustainable growth and transformation. You'll learn how your brain and nervous system are wired for safety, how subconscious patterns shape your habits, and how to gently rewire them through awareness, compassion, and incremental action. This episode is an invitation to stop fighting yourself and start partnering with your body, mind, and soul. HOW TO WORK WITH RESISTANCE Step 1: Awareness - Just notice it. What am I resisting? What is this resistance around? Where do I feel it — in my mind, my body, my soul or my energy? Step 2: Decode the Story Ask yourself: What is stopping me from doing? What might under that? What might I actually be afraid of? What am I afraid of happening? What would that mean about me? Step 3: Compassion First You cannot shame your nervous system into expansion. Growth responds to gentleness. Say some nice words to yourself with self compassion and just see how it is normal to have fear, reaction or nervousness. Step 4: Incremental Action Your brain rewires through small, repeated, safe experiences. So instead of a quantum leap, ask - What's a 5% stretch?   MENTIONED  

In this powerful returning episode, Michael Jaco sits down with Gene Decode for a deep and wide-ranging discussion exploring spirituality, consciousness, and what Gene describes as hidden forces shaping world events. Gene recounts a life-changing near-death experience following a severe martial-arts injury, describing how he believes he left his body, traveled beyond Earth, encountered the Creator, and returned with new awareness about timelines, consciousness, and humanity's possible futures. He explains his perspective on a coming divergence — what he calls a split between a lower-consciousness path and a higher-frequency “5D Earth.” The conversation also explores disclosure themes, hidden systems, and Gene's interpretation of the Epstein files and their broader implications. He discusses awakening, timeline shifts, and humanity's crossroads between conflict and transformation. The episode closes with reflections on faith, purpose, and the future — and plans for Gene to return for a deeper visual presentation.  

Hearing a bird sing, a dog bark, an orca squeal has led so many of us to wonder if might be possible to talk to animals. Aza Raskin wants to listen to them. He's the co-founder and CEO of the Earth Species Project, which uses artificial intelligence to decode the sounds and signals of other species. The aim isn't just translation; it's understanding. Early breakthroughs from studying highly intelligent crows to other vocal animals suggest we're beginning to hear patterns that were once invisible to us. Raskin believes that learning to truly listen to animals could transform how we see and treat each other and the rest of life on Earth.

Hearing a bird sing, a dog bark, an orca squeal has led so many of us to wonder if might be possible to talk to animals. Aza Raskin wants to listen to them. He's the co-founder and CEO of the Earth Species Project, which uses artificial intelligence to decode the sounds and signals of other species. The aim isn't just translation; it's understanding. Early breakthroughs from studying highly intelligent crows to other vocal animals suggest we're beginning to hear patterns that were once invisible to us. Raskin believes that learning to truly listen to animals could transform how we see and treat each other and the rest of life on Earth.

In this episode of Home Truths, we unpack one of the most pivotal — and often confusing, stages of any renovation: receiving and reviewing quotes.We talk about why prices can differ dramatically, the difference between budgets, estimates and quotes, and why a single lump sum isn't enough to make an informed decision. Jane explains how to properly review a tender, what a cost breakdown should include, and how to compare builders fairly, so you're not caught out later.We also cover the hidden costs that frequently cause budgets to spiral, including provisional sums, client-supplied items, VAT, scaffolding, and permits, and share the one question every homeowner should ask: “What's not included?”If you're planning a renovation or about to receive quotes, this episode will help you approach the process with clarity and confidence - and avoid the costly misunderstandings that often begin with “I assumed that was included.If you're about to get quotes back from your builder - this one's for you!!Sponsored by Plykea;Web:  https://www.plykea.com/Insta: @plykeakitchensBrought to you by HomeNotes;Web: homenotes.coInsta: @wearehomenotes Try the HomeNotes App;Web: homenotes.coInsta: @wearehomenotes Check out our FREE webinars here >>

