Podcasts about Snips

Išgirsime dainas iš ateities – didingo fantastinės roko muzikos albumo, kokie tik ir galėjo būt įrašyti 1977 metais, o gal visgi 3035 m., kai paskui žemiečių kosminius laivus į pirmuosius koncertus kituose pasauliuose išvyko ir ansamblis „Intergalactic Touring Band“, savo įspūdžius įamžinęs to pat pavadinimo plokštelėje. Grupėje dalyvauja anglų ir amerikiečių dainininkai: Annie Haslam, Dave Cousins, Steve Barth, Jim Cuomo, Ben Earl King, Mr. Snips, Meatloaf ir kt.Ved. Lukas Devita

We're joined (once again!) by none other than Sean Chalmers – fresh off his Edinburgh Half Marathon win and a new course record to boot! Always a great guest, and even better when he's smashing records. Meanwhile, Kyle's been in recovery mode – and if you know Kyle, you know that probably means too much information. Tune in to hear the full story... Lewis has been keeping busy winding Kyle up and proudly Team Managing the Scottish squad at the Loughborough International – plus supporting athletes in training and racing across the board. Enjoy!

In drug development, the right biomarker can mean the difference between success and a missed opportunity. In this episode of SNiPs, Bracken Senior Partner David Raunig, PhD explores how imaging biomarkers—like DXA and the fracture risk score—are being used in new ways to assess efficacy in clinical trials, especially for rare and complex diseases. David breaks down the evolving landscape of FDA qualification, highlighting a flexible path that allows sponsors to leverage novel endpoints without requiring tens of thousands of patients. From muscle mass in aging populations to trial-specific biomarker strategies, he shares valuable insight into what's possible today—and what's coming next.

Get ready to meet the voice behind some of your favorite childhood characters—this week on The Razzle Dazzle Show, we're joined by the legendary Lee Tockar! From Frieza in Dragon Ball Kai to Bibble in the Barbie movies, Bling Bling Boy in Johnny Test, and Snips in My Little Pony, Lee's vocal range is as wild as his imagination! He's also a muralist, playwright, children's book author, and advocate for the visually impaired—talk about a creative powerhouse! Join us as we dive into Lee's incredible journey through voice acting, visual art, and storytelling.Special Guest - Lee Tockar https://linktr.ee/leetockarworld?utm_source=linktree_profile_share

We finish our discussion of Ahsoka's journey by going back to the beginning where it all started in the Clone Wars!  Tiara from Crafting on Illum returns once again to help us break down Ahsoka's journey from new padawan, coming into her own leadership skills, and finally making that fateful decision to walk away from the Jedi Order.  She started out as Snips and now she's standing tall in all of our hearts!

