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The Summer of Rollin continues...but this time, Jean takes a detour.Episode 576 moves away from vampires and into two radically different films from Rollin's early career: Schoolgirl Hitchhikers (1972) and The Iron Rose (1973).One is a bizarre softcore comedy packed with nudity, slapstick, sexual liberation and some decidedly uncomfortable attitudes towards women. The other is, in my humble opinion, one of Jean Rollin's greatest achievements — a haunting, beautiful descent into dream logic, death and romantic nightmare.First up is Schoolgirl Hitchhikers, released under the pseudonym Michel Gentil. Trading gothic castles for an isolated rural house, Rollin embraces softcore cinema with a strange mix of nudity, slapstick and increasingly uncomfortable sexual politics.It's perhaps the hardest film to reconcile with the poetic filmmaker seen elsewhere in his work. Freedom, sexuality and liberation collide awkwardly with sexual violence, questionable agency and moments of outright misogyny.Yet even here, Rollin's fingerprints remain: isolation, decaying locations, sexuality, fantasy and characters cut adrift from reality.Then comes The Iron Rose. And everything changes.Two characters. Minimal dialogue. A cemetery that slowly transforms into an impossible labyrinth.What begins as gothic romance becomes something far stranger as passion gives way to fear, mistrust and disorientation. Are the paths changing? Are they losing their minds? Or were they ever supposed to escape?The Iron Rose is Rollin at his most confident and hypnotic. Powered less by plot than atmosphere, emotion and dream logic, reality dissolves as the cemetery becomes its own beautiful, terrifying and inescapable world.We'll explore:Rollin's strange sidestep into softcore cinema as Michel GentNudity, sexual liberation & uncomfortable misogynyFemale agency and the collision of sex, fantasy & absurdityWhy Rollin's signature obsessions remain without vampiresThe beauty and isolation of The Iron RoseDream logic and the cemetery as nightmare labyrinthFrançoise Pascal's remarkable performanceGothic romance, sex, death & the impossibility of escapeRollin's visual poetry, cinematography & haunting musicWhy The Iron Rose may be the definitive Rollin movieThis episode takes us from one of Rollin's strangest diversions to one of his most perfectly realised visions.Schoolgirl Hitchhikers shows a filmmaker chasing another market, but The Iron Rose reminds us exactly why Jean Rollin matters.By 1973, he isn't simply experimenting with style.He has mastered his own. Beautiful. Isolated. Erotic. Melancholic. Dreamlike.And utterly impossible to escape.So step inside the cemetery, follow the paths, and whatever you do...Try not to get lost.The Summer of Rollin continues...The following texts and documentaries were used in this series:* Lost Girls: The Phantasmagorical Cinema of Jean Rollin - Samm Deighan* Orchestrator of Storms: The Fantastique World of Jean Rollin (2022) - Kat Ellinger and Dima Ballin* Indicator 4KUHD Releases of Girls without Shame & The Iron Rose - Street date May 2025.The grading follows the Netflix rating style of 1 = Hated It, 2 = Didn't Like It, 3 = Liked It, 4 = Really Liked It & 5 = Loved ItGirls without Shame:Duncan: 2.5The Iron Rose:Duncan: 5Our new RSS Feed: ⁠https://anchor.fm/s/13ba6ef0/podcast/rss⁠Check out the show on ⁠Anchor⁠, ⁠iTunes⁠, ⁠TuneIn⁠ & on ⁠Stitcher Radio⁠.Please leave us feedback on ⁠iTunes⁠, podcastunderthestairs@gmail.com and follow us on ⁠Facebook⁠.Timecode For Episode 576:00:00:00 - Intro 00:03:51 - Girls without Shame00:23:15 - The Iron Rose00:38:43 - The Indicator 4KUHD's 00:43:22 - Closing the Show

Andy & Kieran from Nuffink & Like It return to Hanley to review such things as Mark Rocco's return, Jamaica George, Jim Breaks vs Johnny Saint and much more!!!Support this podcast at — https://redcircle.com/graps-and-claps-podcast/donations

Did you know: Today's dentists are waiting five years longer to buy a practice than they were a generation ago? Kiera is joined by Brian Hanks of Dental Buyer Advocates to talk about delayed ownership traps and why the future of private practice is an encouraging one (Brian shares numerous data points to back that up). They also touch on overcoming fears and all the information out there that makes everyone seem more prepared for business ownership than they actually are, and how to go about buying a practice while asking the right questions. Episode resources: Subscribe to The Dental A-Team podcast Schedule a Practice Assessment Leave us a review Transcript: Kiera (00:00) Hello, Dental A Team Listeners, this is Kiera, and today is an awesome day. I am so excited to be podcasting with one of my favorite humans. He and I have spoken across the country together. We go to different things, we share clients together. I have Brian Hanks, the owner of Dental Dental Buyer Advocates. And today we're gonna talk about like delayed ownership trap because I think so many people get stuck into this of should I buy, should I not buy? And Brian and I are just here to have a fun rift. So, Brian, welcome to the show today. How are you?   Brian Hanks (00:28) So nice to be back, Kiera. You're one of my favorite people too. Thank you for having me.   Kiera (00:32) Of course. I'm excited, Brian. It's a good time. It's been a hot minute since we podcasted together. So it's time, it's time to talk about this. Because when we were chatting about episodes, you were saying that dentists are now waiting like five years longer to buy a practice than they were a generation ago, which is fascinating to me because I've been on this like whole hot to trap of like, do people buy? Are DSOs taking over? Like, is there still money to be made in private practice? Like literally my chiropractor and I were talking about this the other day because she's like,   My dentist told me that they were like not able to make any money. And I was like, well, they sh just give them my card. Like private practice to me is still one of the best businesses and industries, even if you have to buy a top dollar right now. and so just like super fascinating to talk about like delaying that purchasing, why people do it. But Brian, I've jumped right in and pretended like everybody knows who you are. Brian, give us a little intro of like who you are, how you got into Dental Buyer Advocates, what your background is, and then like let's talk about to delay or not delay buying a practice.   Brian Hanks (01:29) Sure.   Yeah, I one of my favorite stories. I'm an ex-Wall Street guy, so I'm a reformed Wall Streeter. And my father-in-law is a dentist. And I would watch these Wall Street people come in and like sell a very aggressive investments. And when they went bust, they would turn around and sell the crappy investments to dentists who at the time my was my father in law. Active practice, he lived in the Seattle area. And anyway, I went to go work for a dental CPA in the Dallas area. I went to work for another one. So I'm I've lived in the accounting world, Kiera.   And when I was in that world, I got younger dentists who were in the pro they were the associates and they were asking accounting questions and tax questions and you know financial planning questions. And inevitably they would come back to dental practice ownership. Like, how do I do this? How much do I pay? Is   Kiera (02:13) Yeah.   Brian Hanks (02:13) is this a good deal? And so I went looking for the book. I was like, well, where's the book? I was on Amazon, I was other places. There was no book. And I thought, all right, well, let me try writing this book. Famous Last Words, by the way, it's way harder than you assume. But the book is called.   Very creatively, How To Buy A Dental Practice. And that helped me start my own business. And that's   Kiera (02:30) I like it.   Brian Hanks (02:33) what I do. I I only help buyers of dental practices. And, you know, Kiera, my business is good, your business is good. Dentist business, we can talk about why the future of private practice is very bright. I can give you some stats and   Kiera (02:46) Mm-hmm.   Brian Hanks (02:46) statistics. But one of the interesting, the most interesting facts for me is Health Policy Institute has data that shows that.   Dentists get into ownership, like they they end up in ownership. Okay, so I'll give you like they've broken it down by like graduation rates. So like the the   Kiera (03:07) And what I   Brian Hanks (03:08) dental school grads from 1990 and then 1995, and everybody between 95 and 2000, so and so forth. So they have these like vintages of graduates. And   Kiera (03:16) Mm-hmm. Mm-hmm.   Brian Hanks (03:17) very reliably, they're showing that nine out of ten dentists, of which you know there's 203,000 in the US, nine out of ten end up in ownership.   At some point in their career. But like you said,   Kiera (03:27) Fascinating.   Brian Hanks (03:28) they're waiting longer to do it. And I think that's what we're going to talk about.   