What if every heartbreak, every failure, every person who showed up and walked away — was actually pointing you toward your purpose?Most of us move through life reacting to what happens — calling it bad luck, calling it unfair, calling it "just the way things are." But what if you zoomed out far enough to see the pattern? The same type of relationship that keeps showing up. The same wall you keep hitting at work. The same feeling that follows you no matter how much you try to outrun it.What if none of it was random — and all of it was trying to teach you something?In this episode, Raj introduces a simple but powerful idea: your life has a purpose, and that purpose is hidden inside the very experiences you wish never happened. He breaks it down into two layers — the lessons you're here to heal from and the life you're here to step into — and explains why most people stay stuck in the first layer without ever realizing there's a second one waiting for them.What You'll Discover:Why the same painful patterns keep repeating in your life — and what they're actually trying to show you about your deeper purposeThe difference between the wounds you're here to heal and the life you're here to build — and why understanding both is the key to finally moving forwardWhy "just the way I am" is the most expensive belief you'll ever carry — and the mindset shift that puts your life back in your handsThe moment Raj realized that pain is inevitable but suffering is a choice — and the simple distinction that changed everythingHow to use your past as a map — a reflection practice that helps you connect the dots and see the deeper intelligence behind what you've been throughWhy trusting yourself enough to try something new — even without a guarantee — is the real work most personal growth skips overThe reason your life might feel like it's falling apart right now — and why that breakdown could be the setup for the version of you that's trying to emergeHow to stop waiting for permission, clarity, or the "right time" and start walking toward the life that's been calling you all alongIf you've ever felt like there has to be more to life than what you're experiencing — like there's a reason behind the struggle that you just can't see yet — this episode will help you see it. Press play and start connecting the dots.Connect with Raj:Liber8: www.liber8.health/programNewsletter – Sign up here: https://www.rajjana.com/staygrounded/Website: http://www.rajjana.com/Instagram: @raj_janaiTunes: https://podcasts.apple.com/rs/podcast/stay-grounded-with-raj-jana/id1318038490Spotify: https://open.spotify.com/show/22Hrw6VWfnUSI45lw8LJBPYouTube: https://www.youtube.com/@raj_janaLegal Disclaimer: The information and opinions discussed in this podcast are for educational and entertainment purposes only. The host and guests are not medical or mental health professionals, and their advice should not be a substitute for seeking professional help. Any action taken based on the information presented is strictly at your own risk. The podcast host and their guests shall have neither liability nor responsibility to any person or entity with respect to any loss, damage, or injury caused or alleged to be caused directly or indirectly by information shared in this podcast. Consult your physician before making any changes to your mental health treatment or lifestyle. Hosted on Acast. See acast.com/privacy for more information.

China is entering the Year of the Fire Horse — a zodiac pairing that comes around just once every 60 years. The last time was 1966, the year the Cultural Revolution began. So is this simply symbolism… or could it hint at something more? In this special Lunar New Year episode of China Decode, Alice Han is joined by writer and commentator Lijia Zhang to unpack the meaning — and the mythology — behind the Fire Horse. They explore how astrology, politics, and economics intersect at a pivotal moment for China. From falling birth rates and zodiac baby booms to record-breaking Spring Festival travel, what does this year reveal about where China may be headed next? Learn more about your ad choices. Visit podcastchoices.com/adchoices

follow indigo angel:indigoangel222.comcourses:learn.indigoangel222.comIndy Youtube:/ @indigoangelImportant News and Links and what not for Typical Skeptic Podcast. Please be sure to Like, Comment, Share my videos, and Subscribe:Typical Skeptic Podcast 2.0 On Youtube:/ @typicalskepticpodcast_2.0Rumblerumble.com/c/typicalskepticpodcastSpreaker Audiospreaker.com/podcast/typical-skeptic-podcast--5897400Spotifyopen.spotify.com/show/4cgu5sK7h852WVw33oi2BpOdyseeodysee.com/@typicalskeptic:3Tik Toktiktok.com/@typicalskepticpodcastSubstacksubstack.com/@typicalskepticpodcastRedditreddit.com/r/TypicalSkepticPodcastInstagraminstagram.com/kalilrobertfacebookfacebook.com/Robert.Kalil.7xx.com/robertkalil1121Support the Podcast:Typical Skeptic Podcast Links and Affiliates:Support the Mission:

Welcome to Integrative Medicine for Energy and Health! The Go-To Holistic Health Podcast for Christian Women Seeking to Boost Their Energy and Overall Well-Being! Blubrry Nominated as a Favorite Woman Podcaster! Ranked in the Best 15 Christian Health Podcasts! Hormone imbalance in women is often dismissed as “normal aging” or everyday stress. Yet symptoms like fatigue, mood swings, digestive changes, sleep disturbances, and weight fluctuations are often your body's early warning signals that something deeper needs attention. In this episode, Dr. Rekishia McMillan explains how the body constantly communicates through subtle cues and symptoms — and how ignoring those signals can lead to worsening hormonal and metabolic health over time. You'll learn how hormonal shifts affect energy, mood, metabolism, and digestion, why early awareness prevents chronic health issues, and how biblical principles of honoring the body align with modern science on women's hormonal health. She shares her personal experience navigating perimenopause, being told her symptoms were “normal,” and how learning to listen to her body transformed her energy, hormone balance, and overall well-being. Through intentional nutrition, stress reduction, and faith-based practices, she discovered how to partner with her body instead of pushing through exhaustion. This episode is ideal for women seeking natural, holistic, and faith-aligned approaches to hormone balance, energy restoration, and long-term wellness ✨ In this episode, you'll learn: Why many women ignore early signs of hormone imbalance How fatigue, cravings, and mood changes are communication signals The connection between stress, cortisol, and hormone disruption How perimenopause impacts energy and metabolic health Biblical principles for honoring and listening to your body A practical body-listening exercise you can start today Simple lifestyle strategies to support hormone balance Join Dr. Rekishia for her Feel Great Webinar Sign up on Eventbrite Want to Go Deeper? Access resources, upcoming events, and ways to work with Dr. Rekishia "Your word is a lamp to my feet and a light to my path"." Psalm 119:105. Love, Health and Blessings, Dr. Rekishia Listen to Related Episodes: 277 | Hot Flashes & Night Sweats in Women, What Your Body Is Really Telling You About Hormone Imbalance 274 | How Stress Dysregulates Women's Hormones, Faith Based Tapping Restores Your Energy 270 | Low Magnesium in Women Linked to Body Cramps, 3 Simple Fixes to Restore Balance   Disclaimer: Information shared on this podcast and any referenced websites are not to be taken as medical advice or to be used as a diagnosis or treatment plan for any medical condition. I am sharing my educated opinions and experience, but nothing shared here can be taken on a one size fits all basis and we always recommend you do your own research, talk to your own doctors and practitioners, and take full responsibility for any health medical choices you make.

If you've ever stood in the kitchen thinking,“I know what to do… so why can't I stop?” - this is for you.Because underneath the cravings that we are fighting, holds the wisdom that is trying to guide you. In this episode, I share one of the most vulnerable turning points in my own relationship with food, a moment where I knew exactly what I “should” be doing… and still felt pulled into the kitchen by something stronger.For years, I believed that if I just had more discipline, more knowledge, more control, I'd finally feel at peace. But what I discovered in that moment changed everything.Cravings aren't weakness.And they're not a lack of willpower.They're communication. A calling from deep within us, trying to get our attention. When you learn how to pause, listen, and decode what's really happening beneath the urge, something powerful shifts. The inner war softens. Shame dissolves. And self-trust grows. In this video, you'll learn:• Why knowing what to eat isn't enough• What's actually happening when you feel an urge with food• How cravings can become a doorway to knowing ourselves more deeply• The foundational practice to move through emotional eating, overeating, and challenging patterns with food and deepen the trust you feel, within yourself. chapters: 00:00 The Moment You Realize It's Not About Food00:37 Why “Knowing Better” Doesn't Stop the Pull02:55 When Everything Slowed Down (And the Urge Got Louder)04:53 The Granola Moment That Changed Everything09:16 What a Craving Is Really Trying to Show You14:15 How to Pause and Decode the Message19:22 Turning the Urge Into GrowthI hope this one gave you a new “aha” or breadcrumb on your path. I'd always love to hear if it resonated. If you're ready to go deeper: free training, Reclaiming Your Power with Food, is where I walk you through the 3-step process to rebuild trust with your bodyTo work together you can apply here for Mastering Mindfulness. #foodcravings #emotionaleating #mindfuleating #foodfreedom #bingeating #selftrust