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We are working with Amplify on the 2025 State of AI Engineering Survey to be presented at the AIE World's Fair in SF! Join the survey to shape the future of AI Eng!We first met Snipd over a year ago, and were immediately impressed by the design, but were doubtful about the behavior of snipping as the title behavior:Podcast apps are enormously sticky - Spotify spent almost $1b in podcast acquisitions and exclusive content just to get an 8% bump in market share among normies.However, after a disappointing Overcast 2.0 rewrite with no AI features in the last 3 years, I finally bit the bullet and switched to Snipd. It's 2025, your podcast app should be able to let you search transcripts of your podcasts. Snipd is the best implementation of this so far.And yet they keep shipping:What impressed us wasn't just how this tiny team of 4 was able to bootstrap a consumer AI app against massive titans and do so well; but also how seriously they think about learning through podcasts and improving retention of knowledge over time, aka “Duolingo for podcasts”. As an educational AI podcast, that's a mission we can get behind.Full Video PodFind us on YouTube! This was the first pod we've ever shot outdoors!Show Notes* How does Shazam work?* Flutter/FlutterFlow* wav2vec paper* Perplexity Online LLM* Google Search Grounding* Comparing Snipd transcription with our Bee episode* NIPS 2017 Flo Rida* Gustav Söderström - Background AudioTimestamps* [00:00:03] Takeaways from AI Engineer NYC* [00:00:17] Weather in New York.* [00:00:26] Swyx and Snipd.* [00:01:01] Kevin's AI summit experience.* [00:01:31] Zurich and AI.* [00:03:25] SigLIP authors join OpenAI.* [00:03:39] Zurich is very costly.* [00:04:06] The Snipd origin story.* [00:05:24] Introduction to machine learning.* [00:09:28] Snipd and user knowledge extraction.* [00:13:48] App's tech stack, Flutter, Python.* [00:15:11] How speakers are identified.* [00:18:29] The concept of "backgroundable" video.* [00:29:05] Voice cloning technology.* [00:31:03] Using AI agents.* [00:34:32] Snipd's future is multi-modal AI.* [00:36:37] Snipd and existing user behaviour.* [00:42:10] The app, summary, and timestamps.* [00:55:25] The future of AI and podcasting.* [1:14:55] Voice AITranscriptswyx [00:00:03]: Hey, I'm here in New York with Kevin Ben-Smith of Snipd. Welcome.Kevin [00:00:07]: Hi. Hi. Amazing to be here.swyx [00:00:09]: Yeah. This is our first ever, I think, outdoors podcast recording.Kevin [00:00:14]: It's quite a location for the first time, I have to say.swyx [00:00:18]: I was actually unsure because, you know, it's cold. It's like, I checked the temperature. It's like kind of one degree Celsius, but it's not that bad with the sun. No, it's quite nice. Yeah. Especially with our beautiful tea. With the tea. Yeah. Perfect. We're going to talk about Snips. I'm a Snips user. I'm a Snips user. I had to basically, you know, apart from Twitter, it's like the number one use app on my phone. Nice. When I wake up in the morning, I open Snips and I, you know, see what's new. And I think in terms of time spent or usage on my phone, I think it's number one or number two. Nice. Nice. So I really had to talk about it also because I think people interested in AI want to think about like, how can we, we're an AI podcast, we have to talk about the AI podcast app. But before we get there, we just finished. We just finished the AI Engineer Summit and you came for the two days. How was it?Kevin [00:01:07]: It was quite incredible. I mean, for me, the most valuable was just being in the same room with like-minded people who are building the future and who are seeing the future. You know, especially when it comes to AI agents, it's so often I have conversations with friends who are not in the AI world. And it's like so quickly it happens that you, it sounds like you're talking in science fiction. And it's just crazy talk. It was, you know, it's so refreshing to talk with so many other people who already see these things and yeah, be inspired then by them and not always feel like, like, okay, I think I'm just crazy. And like, this will never happen. It really is happening. And for me, it was very valuable. So day two, more relevant, more relevant for you than day one. Yeah. Day two. So day two was the engineering track. Yeah. That was definitely the most valuable for me. Like also as a producer. Practitioner myself, especially there were one or two talks that had to do with voice AI and AI agents with voice. Okay. So that was quite fascinating. Also spoke with the speakers afterwards. Yeah. And yeah, they were also very open and, and, you know, this, this sharing attitudes that's, I think in general, quite prevalent in the AI community. I also learned a lot, like really practical things that I can now take away with me. Yeah.swyx [00:02:25]: I mean, on my side, I, I think I watched only like half of the talks. Cause I was running around and I think people saw me like towards the end, I was kind of collapsing. I was on the floor, like, uh, towards the end because I, I needed to get, to get a rest, but yeah, I'm excited to watch the voice AI talks myself.Kevin [00:02:43]: Yeah. Yeah. Do that. And I mean, from my side, thanks a lot for organizing this conference for bringing everyone together. Do you have anything like this in Switzerland? The short answer is no. Um, I mean, I have to say the AI community in, especially Zurich, where. Yeah. Where we're, where we're based. Yeah. It is quite good. And it's growing, uh, especially driven by ETH, the, the technical university there and all of the big companies, they have AI teams there. Google, like Google has the biggest tech hub outside of the U S in Zurich. Yeah. Facebook is doing a lot in reality labs. Uh, Apple has a secret AI team, open AI and then SwapBit just announced that they're coming to Zurich. Yeah. Um, so there's a lot happening. Yeah.swyx [00:03:23]: So, yeah, uh, I think the most recent notable move, I think the entire vision team from Google. Uh, Lucas buyer, um, and, and all the other authors of Siglip left Google to join open AI, which I thought was like, it's like a big move for a whole team to move all at once at the same time. So I've been to Zurich and it just feels expensive. Like it's a great city. Yeah. It's great university, but I don't see it as like a business hub. Is it a business hub? I guess it is. Right.Kevin [00:03:51]: Like it's kind of, well, historically it's, uh, it's a finance hub, finance hub. Yeah. I mean, there are some, some large banks there, right? Especially UBS, uh, the, the largest wealth manager in the world, but it's really becoming more of a tech hub now with all of the big, uh, tech companies there.swyx [00:04:08]: I guess. Yeah. Yeah. And, but we, and research wise, it's all ETH. Yeah. There's some other things. Yeah. Yeah. Yeah.Kevin [00:04:13]: It's all driven by ETH. And then, uh, it's sister university EPFL, which is in Lausanne. Okay. Um, which they're also doing a lot, but, uh, it's, it's, it's really ETH. Uh, and otherwise, no, I mean, it's a beautiful, really beautiful city. I can recommend. To anyone. To come, uh, visit Zurich, uh, uh, let me know, happy to show you around and of course, you know, you, you have the nature so close, you have the mountains so close, you have so, so beautiful lakes. Yeah. Um, I think that's what makes it such a livable city. Yeah.swyx [00:04:42]: Um, and the cost is not, it's not cheap, but I mean, we're in New York city right now and, uh, I don't know, I paid $8 for a coffee this morning, so, uh, the coffee is cheaper in Zurich than the New York city. Okay. Okay. Let's talk about Snipt. What is Snipt and, you know, then we'll talk about your origin story, but I just, let's, let's get a crisp, what is Snipt? Yeah.Kevin [00:05:03]: I always see two definitions of Snipt, so I'll give you one really simple, straightforward one, and then a second more nuanced, um, which I think will be valuable for the rest of our conversation. So the most simple one is just to say, look, we're an AI powered podcast app. So if you listen to podcasts, we're now providing this AI enhanced experience. But if you look at the more nuanced, uh, podcast. Uh, perspective, it's actually, we, we've have a very big focus on people who like your audience who listened to podcasts to learn something new. Like your audience, you want, they want to learn about AI, what's happening, what's, what's, what's the latest research, what's going on. And we want to provide a, a spoken audio platform where you can do that most effectively. And AI is basically the way that we can achieve that. Yeah.swyx [00:05:53]: Means to an end. Yeah, exactly. When you started. Was it always meant to be AI or is it, was it more about the social sharing?Kevin [00:05:59]: So the first version that we ever released was like three and a half years ago. Okay. Yeah. So this was before ChatGPT. Before Whisper. Yeah. Before Whisper. Yeah. So I think a lot of the features that we now have in the app, they weren't really possible yet back then. But we already from the beginning, we always had the focus on knowledge. That's the reason why, you know, we in our team, why we listen to podcasts, but we did have a bit of a different approach. Like the idea in the very beginning was, so the name is Snips and you can create these, what we call Snips, which is basically a small snippet, like a clip from a, from a podcast. And we did envision sort of like a, like a social TikTok platform where some people would listen to full episodes and they would snip certain, like the best parts of it. And they would post that in a feed and other users would consume this feed of Snips. And use that as a discovery tool or just as a means to an end. And yeah, so you would have both people who create Snips and people who listen to Snips. So our big hypothesis in the beginning was, you know, it will be easy to get people to listen to these Snips, but super difficult to actually get them to create them. So we focused a lot of, a lot of our effort on making it as seamless and easy as possible to create a Snip. Yeah.swyx [00:07:17]: It's similar to TikTok. You need CapCut for there to be videos on TikTok. Exactly.Kevin [00:07:23]: And so for, for Snips, basically whenever you hear an amazing insight, a great moment, you can just triple tap your headphones. And our AI actually then saves the moment that you just listened to and summarizes it to create a note. And this is then basically a Snip. So yeah, we built, we built all of this, launched it. And what we found out was basically the exact opposite. So we saw that people use the Snips to discover podcasts, but they really, you know, they don't. You know, really love listening to long form podcasts, but they were creating Snips like crazy. And this was, this was definitely one of these aha moments when we realized like, hey, we should be really doubling down on the knowledge of learning of, yeah, helping you learn most effectively and helping you capture the knowledge that you listen to and actually do something with it. Because this is in general, you know, we, we live in this world where there's so much content and we consume and consume and consume. And it's so easy to just at the end of the podcast. You just start listening to the next podcast. And five minutes later, you've forgotten everything. 90%, 99% of what you've actually just learned. Yeah.swyx [00:08:31]: You don't know this, but, and most people don't know this, but this is my fourth podcast. My third podcast was a personal mixtape podcast where I Snipped manually sections of podcasts that I liked and added my own commentary on top of them and published them as small episodes. Nice. So those would be maybe five to 10 minute Snips. Yeah. And then I added something that I thought was a good story or like a good insight. And then I added my own commentary and published it as a separate podcast. It's cool. Is that still live? It's still live, but it's not active, but you can go back and find it. If you're, if, if you're curious enough, you'll see it. Nice. Yeah. You have to show me later. It was so manual because basically what my process would be, I hear something interesting. I note down the timestamp and I note down the URL of the podcast. I used to use Overcast. So it would just link to the Overcast page. And then. Put in my note taking app, go home. Whenever I feel like publishing, I will take one of those things and then download the MP3, clip out the MP3 and record my intro, outro and then publish it as a, as a podcast. But now Snips, I mean, I can just kind of double click or triple tap.Kevin [00:09:39]: I mean, those are very similar stories to what we hear from our users. You know, it's, it's normal that you're doing, you're doing something else while you're listening to a podcast. Yeah. A lot of our users, they're driving, they're working out, walking their dog. So in those moments when you hear something amazing, it's difficult to just write them down or, you know, you have to take out your phone. Some people take a screenshot, write down a timestamp, and then later on you have to go back and try to find it again. Of course you can't find it anymore because there's no search. There's no command F. And, um, these, these were all of the issues that, that, that we encountered also ourselves as users. And given that our background was in AI, we realized like, wait, hey, this is. This should not be the case. Like podcast apps today, they're still, they're basically repurposed music players, but we actually look at podcasts as one of the largest sources of knowledge in the world. And once you have that different angle of looking at it together with everything that AI is now enabling, you realize like, hey, this is not the way that we, that podcast apps should be. Yeah.swyx [00:10:41]: Yeah. I agree. You mentioned something that you said your background is in AI. Well, first of all, who's the team and what do you mean your background is in AI?Kevin [00:10:48]: Those are two very different things. I'm going to ask some questions. Yeah. Um, maybe starting with, with my backstory. Yeah. My backstory actually goes back, like, let's say 12 years ago or something like that. I moved to Zurich to study at ETH and actually I studied something completely different. I studied mathematics and economics basically with this specialization for quant finance. Same. Okay. Wow. All right. So yeah. And then as you know, all of these mathematical models for, um, asset pricing, derivative pricing, quantitative trading. And for me, the thing that, that fascinates me the most was the mathematical modeling behind it. Uh, mathematics, uh, statistics, but I was never really that passionate about the finance side of things.swyx [00:11:32]: Oh really? Oh, okay. Yeah. I mean, we're different there.Kevin [00:11:36]: I mean, one just, let's say symptom that I noticed now, like, like looking back during that time. Yeah. I think I never read an academic paper about the subject in my free time. And then it was towards the end of my studies. I was already working for a big bank. One of my best friends, he comes to me and says, Hey, I just took this course. You have to, you have to do this. You have to take this lecture. Okay. And I'm like, what, what, what is it about? It's called machine learning and I'm like, what, what, what kind of stupid name is that? Uh, so you sent me the slides and like over a weekend I went through all of the slides and I just, I just knew like freaking hell. Like this is it. I'm, I'm in love. Wow. Yeah. Okay. And that was then over the course of the next, I think like 12 months, I just really got into it. Started reading all about it, like reading blog posts, starting building my own models.swyx [00:12:26]: Was this course by a famous person, famous university? Was it like the Andrew Wayne Coursera thing? No.Kevin [00:12:31]: So this was a ETH course. So a professor at ETH. Did he teach in English by the way? Yeah. Okay.swyx [00:12:37]: So these slides are somewhere available. Yeah. Definitely. I mean, now they're quite outdated. Yeah. Sure. Well, I think, you know, reflecting on the finance thing for a bit. So I, I was, used to be a trader, uh, sell side and buy side. I was options trader first and then I was more like a quantitative hedge fund analyst. We never really use machine learning. It was more like a little bit of statistical modeling, but really like you, you fit, you know, your regression.Kevin [00:13:03]: No, I mean, that's, that's what it is. And, uh, or you, you solve partial differential equations and have then numerical methods to, to, to solve these. That's, that's for you. That's your degree. And that's, that's not really what you do at work. Right. Unless, well, I don't know what you do at work. In my job. No, no, we weren't solving the partial differential. Yeah.swyx [00:13:18]: You learn all this in school and then you don't use it.Kevin [00:13:20]: I mean, we, we, well, let's put it like that. Um, in some things, yeah, I mean, I did code algorithms that would do it, but it was basically like, it was the most basic algorithms and then you just like slightly improve them a little bit. Like you just tweak them here and there. Yeah. It wasn't like starting from scratch, like, Oh, here's this new partial differential equation. How do we know?swyx [00:13:43]: Yeah. Yeah. I mean, that's, that's real life, right? Most, most of it's kind of boring or you're, you're using established things because they're established because, uh, they tackle the most important topics. Um, yeah. Portfolio management was more interesting for me. Um, and, uh, we, we were sort of the first to combine like social data with, with quantitative trading. And I think, uh, I think now it's very common, but, um, yeah. Anyway, then you, you went, you went deep on machine learning and then what? You quit your job? Yeah. Yeah. Wow.Kevin [00:14:12]: I quit my job because, uh, um, I mean, I started using it at the bank as well. Like try, like, you know, I like desperately tried to find any kind of excuse to like use it here or there, but it just was clear to me, like, no, if I want to do this, um, like I just have to like make a real cut. So I quit my job and joined an early stage, uh, tech startup in Zurich where then built up the AI team over five years. Wow. Yeah. So yeah, we built various machine learning, uh, things for, for banks from like models for, for sales teams to identify which clients like which product to sell to them and with what reasons all the way to, we did a lot, a lot with bank transactions. One of the actually most fun projects for me was we had an, an NLP model that would take the booking text of a transaction, like a credit card transaction and pretty fired. Yeah. Because it had all of these, you know, like numbers in there and abbreviations and whatnot. And sometimes you look at it like, what, what is this? And it was just, you know, it would just change it to, I don't know, CVS. Yeah.swyx [00:15:15]: Yeah. But I mean, would you have hallucinations?Kevin [00:15:17]: No, no, no. The way that everything was set up, it wasn't like, it wasn't yet fully end to end generative, uh, neural network as what you would use today. Okay.swyx [00:15:30]: Awesome. And then when did you go like full time on Snips? Yeah.Kevin [00:15:33]: So basically that was, that was afterwards. I mean, how that started was the friend of mine who got me into machine learning, uh, him and I, uh, like he also got me interested into startups. He's had a big impact on my life. And the two of us were just a jam on, on like ideas for startups every now and then. And his background was also in AI data science. And we had a couple of ideas, but given that we were working full times, we were thinking about, uh, so we participated in Hack Zurich. That's, uh, Europe's biggest hackathon, um, or at least was at the time. And we said, Hey, this is just a weekend. Let's just try out an idea, like hack something together and see how it works. And the idea was that we'd be able to search through podcast episodes, like within a podcast. Yeah. So we did that. Long story short, uh, we managed to do it like to build something that we realized, Hey, this actually works. You can, you can find things again in podcasts. We had like a natural language search and we pitched it on stage. And we actually won the hackathon, which was cool. I mean, we, we also, I think we had a good, um, like a good, good pitch or a good example. So we, we used the famous Joe Rogan episode with Elon Musk where Elon Musk smokes a joint. Okay. Um, it's like a two and a half hour episode. So we were on stage and then we just searched for like smoking weed and it would find that exact moment. It will play it. And it just like, come on with Elon Musk, just like smoking. Oh, so it was video as well? No, it was actually completely based on audio. But we did have the video for the presentation. Yeah. Which had a, had of course an amazing effect. Yeah. Like this gave us a lot of activation energy, but it wasn't actually about winning the hackathon. Yeah. But the interesting thing that happened was after we pitched on stage, several of the other participants, like a lot of them came up to us and started saying like, Hey, can I use this? Like I have this issue. And like some also came up and told us about other problems that they have, like very adjacent to this with a podcast. Where's like, like this. Like, could, could I use this for that as well? And that was basically the, the moment where I realized, Hey, it's actually not just us who are having these issues with, with podcasts and getting to the, making the most out