Kiera (03:32) Yeah. Which like again, I think people are scared. So many students I worked at Midwestern and they're like, Kiera, should I buy? Should I go associate? And I was like, listen, you're just delaying the inevitable so like get in there and get it done. Now, I like always throw an asterisk on that. Like if you're not good at your hand skills, like yeah, go go associate for a hot minute. like if you aren't confident with your speed and with case acceptance and like presenting, that's gonna be but I'll tell you there is nothing more thrilling than throwing yourself into a business that you have to produce for.   You learn case acceptance really freaking fast. Like, ask me how I know. We surely did that. Like I took a student, we took our first practice from 500,000 to 2.4 million in nine months. Like she was a she was a power producer. Do I have an office right now that just bought a practice less than a year ago? We're already on track for two and a half million. Yes. Like there are a lot of success stories from that small town. It's not like they were just given the keys to the kingdom. Like they've had to work for it, they've had to build things. They don't have full schedules. But   I just, I don't know. I'm the same way and I I don't know. I'm I'm at a space of but do what makes you happy. Like, do not go   Brian Hanks (04:37) Yeah.   Kiera (04:38) own a practice and make less than being an associate. That's like a hard line for me too. I'm like, 'cause if you're gonna like not be a good business owner, keep associating. But I   Brian Hanks (04:43) No. Yeah.   Kiera (04:46) agree, I feel like the trajectory of dentists is always to purchase. Like they want their own stamp, they want their name on the building. I will also highly recommend don't put your name on the building. Like that's really fun and not scalable. Ask me again how I know that. Like   Cura's dental consulting was real fun till it wasn't. Like the things you the things you evolve on, but truly I I'm excited to hear why you think people are delaying, what that's costing them. Brian, I love that you always come with a bunch of stats and facts. And I love that you named your book, like How To Buy A Dental Practice. That's what people want to know. so it sometimes simple is no, that is the best.   Brian Hanks (05:13) I know. I just yeah. I'm not the best at marketing, right? So yeah, like we we call Kiera when we need   marketing advice. So okay.   Kiera (05:24) Mm-hmm.   Brian Hanks (05:24) So Kiera, here are some more stats for you.   Kiera (05:28) Okay, ready?   Brian Hanks (05:29) the average owner, dentist, makes $151,000 than the average more than the average associate. Okay, 151. Now that's   Kiera (05:37) I was like, hold on, 151   is bad. That's more than if you're being an associate. You're gonna make 151,000 more. Okay.   Brian Hanks (05:43) Yep. Yeah. And think about why   that is. Yep. That's obviously the you're taking on the risk. You're taking on the the pain and suffering of being an owner, right? So there's some compensation involved in   Kiera (05:51) Mm-hmm.   Brian Hanks (05:52) that. Those are two medians, right? And there is a bell curve around both of those numbers. So is it possible   Kiera (05:57) Course.   Brian Hanks (05:58) to make less as an associate? Yes. Yeah. Is it possible   to make a hell   Kiera (06:01) Mm-hmm. Uh-huh.   Brian Hanks (06:02) of a lot more than $151,000 more than an associate? Absolutely, yes, right. So there's there's room on both end of the ends of those those bell curves. but think about   So here's why I one of the data points why I think private practice ownership and dentistry is still it's bright and it's getting brighter. Is you think about the average associate you talk to, Kiera, the average associate I talk to when we're standing around a cocktail party or at mid mid the you know, wherever, some conference, Yankee, Midwestern.   Kiera (06:30) Mm-hmm.   Brian Hanks (06:31) And I will tell you the average associate that I talk to isn't saying, gosh, Brian, you know what? I love my boss. I love the DSO I'm working for.   I love my hours. I love the insurances we take, the assistant they force me to use, I love her, right? It's the future of private practice dentistry is bright because dentists are people. And people generally like   Kiera (06:52) Mm-hmm.   Brian Hanks (06:52) a little bit of control over their career if they can get it. And dentists absolutely can get it. So that's one of the data points that   Kiera (06:55) Yeah.   Brian Hanks (06:58) I love. Now, are dentists scared to get into ownership? And do higher on average student loan balances scare them marginally more than they did 10 years ago, 20 years ago? For sure.   Yep, absolutely. Here's the mistake   Kiera (07:11) Absolutely.   Brian Hanks (07:11) they make. So I'll give the associates listening or the students or whoever it is that's maybe telling you, Kiera, or telling me, or they're telling their, you know, the the person next to them on the treadmill at the gym while they're listening to this, like, sure, Brian, easy for you to say, but I don't feel ready. Right? I haven't taken all of Care's courses.   Kiera (07:30) Mm-hmm.   Brian Hanks (07:31) I haven't, I don't know how you know, I'm not the pro at treatment planning. My hands beat because you I I want to take this implant course first, right?   You come up, your brain comes up with all these excuses of why you don't feel ready. And I'm not gonna dismiss your feelings. I think your   Kiera (07:45) Mm-hmm.   Brian Hanks (07:46) feelings are valid. You should listen to them, but don't here here's another thing to consider in addition to your feelings. Is you know how there were like a hundred people in your dental school class, probably ish, right? And 10 of whom you would never let near your teeth. Like you watch them go through all four years of dental school and you're like,   Okay, of those 10 over there, like they're never getting, they're never giving me a shot. They're never in that nothing, right?   Kiera (08:10) Yep.   Brian Hanks (08:10) Because I guarantee you, nine out of ten of those dentists, they already own their practice. They're not bankrupt. They're making more money than you,   Kiera (08:16) Yeah.   Brian Hanks (08:17) and they are killing it. Meanwhile, you're scared to run a practice. And those, if   Kiera (08:22) Mm-hmm.   Brian Hanks (08:22) those jokers can figure it out, you can figure it out.   Kiera (08:26) Totally. Well, and I think also on there like, Brian, let's be real. Is anybody ready to be a business owner? Like I wasn't, I'm sure you weren't.   Brian Hanks (08:31) Nope. Nope.   Kiera (08:33) I think are people ready to be parents? The answer is no. Like nobody feels ready for that. Were you ready when you went into dental school? The answer's no. I think that there's this imposter syndrome that hits us all that we think, like, give me a little more time and I'm gonna get ready. Give me a little more time. And I will say that like the brass taxes, you jump into owning a business and you figure it out. Now, should you listen to some podcasts? Should you do some things? Like for sure.   But   like how many consultants and coaches are there that literally are gonna like grab your hand, walk you through, and make sure you don't make the mistakes? Like how many people like yourself are gonna walk you through buying the practice to where it's an actually great practice? I I think that I think there's more help today. Now, do I think there's a lot of noise and a lot of people that might be like posturing out there saying that they know what they're doing? Yes. So make sure you like vet them a little bit before you go and jump on a bandwagon of somebody, like someone who's been there, done that, done that successfully multiple times is who I'd bet on. But like   We are in such a day and age where there is so much information out there. You need to be a great clinician. We're gonna teach you how to be a great business owner. And as long as you're comfortable realizing that you've got to learn that side of it, that's to me, like if you're a good producer and you're a good human, like go for it. There's dentistry is so fun owning and practice because the sky is the limit. And ultimately there is no cap on what you're able to do, what you're able to produce, how you're able to do it.   And I think that there are very few careers out there, very few job opportunities that really are the sky's limit. Now, remember how I told you about that dentist who bought their own practice. They're now doing like two fifty this year, whatever they're he was making five hundred thousand as an associate. And so this   Brian Hanks (10:06) Yeah. Hi Bart.   Kiera (10:08) is one where like people be like, Well, gosh, like, you know, he went from five hundred thousand and now he's at a two point, I think he's gonna end around two to two point four this year. But like he had a great associateship. And so I think   There is still this just like uncanny, unnatural desire that you want to just own, you want to build. And I think dentistry is also if I look at like banks, they lend to dental practices, like almost guaranteed, like they have a they're pretty lucrative with like just shelling money out to your dental practice. And I'm like, if banks are willing to back, you've got to also see that your dental practice, like you have the greatest opportunity of not failing.   