In this episode of China Decode, Alice Han and James Kynge dig into China's so-called “genius camps” — the small, brutally selective talent pipeline behind many of the country's biggest tech and AI breakthroughs. Then they turn to rising nuclear tensions after the U.S. accuses China of having conducted a secret nuclear test in 2020, just as the last major U.S.-Russia arms control treaty expires. How credible are the claims, and what does this mean for global nuclear negotiations? Plus, China's underground club scene is roaring back after years of pandemic closures, as global music crosses borders in new ways — including Bad Bunny topping the charts in China. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Cravings aren't character flaws—they're communication. Learn to decode what your body is really asking for when cravings strike during perimenopause and menopause.  Discover common craving patterns for women over 40, underlying needs being expressed (nutrient deficiencies, emotional needs, habit patterns), and practical strategies for responding effectively rather than fighting willpower battles. Perfect for women struggling with sugar cravings, emotional eating, or feeling controlled by food urges. Includes craving translation guide and response strategies. If you want to take this work deeper, grab my book The Consistency Code: A Midlife Woman's Guide to Deep Health and Happiness. ✨ It's the roadmap midlife women are using to lead themselves powerfully in the health arena and beyond. Available now at https://theconsistencycode.com 

 believe a shift has taken place and things are being revealed to us but it seems everyone else has missed it. Signs and signals for both our physical and spiritual reality. You wont get this anywhere else. Want to Understand and Explain Everything Biblically?  Click Here: Decoding the Power of Three: Understand and Explain Everything or go to www.rightonu.com and click learn more.  Thank you for Listening to Right on Radio. Prayerfully consider supporting Right on Radio. Click Here for all links, Right on Community ROC, Podcast web links, Freebies, Products (healing mushrooms, EMP Protection) Social media, courses and more... https://linktr.ee/RightonRadio Live Right in the Real World! We talk God and Politics, Faith Based Broadcast News, views, Opinions and Attitudes We are Your News Now. Keep the Faith

In this episode of China Decode, Alice Han and James Kynge unpack how China is reshaping global power—sometimes loudly, sometimes through pandas, ports, and pop culture. As Donald Trump warns allies like the U.K. and Canada that getting closer to Beijing is “dangerous,” reality tells a messier story: British pharma giant AstraZeneca is cutting billion-dollar deals in China, Japan is losing its last pandas amid rising tensions, and Washington is scrambling to blunt China's grip on critical minerals. They also dive into a Panamanian court ruling that just blew up a Hong Kong firm's control over key canal ports—an apparent U.S. win that could quickly become a new U.S.–China flashpoint over one of the world's most important trade chokepoints. And finally, they decode the viral idea that everyone is living a “very Chinese time,” from wellness trends to memes, and what it says about growing American disillusionment—and China's evolving soft power. Why does all this matter? Because these fights aren't abstract: they affect supply chains, prices, travel, jobs, and how the next generation sees America's place in the world. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Decode the Greenville County Budget with Susan Bell. Learn how property taxes fund your community and explore the League of Women Voters' new Budget Basics tool.Episode Resources:League of Women Voters of Greenville County: Budget BasicsGreenville County Official WebsiteSimple Civics: How to Speak at a Public MeetingSouth Carolina Local Property Tax Incentives & FILOTSimple Civics:Simple Civics: Greenville County is a project of Greater Good GreenvilleGet in touchSupport Simple Civics with a tax-deductible contributionSign up for the Simple Civics newsletter.View our entire catalogueSimple Civics: Greenville County is produced by Podcast Studio X.

In this episode of the IBKR Podcast, Steve Sosnick, Chief Strategist at Interactive Brokers, and Jose Torres, Senior Economist, break down the market reaction to Kevin Warsh's Fed nomination. They examine whether Warsh is a policy hawk, a political pragmatist, or something in between, and what his potential influence means for interest rates and investor expectations heading into the second half of the year.

Typical Skeptic Podcast #24381/30/2026 – 7:30 PM Eastern✨ Stargate 10 Extension in Minnesota: Corruption Decode ✨