of this knowledge. Yeah. The other people. Yeah. That was now, I guess like four years ago or something like that. And then, yeah, we decided to quit our jobs and start, start this whole snip thing. Yeah. How big is the team now? We're just four people. Yeah. Just four people. Yeah. Like four. We're all technical. Yeah. Basically two on the, the backend side. So one of my co-founders is this person who got me into machine learning and startups. And we won the hackathon together. So we have two people for the backend side with the AI and all of the other backend things. And two for the front end side, building the app.swyx [00:18:18]: Which is mostly Android and iOS. Yeah.Kevin [00:18:21]: It's iOS and Android. We also have a watch app for, for Apple, but yeah, it's mostly iOS. Yeah.swyx [00:18:27]: The watch thing, it was very funny because in the, in the Latent Space discord, you know, most of us have been slowly adopting snips. You came to me like a year ago and you introduced snip to me. I was like, I don't know. I'm, you know, I'm very sticky to overcast and then slowly we switch. Why watch?Kevin [00:18:43]: So it goes back to a lot of our users, they do something else while, while listening to a podcast, right? Yeah. And one of the, us giving them the ability to then capture this knowledge, even though they're doing something else at the same time is one of the killer features. Yeah. Maybe I can actually, maybe at some point I should maybe give a bit more of an overview of what the, all of the features that we have. Sure. So this is one of the killer features and for one big use case that people use this for is for running. Yeah. So if you're a big runner, a big jogger or cycling, like really, really cycling competitively and a lot of the people, they don't want to take their phone with them when they go running. So you load everything onto the watch. So you can download episodes. I mean, if you, if you have an Apple watch that has internet access, like with a SIM card, you can also directly stream. That's also possible. Yeah. So of course it's a, it's basically very limited to just listening and snipping. And then you can see all of your snips later on your phone. Let me tell you this error I just got.swyx [00:19:47]: Error playing episode. Substack, the host of this podcast, does not allow this podcast to be played on an Apple watch. Yeah.Kevin [00:19:52]: That's a very beautiful thing. So we found out that all of the podcasts hosted on Substack, you cannot play them on an Apple watch. Why is this restriction? What? Like, don't ask me. We try to reach out to Substack. We try to reach out to some of the bigger podcasters who are hosting the podcast on Substack to also let them know. Substack doesn't seem to care. This is not specific to our app. You can also check out the Apple podcast app. Yeah. It's the same problem. It's just that we actually have identified it. And we tell the user what's going on.swyx [00:20:25]: I would say we host our podcast on Substack, but they're not very serious about their podcasting tools. I've told them before, I've been very upfront with them. So I don't feel like I'm shitting on them in any way. And it's kind of sad because otherwise it's a perfect creative platform. But the way that they treat podcasting as an afterthought, I think it's really disappointing.Kevin [00:20:45]: Maybe given that you mentioned all these features, maybe I can give a bit of a better overview of the features that we have. Let's do that. Let's do that. So I think we're mostly in our minds. Maybe for some of the listeners.swyx [00:20:55]: I mean, I'll tell you my version. Yeah. They can correct me, right? So first of all, I think the main job is for it to be a podcast listening app. It should be basically a complete superset of what you normally get on Overcast or Apple Podcasts or anything like that. You pull your show list from ListenNotes. How do you find shows? You've got to type in anything and you find them, right?Kevin [00:21:18]: Yeah. We have a search engine that is powered by ListenNotes. Yeah. But I mean, in the meantime, we have a huge database of like 99% of all podcasts out there ourselves. Yeah.swyx [00:21:27]: What I noticed, the default experience is you do not auto-download shows. And that's one very big difference for you guys versus other apps, where like, you know, if I'm subscribed to a thing, it auto-downloads and I already have the MP3 downloaded overnight. For me, I have to actively put it onto my queue, then it auto-downloads. And actually, I initially didn't like that. I think I maybe told you that I was like, oh, it's like a feature that I don't like. Like, because it means that I have to choose to listen to it in order to download and not to... It's like opt-in. There's a difference between opt-in and opt-out. So I opt-in to every episode that I listen to. And then, like, you know, you open it and depends on whether or not you have the AI stuff enabled. But the default experience is no AI stuff enabled. You can listen to it. You can see the snips, the number of snips and where people snip during the episode, which roughly correlates to interest level. And obviously, you can snip there. I think that's the default experience. I think snipping is really cool. Like, I use it to share a lot on Discord. I think we have tons and tons of just people sharing snips and stuff. Tweeting stuff is also like a nice, pleasant experience. But like the real features come when you actually turn on the AI stuff. And so the reason I got snipped, because I got fed up with Overcast not implementing any AI features at all. Instead, they spent two years rewriting their app to be a little bit faster. And I'm like, like, it's 2025. I should have a podcast that has transcripts that I can search. Very, very basic thing. Overcast will basically never have it.Kevin [00:22:49]: Yeah, I think that was a good, like, basic overview. Maybe I can add a bit to it with the AI features that we have. So one thing that we do every time a new podcast comes out, we transcribe the episode. We do speaker diarization. We identify the speaker names. Each guest, we extract a mini bio of the guest, try to find a picture of the guest online, add it. We break the podcast down into chapters, as in AI generated chapters. That one. That one's very handy. With a quick description per title and quick description per each chapter. We identify all books that get mentioned on a podcast. You can tell I don't use that one. It depends on the podcast. There are some podcasts where the guests often recommend like an amazing book. So later on, you can you can find that again.swyx [00:23:42]: So you literally search for the word book or I just read blah, blah, blah.Kevin [00:23:46]: No, I mean, it's all LLM based. Yeah. So basically, we have we have an LLM that goes through the entire transcript and identifies if a user mentions a book, then we use perplexity API together with various other LLM orchestration to go out there on the Internet, find everything that there is to know about the book, find the cover, find who or what the author is, get a quick description of it for the author. We then check on which other episodes the author appeared on.swyx [00:24:15]: Yeah, that is killer.Kevin [00:24:17]: Because that for me, if. If there's an interesting book, the first thing I do is I actually listen to a podcast episode with a with a writer because he usually gives a really great overview already on a podcast.swyx [00:24:28]: Sometimes the podcast is with the person as a guest. Sometimes his podcast is about the person without him there. Do you pick up both?Kevin [00:24:37]: So, yes, we pick up both in like our latest models. But actually what we show you in the app, the goal is to currently only show you the guest to separate that. In the future, we want to show the other things more.swyx [00:24:47]: For what it's worth, I don't mind. Yeah, I don't think like if I like if I like somebody, I'll just learn about them regardless of whether they're there or not.Kevin [00:24:55]: Yeah, I mean, yes and no. We we we have seen there are some personalities where this can break down. So, for example, the first version that we released with this feature, it picked up much more often a person, even if it was not a guest. Yeah. For example, the best examples for me is Sam Altman and Elon Musk. Like they're just mentioned on every second podcast and it has like they're not on there. And if you're interested in it, you can go to Elon Musk. And actually like learning from them. Yeah, I see. And yeah, we updated our our algorithms, improved that a lot. And now it's gotten much better to only pick it up if they're a guest. And yeah, so this this is maybe to come back to the features, two more important features like we have the ability to chat with an episode. Yes. Of course, you can do the old style of searching through a transcript with a keyword search. But I think for me, this is this is how you used to do search and extracting knowledge in the in the past. Old school. And the A.I. Web. Way is is basically an LLM. So you can ask the LLM, hey, when do they talk about topic X? If you're interested in only a certain part of the episode, you can ask them for four to give a quick overview of the episode. Key takeaways afterwards also to create a note for you. So this is really like very open, open ended. And yeah. And then finally, the snipping feature that we mentioned just to reiterate. Yeah. I mean, here the the feature is that whenever you hear an amazing idea, you can trip. It's up your headphones or click a button in the app and the A.I. summarizes the insight you just heard and saves that together with the original transcript and audio in your knowledge library. I also noticed that you you skip dynamic content. So dynamic content, we do not skip it automatically. Oh, sorry. You detect. But we detect it. Yeah. I mean, that's one of the thing that most people don't don't actually know that like the way that ads get inserted into podcasts or into most podcasts is actually that every time you listen. To a podcast, you actually get access to a different audio file and on the server, a different ad is inserted into the MP3 file automatically. Yeah. Based on IP. Exactly. And that's what that means is if we transcribe an episode and have a transcript with timestamps like words, word specific timestamps, if you suddenly get a different audio file, like the whole time says I messed up and that's like a huge issue. And for that, we actually had to build another algorithm that would dynamically on the floor. I re sync the audio that you're listening to the transcript that we have. Yeah. Which is a fascinating problem in and of itself.swyx [00:27:24]: You sync by matching up the sound waves? Or like, or do you sync by matching up words like you basically do partial transcription?Kevin [00:27:33]: We are not matching up words. It's happening on the basically a bytes level matching. Yeah. Okay.swyx [00:27:40]: It relies on this. It relies on the exact match at some point.Kevin [00:27:46]: So it's actually. We're actually not doing exact matches, but we're doing fuzzy matches to identify the moment. It's basically, we basically built Shazam for podcasts. Just as a little side project to solve this issue.swyx [00:28:02]: Actually, fun fact, apparently the Shazam algorithm is open. They published the paper, it's talked about it. I haven't really dived into the paper. I thought it was kind of interesting that basically no one else has built Shazam.Kevin [00:28:16]: Yeah, I mean, well, the one thing is the algorithm. If you now talk about Shazam, the other thing is also having the database behind it and having the user mindset that if they have this problem, they come to you, right?swyx [00:28:29]: Yeah, I'm very interested in the tech stack. There's a big data pipeline. Could you share what is the tech stack?Kevin [00:28:35]: What are the most interesting or challenging pieces of it? So the general tech stack is our entire backend is, or 90% of our backend is written in Python. Okay. Hosting everything on Google Cloud Platform. And our front end is written with, well, we're using the Flutter framework. So it's written in Dart and then compiled natively. So we have one code base that handles both Android and iOS. You think that was a good decision? It's something that a lot of people are exploring. So up until now, yes. Okay. Look, it has its pros and cons. Some of the, you know, for example, earlier, I mentioned we have a Apple Watch app. Yeah. I mean, there's no Flutter for that, right? So that you build native. And then of course you have to sort of like sync these things together. I mean, I'm not the front end engineer, so I'm not just relaying this information, but our front end engineers are very happy with it. It's enabled us to be quite fast and be on both platforms from the very beginning. And when I talk with people and they hear that we are using Flutter, usually they think like, ah, it's not performant. It's super junk, janky and everything. And then they use it. They use our app and they're always super surprised. Or if they've already used our app, I couldn't tell them. They're like, what? Yeah. Um, so there is actually a lot that you can do with it.swyx [00:29:51]: The danger, the concern, there's a few concerns, right? One, it's Google. So when were they, when are they going to abandon it? Two, you know, they're optimized for Android first. So iOS is like a second, second thought, or like you can feel that it is not a native iOS app. Uh, but you guys put a lot of care into it. And then maybe three, from my point of view, JavaScript, as a JavaScript guy, React Native was supposed to be there. And I think that it hasn't really fulfilled that dream. Um, maybe Expo is trying to do that, but, um, again, it is not, does not feel as productive as Flutter. And I've, I spent a week on Flutter and dot, and I'm an investor in Flutter flow, which is the local, uh, Flutter, Flutter startup. That's doing very, very well. I think a lot of people are still Flutter skeptics. Yeah. Wait. So are you moving away from Flutter?Kevin [00:30:41]: I don't know. We don't have plans to do that. Yeah.swyx [00:30:43]: You're just saying about that. What? Yeah. Watch out. Okay. Let's go back to the stack.Kevin [00:30:47]: You know, that was just to give you a bit of an overview. I think the more interesting things are, of course, on the AI side. So we, like, as I mentioned earlier, when we started out, it was before chat GPT for the chat GPT moment before there was the GPT 3.5 turbo, uh, API. So in the beginning, we actually were running everything ourselves, open source models, try to fine tune them. They worked. There was us, but let's, let's be honest. They weren't. What was the sort of? Before Whisper, the transcription. Yeah, we were using wave to work like, um, there was a Google one, right? No, it was a Facebook, Facebook one. That was actually one of the papers. Like when that came out for me, that was one of the reasons why I said we, we should try something to start a startup in the audio space. For me, it was a bit like before that I had been following the NLP space, uh, quite closely. And as, as I mentioned earlier, we, we did some stuff at the startup as well, that I was working up. But before, and wave to work was the first paper that I had at least seen where the whole transformer architecture moved over to audio and bit more general way of saying it is like, it was the first time that I saw the transformer architecture being applied to continuous data instead of discrete tokens. Okay. And it worked amazingly. Ah, and like the transformer architecture plus self-supervised learning, like these two things moved over. And then for me, it was like, Hey, this is now going to take off similarly. It's the text space has taken off. And with these two things in place, even if some features that we want to build are not possible yet, they will be possible in the near term, uh, with this, uh, trajectory. So that was a little side, side note. No, it's in the meantime. Yeah. We're using whisper. We're still hosting some of the models ourselves. So for example, the whole transcription speaker diarization pipeline, uh,swyx [00:32:38]: You need it to be as cheap as possible.Kevin [00:32:40]: Yeah, exactly. I mean, we're doing this at scale where we have a lot of audio.swyx [00:32:44]: We're what numbers can you disclose? Like what, what are just to give people an idea because it's a lot. So we have more than a million podcasts that we've already processed when you say a million. So processing is basically, you have some kind of list of podcasts that you will auto process and others where a paying pay member can choose to press the button and transcribe it. Right. Is that the rough idea? Yeah, exactly.Kevin [00:33:08]: Yeah. And if, when you press that button or we also transcribe it. Yeah. So first we do the, we do the transcription. We do the. The, the speaker diarization. So basically you identify speech blocks that belong to the same speaker. This is then all orchestrated within, within LLM to identify which speech speech block belongs to which speaker together with, you know, we identify, as I mentioned earlier, we identify the guest name and the bio. So all of that comes together with an LLM to actually then assign assigned speaker names to, to each block. Yeah. And then most of the rest of the, the pipeline we've now used, we've now migrated to LLM. So we use mainly open AI, Google models, so the Gemini models and the open AI models, and we use some perplexity basically for those things where we need, where we need web search. Yeah. That's something I'm still hoping, especially open AI will also provide us an API. Oh, why? Well, basically for us as a consumer, the more providers there are.swyx [00:34:07]: The more downtime.Kevin [00:34:08]: The more competition and it will lead to better, better results. And, um, lower costs over time. I don't, I don't see perplexity as expensive. If you use the web search, the price is like $5 per a thousand queries. Okay. Which is affordable. But, uh, if you compare that to just a normal LLM call, um, it's, it's, uh, much more expensive. Have you tried Exa? We've, uh, looked into it, but we haven't really tried it. Um, I mean, we, we started with perplexity and, uh, it works, it works well. And if I remember. Correctly, Exa is also a bit more expensive.swyx [00:34:45]: I don't know. I don't know. They seem to focus on the search thing as a search API, whereas perplexity, maybe more consumer-y business that is higher, higher margin. Like I'll put it like perplexity is trying to be a product, Exa is trying to be infrastructure. Yeah. So that, that'll be my distinction there. And then the other thing I will mention is Google has a search grounding feature. Yeah. Which you, which you might want. Yeah.Kevin [00:35:07]: Yeah. We've, uh, we've also tried that out. Um, not as good. So we, we didn't, we didn't go into. Too much detail in like really comparing it, like quality wise, because we actually already had the perplexity one and it, and it's, and it's working. Yeah. Um, I think also there, the price is actually higher than perplexity. Yeah. Really? Yeah.swyx [00:35:26]: Google should cut their prices.Kevin [00:35:29]: Maybe it was the same price. I don't want to say something incorrect, but it wasn't cheaper. It wasn't like compelling. And then, then there was no reason to switch. So, I mean, maybe like in general, like for us, given that we do work with a lot of content, price is actually something that we do look at. Like for us, it's not just about taking the best model for every task, but it's really getting the best, like identifying what kind of intelligence level you need and then getting the best price for that to be able to really scale this and, and provide us, um, yeah, let our users use these features with as many podcasts as possible. Yeah.swyx [00:36:03]: I wanted to double, double click on diarization. Yeah. Uh, it's something that I don't think people do very well. So you know, I'm, I'm a, I'm a B user. I don't have it right now. And, and they were supposed to speak, but they dropped out last minute. Um, but, uh, we've had them on the podcast before and it's not great yet. Do you use just PI Anode, the default stuff, or do you find any tricks for diarization?Kevin [00:36:27]: So we do use the, the open source packages, but we have tweaked it a bit here and there. For example, if you mentioned the BAI guys, I actually listened to the podcast episode was super nice. Thank you. And when you started talking about speaker diarization, and I just have to think about, uh, I don't know.Kevin [00:36:49]: Is it possible? I don't know. I don't know. F**k this. Yeah, no, I don't know.Kevin [00:36:55]: Yeah. We are the best. This is a.swyx [00:37:07]: I don't know. This is the best. I don't know. This is the best. Yeah. Yeah. Yeah. You're doing good.Kevin [00:37:12]: So, so yeah. This is great. This is good. Yeah. No, so that of course helps us. Another thing that helps us is that we know certain structural aspects of the podcast. For example, how often does someone speak? Like if someone, like let's say there's a one hour episode and someone speaks for 30 seconds, that person is most probably not the guest and not the host. It's probably some ad, like some speaker from an ad. So we have like certain of these heuristics that we can use and we leverage to improve things. And in the past, we've also changed the clustering algorithm. So basically how a lot of the speaker diarization works is you basically create an embedding for the speech that's happening. And then you