of any business venture you're going to do. Why is private equity coming in strong? Because they know dental practices are almost bulletproof of an investment to have. So when I look at all those reasons, I agree with you, Brian. People don't feel like they're ready, but I'm like, you're never gonna feel ready. But you have so many things stacking in your favor to help you be successful.   Brian Hanks (11:03) At the beginning of that, I   I don't I don't want people to miss that. If they missed the wisdom that Kiera just shared at the beginning of that, as she said, yeah, you use parenting. I think you use business ownership as some advice. Like I I just want to repeat what you said because it's so important. Dentistry is not like, I don't know, Kiera, scuba diving, right? If you go get scuba certified, you like practice in the pool. And then they like make you, you know, they learn, you know, you you learn taking the regulator out of your mouth and putting it back in and all that. And I imagine like dentists think   ownership, like there's gonna be some course I can take that's gonna prepare me for ownership kinda like scuba certification. That's like you gotta help me come up with   Kiera (11:38) Yeah.   Brian Hanks (11:39) a better example, but it's not it's not true. It's like parenting,   Kiera (11:42) I got you.   Brian Hanks (11:42) it's like marriage. It's like I don't know, business ownership, whatever it is. Like the the thing that prepares you for it is just doing it. Just just   try it out.   Kiera (11:50) Mm-hmm.   Brian Hanks (11:50) Yep.   Kiera (11:51) Well, and I think Brian, to that point, like the analogy is I think people think business ownership is a skill that can be learned in a one, two, three step versus like marriage, relationships, child, like being parents, business ownership. It's an evolution of soul and it's a it's a creating of who you are. It is not a skill. Like there are skill points to it, like learning to read a p PL, learning how what profitability is.   But business ownership in and of itself, I had a friend she's like, Kiera, you have to have kids. Like it will strip you down to your core and it will like show things to you that you've never had. And I said, Have you ever been a business owner? Cause I'll tell you that I'm pretty confident. I've got a lot of that stripping over here that's like breaking me down to my utter like most. But I think we think business ownership and running a practice, I'm not here to say that there's not like tactical pieces and we've broken it down. Like our team actually just went through this something. I'm like, there's really like   10 things that you need as systems that are really gonna make or break it. And you gotta know a couple of like core foundations and you got to know your numbers. Like beyond that, that's kind of your checklist. But to your point of like scuba diving or cooking or whatever, it's not this like checklist skill that you're going to have. And so I think, like you said, you're gonna look for this course. But I'm like, the course is life, the course is doing it, the course is going through it. And I think you've got to have the confidence of are you confident in you that no matter what comes your way, you're gonna be able to figure it out. And if so, business ownership is there for you.   And I would give more confidence to you than you give yourself. I've watched a lot of students. I worked at Midwestern. To your point of those 10 students, there was probably like 50 of them. Sorry, Midwestern grads, I was not letting any of you touch my mouth. Like genuinely, you needed a few years to practice and I'm not your practicey. But like I think I think you're more equipped than you give yourself credit for. Just like you're more equipped for life than you give yourself credit for. And I think business ownership is the same.   Brian Hanks (13:31) So Kiera, let's break down some of those numbers. by the way, better   analogy for business ownership is like health. Do you remember the first time by the way? if you're listening to this, it's pretty obvious if you're watching, but if you're listening, Kiera's in a lot better shape than me. But if if Kiera, I don't know if you had this moment. I I did when I was like 21, 22, that I realized at the I was at the gym, I was like lifting some weights, and I realized, I'll never be done with this. Like you're never done with health. So I think business ownership is a lot like.   Kiera (13:59) I do remember my moment   of that. Mine was   Brian Hanks (14:01) Yeah.   Kiera (14:03) not at the gym, Brian. Mine was actually in Bali, like a little flex there. I remember because   Brian Hanks (14:07) There you go.   Kiera (14:07) I was like having a lot of like knee and hip pain. And I was like, okay, I just have to like work out and then eventually this is gonna get better. And I remember I was walking down to the pool overlooking the ocean. I was like, I'm never gonna be done. Like this is my forever. Like I'm not like I used to just work out to be like skinny and fit. And now I'm like, no, you gotta do this so you don't freaking hurt and you can actually walk and get out of bed. Like it's never gonna end. And   I   sat there and read a book, quite depressed. And then I was like, okay, like this is what it you're right. It's it's a constant evolution of soul. You're never done parenting, you're never done in a relationship. Like you don't hit this, like, check the box, we've got a golden thing. It is a forever perpetual. But I also think that that's what drives dentists to go into that because they are of this obsession of wanting to be the best of the best. You want to get a better prep. You want to get a better crown crop. You go to CE, you're CE junkies out there. Like, this is just another level of obsession.   Of a space that's going to evolve you as a human and it's gonna allow you to grow. So yeah, thanks. That was that was a great that was a great analogy, Brian. Good good call on that one.   Brian Hanks (15:02) Yeah. Yeah, the the   the negative of the health analogy is that you're never done, but the positive is you can break it down. Like you can learn how to do certain lifts a little better. You can learn how to macro track. You can learn diet and exercise.   Kiera (15:14) So you're right, Brian. Like that was a solid call out on the health analogy. Like this is what people are obsessed about, but they want to have that evolution of soul. They want to like I think that that's why dentists are drawn to ownership, but I think they're just afraid. But I'm like, we're also afraid to work out. We're afraid to have kids. We're afraid like, so don't let fear hold you back. I think it's just a like, I don't know. It doesn't be like Nike, just do it, guys. Like that sounds like terrible business advice on my side.   Brian Hanks (15:37) Well just do it and but remember   remember how good you weren't at at all the clinical stuff that you're really   Kiera (15:44) Mm-hmm.   Brian Hanks (15:44) good at now, right? So dentists, the the superpower that most dentists have is that attention to detail, like the obsession over the details and and the the minutiae. And and as a patient, like I gotta go to filling next week, and as a patient, I want my sister thinking about all of the all of the little details, right? and   Kiera (16:04) Mm-hmm.   Brian Hanks (16:04) that superpower is real.   And I want the density like lean into it. If you're listening to this and that evolution of soul that that Kiera's talking about, part of that evolution for you is just remembering that that superpower that you have comes like there's another side to that coin. It comes with a downside. And the downside is the overthinking when you're not.   You know you're not that good at a thing. And if you know you're not that good at finding a dental practice to buy, analyzing a dental practice to buy, actually buying that practice, applying for a loan, like talking to lawyers, all those things, your brain is gonna start to spin a little bit. And j but but but here's the good news: your brain spun a thousand times already. Remember that first time they opened up the little mannequin to like practice, like prepping a crown or something, and you were like, How do I even do this? Right.   Kiera (16:49) Dexter, their little type   it on.   Brian Hanks (16:51) Yeah, like seriously, like you figure this out. You like and if the dentists that I deal with they're the smartest people on the planet, they're awesome. And and so if you can figure that stuff out,   Kiera (17:02) Mm-hmm.   Brian Hanks (17:02) my gosh, like first of all, hire somebody else like you to just be amazing for you in all the areas that you aren't amazing, and just remember that it doesn't this isn't rocket science. yeah, so you can figure this stuff out.   Kiera (17:14) Mm-hmm.   Brian Hanks (17:14) But okay, so speaking of minutia, speaking of details, I gave you the hundred and fifty one thousand dollar number.   