Send us a textIn this episode, we sit down with Tara-Meyer Robson, the creator of The Flow Method and Body Decode Method, to explore how mental and physical health are deeply interconnected—and why the body plays such a critical role in healing. Our guest shares how these methodologies were developed, how they're being used by practitioners around the world, and what happens when clinicians learn to listen to the body as part of the therapeutic process. We discuss practical ways therapists can expand their clinical lens beyond symptoms and diagnoses to support more integrated, sustainable change. This conversation invites mental health professionals to rethink healing as something that unfolds in motion, awareness, and connection between mind and body. Resources: Science of Consciousness Paper: https://drive.google.com/file/d/1TENPVlGPfKpVDMIi2dvl9FrvyjgSMqVP/view?usp=sharingMaster's Level Documentation: https://drive.google.com/file/d/1OdUC5E5BDmH2JIjBu8OnNvT7K5rZLWYv/view?usp=sharingWhat You'll Learn:The core principles behind The Flow Method and Body Decode Method, and how they were developed.Why the body holds important information that can guide therapeutic insight and intervention.How practitioners around the world are integrating these methodologies into their clinical work.Practical ways mental health professionals can expand their approach without abandoning existing modalities.Bio:Tara Meyer-Robson is an award-winning author and the creator of The Flow Method and Body Decode Method—two groundbreaking, science-backed methodologies that reveal the unconscious beliefs driving both mental and physical symptoms. Her work bridges the gap between psychology, neuroscience, and mind-body medicine, giving practitioners a clear, structured framework to uncover root causes and accelerate healing. Tara has trained therapists, coaches, and healers worldwide to achieve stunning client results in a fraction of the usual time. Known for her engaging style and live “body decoding” demonstrations, she leaves professional audiences inspired and equipped with practical tools they can use immediately.Connect with Tara-Meyer Robson:https://www.facebook.com/tarameyerrobsonhttps://www.linkedin.com/in/tarameyerrobson/https://www.instagram.com/tarameyerrobson/Dr. Margo Jacquot is the award-winning founder and Chief Care Officer of The Juniper Center, one of the largest woman-owned counseling and therapy practices in the Chicago area. With over 20 years of experience, she specializes in trauma recovery, addiction treatment, and LGBTQ-affirming therapy. Dr. Jacquot is also the host of the "Mental Health Business Mentor" podcast, where she shares insights on running a successful mental health practice. thejunipercenter.com Connect with Dr. Margo Jacquot: Website: thejunipercenter.com Instagram: @thejunipercenter Facebook: The Juniper Center

In this episode of China Decode, Alice Han and James Kynge break down a seismic week in Beijing. China has effectively blown up the top of its military command, sidelining Xi Jinping's most trusted lieutenant and raising questions about loyalty, readiness, and how secure Xi really is at the apex of power. They explain what this unprecedented purge inside the PLA means—not just for China's military, but for regional stability and markets. They also unpack the post-China future of TikTok. After years of bans, lawsuits, and security concerns, a last-minute deal keeps the app alive in the U.S.—but does it truly sever Beijing's influence, or just repackage it? With 180 million American users and a generation getting its news from TikTok, we explain why this deal matters far beyond social media. And finally, Alice sits down with economist Houze Song to cut through the spin on China's economy—from headline growth numbers and export dependence to the long shadow of the property collapse and what Beijing may (or may not) do next.  Learn more about your ad choices. Visit podcastchoices.com/adchoices