try to somehow cluster these embeddings and then find out this is all one speaker. This is all another speaker. And there we've also tweaked a couple of things where we again used heuristics that we could apply from knowing how podcasts function. And that's also actually why I was feeling so much with the BAI guys, because like all of these heuristics, like for them, it's probably almost impossible to use any heuristics because it can just be any situation, anything.Kevin [00:38:34]: So that's one thing that we do. Yeah, another thing is that we actually combine it with LLM. So the transcript, LLMs and the speaker diarization, like bringing all of these together to recalibrate some of the switching points. Like when does the speaker stop? When does the next one start?swyx [00:38:51]: The LLMs can add errors as well. You know, I wouldn't feel safe using them to be so precise.Kevin [00:38:58]: I mean, at the end of the day, like also just to not give a wrong impression, like the speaker diarization is also not perfect that we're doing, right? I basically don't really notice it.swyx [00:39:08]: Like I use it for search.Kevin [00:39:09]: Yeah, it's not perfect yet, but it's gotten quite good. Like, especially if you compare, if you look at some of the, like if you take a latest episode and you compare it to an episode that came out a year ago, we've improved it quite a bit.swyx [00:39:23]: Well, it's beautifully presented. Oh, I love that I can click on the transcript and it goes to the timestamp. So simple, but you know, it should exist. Yeah, I agree. I agree. So this, I'm loading a two hour episode of Detect Me Right Home, where there's a lot of different guests calling in and you've identified the guest name. And yeah, so these are all LLM based. Yeah, it's really nice.Kevin [00:39:49]: Yeah, like the speaker names.swyx [00:39:50]: I would say that, you know, obviously I'm a power user of all these tools. You have done a better job than Descript. Okay, wow. Descript is so much funding. They had their open AI invested in them and they still suck. So I don't know, like, you know, keep going. You're doing great. Yeah, thanks. Thanks.Kevin [00:40:12]: I mean, I would, I would say that, especially for anyone listening who's interested in building a consumer app with AI, I think the, like, especially if your background is in AI and you love working with AI and doing all of that, I think the most important thing is just to keep reminding yourself of what's actually the job to be done here. Like, what does actually the consumer want? Like, for example, you now were just delighted by the ability to click on this word and it jumps there. Yeah. Like, this is not, this is not rocket science. This is, like, you don't have to be, like, I don't know, Android Kapathi to come up with that and build that, right? And I think that's, that's something that's super important to keep in mind.swyx [00:40:52]: Yeah, yeah. Amazing. I mean, there's so many features, right? It's, it's so packed. There's quotes that you pick up. There's summarization. Oh, by the way, I'm going to use this as my official feature request. I want to customize what, how it's summarized. I want to, I want to have a custom prompt. Yeah. Because your summarization is good, but, you know, I have different preferences, right? Like, you know.Kevin [00:41:14]: So one thing that you can already do today, I completely get your feature request. And I think it just.swyx [00:41:18]: I'm sure people have asked it.Kevin [00:41:19]: I mean, maybe just in general as a, as a, how I see the future, you know, like in the future, I think all, everything will be personalized. Yeah, yeah. Like, not, this is not specific to us. Yeah. And today we're still in a, in a phase where the cost of LLMs, at least if you're working with, like, such long context windows. As us, I mean, there's a lot of tokens in, if you take an entire podcast, so you still have to take that cost into consideration. So if for every single user, we regenerate it entirely, it gets expensive. But in the future, this, you know, cost will continue to go down and then it will just be personalized. So that being said, you can already today, if you go to the player screen. Okay. And open up the chat. Yeah. You can go to the, to the chat. Yes. And just ask for a summary in your style.swyx [00:42:13]: Yeah. Okay. I mean, I, I listen to consume, you know? Yeah. Yeah. I, I've never really used this feature. I don't know. I think that's, that's me being a slow adopter. No, no. I mean, that's. It has, when does the conversation start? Okay.Kevin [00:42:26]: I mean, you can just type anything. I think what you're, what you're describing, I mean, maybe that is also an interesting topic to talk about. Yes. Where, like, basically I told you, like, look, we have this chat. You can just ask for it. Yeah. And this is, this is how ChatGPT works today. But if you're building a consumer app, you have to move beyond the chat box. People do not want to always type out what they want. So your feature request was, even though theoretically it's already possible, what you are actually asking for is, hey, I just want to open up the app and it should just be there in a nicely formatted way. Beautiful way such that I can read it or consume it without any issues. Interesting. And I think that's in general where a lot of the, the. Opportunities lie currently in the market. If you want to build a consumer app, taking the capability and the intelligence, but finding out what the actual user interface is the best way how a user can engage with this intelligence in a natural way.swyx [00:43:24]: Is this something I've been thinking about as kind of like AI that's not in your face? Because right now, you know, we like to say like, oh, use Notion has Notion AI. And we have the little thing there. And there's, or like some other. Any other platform has like the sparkle magic wand emoji, like that's our AI feature. Use this. And it's like really in your face. A lot of people don't like it. You know, it should just kind of become invisible, kind of like an invisible AI.Kevin [00:43:49]: 100%. I mean, the, the way I see it as AI is, is the electricity of, of the future. And like no one, like, like we don't talk about, I don't know, this, this microphone uses electricity, this phone, you don't think about it that way. It's just in there, right? It's not an electricity enabled product. No, it's just a product. Yeah. It will be the same with AI. I mean, now. It's still a, something that you use to market your product. I mean, we do, we do the same, right? Because it's still something that people realize, ah, they're doing something new, but at some point, no, it'll just be a podcast app and it will be normal that it has all of this AI in there.swyx [00:44:24]: I noticed you do something interesting in your chat where you source the timestamps. Yeah. Is that part of this prompt? Is there a separate pipeline that adds source sources?Kevin [00:44:33]: This is, uh, actually part of the prompt. Um, so this is all prompt engine. Engineering, um, uh, you should be able to click on it. Yeah, I clicked on it. Um, this is all prompt engineering with how to provide the, the context, you know, we, because we provide all of the transcript, how to provide the context and then, yeah, I get them all to respond in a correct way with a certain format and then rendering that on the front end. This is one of the examples where I would say it's so easy to create like a quick demo of this. I mean, you can just go to chat to be deep, paste this thing in and say like, yeah, do this. Okay. Like 15 minutes and you're done. Yeah. But getting this to like then production level that it actually works 99% of the time. Okay. This is then where, where the difference lies. Yeah. So, um, for this specific feature, like we actually also have like countless regexes that they're just there to correct certain things that the LLM is doing because it doesn't always adhere to the format correctly. And then it looks super ugly on the front end. So yeah, we have certain regexes that correct that. And maybe you'd ask like, why don't you use an LLM for that? Because that's sort of the, again, the AI native way, like who uses regexes anymore. But with the chat for user experience, it's very important that you have the streaming because otherwise you need to wait so long until your message has arrived. So we're streaming live the, like, just like ChatGPT, right? You get the answer and it's streaming the text. So if you're streaming the text and something is like incorrect. It's currently not easy to just like pipe, like stream this into another stream, stream this into another stream and get the stream back, which corrects it, that would be amazing. I don't know, maybe you can answer that. Do you know of any?swyx [00:46:19]: There's no API that does this. Yeah. Like you cannot stream in. If you own the models, you can, uh, you know, whatever token sequence has, has been emitted, start loading that into the next one. If you fully own the models, uh, I don't, it's probably not worth it. That's what you do. It's better. Yeah. I think. Yeah. Most engineers who are new to AI research and benchmarking actually don't know how much regexing there is that goes on in normal benchmarks. It's just like this ugly list of like a hundred different, you know, matches for some criteria that you're looking for. No, it's very cool. I think it's, it's, it's an example of like real world engineering. Yeah. Do you have a tooling that you're proud of that you've developed for yourself?Kevin [00:47:02]: Is it just a test script or is it, you know? I think it's a bit more, I guess the term that has come up is, uh, vibe coding, uh, vibe coding, some, no, sorry, that's actually something else in this case, but, uh, no, no, yes, um, vibe evals was a term that in one of the talks actually on, on, um, I think it might've been the first, the first or the first day at the conference, someone brought that up. Yeah. Uh, because yeah, a lot of the talks were about evals, right. Which is so important. And yeah, I think for us, it's a bit more vibe. Evals, you know, that's also part of, you know, being a startup, we can take risks, like we can take the cost of maybe sometimes it failing a little bit or being a little bit off and our users know that and they appreciate that in return, like we're moving fast and iterating and building, building amazing things, but you know, a Spotify or something like that, half of our features will probably be in a six month review through legal or I don't know what, uh, before they could sell them out.swyx [00:48:04]: Let's just say Spotify is not very good at podcasting. Um, I have a documented, uh, dislike for, for their podcast features, just overall, really, really well integrated any other like sort of LLM focused engineering challenges or problems that you, that you want to highlight.Kevin [00:48:20]: I think it's not unique to us, but it goes again in the direction of handling the uncertainty of LLMs. So for example, with last year, at the end of the year, we did sort of a snipped wrapped. And one of the things we thought it would be fun to, just to do something with, uh, with an LLM and something with the snips that, that a user has. And, uh, three, let's say unique LLM features were that we assigned a personality to you based on the, the snips that, that you have. It was, I mean, it was just all, I guess, a bit of a fun, playful way. I'm going to look up mine. I forgot mine already.swyx [00:48:57]: Um, yeah, I don't know whether it's actually still in the, in the, we all took screenshots of it.Kevin [00:49:01]: Ah, we posted it in the, in the discord. And the, the second one, it was, uh, we had a learning scorecard where we identified the topics that you snipped on the most, and you got like a little score for that. And the third one was a, a quote that stood out. And the quote is actually a very good example of where we would run that for user. And most of the time it was an interesting quote, but every now and then it was like a super boring quotes that you think like, like how, like, why did you select that? Like, come on for there. The solution was actually just to say, Hey, give me five. So it extracted five quotes as a candidate, and then we piped it into a different model as a judge, LLM as a judge, and there we use a, um, a much better model because with the, the initial model, again, as, as I mentioned also earlier, we do have to look at the, like the, the costs because it's like, we have so much text that goes into it. So we, there we use a bit more cheaper model, but then the judge can be like a really good model to then just choose one out of five. This is a practical example.swyx [00:50:03]: I can't find it. Bad search in discord. Yeah. Um, so, so you do recommend having a much smarter model as a judge, uh, and that works for you. Yeah. Yeah. Interesting. I think this year I'm very interested in LM as a judge being more developed as a concept, I think for things like, you know, snips, raps, like it's, it's fine. Like, you know, it's, it's, it's, it's entertaining. There's no right answer.Kevin [00:50:29]: I mean, we also have it. Um, we also use the same concept for our books feature where we identify the, the mention. Books. Yeah. Because there it's the same thing, like 90% of the time it, it works perfectly out of the box one shot and every now and then it just, uh, starts identifying books that were not really mentioned or that are not books or made, yeah, starting to make up books. And, uh, they are basically, we have the same thing of like another LLM challenging it. Um, yeah. And actually with the speakers, we do the same now that I think about it. Yeah. Um, so I'm, I think it's a, it's a great technique. Interesting.swyx [00:51:05]: You run a lot of calls.Kevin [00:51:07]: Yeah.swyx [00:51:08]: Okay. You know, you mentioned costs. You move from self hosting a lot of models to the, to the, you know, big lab models, open AI, uh, and Google, uh, non-topic.Kevin [00:51:18]: Um, no, we love Claude. Like in my opinion, Claude is the, the best one when it comes to the way it formulates things. The personality. Yeah. The personality. Okay. I actually really love it. But yeah, the cost is. It's still high.swyx [00:51:36]: So you cannot, you tried Haiku, but you're, you're like, you have to have Sonnet.Kevin [00:51:40]: Uh, like basically we like with Haiku, we haven't experimented too much. We obviously work a lot with 3.5 Sonnet. Uh, also, you know, coding. Yeah. For coding, like in cursor, just in general, also brainstorming. We use it a lot. Um, I think it's a great brainstorm partner, but yeah, with, uh, with, with a lot of things that we've done done, we opted for different models.swyx [00:52:00]: What I'm trying to drive at is how much cheaper can you get if you go from cloud to cloud? Closed models to open models. And maybe it's like 0% cheaper, maybe it's 5% cheaper, or maybe it's like 50% cheaper. Do you have a sense?Kevin [00:52:13]: It's very difficult to, to judge that. I don't really have a sense, but I can, I can give you a couple of thoughts that have gone through our minds over the time, because obviously we do realize like, given that we, we have a couple of tasks where there are just so many tokens going in, um, at some point it will make sense to, to offload some of that. Uh, to an open source model, but going back to like, we're, we're a startup, right? Like we're not an AI lab or whatever, like for us, actually the most important thing is to iterate fast because we need to learn from our users, improve that. And yeah, just this velocity of this, these iterations. And for that, the closed models hosted by open AI, Google is, uh, and swapping, they're just unbeatable because you just, it's just an API call. Yeah. Um, so you don't need to worry about. Yeah. So much complexity behind that. So this is, I would say the biggest reason why we're not doing more in this space, but there are other thoughts, uh, also for the future. Like I see two different, like we basically have two different usage patterns of LLMs where one is this, this pre-processing of a podcast episode, like this initial processing, like the transcription, speaker diarization, chapterization. We do that once. And this, this usage pattern it's, it's quite predictable. Because we know how many podcasts get released when, um, so we can sort of have a certain capacity and we can, we, we're running that 24 seven, it's one big queue running 24 seven.swyx [00:53:44]: What's the queue job runner? Uh, is it a Django, just like the Python one?Kevin [00:53:49]: No, that, that's just our own, like our database and the backend talking to the database, picking up jobs, finding it back. I'm just curious in orchestration and queues. I mean, we, we of course have like, uh, a lot of other orchestration where we're, we're, where we use, uh, the Google pub sub, uh, thing, but okay. So we have this, this, this usage pattern of like very predictable, uh, usage, and we can max out the, the usage. And then there's this other pattern where it's, for example, the snippet where it's like a user, it's a user action that triggers an LLM call and it has to be real time. And there can be moments where it's by usage and there can be moments when there's very little usage for that. There. So that's, that's basically where these LLM API calls are just perfect because you don't need to worry about scaling this up, scaling this down, um, handling, handling these issues. Serverless versus serverful.swyx [00:54:44]: Yeah, exactly. Okay.Kevin [00:54:45]: Like I see them a bit, like I see open AI and all of these other providers, I see them a bit as the, like as the Amazon, sorry, AWS of, of AI. So it's a bit similar how like back before AWS, you would have to have your, your servers and buy new servers or get rid of servers. And then with AWS, it just became so much easier to just ramp stuff up and down. Yeah. And this is like the taking it even, even, uh, to the next level for AI. Yeah.swyx [00:55:18]: I am a big believer in this. Basically it's, you know, intelligence on demand. Yeah. We're probably not using it enough in our daily lives to do things. I should, we should be able to spin up a hundred things at once and go through things and then, you know, stop. And I feel like we're still trying to figure out how to use LLMs in our lives effectively. Yeah. Yeah.Kevin [00:55:38]: 100%. I think that goes back to the whole, like that, that's for me where the big opportunity is for, if you want to do a startup, um, it's not about, but you can let the big labs handleswyx [00:55:48]: the challenge of more intelligence, but, um, it's the... Existing intelligence. How do you integrate? How do you actually incorporate it into your life? AI engineering. Okay, cool. Cool. Cool. Cool. Um, the one, one other thing I wanted to touch on was multimodality in frontier models. Dwarcash had a interesting application of Gemini recently where he just fed raw audio in and got diarized transcription out or timestamps out. And I think that will come. So basically what we're saying here is another wave of transformers eating things because right now models are pretty much single modality things. You know, you have whisper, you have a pipeline and everything. Yeah. You can't just say, Oh, no, no, no, we only fit like the raw, the raw files. Do you think that will be realistic for you? I 100% agree. Okay.Kevin [00:56:38]: Basically everything that we talked about earlier with like the speaker diarization and heuristics and everything, I completely agree. Like in the, in the future that would just be put everything into a big multimodal LLM. Okay. And it will output, uh, everything that you want. Yeah. So I've also experimented with that. Like just... With, with Gemini 2? With Gemini 2.0 Flash. Yeah. Just for fun. Yeah. Yeah. Because the big difference right now is still like the cost difference of doing speaker diarization this way or doing transcription this way is a huge difference to the pipeline that we've built up. Huh. Okay.swyx [00:57:15]: I need to figure out what, what that cost is because in my mind 2.0 Flash is so cheap. Yeah. But maybe not cheap enough for you.Kevin [00:57:23]: Uh, no, I mean, if you compare it to, yeah, whisper and speaker diarization and especially self-hosting it and... Yeah. Yeah. Yeah.swyx [00:57:30]: Yeah.Kevin [00:57:30]: Okay. But we will get there, right? Like this is just a question of time.swyx [00:57:33]: And, um, at some point, as soon as that happens, we'll be the first ones to switch. Yeah. Awesome. Anything else that you're like sort of eyeing on the horizon as like, we are thinking about this feature, we're thinking about incorporating this new functionality of AI into our, into our app? Yeah.Kevin [00:57:50]: I mean, we, there's so many areas that we're thinking about, like our challenge is a bit more... Choosing. Yeah. Choosing. Yeah. So, I mean, I think for me, like looking into like the next couple of years, like the big areas that interest us a lot, basically four areas, like one is content. Um, right now it's, it's podcasts. I mean, you did mention, I think you mentioned like you can also upload audio books and YouTube videos. YouTube. I actually use the YouTube one a fair amount. But in the future, we, we want to also have audio books natively in the app. And, uh, we want to enable AI generated content. Like just think of, take deep research and notebook analysis. Like put these together. That should be, that should be in our app. The second area is discovery. I think in general. Yeah.swyx [00:58:38]: I noticed that you don't have, so you