Okay, here I did some math. I'm an accountant. I I know I know spreadsheets.   Kiera (17:22) Yeah.   Brian Hanks (17:24) I know how to do like compound interest and some those things. Here's what I did is I just is I said, what's the cost? Okay, if dentists aren't feeling ready, they want to feel like they have their student loans under control, which is smart, right? I'm a financial planner. Yeah, don't get yourself over your skis in debt. That's great. But like, how much is it gonna cost if you're the statistic?   Right. And the statistic is you're you, listener, right now, if you're not a practice owner, are waiting five years longer to own a practice. How much does that five years cost you? Right. And if you do the math, and I did the math at like a 38-year-old dentist versus a 33-year-old dentist. And I assumed that they actually retired at age, both retired at age 60. Okay. So like different lengths of associate part of your career and owner part of your career.   with compound interest, assuming 7% and some of those other variables that I put in there, it was a $1.14 million difference between those two numbers. So don't forget that while you're busy like taking care of your student loans so you can feel ready to buy a practice, it's costing you an enormous amount of money. And Kiera, I would just add, and I'm curious if you can think of any others, I would say the compound.   the compound effect that I'm talking about is not just money, although money is a big part of it. I think the compound effect applies to other things. Like how many more times and at bats would you have for treatment planning, for managing that difficult assistant, teaching someone how to answer the phones better, hiring, firing. Like there's a compound effect on all of those behavioral things too and and it's gonna cost you some money. So any thoughts on that?   Kiera (19:04) Mm-hmm.   Yeah, I think it's a I I was fascinated. I'm so glad that you went into the 1.1 because we had talked about that pre-show and I was just very fascinated of like, my gosh, like that's so much for people. That's so many things. Like there's a financial dollar amount, which I love because I think dentists really do. Like that's an easy one for me to be like, gosh, like me delaying this decision can cost me that much. But I think like there's also you still have to go through the   growth of learning to run a business. So not only is there a financial delay, but there's also the growth of you getting good at running a business and having it profitable and being able to make this thing run longer. And then you have more opportunities like I think about yourself. And the longer you're able to build this practice and like maybe do multiple like there's to me that's like such a it's fascinating. And I think I think the the call to today is there are some people that definitely are meant to be owners and there's some that aren't.   but I think if you have that itch, that scratch, I would really ask yourself, like, what truly are you waiting for? And when are you going to know that you're actually ready? Like you're never going to feel ready to have a child. You're like, I need to get these ducks in a row. Well, those ducks get in a row and then you got seven more ducks that come behind that you're like, I need get those in a row. So to me it'd be if I'm really wanting to buy a practice, what things do I need to have? Cl schedule a call with Brian. Like, I think Brian, this is why we put you on the podcast. I think you're fantastic. You don't put people into weird zones. you're very much like   If that dentist is producing and you don't do those skills and you don't do those type of procedures, don't buy that practice. Like you're not, you're gonna be broke. You're very, very pro making sure people feel confident and that they're able to buy it. And I think it's like buying a home. I remember when I first like went and talked to somebody about buying a home, I had no freaking clue and I wish I would have known more. But like until you start having the conversations, I think it can feel more daunting than it actually is. Then from there, like listen to the podcast, start listening to there's our podcast, there's other podcasts out there, start reading up on how to buy a practice.   But I think to me, there is like two parts to it. One is finding the right practice. Like what you buy, and I say like eyes wide open when you're looking in, and then rosy glasses as soon as you sign on that dotted line, and you're gonna see a lot and you're just gonna deal with it. From there, make sure you got somebody really solid in your corner. Like our practices, as soon as they buy, we take them on. I try to get them two to three months before they close. I wanna make sure we're getting things in. If you don't close on time or things happen, no problem. We're gonna pause you, get your practice in place. Like it's happened twice in hundreds of offices we've helped.   But then, like from there, just have somebody in your corner, somebody who's gonna help you grow in your first year. Most practices are seeing like a 10 to 30% increase in their first year. So if I'm buying a one million dollar practice, that's a hundred to three hundred thousand dollar uptick just by having somebody in the corner. That's very conservative. A million dollar practice, like we are usually growing those exponentially. But like you don't have to stress and freak out. Hey, I'm pinned.   Brian Hanks (21:45) Yep. By the way, I I d pin put a pin, put a pin, Kiera. You you gotta you gotta underline that. Yeah.   That's like underline that, underline it. Like keep going, keep going. I I'm throwing you off. I'm interrupting you, but like I will tell you the   Kiera (21:59) Yeah.   Brian Hanks (21:59) average buyer I talk to on the phone is so scared of patient attrition. They're like, Kiera, like   I'm gonna have 10%, 20%. What if 50% of the patients don't show up? Listen, that's a real fear. By the way, I want you to have that   Kiera (22:10) Right. Mm-hmm.   Brian Hanks (22:12) fear when you're like doing the margin on my crown, right? Like again, it's your superpower dentist,   Kiera (22:16) Mm-hmm.   Brian Hanks (22:17) but like my stats show exactly the same thing, Kiera is saying I have data to support what Kiera is saying that the average   Kiera (22:22) Mm-hmm.   Brian Hanks (22:24) dentist doesn't they have a negative attrition, which is just two negatives, right? So it's a positive. They the average buyer has more enthusiasm, they've got some more energy, they're gonna update the website, they're gonna maybe get rid of.   That one employee that everybody kind of knew probably s needed to go. And suddenly the practice is just gonna it's gonna take off. Ten to thirty percent. That's yeah, right in line with what I'm seeing. That's awesome. So sorry, I I'm interrupting you, keep going.   Kiera (22:47) Mm-hmm. And I think, no, y you are always this is a conversation. It's not like a dictation. So we're like this is real life rift here. I just think people like when you look at it, I think you're more capable than you think you are. I know that you can get the skills, you can figure it out. Like you said, I'm always like, okay, play the what ifs, lose 50% of your patients. Great. Well, we're gonna take those 50%. And there's ways you can actually grow a practice without even needing to have more new patients.   So   we're gonna maximize all those, we're gonna optimize them. You're going to pull in more people. Like it is one of those things that I'm like, I have yet to have a practice go bankrupt. So knock on wood, like you can be my first challenge accepted. Like I feel very confident that I'm not like, unless you completely botch it and you go into malpractice, like we're probably gonna be just fine. So odds of it happening, so minimal. Are you gonna be a little stressed out? Yeah. Like, welcome to business ownership, but you're also looking for growth, and that's why you're being called to this moment. Like   It will not go away. That itch will not go away until you scratch it. And scratching it, and I love that you said like they're waiting five years and that's a $1.1 million minimum. There's so many other pieces to it. So I think I think a lot of dentists like to have facts. I think a lot of dentists like to have that decision make logical sense. And then we back it up with emotional reasons. And I think it's a wise way to make decisions. But I I would just say if you're even remotely curious, like start going down the path. I know when I was going to buy a house.   