What if your body has been trying to tell you something all along—and you just didn't know how to listen? Twenty-five years ago, Inna was trapped in chronic pain. Psoriasis covered her body. She could barely walk due to back issues. She struggled with anxiety, depression, and digestive problems. She was stuck in the medical system, being told her conditions were genetic and permanent, taking medications that didn't work. Then, at age 20, she lost her baby. And in the depths of that grief and physical agony, one statement from her chiropractor changed everything: "Your body wants to be stuck." That single sentence—which initially enraged her—became the doorway to her awakening. Because it made her realize: if her body WANTS something, it has intelligence. It has language. It's trying to communicate. That night, she placed her hands on her back, breathed, and asked a simple question: "What does my back look like? Why am I in pain?" What happened next awakened an ability that would eventually help tens of thousands of people across the globe. She could suddenly SEE inside her body. She understood the emotional, psychological, and ancestral patterns creating her physical symptoms. And within three weeks, she healed conditions she'd been told were permanent. In this deeply moving conversation, we explore: The Journey to Awakening Inna shares her full story—from growing up in Belarus and being raised to believe doctors were half-gods, to moving to Australia and being bullied, to the pregnancy and loss that became her breaking point, to the moment she took radical responsibility for her own healing and everything changed. How Medical Intuition Actually Works Inna explains how she learned to see into people's energy fields and bodies—from the first time she saw a cartoon liver above her friend's head, to working with a medical doctor who had her place acupuncture needles based on what she was seeing, to learning how to turn the ability on and off so she didn't go insane. The Logic of the Body This is one of my favorite parts of our conversation. Inna breaks down why the body is completely logical—not random, not punishing, but communicating with incredible intelligence. Every symptom has layers of meaning. Every disease has a story. And when you understand the logic, you can begin to heal. What Your Symptoms Are Really Telling You We dive deep into specific body parts and systems: Why your immune system breaks down (insecurity, inner conflict, self-neglect, stress, not being able to say no) What back pain is really about (lack of support—both emotional AND financial) Why skin issues appear (not feeling safe, not belonging, ancestral trauma) How your digestive system holds loss and grief The Power of Color Healing Inna teaches how color is directly connected to emotion, and how you can use color intentionally every single day to shift your state. She shares stories of using pink light for protection, green for manifestation, and how wearing different colors changes how you feel, think, and show up in the world. Taking Radical Responsibility We discuss what it really means to move from being a victim of your body to being the healer of your body. This isn't about blaming yourself for illness—it's about recognizing that you have power, intelligence, and the ability to participate in your own healing. Ancestral Trauma in the Body Inna explains how family patterns and generational trauma show up in your physical body—in your digestive system, your immune response, your nervous system. She shares her own story of recognizing her grandmother's trauma living in her body. Practical Self-Healing Techniques Throughout the conversation, Inna shares tangible practices you can use immediately—from breathing into pain, to asking your body questions, to using color intentionally, to working with pressure points and movement. The Difference Between Caring and Carrying One insight that really struck me was Ina's distinction between caring for people and carrying them. This is huge for healers, coaches, yoga teachers, and anyone in helping professions. Why Healing Pulls You Toward Knowing Yourself Ina's closing wisdom is so powerful: "Healing always pulls you toward knowing you. You cannot heal without self-knowledge. The more you dive in, the more you realize what a layered person you are and how beautifully colorful and complex you are on the soul level." This episode is for anyone dealing with chronic health issues, anyone who feels stuck in their body, healers and coaches who want to understand the deeper layers of what's happening with their clients, yoga teachers, energy workers, bodyworkers, and anyone curious about the profound intelligence of the body. GUEST BIO: Inna Segal is an internationally recognized healer, bestselling author, speaker, and intuitive guide. Born in Belarus and raised in Italy and Australia, Ina's journey to becoming a medical intuitive began after her own healing crisis at age 20. For over 25 years, she has worked with tens of thousands of clients across six continents, helping them decode their body's messages and activate their innate healing abilities. She is the author of The Secret Language of Your Body and is currently writing a book on the 8 Stages of Healing. CONNECT WITH INNA: Website: innasegal.com Free Masterclasses: innasegal.com/secret Instagram: @innasegal Book: The Secret Language of Your Body SPECIAL OFFER: Inna is offering FREE masterclasses for Finding Harmony listeners on: • The Secret Language of Your Body • Color Healing • Ancestral Trauma • Childhood Patterns • Soul Guidance & Purpose Register at: innasegal.com/secret KEY INSIGHTS: Your body has an intelligent language—symptoms aren't random • Taking radical responsibility for your health is transformative • The body is completely logical—every symptom has layered meaning • Color is directly connected to emotion and can be used for healing daily • Your immune system responds to how safe and supported you feel • Back pain often relates to lack of support (emotional and financial) • Skin issues connect to feeling safe in your own skin and belonging • Ancestral trauma lives in your physical body and can be healed • You can develop your intuitive abilities through practice • Healing always pulls you toward deeper self-knowledge • The difference between caring for people and carrying them is essential RESOURCES MENTIONED: • The Secret Language of Your Body by Inna Segal • Network Chiropractic (now Network Spinal Analysis) • Spinal Energetics • Caroline Myss and Anatomy of the Spirit • Donald Epstein's 12 Stages of Healing • Ina's free masterclasses at innasegal.com FIND Harmony online: https://harmonyslater.com/ Harmony on IG: https://www.instagram.com/harmonyslaterofficial/ Finding Harmony Podcast on IG: https://www.instagram.com/findingharmonypodcast/ FREE Manifestation Activation: https://harmonyslater.kit.com/manifestation-activation

Decode the bro Foreign Film Game Is Woody a cool Dad? Mat Damon & Ben Affleck Ball Beats for AO Tix See omnystudio.com/listener for privacy information.