It was a fulfilling weekend getting to see everyone that came out to the Theory Sabers booth at Megacon Fan Expo Orlando. It was nice seeing my toxic friends like  @GeeksandGamers   @ryankinel-rkoutpost1   @youngrippa59   @TheCriticalDrinker  and  @TheStupendousWave  ( @Drunk3PO  )... Can't wait to see you all of course again next year, but until then, we'll se coming to a new Fan Expo every month in the USA and having the Theory Sabers team there with me. I hope you're excited for all the new vlogs and adventures to come all with the final goal of Vader Episode 2 and 3 which is looking beyond amazing. Our new limited edition Snips sabers are about to launch on Monday at midnight PST March 17th THEORY SABERS - https://theorysabers.com/ Learn more about your ad choices. Visit megaphone.fm/adchoices

The freshly clipped wings of the Hill Kings find the duo of Brad Hild & Chris Covey in the nest of Kevin & Thomas at Oops All Segments. After Brad dishes on his vasectomy, the quadrant go trio as Thomas (soon Travis) signs off.Then the trio dive into the life of Jim Varney before playing My Movie.Then the Hill Kings take over control as Chris walks us through a draft of hot male cartoon characters and everyone balls out with Brad's new game.00:00 Intro & Check Ins10:24 Sign Off12:31 The Importance of Being Varney16:58 My Movie32:08 Cartoon Boys that Make Your Wolf Eyes Bug Out48:15 Snips, All Wieners Hill Kings Podcast:https://podcasts.apple.com/us/podcast/hill-kings-podcast/id1710916157https://www.youtube.com/channel/UCF8g96pJfgKOXmz7Mj_1xiACheck out our DnD show: 'What We Do in the Basement': https://podcasts.apple.com/ca/podcast/what-we-do-in-the-basement/id1552947049FOLLOW Oops All Segments on Instagram: www.instagram.com/oopsallsegmentsFOLLOW Oops All Segments on TikTok: www.tiktok.com/@oopsallsegmentsSUBSCRIBE to Oops All Segments on YouTube: www.youtube.com/@oopsallsegments