I needed to go find out, like, I don't know about lenders, I didn't know about interest rates. I did and until you get into it, just like you wanted to be a dentist, but until you got into it and you started working on that type it on and you learned about dropping the box and like waxing it up and working on Dexter and then taking x-rays, like you didn't know it. And I think most of the time the fear comes from the lack of knowing. I will also say, and I've seen this a lot, Brian, a lot of dentists feel like because I'm a doctor and I'm a dentist, if I buy a practice, I should know how to run a practice. And   Brian Hanks (24:38) And   Kiera (24:38) I just want to like   Scratch that out. I want to tell you that that's not true. But I know a lot of you come in feeling like but Kiera, I'm a dentist, or Brad, I'm a dentist, like I'm a doctor, like people expect me to know this. And I want to say you think people expect you to know that, but the reality is you don't. You just need to be scrappy enough to figure it out. No one's expecting you to know anything. Honestly, you probably know way more than you think you do already. But I I want to just cut that because I know a lot of you have perfectionism like fear of being exposed that you're not that great.   Except that you don't know how to run a business just like you didn't know how to prep a crown, but you learned that and you're gonna learn how to do a business and you're gonna do it exponentially well because you are so detail oriented and you're gonna hire a great team around you, hire great coaches around you that you're literally like it's impossible for you to fail. And so I think Brian, like kudos on it, kudos on the stats, any other thoughts that you have around people and like how do they get to the nitty-gritty of actually going through   Brian Hanks (25:26) Let's get some yeah. I'll hit I'll hit you with more stats. Yeah.   Kiera (25:31) that.   Brian Hanks (25:32) Some more facts for dentists. You and you mentioned the failure rate. What is the actual failure rate in dentistry? It's it's 0.14% of dentists go bankrupt. Okay. And it's always, always, always one   Kiera (25:43) Incredible.   Brian Hanks (25:43) of three things. It's drugs, divorce, and then jail. You know, some kind of felony that doesn't have anything to do with practice. so you stay away from those   Kiera (25:51) Yep.   Brian Hanks (25:52) three things and you're guaranteed not to go bankrupt.   And it so what do dentists actually need to buy practice? We've done a good job of pumping people up, given the rah-rah speech. What do you actually need? You need five things, okay? and I almost guarantee you, unless you're in dental school right now, listening to this, you have the five right now. All right. almost guaranteed. and I'll go from hardest to easiest, Kiera. Okay. Hardest for people to get is you need 50k   Kiera (26:18) Okay.   Brian Hanks (26:19) cash. You need some cash. 50k is your magic number.   Has to be liquid. It's gotta be in a checking   Kiera (26:24) Mm-hmm.   Brian Hanks (26:24) savings money market account. Can't be in an IRA or home equity or something like that. but you need that money to show the bank that you're responsible. And by the way, you don't actually hand that money over to the bank. You keep it. Yeah, the bank just wants to see that you have some money to see that you're responsible.   Kiera (26:39) Mm.   Brian Hanks (26:40) And if you know COVID shuts us down again, can you still pay the bank the bank back a few months? All right. So most people have that.   Kiera (26:46) Mm-hmm, mm-hmm.   Brian Hanks (26:47) They've got fifty K or access to fifty K. That's like a side thing we could talk about.   Kiera (26:51) Totally.   Brian Hanks (26:52) Yep.   Kiera (26:52) Mm-hmm.   Brian Hanks (26:53) you need production history. You got to be able to do about 80% of the production of what a seller could do. So million-dollar GP practice, let's say 250 of that Kiera is hygiene, means the doctor was doing 750k a year in production. that means you as an associate need to do about 600   a year   Kiera (27:12) Mm-hmm.   Brian Hanks (27:12) to buy a million-dollar practice. Okay. Most associates listening, you know, public health, military, there are some special exceptions where we need to learn how to count.   procedures and things   Kiera (27:22) Mm-hmm.   Brian Hanks (27:23) like that. But most associates, they can do 600 to buy a million dollar practice. Okay, the 80%. most dentists don't have any problem with numbers threes and four, number three and four. Number three is you got to have a credit score over 680. It's pretty low. And it's a green light, red light. 681 credit score gets you the same interest rate as an 820. And and then you need a clean credit history is number four. And so no bankruptcies, no short sales, or a really good story.   Behind a bankruptcy or short sale. And then you need one year of experience out of dental school or a residency program. GPR, AEGD, specialty program, whatever it is. If you're in a residency program, you could buy a practice the day you get out of your residency. So that's it. And so technically, Kiera, you need number six. Number six is you need a practice to buy. And I'll be I'll be really blunt with people, that's the   Kiera (28:17) Mm-hmm.   Brian Hanks (28:17) hardest step.   Finding a good practice to buy is the hardest thing because everybody   Kiera (28:21) I agree.   Brian Hanks (28:22) wants to look for the practice in their pajamas. They think it's like buying a house. Like I'm gonna go on the MLS and I'm gonna look   Kiera (28:28) Mm-hmm.   Brian Hanks (28:28) for a dental practice. There is no such thing as the DLS, there's no dental listing service. And so if you're in your pajamas looking for a practice to buy, it's   Kiera (28:34) Mm-hmm.   Brian Hanks (28:36) not there. Sometimes it is, which is why people do it, but it's almost certainly not there, especially in the city you want to live right now. and so we'll have a podcast episode about how to   Find a practice well. But the sh here's the short version is you go talk to dentists. Build a network of dentists that know like and trust you. That's the   Six things and and most associates have And so attitude, like don't let us stop you, don't be scared. Like we did the like pump you up version of the speech. And here's the facts to back that up, is it's not actually that hard. Like with those six things, banks will not only give you a hundred percent of the purchase price, they'll give you a hundred percent of the purchase price, and then they'll hand you another seventy-five K in cash just to make sure you don't run out of money on the first day. Sometimes it's a hundred K. I've seen d banks give two hundred thousand dollars in cash.   Kiera (29:21) Mm-hmm.   Brian Hanks (29:21) before they even walk through the doors with you know the key in hand as an owner. So it's awesome. If if you're thinking about ownership and nine out of ten dentists are at some point in their career, it's it's really not it's not it's simple. It's not necessarily easy, but it's simple.   Kiera (29:41) Yeah. And Brian, even on the I've been talking to the Bank of America guys, and they were like, we even give like thirty to forty thousand to a new startup practice for consulting fees in addition to our working capital because   Brian Hanks (29:52) Yeah.   Kiera (29:53) we know that it's also going to help grow them. So there's so many pieces, and I think you've just listed off like really, I agree, like finding the practice and like sending out the postcards, getting to know the network, finding the dentist, like the practice that actually works for you, finding a seller that wants to sell for the price that you want.   I agree with you 100%. That is the hardest part. But I think Brian, you did an incredible job of breaking this down from the like, okay, you're probably gonna do it. Nine out of ten is do buy that. What are the exact steps that I need to take for this? And then I agree with you. Like, absolutely a follow-up podcast on like how to actually find a practice. But Brian, I'm curious if people are interested, like they want to start connecting and like this is what you do. And I know you guys are really generous with your time. How do people connect in with you to like even start the process? Like, again, I feel like curiosity.   Is the best place to be. Like let's just ask the questions. Let's figure it out. So Brian, how do people get connected in with you?   Brian Hanks (30:41) Pop over to Amazon, type in How To Buy A Dental Practice. That's the book. if you want, by the way, if you want a cheaper copy, you can go to the website. The website is DentalBuyerAdvocates.com. I'm happy to ship it to you like as a publisher copy, no strings attached. but yeah, just pop over to Amazon, DentalBuyerAdvocates.com. Care if people want to email me directly. I always offer this. And it's so fascinating to me how few people actually take me up on it. I would be more than happy to have a half an hour conversation with whoever you are, free of charge.   Send me an email, Brian@BrianHanks.com. It's B-R-I-A-N and Hanks like Tom Hanks. So yeah, that's how you get a hold of me.   Kiera (31:20) Amazing.   Well, Brian, thank you for breaking this down and for all of you listening. I hope that today was just a really insightful podcast for you. I hope it gave you the facts to back it up. I hope it gave you the emotional piece. I hope it gave you kind of the like step by step by step of how to get there. I'm so grateful for Brian being here. Everybody connect in with him. And for all of you listening, thank you for listening and I'll catch you next time on the Dental A Team Podcast.  