In this episode of China Decode, Alice Han and James Kynge break down Beijing's drive to pull U.S. allies closer—from Canada's EV tariff to Europe's growing economic hedge. They unpack China's lopsided economy, as exports boom while consumers pull back and the property slump deepens. Plus, a viral app meant to check if users are still alive sparks a deeper look at China's growing loneliness epidemic. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Host: Annik Sobing Guests: Sean Yu and Chen Cui, Co-founders of GingerControl Published: January 2026 Length: ~25 minutes Presented by: Global Training Center In this energetic Simply Trade News Roundup, host Annik Sobing welcomes Sean Yu and Chen Cui, the twenty-something co-founders of GingerControl—an AI-powered trade compliance startup that's shaking up the industry's manual processes with tariff optimization and automation tools. High school friends from New Zealand who bonded over geopolitics, Sean (the numbers guy) and Chen (the ICPA conference hustler) spotted trade's massive tech gap six months ago: legacy systems like SAP/Oracle can't handle tariff volatility, and most tools lack solid data architecture or "ground truth" references.​ They explain GingerControl's origin as a tariff briefing tool (40 enterprise subscribers already) that delivers actionable HTS impacts and financial analysis, evolving into broader automation that liberates compliance teams from repetitive work for strategic scenario planning. Named after the "Ginger Man" (Trump TikTok meme), their platform claims 5-8% average tariff savings through compliant optimization across millions of tariff texts—without hallucinations or legal risks. The duo candidly addresses industry skepticism: Sean trained their AI to score 96.3% on the customs broker exam (beating competitors), while Chen highlights how gatekeeping (hard exams, lack of youth) and "vibe coding" (AI without foundations) plague the sector.​ Annik probes generational dynamics: their youth gave them intuitive AI fluency, but they've engineered intuitive interfaces for all ages. They see tariff chaos elevating compliance from "basement" to "boardroom," predict one-person compliance teams becoming unsustainable, and envision GingerControl as the industry's trusted one-stop solution within five years. Fun close: If they were shipping containers, Chen wants global travel without inspections, Sean aims for Africa's coasts, and Annik dreams of Mediterranean sunsets.​ What You'll Learn in This Episode How two Gen Z friends spotted trade's tech crisis and built GingerControl from tariff briefings to full compliance automation.​ Why legacy ERP systems fail under tariff volatility and how "vibe coding" creates unreliable AI tools.​ GingerControl's edge: 96.3% customs broker exam score, 5-8% tariff savings, and "ground truth" references for audit-proof reasonable care.​ The youth barrier in trade (hard exams, no intentional entrants) and how tariff chaos could force compliance into C-suites.​ Their vision: liberate compliance from grunt work, enabling strategic planning as next-gen talent arrives.​ Key Takeaways Trade's manual processes and gatekeeping create massive tech opportunity for agile, compliant AI startups.​ True AI value lies in reliable references and auditability, not just flashy outputs—96.3% broker exam proves it.​ Tariff volatility demands boardroom compliance; one-person teams importing millions of units won't scale.​ Youth brings intuitive AI design, but success requires understanding all users and building intuitive interfaces. Checkout their new HTS Classification tool: https://tariff.gingercontrol.com/classifier​ Credits Host: Annik Sobing Guests: Sean Yu & Chen Cui – Co-founders, GingerControl Producer: Annik Sobing Subscribe & Follow New episodes weekly! Presented by: Global Training Center

Jimbob joins me to analyze a couple relevant films: Eden (2025) and Gone Girl (2014), both of which have interesting parallels and commentaries on society, gender, psychology ops, modernity and more. Enjoy! Jimbob is here  @MadebyJimbob  Send Superchats at any time here: https://streamlabs.com/jaydyer/tip Join this channel to get access to perks: https://www.youtube.com/channel/UCnt7Iy8GlmdPwy_Tzyx93bA/join Order New Book Available here: https://jaysanalysis.com/product/esoteric-hollywood-3-sex-cults-apocalypse-in-films/ Get started with Bitcoin here: https://www.swanbitcoin.com/jaydyer/ The New Philosophy Course is here: https://marketplace.autonomyagora.com/philosophy101 Set up recurring Choq subscription with the discount code JAY60LIFE for 60% off now https://choq.com Subscribe to my site here: https://jaysanalysis.com/membership-account/membership-levels/ Follow me on R0kfin here: https://rokfin.com/jaydyer Music by Dr Evo the Producer, Jay Dyer and Amid the Ruins 1453 https://www.youtube.com/@amidtheruinsOVERHAUL Join this channel to get access to perks: https://www.youtube.com/channel/UCnt7Iy8GlmdPwy_Tzyx93bA/join #entertainment #movies #comedyBecome a supporter of this podcast: https://www.spreaker.com/podcast/jay-sanalysis--1423846/support.