Hallo Star Wars- und Cosplay-Fans! In der neuesten Episode vom Heir to the Empire - Cos-Talk treffe ich auf Sarah und Holger, auch bekannt als Lady_Snips und ObiDKenobi Wir sprechen über ihre Lego "Vergangenheit", warum ein Helmträger-Cosplay auch sehr gut tun kann und ihre gefühlte zweite Heimat in Paris. Hört rein, lasst euch inspirieren und schreibt uns eure Meinung zur Folge in die Kommentare – wir freuen uns auf euer Feedback!

The Star Wars: The Clone Wars animated movie marked a pivotal moment in Star Wars history, though its initial reception was mixed. In this episode of Star Wars Generations, hosts Matthew, Alex, and Erin explore how this 2008 theatrical release laid crucial groundwork for the beloved Star Wars: The Clone Wars TV series while introducing key characters like Ahsoka Tano and Asajj Ventress.Was giving Anakin Skywalker a Padawan learner actually a good idea? The hosts debate whether Yoda and Obi-Wan's decision to pair him with Ahsoka helped ground him or ultimately contributed to his fall. They examine Yoda's prescient warning that, while Anakin was ready for a Padawan, he wasn't ready to let one go.How did the movie handle the moral complexities of the Clone Wars? The hosts discuss the significance of the Jedi being forced to work with criminal elements like Jabba the Hutt, drawing parallels to real-world wartime compromises and examining how this eroded Jedi principles.What was the significance of Asajj Ventress's introduction? The conversation explores her complex dynamic with Obi-Wan Kenobi and how their flirtatious antagonism would develop throughout the series.Other Topics Covered:The hosts' personal experiences watching the film at different agesRex and Ahsoka's early dynamic and the realities of military command structuresThe evolution of Christopher Lee and Samuel L. Jackson voicing their live-action charactersThe development of Anakin and Ahsoka's teaching relationshipThe origins of nicknames like "Snips" and "Sky Guy"Padmé's characterization and how it maintained her proactive role from Attack of the ClonesThe episode concludes by reflecting on how the movie, despite its initial lukewarm reception, successfully established character dynamics and themes that would become central to Star Wars: The Clone Wars series while planting early seeds of Anakin's eventual fall to the dark side. **************************************************************************This episode is a production of Star Wars Generations, a The Ethical Panda Podcast and part of the TruStory FM Entertainment Podcast Network. Check our our website to find out more about this and our sister podcast Superhero Ethics.We want to hear from you! You can keep up with our latest news, and send us feedback, questions, or comments via social media or email.Email: Matthew@TheEthicalPanda.comFacebook: TheEthicalPandaInstagram: TheEthicalPandaPodcastsTwitter: EthicalPanda77Or you can join jump into the Star Wars Generations and Superhero Ethics channels on the TruStory FM Discord.To learn more about co-host Erin and her incredible cosplay check out her Instagram, LadyTanoCreates.Want to get access to even more content while supporting the podcast? Become a member! For $5 a month, or $55 a year you get access to bonus episodes and bonus content at the end of most episodes. Sign up on the podcast's main page you can even give membership as a gift!You can also support our podcasts through our sponsors:Purchase a lightsaber from Level Up Sabers run by friend of the podcast Neighborhood Master AlanUse Audible for audiobooks. Sign up for a one year membership or gift one through this link.Purchase any media discussed this week through our sponsored links.

ASMR Scissors No Talking Snips and Cutting PaperAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

On this episode of BREAKING TAKES, Sam and Zach discuss the Russian government branding Santa Claus a foreign agent of capitalist society, Sam's mutual Facebook connections with Luigi Mangione, the odd tradition of babies getting circumcised by a Rabbi, the best ways to ride that drinking line around Christmas, and more.  SUBSCRIBE TO BREAKING TAKES PREMIUM: https://breakingtakes.supercast.com/ BREAKING TAKES LINKS: Instagram: https://www.instagram.com/breakingtakes/TikTok: https://www.tiktok.com/@breakingtakesApple: https://apple.co/3K4Yny2Spotify: https://spoti.fi/3pThWCtOvercast: https://bit.ly/43uz1AyPremium: https://breakingtakes.supercast.com/ 

Remember the old poem about the secret ingredients for boys and girls? Snips and snails for boys, sugar and spice for girls. It wasn't just a silly rhyme; it hinted at a truth: boys and girls experience the world differently. This applies to neurodivergence too. Autism and ADHD can manifest differently in males and females, leading to misdiagnosis or underdiagnosis in women. For parents, this raises a crucial question: how can we ensure that neurodiverse children, regardless of gender, feel seen, understood, and supported? On this episode, we'll visit a Connecticut school that intentionally considers gender in its approach to educating students. Our expert panel will discuss how boys and girls experience neurodivergence differently and offer strategies for parents and educators. And later, you'll meet our latest Difference Makers: a Hollywood couple using their influence to cast neurodiverse families in leading roles helping to support autistic children's journeys. --- Support this podcast: https://podcasters.spotify.com/pod/show/a-world-of-difference/support

Frank talks about the prevalence of short-length media. He also opens listener mail. He then gives the UFO Report on mysterious orbs hovering above Manchester Airport. Learn more about your ad choices. Visit megaphone.fm/adchoices

PJ talks to Joe about how community comes together to help more people have the Christmas they deserve. Hosted on Acast. See acast.com/privacy for more information.

ASMR Scissors No Talking Snips and Cutting PaperAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

//EGG AND CHOPPED CHEE' WITH THE S&P //MEMORIES, UNWELCOME, BREAKING THROUGH //AND A VERY HAPPY HALLOWEEN The Wrong Station presents to you on this eve, several snips, somewhat curtailed, of a nature appropriate for the season. --Written by Anthony Botelho, Jacob Duarte Spiel, and Alexander Saxton, and performed by Anthony Botelho. Support The Wrong Station by subscribing at www.patreon.com/thewrongstation. The Wrong Station contains explicit content and mature themes. Episode-specific warnings can be found at www.wrongstation.com/c-w. Learn more about your ad choices. Visit megaphone.fm/adchoices

In this very special interview episode, I am talking to Dave Wain, the proprietor of one of the only TWO remaining Video Stores in the UK! His store is called Snips Movies and we go in depth talking about how the store got started and how they have hung on since 1995 to the present day. Lots of general talk about physical media here - physical media vs. streaming and so forth. Great chat with a great film lover and a gentleman. Check out Dave's Weekly YouTube show "Inside the Video Store" on his channel here: https://www.youtube.com/@UCoF5_IyuGtGcZSUjLipJ7tg https://www.youtube.com/@snipsmovies Also check Dave out on socials here: https://x.com/thedavewain?lang=en https://www.instagram.com/snipsmovies/?hl=en This week's episode is also brought to you by the fine folks at DiabolikDVD - a great place to buy your discs from! https://www.diabolikdvd.com/ Just the Discs Now has a YouTube Channel! Check it out here and subscribe! https://www.youtube.com/channel/UCffVK8TcUyjCpr0F9SpV53g Follow the Show on Twitter here for Episode previews and new Blu-ray News! twitter.com/justthediscspod We're also on Instagram! instagram.com/justthediscspod/

Struggling to lose weight, low libido, or feeling sluggish? Napping every day? Or just wanting to learn more about your thyroid? Dr. Amie shares secrets about your thyroid health in this comprehensive 'thyroid 101' episode. New episodes of Welcome to Wellness released every Friday. Not listening on Spotify? Find additional show notes with hyperlinks on my website: https://www.ashleydeeley.com/w2w/thyroid Buy T2 here (Code: WELCOMEWELLNESS) 2:24: Functions of the thyroid 6:19: The importance of thyroid health on the cognitive development of a child in utero (why it's a good idea to get your thyroid tested before trying to get pregnant) 9:40: Joint problems when taking thyroid medication? Maybe you're not a good converter of T4 or allergic to the fillers 11:29: Ask your doctor for a full thyroid panel, including: TSH Total and Free T4 Total and Free T3 Reverse T3 Thyroid Peroxidase Antibodies (TPO) Thyroglobulin Antibodies (TGA) 14:21: Optimal ranges (Dr. Amie's free guide for optimal thyroid lab ranges) TSH = below a 2 T4 = 0.8 - 1.2 T3 = 3+ (or in upper quadrant of range) Reverse T3= below 15 if T3 is optimal (below 12 if working on optimization) TPO = 0 TPA = 0 (ANY antibodies show the start of autoimmunity) 19:25: Once on thyroid medication, do you need to be on it for life? 20:58: How to support your thyroid: Go gluten-free Supplement with cumin seed oil Supplement with minerals Supplement with iodine Supplement with fulvic acid Supplement with Vitamin D Supplement with Magnesium 24:11: Black Cumin Seed Oil reduces inflammation, helps with weight loss, helps stimulate hair growth, and is protective against cancer 26:49: Ditch fluoride to improve thyroid health (invest in a quality water filter which removes fluoride and opt for fluoride-free toothpaste) 28:51: Consider buying a pre-loved car and secondhand furniture to avoid toxic off-gassing which can threaten thyroid health 32:59: 80% of people with Hashimoto's cannot tolerate NDT (natural desiccated thyroid) because it produces an immune response 36:00: How do you know if you don't convert T4? 38:25: Snips to test your thyroid (genetic testing: DIO1 and DIO2) 39:07: Difference between Hashimoto's and Graves disease 40:43: At-home tests for thyroid 47:49: How T2 can boost your energy, libido, and help burn fat without causing a thyroid problem (better than Ozempic!) 52:52: Foods and beverages to avoid for optimal thyroid health (goodbye Splenda, soy, alcohol, and packaged foods!) 55:21: Where to start when it comes to managing your thyroid (thyropause) 57:04: Red light on your thyroid 59:56: Insulin resistance (they key to losing weight and managing thyroid health) Where to find Dr. Amie: Website Instagram

Our guest this week is an award winning voice actor who's voiced Ripster in Street Sharks, George in George of the Jungle, Kong in Kong: King of the Apes, Frieza in Dragon Ball Z Kai (Ocean Dub), Snips from My Little Pony, and so many more. We welcome Lee Tockar to discuss what inspired him to get into voice acting, some of the characters he's voiced, his upcoming book The Grym Possession of Chesterfield Couch, some of his many other talents, and so much more. This is a very rich conversation you don't want to miss! @leetockar CannedAirPodcast.com Twitter: @CannedAirPod Instagram: @Canned_Air If you'd like to show your support, you can either visit our Patreon page at Patreon.com/CannedAirPod or you can leave us a comment, like, and subscribe! Thanks for listening! Learn more about your ad choices. Visit megaphone.fm/adchoices

Welcome to the last episode in the series! In which, the girls count down to Sophie's Edinburgh Fringe show, discuss elaborate Hen-dos and a surprise encounter with a penis pump. There's also a visit to Urban Dictionary Corner and a brilliant Parenting Tale. This is the last episode for a while, dear listeners. We hope you enjoyed the chat and please stay on the feed for future fun. Hosted on Acast. See acast.com/privacy for more information.