The Summer of Rollin continues...and Jean Rollin is starting to become Jean Rollin.In Episode 575, we journey into The Shiver of the Vampires (1971) and Requiem for a Vampire (1971), two films that show Rollin evolving from an experimental filmmaker finding his voice into an auteur who has seemingly discovered exactly what kind of cinema he wants to make.With The Shiver of the Vampires, Rollin pushes further into his fascination with nudity, sexual liberation, desire and the female form, while surrounding it all with the crumbling castles, deserted landscapes, gothic imagery and dreamlike atmosphere that were rapidly becoming his trademark.But beneath the naked bodies and vampire mythology is something far more interesting: isolation.Rollin's characters often seem detached from the real world, wandering through beautiful spaces that feel simultaneously romantic, threatening and completely unreal. His films aren't simply stories happening in strange locations, the locations themselves become part of the story.Then comes Requiem for a Vampire. And Rollin basically decides that dialogue is optional.For almost 40 minutes, the film barely speaks a word, instead allowing imagery, music, movement and atmosphere to carry the narrative. It's a bold, egotistical and utterly fascinating decision, one that could have collapsed into pretension but instead becomes one of the clearest demonstrations of Rollin's confidence as a filmmaker.We'll explore how Requiem strips away conventional storytelling and replaces it with something closer to a cinematic dream, a film where logic takes a back seat to mood, composition, sexuality, fantasy and the hypnotic power of the image.Along the way we'll explore:The evolution of Rollin's vampire mythology.Nudity, eroticism and sexual liberation in his cinema.The beauty and isolation of his locations.Rollin's growing obsession with dream logic over conventional narrative.The audacity of almost 40 minutes without dialogue.How these films cement the visual and thematic DNA of a Rollin movie.What makes his cinema so instantly recognisable, and so difficult to imitate.By this point, Rollin isn't simply making vampire movies. He's creating Rollin movies.Beautiful, bizarre, erotic, melancholic, surreal and often completely unconcerned with whether the audience knows exactly what the hell is going on.So once again, pour the wine, head for the nearest crumbling castle and prepare to lose yourself in the strange, seductive world of Jean Rollin.The Summer of Rollin continues...The following texts and documentaries were used in this series:Lost Girls: The Phantasmagorical Cinema of Jean Rollin - Samm DeighanOrchestrator of Storms: The Fantastique World of Jean Rollin (2022) - Kat Ellinger and Dima BallinIndicator 4KUHD Releases of both The Rape of the Vampire & The Nude Vampire - Street date June 2023.The grading follows the Netflix rating style of 1 = Hated It, 2 = Didn't Like It, 3 = Liked It, 4 = Really Liked It & 5 = Loved ItShiver of the Vampires:Duncan: 4.5Requiem for a Vampire:Duncan: 5Our new RSS Feed: ⁠https://anchor.fm/s/13ba6ef0/podcast/rss⁠Check out the show on ⁠Anchor⁠, ⁠iTunes⁠, ⁠TuneIn⁠ & on ⁠Stitcher Radio⁠.Please leave us feedback on ⁠iTunes⁠, podcastunderthestairs@gmail.com and follow us on ⁠Facebook⁠.Timecode For Episode 575:00:00:00 - Intro 00:03:44 - Shiver of the Vampires00:14:18 - Requiem for a Vampire00:26:54 - The Indicator 4KUHD's 00:32:14 - Closing the Show

A few years back, Jesse got a random email that turned into an on-camera stint hosting wine expert Jermaine Stone around Savannah for “Street Somm,” a Tastemade series pairing street […] The post Eating and Liking on Netflix first appeared on Eat It & Like It.

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Elle Woods is back! And this time, we're heading to high school....in Seattle?? Jillian breaks down Season 1 of Prime Video's Legally Blonde prequel series, Elle, following a 16-year-old Elle as an unexpected family move sends her from Los Angeles to Seattle, where she faces new friendships, family drama, and plenty of people who underestimate her.Jillian shares why she was initially skeptical of the series, how Lexi Minetree captures the spirit of Reese Witherspoon's iconic character, and why the show's focus on Elle finding her confidence and staying unapologetically herself makes this prequel work. Plus, she counts down the Top 5 “What, Like It's Hard?” moments including surviving the world's most humiliating “pool party” to exposing corruption at her school and making a life-changing decision in the finale. And, of course, we need to discuss that winter informal kiss, the love triangle cliffhanger, and everything Season 2 needs to answer.00:00 Intro to pod00:15 Prequel to Legally Blonde05:08 Lexi Minetree as Elle Woods06:05 YA show07:44 Mother - Daughter08:53 Season 1 recap12:55 Top 5 "What? Like it's hard?"13:23 Pool party17:15 Funeral20:23 Homecoming25:47 Elle exposes corruption28:17 Internship34:45 Seattle changed Elle36:19 Season 2Thank you to Matt Buechele (@mattbooshell) for creating our new theme song. You can listen to "Sunscreen" on Spotify: https://open.spotify.com/artist/1gFHHF3QyQxjbbKXV3qLu9Buy our merch: ⁠https://www.etsy.com/shop/PreviouslyOnTeenTV⁠Follow Previously On Teen TV on Instagram: ⁠⁠https://www.instagram.com/previouslyon_teentv/Follow Previously On Teen TV on TikTok: ⁠⁠https://www.tiktok.com/@previouslyon_teentv⁠⁠Subscribe to our YouTube: ⁠⁠https://www.youtube.com/channel/UCe2lgvvZGKMrQ8v24FmDdWQ?sub_confirmation=1⁠

*5:00am: Medical Procedures That Scares You *6:00am: Spoiled Brats, Who Is the Person That Unexpectedly Changed Your Life? *7:00am: Are We Helping A.I Through TikTok Trends? *8:00am: School Time Changes, Most People Don't Like It, But I Love_____

In recent months, the open vs closed, and US vs China discussions on model ownership and sovereign/local AI have heated up to a fever pitch. So it is very very good news that Poolside AI are finally emerging with new models, like Laguna S 2.1, that are beating Thinking Machines' recent release nearly 10 times their size.Poolside's recent tech report got a lot of praise due to their level of detail, and Vibhu first covered Laguna's recent technical report on our paper club:From spending $12 million building language models for code before the world cared to creating a Model Factory that can take a model from pre-training to release in eight weeks, Eiso Kant has spent more than a decade betting that code is the path to AGI. In this episode, the Poolside co-founder joins swyx and Vibhu to explain why ChatGPT felt like vindication, why Poolside embraced open weights and open research, and why he would rather live in a world with 100 foundation model companies than five even if Poolside were one of the five.We go deep on Poolside's Model Factory: the engineering systems behind 10,000–20,000 experiments per month, streaming data directly into training, reproducible experimentation, low-precision compute, and agents that increasingly write code, launch jobs, evaluate results, and modify the pipelines used to train future models. Eiso also unpacks their recent launch Laguna S, why persistence, verification, and backtracking may matter more than raw intelligence, how much capability remains inside smaller models, why reinforcement learning will move earlier into pre-training, and why next-token prediction is still extracting too little from the web.We also discuss model-harness co-design, Poolside's path from coding agents to AGI, why Eiso thinks MCP and traditional tool calls are “stupid,” the real economics behind frontier-model training, Poolside's $500 million raise, open-source AI, regulation, NVIDIA and TSMC's influence, engineering productivity in the agent era, high-agency teams, and hiring at Poolside.We discuss:* How Andrej Karpathy's RNN work inspired Eiso to start building language models for code in 2015* Why Eiso spent four years and $12 million pursuing an idea before the market cared* Why ChatGPT felt like vindication and brought Poolside back to open source* Why Eiso would prefer 100 foundation model companies over an oligopoly of five* The difference between releasing open weights and publishing genuinely open research* Why Poolside deliberately built a global research organization outside the Bay Area talent war* Why model building is ultimately 90% engineering* The Model Factory: Poolside's end-to-end system for rapidly training and improving models* How fewer than 70 researchers run roughly 10,000–20,000 experiments each month* How Poolside moved from six-month model cycles to five- and eight-week launches* Why streaming data directly into training unlocked faster experimentation* How immutable data, versioned code, and reproducibility enable rigorous model research* Why Eiso wants capable researchers to leave their labs and become Poolside's competitors* Why 95% of model building can be reduced to better data or compute efficiency* Laguna S and why persistence, verification, and backtracking can outperform raw intelligence* Why smaller models may handle far more knowledge work than previously expected* Why reinforcement learning will move earlier into pre-training* Why next-token prediction is still failing to extract enough knowledge from the web* Why distillation and environments have become the AI industry's favorite “drugs”* Why mid-training is really an early form of curriculum design* Low-precision training, networking bottlenecks, and the next gains in compute efficiency* Laguna S: 118 