Numbers aren't just for counting—they are energetic codes that shape our reality. In this episode, we dive deep into Address Numerology and how you can align your environment to support your personal evolution, career goals, and spiritual path. We are currently in a 1 Universal Year, a powerful time for new beginnings and fresh starts. Whether you’re looking to call in a new partner, launch a business, or find deep healing, your home’s address number could be the missing piece of the puzzle. In this episode, you’ll learn: How to calculate your address frequency (and why you should ignore the zip code). The archetypal energy of numbers 1–9 and the Master Numbers (11, 22, 33, 44). The Post-it Note Hack: How to mathematically shift your home’s energy without moving. The best (and worst) times to change your numerology (New Moon vs. Full Moon). How to handle "Shadow Frequencies" so you stay balanced. Specific breakdowns for office spaces and healing environments. Sign-Up for Amanda’s January Workshop! Includes: A guided walkthrough of January—astrologically, numerologically, and energetically—so you can listen and re-listen whenever you need clarity, orientation, or recalibration. A comprehensive roadmap for the month: numerology themes, key transits, New + Full Moon focus points, and prompts to help you track your signal and make aligned choices. Additional Resources: Address Numerology 101: How to Find it, What it Means, & How to Change it Numerology 101: How to Decode the Numbers in Your Life Find Magic, Synchronicity, and Peace with Numerology Thinning the Veil with Numerology: Master Numbers, Angel Numbers, and More How to Align with the Divine Codes of the Universe Unlock Your True Purpose with Soul Urge Numerology Host: Amanda Rieger Green YouTube: @soul_pathology⁩ Instagram: @soulpathology Website: SoulPathology.com Email: Podcast@soulsessions.meFollow Amanda on Instagram: https://www.instagram.com/soulpathology/See omnystudio.com/listener for privacy information.

In the wake of Trump's invasion of Venezuela, how will China respond to the ongoing protests in Iran? In this episode of China Decode, Alice Han and James Kynge take on the geopolitical firestorm brewing in Beijing, as it finds its energy imports, financial partnerships, and global influence all imperiled. Alice and James are joined by Michal Meidan, head of China Energy Research at the Oxford Institute for Energy Studies, to assess how big an impact these events will have on China's future.  Plus — with adult obesity on the rise in China, so-called “fat prisons” are springing up to help people (and pets) lose weight. That's in addition to GLP-1 drugs, which are getting cheaper and more available as Chinese manufacturers begin to produce them themselves. Learn more about your ad choices. Visit podcastchoices.com/adchoices

In this episode of China Decode, Alice Han and James Kynge break down Beijing's response to Trump's sudden takeover of Venezuela — a move that hits China's energy interests, loans, and influence in Latin America, and raises the stakes far beyond oil. Then they turn to the EV race, where BYD has overtaken Tesla for the first time, signaling a potential power shift in the global auto industry. And finally, they look at China's quieter — but surprising — rise as a luxury food superpower, from caviar to truffles, and what it says about trade, consumption, and state-backed strategy.  Learn more about your ad choices. Visit podcastchoices.com/adchoices

‼️BREAKING GENE DECODE INTEL‼️ World-Renowned Intel Analyst, US Navy veteran & Spiritual Researcher Gene Decode joins host Brad Wozny as they unveil the accelerating markers pointing to humanity's next phase of awakening and planetary transition (…Including escalating NDE's, confirmations the Code of Creation and much, much more…) ‼️The Golden Age is Here as Silver Broke $79/oz Last Week‼️ Gold's projected to $8,000/oz…Silver to $120/oz. Physical possession of Gold or Silver is essential as the Dollar crashes…Strategies exist for patriots to buy or leverage their savings or 401K Call America's #1 Precious Metals advisors now  Book a Free Consultation

In this episode of China Decode, Alice Han and James Kynge break down a quieter but consequential shift in Washington's China strategy. They unpack Trump's new national security playbook, why Beijing is suddenly sounding upbeat, and whether this signals a real reset or just a tactical pause in U.S.-China tensions. They also dig into China's baby bust — and the backlash to a new tax on condoms — as policymakers search for answers to falling birth rates. Plus, Alice sits down with Chip War author Chris Miller to discuss Trump's surprise reversal on AI chip exports to China, what it means for NVIDIA, and why semiconductors are now at the center of global power politics. Learn more about your ad choices. Visit podcastchoices.com/adchoices