This week the amazing Sean McCann of Wake The Dead Podcast comes on to explain how and why circumcision is ultimately "child sacrifice". Is this evil, ritual or necessary? Are we still under the law as Christians? Is this medically necessary or even harmful? Are people marking their children as slaves? This isn't just about the medical side, you won't want to miss the conspiracy rabbit hole this spirals down! Come join us and get informed about this ancient practice. Again A HUGE shoutout to the awesome Sean McCann!!! Guest Links: Website: Spotify: IG: Unfiltered Rise Podcast Links: Website: Patreon: YouTube: IG: X: TikTok: Merch: #satanic #circumcision #childsacrifice #slave #ancientrituals #occult #secrets #bloodmagic #magik #shriners #generationaltrauma #psyche

It's not just about the deal—it's about what happens next. In this episode of SNiPS, Bracken COO Dawn Flitcraft uncovers the surprising reactions and feelings of life science CEOs after their companies are acquired. Learn how having an integration leader and providing executive support can make all the difference. Listen now to hear how 95% of the time, these transitions lead to success.

Soul from Jimetta Rose & The Voices Of Creation, Allysha Joy & Ganavya. Part 1 of a mix inspired by Robert's DJ set at the Love Supreme festival recently. Hip Hop from Little Simz, Kendrick Lamar blended with MF DOOM, Samrai blended with Giggs. Broken Beat from Bruk Rogers and Nutmeg. A deep edit of Cleo Sol by Lazeness. Dancefloor Boogie from Comb Edits and Oro's track “Stop The War”. Snips & Eduardo Brecho up the tempo on their cover of Fela Kuti. Plus plenty more music treats.

In episode 29, Johnny talks to Dave Wain, one of the last bastions of the video rental industry. Dave runs Snips Movies, one of the UK's last video stores. The shop, situated in the Wirral near Liverpool, boasts an impressive selection of over 15,000 movies, all available to rent for the great price of 3 for £5. The depth of the range available is eye-watering and is just the tonic against the dull, predictable and limited selections available on the popular streaming services. Johnny's talk with Dave covers the trials and tribulations of running a video rental store in the 21st century, an enterprise that's going from strength to strength with an ever-changing profile of appreciative customers. They also discuss the directors Joe Dante, Quentin Tarantino and William Friedkin, and they lift the lid on Orson Welles editing lesbian shower sequences for porn films in his spare time... This conversation was recorded online in mid-July 2024. Thanks to James Van As who wrote and performed the brilliant podcast music (check out James' ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Loco Looper⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ game) and to Willow Van As who designed the amazing artwork and provided general podcast support. You can contact My Movie DNA on Facebook, Instagram or Twitter @mymovieDNA or email mymovieDNA@gmail.com.

Diese Podcast-Episode ist auch als Video mit Untertiteln auf YouTube verfügbar: https://youtu.be/M4FmlkMFPyc Vor einem Live-Publikum in Wien mampfen wir uns gemeinsam mit unserem Österreich-Korrespondenten Mathias durch die beliebtesten Snacks: Von Mozartkugeln aka "Mozart Balls" (auch in flüssig) geht es zur Käuterlimonade "Almdudler" und den bekannten Manner-Schnitten. Außerdem probieren wir Soletti Salzstangerl, Gösser Naturradler und die berühmte Sachertorte. Zum Schluss lässt Cari eine Tüte "Snips" explodieren — es lohnt sich, die Video-Version dieser Episode zu schauen!   Transkript und Vokabelhilfe Werde ein Easy German Mitglied und du bekommst unsere Vokabelhilfe, ein interaktives Transkript und Bonusmaterial zu jeder Episode: easygerman.org/membership   Sponsoren Hier findet ihr unsere Sponsoren und exklusive Angebote: easygerman.org/sponsors   Support Easy German and get interactive transcripts, live vocabulary and bonus content: easygerman.org/membership

In this debut episode of SNiPs, a special recurring segment of Fractals: Life Science Conversations, Alexander (Sandy) J.B. McEwan, MB, MSc, FRCPC, Bracken's in-house expert in nuclear medicine, returns to the audio stage. Dr. McEwan, who has served as Past President of SNMMI, Chief Medical Officer at Ariceum, and Vice President of Radiopharmaceuticals at Ipsen, brings a wealth of experience and academic knowledge. He and host Colin Miller discuss the anticipated technological advancements in the radiopharmaceutical field to take place over the next decade. Topics include the importance of dosimetry, the "external beam paradigm," treatment options, AI in clinical trials and medical imaging, and more—all in under 6 minutes. This SNiP is a small segment of a larger conversation—to learn more about the necessity of nuclear medicine, tune into Dr. Sandy McEwan's full-length episode now.

Welcome back to another exciting episode of Innovation Somalia Podcast! In today's episode, we're joined by the dynamic LA. Snips, a young barber with a big heart and an even bigger vision for spreading positivity in our community. Get ready to be inspired as LA Snips shares his journey and insights on how positivity can drive innovation and change in Somali community. Let's dive in and explore the power of optimism with LA Snips!

The infiltration team come across a shrine to Norgorber in the bowels of Harrigan's Fortress, and a giant sea beast kept there as a pet. Mr. Snips a giant crab is in close quarters fight and focuses its fury. Will the crew survive this assault before the main fight begins? Find out on this week's episode of DMRNC!

Dr. Jade Dandy is an Idaho native and fell in love with Naturopathic medicine at a young age. She graduated from National University of Natural Medicine (NUMN) in 2015. Focusing on chronic illness, she earned her Doctorates in Natural Medicine as well as Masters of Science in Integrative Medicine Research. Dr. Dandy is an advocate for her patients' health journey, integrating western medicine with time-tested natural medicine to bring patients back to optimal health. It is her strong belief that it is everyone's birthright to live a happy and healthy life. Dr. Dandy is also an avid gardener and a hot springs hunter.The Healing HutMake sure to check out all of our links below!We'd love to answer your questions on the podcast! Fill out this form -> https://harkla.typeform.com/to/ItWxQNP3Brought To You By HarklaThis podcast is brought to you by Harkla.  Our mission at Harkla is to help those with special needs live happy and healthy lives. We accomplish this through high-quality sensory products,  & child development courses.Podcast listeners get 10% off their first order at Harkla with the discount code "sensory". Head to Harkla.co/sensory to start shopping now.LinksAll Things Sensory Podcast InstagramHarkla YouTube ChannelHarkla Website - Shop Sensory Products!Harkla InstagramBook: ADHD 2.0Book: The Myth of NormalBook: Dirty GenesBook: Hunt, Gather, ParentPolyvagal Theory

Welcome to another Tired and Tested podcast! In which Sophie welcomes another special guest... GEORGE LEWIS! Comedian! Author! Instagram's Funniest Dad! George joins Sophie and Lucy to talk about The Snip, take on a special Urban Dictionary Corner and a work-from-home Parenting Fail. Want to win a FREE ICONIC MASCARA? Submit your parenting tale to tiredandtested@acast.com - and if we pick yours, we'll send you a free mascara!Sophie is on a UK tour! Find out where you can see her hereTickets for Sophie's tour in Australia and New Zealand hereGeorge Lewis tour dates and more here Hosted on Acast. See acast.com/privacy for more information.

Hopefully not the dystopian future of Huxley amirite. In this shorter episode (we'll tell you why when we start), Kenny and Sam give quick thoughts on minimal plays of Luke and Plo, and then give more substantial thoughts on revisiting Barriss, Sabe, and Snips in the context of the new units that have dropped. Thank you for listening! Join the Slack!

Ahsoka Episode 3 “Time to Fly” is here and we're rewatching it! We're three episodes into our rewatch of the Disney Plus Star Wars show Ahsoka. It's got us thinking…should these Star Wars Television shows be binged or watched week to week? We need to talk about Ashoka's treatment of Huyang…dude deserves more respect from Snips! Also, what about Ai in real life is it a good thing? Then we need to get into Mon Mothma's bad hair. Do we want more politics in Star Wars and has there really been anything visually iconic since Disney took over Star Wars? It's time to listen to your two favorite gays dish on all things in our galaxy far, far away…let's DRINK UP! Let us know in the comments below what iconic visual things Disney has introduced to Star Wars? For more nerd-culture news and conversation: www.deathxrobot.com Want to support? Check out some sweet merch at www.deathxrobot.com/merch Follow Bryan at: YouTube: www.youtube.com/@deathxrobot Instagram: www.instagram.com/deathxrobot Threads: https://www.threads.net/@deathxrobot Email the show at: pinkmilk@deathxrobot.com All opinions expressed are solely those creating the content and we reserve the right to change our minds at any point in time. --- Send in a voice message: https://podcasters.spotify.com/pod/show/servingpinkmilk/message

Recently, Accademia Giallo presented a rare interview with genre director extraordinaire, Sergio Martino--filmed during a visit to Chicago's historic Music Box Theatre, where he showed two of his most iconic thrillers, Torso and The Strange Vice of Mrs. Wardh.While recording the intro to that piece, Ian and Bryan spoke at length about meeting Martino, what his films mean to them, and their surprised reaction to the Maestro's own estimation of his reputation as a filmmaker. I think we can all agree that 20 minutes is way too long for an interview intro, so Ian trimmed the fat to a lean five.Presented here is that full intro, as well as the answer to a fan question from the Strange Vice Q&A--and a little something extra at the very end!Subscribe, like, and comment to the Kicking the Seat YouTube channel, and check out kickseat.com for multiple movie podcasts each week!Show LinksWatch the full hour-long interview with Sergio Martino here.Support Chicago's historic Music Box Theatre, who made this interview possible. From movies to merch to incredible year-round programming that spans all genres, this is The Windy City's premiere indie arthouse cinema!Follow our amazing translator, Alice Pistono!On Instagram Listen to her podcast, (N)ice Breakers on Spotify (Italian-only)Watch her 2022 TEDx Talk, "Il Jazz di Darwin" (Italian-only):Follow the Martino event's tenacious and talented photographer, Gabriele Garofletti on Instagram.Check out Severin Films, who partnered with The Music Box to provide a huge selection of Giallo-themed movies and memorabilia during the event!Support all of our terrifying teachers' axe-tracurricular activities!Stay studious with Aaron Christensen at Horror101 with Dr. AC!If you dare, venture down into Kitley's Krypt with Jon Kitley! And listen to Jon's scary-good podcast, Discover the Horror!Get devious with Bryan Martinez's Film Deviant podcast!And check out his YouTube show, The Giallo Room!Buy J. Blake Fichera's "Scored to Death" Volume I and II on Amazon (mentioned in the show).And catch up with classic episodes of his Saturday Night Movie Sleepovers podcast!Continue your education with our "Accademia Giallo" Playlist!

Aubrey and Todd Discuss the Lead by Example Squad Pack that contains Plo Koon, Snips, Commander Wolffe, and the Wolfpack.Shatterpoint Rulebook Facebook Instagram Twitter YouTube Podcast Discord: https://discord.gg/uvuzgxpn 

Just in time for Valentine's Day, Jay has rounded up some great Star Wars gift ideas for all your loved ones.   In this fully armed and operational episode of Podcast Stardust, we discuss: Recent Star Wars fashion and lifestyle acquisitions including a “Snips” patch from Jedi Kaylin Embroidery, New “I Love You” and “I Know” spirit jerseys from shopDisney, Other Valentine's Day Star Wars themed items from shopDisney, A script based Ahsoka Tano Woven Shirt also from shopDisney, Star Wars jewelry from Girls Crew, New Star Wars jewelry from RockLove Jewelry, Fun Star Wars Valentine's Day gifts from Funko, Valentine's Day greeting cards from SunflowerStardust, “Pascalentines” from A Fan of____ Shop, and Vacuum insulated water bottles from the JoyJolt Destination Collection. Find more fun Star Wars fashion and lifestyle product gift ideas in last month's edition of World Between Worlds in episode 678.   Thanks for joining us for another episode! Subscribe to Podcast Stardust for all your Star Wars news, reviews, and discussion wherever you get your podcasts. And please leave us a five star review on Apple Podcasts.   Find Jay and her cosplay adventures on J.Snips Cosplay on Instagram. Follow us on social media: Twitter | Facebook | Instagram | Pinterest | YouTube. T-shirts, hoodies, stickers, masks, and posters are available on TeePublic. Find all episodes on RetroZap.com.