billion total parameters, 8 billion active, and eight weeks from training to launch* Why model builders can often evaluate a new checkpoint within its first 30 minutes* Model versus harness: where agent capabilities actually come from* Why Poolside sees coding and long-horizon software tasks as a path to AGI* Why Eiso thinks MCP and traditional tool calls are “stupid”* Why future agents will write scripts instead of choosing from dozens of predefined tools* The case for minimal harnesses, containers, and model freedom* Why Poolside is prioritizing vision but does not expect to work on audio soon* Why language may be the most compute-efficient modality for encoding knowledge and reasoning* The real cost of model development and why the final training run is anticlimactic* The story behind the Poolside name and why it represents refusing to lower ambitions* How Poolside raised $500 million while investors still questioned whether AGI was real* Why intelligence could become the world's most demanded and commoditized resource* When open models may become too capable to release without restrictions* Why unilateral AI safety does not work in a globally competitive environment* How regulation could accidentally lock in an oligopoly of two or three AI companies* NVIDIA, TSMC, and the hardware systems underpinning foundation-model progress* Why reinforcement-learning wall-clock time is one of Poolside's biggest bottlenecks* Why Poolside trains models from scratch instead of simply distilling larger models* How AI changes the way companies should measure engineering productivity* Why agency may become the most important quality for employees in the AI era* How leaders align high-agency people through shared goals and clear constraints* Hiring across research, post-training, pre-training, architecture, evals, and engineering at PoolsideEiso KantLinkedIn: https://www.linkedin.com/in/eisokantX: https://x.com/eisokantPoolside: https://poolside.aiTimestamps00:00:00 Introduction00:00:54 Karpathy, RNNs, and Building Code Models Before Transformers00:02:26 The $12M Failure and ChatGPT Vindication00:03:39 Open Source and the Case for 100 Foundation Model Companies00:09:22 Open Weights, Open Research, and Poolside's Global Team00:16:04 The Model Factory: Why Model Building Is 90% Engineering00:20:19 Agents, Automated Experiments, and Early Signs of RSI00:24:04 Streaming Data, Reproducibility, and Scientific Rigor00:30:35 Creating More Foundation Model Companies00:36:07 Laguna S: Persistence vs. Raw Intelligence00:43:01 Reinventing Pre-Training, RL, and Curriculum Design00:52:33 Low-Precision Training and Squeezing More From Smaller Models00:58:37 Model Harnesses, Coding Agents, and the Path to AGI01:09:26 Why MCP and Traditional Tool Calls Are “Stupid”01:13:04 Vision, Multimodality, and Why Language Still Matters01:18:15 Scaling Models and the Real Economics of Training01:20:40 Why Poolside Is Called Poolside and Raising $500M01:27:37 Open Models, AI Safety, and the Risk of an Oligopoly01:33:53 NVIDIA, TSMC, and the Reinforcement-Learning Bottleneck01:41:52 Smaller Models, Distillation, Engineering Productivity, and HiringTranscriptIntroduction: Eiso Kant, Poolside, and Open ModelsSwyx [00:00:00]: All right, we're here in the studio with Eiso Kant from Poolside, together with Vibhu. Welcome.Eiso Kant [00:00:08]: Thanks. Thanks for having me, guys. Good to be here.Swyx [00:00:10]: Yeah, fresh on the plane. You texted me, you were like, “Hey, I'm on my way to SF.” I was like, “You're on a plane right now, right?” Like, hey.Eiso Kant [00:00:16]: I know. After I texted you, I realized that probably coming in with major jet lag was gonna offer some fun experiences today, but let's do it.Swyx [00:00:23]: I mean, I think the thing I would tell guests is that they don't have to prepare that much because if you're truly working on this every single day, then even, like, what you hazily remember is going to be new for a lot of the audience that don't live in your world every day, right? so 10 years ago, you did a talk at Google Slush, talking about the democratization of AI. and, now here you are, like, open sourcing an incredible new model that we're gonna talk about. But I guess, like, what got you into democratization of AI? Like, it's not obvious from your LinkedIn or something.From Karpathy's RNN Post to SourcedEiso Kant [00:00:57]: No, it's not at all. I don't think it's obvious how I got in this space. I owe getting into this space to Andrej Karpathy.Eiso Kant [00:01:05]: In 2015, he wrote an article called “The Unreasonable Effectiveness of Recurrent Neural Nets.”Swyx [00:01:10]: Neural Nets, yep.Eiso Kant [00:01:11]: And that article, I read it, and I pivoted my startup at the time overnight to working on RNNs, and later LSTMs and Transformer models to be able to write code. If you go to this article and you scroll down, you can start seeing, like, this was the precursor to what ended up becoming language models. So, at least when he was character-level language models that were starting to predict letters, he has an example out here. There's a little Paul Graham generator, and you can read it, and the text makes sense, but it doesn't. and there's a little-- There's an example of code a little bit further down. Yeah, so Shakespeare.Swyx [00:01:47]: Shakespeare.Swyx [00:01:49]: CoolEiso Kant [00:01:49]: And for some reason, I read this, and I went down the rabbit hole of learning everything I could about RNNs and LSTMs, right? This is Transformer paper. And I had built a completely unreasonable belief, that neural nets should be able to generalize to anything and everything, and that language should be able to generalize, to a lot of things that are intelligent and the ability to write code. And so I started building Sourced, which was a fully open source company trying to build, what we used to call machine learning on code, language models on code. And we spent about four or five years on this, till the end of 2019. And that sounds really cool today, but back then, no one cared.Eiso Kant [00:02:29]: Right? Like, no one cared. We were in the dark. Like, we did things along the way. We tried applying convolutional neural nets to, like, the structure of code. We were. when attention came out, we were applying it to LSTMs, and then the Transformer paper came out. And it - it wasn't obvious, and what we missed throughout that entire journey, that we were on the right track, but we should have just kept scaling up. And today, to all of us, the scaling laws and scaling up seems like the most obvious thing. But having spent four or five years of my life on working on language models on code, it wasn't obvious. So I have a lot of respect to folks at Google and OpenAI and others who took that confidence and kept going. we failed ultimately at the time, and it was, like, biggest failure of my career, right? You blew $12 million of investors' money, which was a lot back then.Swyx [00:03:18]: Yep.Eiso Kant [00:03:19]: You spent, still a lot, but, And you spent years with, like, a group of 40 people just obsessing over this problem. And life took a different turn, And it was, and family became a focus, and I kept my heads down and really, didn't really look at language models for the following two years. big mistake considering Following years are gonna be really interesting. And then ChatGPT came out And it was like a vindication. It's like people started texting me. I found, like, my old, work decks and these old talks. And throughout that whole journey, we,ChatGPT, Vindication, and Returning to Open SourceEiso Kant [00:03:56]: We really had a strong point of view at the time that, like, as you're building more capable intelligence, it should be open and open source.Eiso Kant [00:04:04]: When we started Poolside, that wasn't the case at all, and I wanna be very open about it. When we started Poolside, we were like, there was a premise of two things. One is this technology is not gonna stop compounding in capabilities. I think to most people obvious today, but three-plus years ago when we started, most people were still arguing if these were stochastic parrots or not.Eiso Kant [00:04:23]: And the second was that reinforcement learning was gonna be the biggest driver for LLM capabilities. Today, very obvious. Three years ago, was not an opinion held or direction held at either OpenAI or Google or Anthropic or others. And so people looked down on us a little bit. They were like, “ is this really gonna work?” And so we just started working the problem, and we never really thought about open source again. We just kept our heads down and we built our, like, knowledge, understanding from scratch, right? We didn't roll out of an existing lab. So we picked up the papers and started writing code and figuring things out.Eiso Kant [00:04:59]: And it wasn't until the beginning of this year that me and my founder, Jason, picked up the open source conversation again.Eiso Kant [00:05:07]: And if you go back to some of the early things on our website, it was very straightforward. It was we wanna get to AGI, we wanna support a world of abundance, and we wanna be the first company that gets there.Eiso Kant [00:05:20]: But we started talking at the beginning of this year because it became obvious that the world was going in a direction that was starting to like, pick at us a little bit. Like, it didn't, this didn't happen overnight. It was, like, a little bit we were seeing this and we're like, “Okay, The world's going down a path.” And Throughout