Steve Parsons in conversation with David Eastaugh Sharks are a British rock band formed in 1972 by former Free bassist Andy Fraser upon his departure from Free. They were signed to Island Records and were highly rated by critics, especially for Chris Spedding's guitar work. The original line-up consisted of Fraser (bass, piano), Snips (real name, Steve Parsons) (vocals), Spedding (guitar) and Marty Simon (drums). Steve Parsons and Anke Trojan directed the 2023 documentary Not a Rock-Doc: A Shark's Tail, about the ups and downs in the story of this band, from the success heights in the '70 to the issues that led to its dissolution and then to further insights around the subsequent reunion. Filmed in Berlin, Tokyo and London, the film was noticed for its integration of various angles of raw footage and for its humor and irony. The narrative is stirred by interactions with Steve Parsons and Chris Spedding, notably Jordan Mooney (Pamela Rooke) managing to bring to light previously unknown nuances in discussions with an otherwise tight Chris Spedding.

Join us in Episode 11 of 'Threaded Together' as we blend the art of sewing with the flair of high fashion, all while keeping sustainability at the forefront. This holiday-outfit themed episode, hosted by Tracy and Rebecca, is your go-to guide for creating eco-friendly and stylish party outfits. We’ll explore working with eye-catching fabrics like sequins, velvet, and brocade, and introduce you to greener alternatives perfect for festive attire. Gain insights into sewing techniques that bring a touch of couture to your creations, and get inspired by the latest sustainable fashion trends for the holiday season. If you're passionate about fashion, sewing, sustainability and making a statement this holiday season, this episode is sure to spark your creativity and prepare you for any festive occasion. Full show notes also at www.ThreadedTogetherPodcast.com Links mentioned in the introduction Freddie jacket https://bellalovespatterns.com/products/freddie-jacket-pdf-sewing-pattern Tips for sewing welted pockets - Threaded Together Episode 7 Working with Velvet - Resources https://www.seamwork.com/articles/a-beginners-guide-to-sewing-velvet https://www.threadsmagazine.com/2020/02/10/how-to-sew-velvet-like-a-pro Sewing with Sequins https://www.tillyandthebuttons.com/2018/10/sequin-fabric-tips.html#:~:text=Snips%20may%20not%20be%20visible,not%20an%20overlocker%20(serger). https://byhandlondon.com/blogs/by-hand-london/16700656-nerdy-sewing-tips-sewing-with-sequin-fabric https://wunderlabel.com/blog/p/tips-working-sequin-fabric/ What's Next . . . We will be reflecting on the year, Reviewing our favourite makes Toughest makes, most worn makes… and looking to the year ahead -our sewing resolutions, and more! We have loved having you with us the past 11 episodes this season and if you have any thoughts, questions, or just want to say hi, sign up for our newsletter or give us a shout on social media @Threaded Together Podcast. We also JUST launched our newsletter to give you exclusive behind the scenes content, photos and links to what we are up to between podcasts.

Caitlin, Matt, and Brian return from hiatus for a long overdue discussion on Star Wars: Ahsoka. Also in the mix: strikes, Marvel, tax write-offs, Glenn Howerton, Thrawghts, broken promises, and much much more!Support the showFollow us at Return of the Pod!

Snips!  This week on an all new So Wizard, Joey is back from New York Comic Con and tells you about his journey, and the team reviews Ahsoka season one!  Feel the force when you listen on Apple Podcasts, Spotify, or right on our website! Check out our merch store! You can now support us on Patreon and get an extra episode of the podcast every month! Check out our You Tube channel!  Follow us on Tik Tok!  Follow us on Twitter! Like us on Facebook! Follow us on Instagram

What happens when you have five friends get together for a rare live show to discuss the entirety of Season One of Ahsoka? Well aside from the occasional nugget of eloquence there is a game of ring around the Peridea, rollercoaster fingerblasting with Rick and Mortis, and we attempt to build a better jedi not covered in swars. All that and there were zero occurrences of Snips nip slips. Don't miss our Ahsoka wrap up show! Turn up your headphones, dial back your sensibilities, and join the wretched hive of scum and villainy as we take the low road to resistance on Season Four, Episode Thirty Three of Force Insensitive!Send Email/Voicemail: mailto:forceinsensitive@gmail.comDirect Voice Message: https://www.speakpipe.com/ForceInsensitiveStart your own podcast: https://www.buzzsprout.com/?referrer_id=386Use our Amazon link: http://amzn.to/2CTdZzKFB Group: https://www.facebook.com/groups/ForceInsensitive/Twitter: http://twitter.com/ForceNSensitiveFacebook: http://facebook.com/ForceInsensitiveInstagram: http://instagram.com/ForceInsensitive

For one night, Star Wars returned to theaters. On Tuesday, September 12th, Lucasfilm aired the momentous fifth episode of the Ahsoka series at select theaters across the country and around the world. And Star Wars fan and Ahsoka collector Christopher James Leddy was one of the fortunate few to score a ticket to an unforgettable evening at the movies. Join host David Quinn for an in-depth conversation with Chris about what the experience was like for Star Wars fans eager to see Ahsoka back on the big screen. *Note: This episode covers events that occurred in episodes 1-5 of the Ahsoka series. To Listen to the Episode on the Prototype Archives Site: https://www.prototypearchives.com/podcast Links to the Episode on Various Podcast Platforms: APPLE PODCASTS: https://podcasts.apple.com/us/podcast/star-wars-prototypes-and-production/id1448205460 SPOTIFY: https://open.spotify.com/show/744L0XQhmpXn2AZeaxUhOZ GOOGLE PODCASTS: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5zb3VuZGNsb3VkLmNvbS91c2Vycy9zb3VuZGNsb3VkOnVzZXJzOjU2NTA4ODM3Ni9zb3VuZHMucnNz CASTBOX: https://castbox.fm/channel/Star-Wars%3A-Prototypes-and-Production-id1904296?utm_source=website&utm_medium=dlink&utm_campaign=web_share&utm_content=Star%20Wars%3A%20Prototypes%20and%20Production-CastBox_FM STITCHER: https://www.stitcher.com/show/1054209 PANDORA: https://www.pandora.com/podcast/star-wars-prototypes-and-production/PC:1001054209 PODBEAN: https://www.podbean.com/podcast-detail/u4ywr-80960/Star-Wars-Prototypes-and-Production-Podcast AMAZON MUSIC: https://music.amazon.com/podcasts/c98fb265-c233-43d9-ae3b-1102bfb03e45/star-wars-prototypes-and-production PLAYERFM: https://player.fm/series/2473540 SOUNDCLOUD: https://soundcloud.com/david-quinn-908355451/tracks PODVINE: https://podvine.com/podcast/star-wars-prototypes-and-production iHEART: https://www.iheart.com/podcast/256-star-wars-prototypes-and-p-31050806/ https://podcasts.apple.com/us/podcast/star-wars-prototypes-and-production/id1448205460

The Smuggler's Three have returned and we have reached the mid-season of Ahsoka. Before we get to that, we discuss some new toys and collectibles based on Ahsoka and Ahsoka episode 5 is coming to a couple of theaters around the country on Sept 12. Then we start to talk about Episode 4 of Ahsoka. […]

We break down our favorite episode in a Star Wars series ever. 

Hey there Snips! It's time to dive deep into the fourth episode of 'Ahsoka' (08:53). Mal and Jo venture into deep space and discuss the riveting episode that takes our hero away from her apprentice and causes strife within (15:39). Much later, Ben Lindbergh joins for a discussion of the final scene in the world between worlds (02:49:18) Hosts: Mallory Rubin and Joanna Robinson Guest: Ben Lindbergh Senior Producer: Steve Ahlman Additional Production: Arjuna Ramgopal Social: Jomi Adeniran Learn more about your ad choices. Visit podcastchoices.com/adchoices

David and Hannah review Part 4 of Ahsoka which included a very shocking return. They also discuss a new novel announcement, the early struggles of the New Republic, and more. For more Star Wars content visit insidetheforce.com. Join our Facebook Group, follow us on Twitter, and subscribe to our YouTube Channel. If you like the show, please leave us a review and share us with your friends and family. May the Force be with You!

Some fans have gone to the net to express their disdain for the acting in the Ahsoka show, saying it's boring and mid and lacks emotion. Here's what I think about this...much like how Hayden purposefully acted the way he did to keep the same cadence as Darth Vader when playing Anakin Skywalker, I believe Ahsoka, Hera and Sabine are doing the same given the current state of their lives and the galaxy. SNIPS 1/2 ZIP FLEECE SWEATER - https://unlockd.teespring.com/drop/swt-halfzip-pullover/ Learn more about your ad choices. Visit megaphone.fm/adchoices

The Clone Wars premiered 15 years ago this week. After the film's release on August 15, 2008, a television series soon followed. Together, they introduced the world to Ahsoka Tano and showcased the further adventures of Anakin Skywalker, Obi-Wan Kenobi and the Jedi of the prequel era. And over the past 15 years, The Clone Wars has become a generation-defining Star Wars series and has served as the foundation for many of the current Lucasfilm stories, including Dave Filoni's new Ahsoka show. Join host David Quinn for a celebration of The Clone Wars film, series and memorabilia, through the memories and reflections of our fellow Star Wars fans and collectors. Featuring contributions from: FJ DeRobertis, Erik Janniche, Christopher James Leddy, Joe O'Neill, Sam Sams, David Tree, Daniel Uthman and David Kevin White. This is a celebration of Snips and Skyguy. And this is Star Wars: Prototypes and Production! To Listen to the Episode on the Prototype Archives Site: https://www.prototypearchives.com/podcast Links to the Episode on Various Podcast Platforms: APPLE PODCASTS: https://podcasts.apple.com/us/podcast/star-wars-prototypes-and-production/id1448205460 SPOTIFY: https://open.spotify.com/show/744L0XQhmpXn2AZeaxUhOZ GOOGLE PODCASTS: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5zb3VuZGNsb3VkLmNvbS91c2Vycy9zb3VuZGNsb3VkOnVzZXJzOjU2NTA4ODM3Ni9zb3VuZHMucnNz CASTBOX: https://castbox.fm/channel/Star-Wars%3A-Prototypes-and-Production-id1904296?utm_source=website&utm_medium=dlink&utm_campaign=web_share&utm_content=Star%20Wars%3A%20Prototypes%20and%20Production-CastBox_FM STITCHER: https://www.stitcher.com/show/1054209 PANDORA: https://www.pandora.com/podcast/star-wars-prototypes-and-production/PC:1001054209 PODBEAN: https://www.podbean.com/podcast-detail/u4ywr-80960/Star-Wars-Prototypes-and-Production-Podcast AMAZON MUSIC: https://music.amazon.com/podcasts/c98fb265-c233-43d9-ae3b-1102bfb03e45/star-wars-prototypes-and-production PLAYERFM: https://player.fm/series/2473540 SOUNDCLOUD: https://soundcloud.com/david-quinn-908355451/tracks PODVINE: https://podvine.com/podcast/star-wars-prototypes-and-production iHEART: https://www.iheart.com/podcast/256-star-wars-prototypes-and-p-31050806/ https://podcasts.apple.com/us/podcast/star-wars-prototypes-and-production/id1448205460