this journey, there was something that I used as a, as an analogy or thing. So I said well, if I go back to back in those days, 2015 or 2016, we're working on this, and I picked up a fi book off the shelf, and I was reading the book about 2035. AGI is achieved, and the story would be over the following, decades. And it would have that first chapter where everyone's trying to figure things out. You'd get the chapter of ChatGPT coming out And then you would get to the chapter where the world was at a fork in the road, and the one that it picked was one where three or four or a handful of companies were going to create all of intelligence moving forward.Eiso Kant [00:06:21]: And when I thought about that story, it felt like a dystopian fi book, not a utopian fi book. And the reality is, I'm a utopian fi guy. Like, and so We took a step back and said, “Hey, can we play a role here?” Now it was easy for us to do so because we were not at the frontier.Eiso Kant [00:06:41]: If we were at the frontier, I don't think we could have changed our mind. and I don't mean this like it's when the moment there's too much capital involved, too much expectations, you've built up things, right? We're a small team, just improving and improving. And so we knew that we could make that decision now, but it would be a lot harder to make as we got closer and closer to the frontier and caught up to others. And did a lot of soul-searching and a lot of conversations, and said, “No, this makes sense,” Even if there's big unanswered questions, like how the hell do you build a business model with foundation models about open source? Big open-ended question that we do not fully have the answer to yet, right? At what point do you no longer wanna release open source models because misuse of models has, real potential risks associated with it? how is the government gonna respond to open source? but I think it all just came down to one thing, and I'll stop the monologue, is the fact that I rather live in a world that has 100 foundation model companies than a world that has five, even if I was one of the five. And the smallest and most meaningful contribution we can make for 100 to exist is to open up our research and open up, like, our weights right now and figure out along the way how we can, like, do more.Neo-Labs, Model Choice, and the Token EconomySwyx [00:08:01]: Yeah. I think if anything, over the past three years, that has become a bit more true. you are one of a cohort of Neo labsEiso Kant [00:08:10]: YeahSwyx [00:08:10]: That people are now calling that. And, we're, we're doing this on the day that Thinky launched their, new model and you are outperforming them on their, on some benchmarks that they released, right? Like, they just don't have it yet. so it goes to show that I think, like, this is one of those things where, like, there is room for multiple players, and you are seeing a little bit more of the future. Maybe more like 20, not 100, but, like, you are one of the 20.Eiso Kant [00:08:36]: I really hope so, right? I think we I'm, I'm excited about their release, and I'm excited about everyone releasing because, like, ultimately, like, choice competition is both gonna drive progress in the right direction. But the fact that like, we create models and while we all, drink out of the same well of data effectively, we do introduce very different behaviors and biases in our models. Some are intended biases, some are completely unintended biases.Swyx [00:09:03]: Yeah.Eiso Kant [00:09:03]: And if we shape up in an ecosystem in the world where open models are gonna be a part of the token economy, like, I don't think there's any question about it anymore Then we want to be able to live in a world where companies, countries, people can choose and say, “Hey, I am most aligned and I trust most this provider for these things.”Swyx [00:09:25]: Yeah.Vibhu [00:09:26]: I think more than just one of the 20 Neo labs, up until recently, most of open source innovation was coming from the Chinese labs, right? So there's the DeepSeek of the West. Is it today? Okay, maybe it's thinking machines reflection, but there aren't many, right? So, one of the things you guys started in France, Europe, but very much now you're taking that American standpoint and more than just that, the point is the Chinese models that we see, they're not super open research. the work you put out is, I think, some of the best. So every few months you get not only frontier models, but also here's a breakdown blog, paper, technical report of here's everything for state of the art to build, frontier intelligence and you're filling that gap too, right? So not just only open weight, not just Western, but also pretty open research.Open Weights vs. Open ResearchEiso Kant [00:10:20]: No, I appreciate it. Look, I think it's, I think it's the most meaningful contribution, right? Weights are a binary. Let's call them what they are. Yes, we can modify them, we can change them, but, like, giving someone the weights does not allow them ultimately to recreate what you're doing, right? And so now there's challenges around releasing data sets, challenges around like releasing certain things, but being able to share your research, like, right, how do we do it? What are the lessons we learned that we spent, tens of thousands of experiments of compute on? I think very much so. One correction though, Vibhu, and I say this because it's been haunting us for quite a few years. We from day zero were an American company.Swyx [00:10:55]: Yeah. They movedPoolside's Global Team and American Company StorySwyx [00:10:56]: To France.Eiso Kant [00:10:56]: So the story once and for all is very. We start as an American company. We have always been an American company, and early on we made a very conscious decision. We said, “We're not gonna hire any researchers in the Bay Area. We're gonna look for talent everywhere else in the world.” and that is everything from Middle Americas, Seattle to, Serbia, and to Taiwan and Singapore and other places. And it was because we took a view that this was gonna become a talent war for this, and I think it has over the years now. Three years ago, that wasn't fully obvious yet. I think today it very much is. And we also realized that, like, some of the world's most capable people with, like, the most interesting, innovative ideas were not just gonna be here. And so it led us to create like a fully remote company. and we ended up opening an office in Paris and London and different places and we have a lot of the team in the US and a lot of team outside. But we always took this view of like, we're an American company, but if we want the best of the best to work with us, we need to take a global view. Now we do also have people here in Silicon Valley, like the company's grown and others, but I think one of the things that, it slowed us down at the beginning, but it has sped us up now, and it's why you're seeing like the progress, I think, on our models and the cadence at which we release, is because we didn't roll out of an existing lab. Right? we didn't, we didn't have a lot of the information that's freely flowing around here at the time. We just took this point of view as like, “Okay, well, let's just work the problem. Let's just go and, like, read the few papers that are out there, and let's just figure this stuff out.” And we made some hilarious mistakes in model training because of that over the yearsEiso Kant [00:12:35]: Like especially in the first 12 months. there's a few that I think still haunt me and scare me. We can talk about them later. but it created a, like, a resiliency and persistency in the team, right? with extremely few people have left us over the years, that, like, told us, “Okay, we can do this.” When we first wrote our first training code base completely from scratch, it wasn't a fork of any open source. It was just like, “Okay, let's build it from scratch.” I remember we had this one moment where we spent three weeks working out an optimizer bug. Like, it was like training just couldn't get stable. We, like, obsessed over it, and we thought, like, maybe we were wrong. Maybe we should have just forked this repo, or we should have. But then when we solved it, I still remember at the time we were like five people in the company. when we solved it, we were like, “Oh, we can do things,” like if we're just willing to work hard. and I think that culture with a very strong engineering bias has helped us, like, get to where we were. And so there's this notion of open source and talent and these things. I think we, We just took different decisions from a different starting point. and I think we are lucky. I do want to definitely call it lucky. And there was a lot of hard work at the team that now, like, that's starting to show up in results.Swyx [00:13:52]: Just ‘cause we probably won't revisit this again, but, and this is a fun recruiting challenge if someone knows the answer. What was the bug? And then we won't tell the solution, but we'An Optimizer Bug and the Value of Building From ScratchEiso Kant [00:14:01]: So the - This - You're gonna test my memory here,Swyx [00:14:04]: Oh, okayEiso Kant [00:14:04]: So but I thinkSwyx [00:14:05]: DirectlyEiso Kant [00:14:05]: I think I can recall. So if you, so if you look at, So if you take like Adam as an optimizer, you have epsilonSwyx [00:14:12]: YeahEiso Kant [00:14:13]: Which is, right, like in the denominatorSwyx [00:14:14]: Momentum and weights. YeahEiso Kant [00:14:15]: Is exactly, in the denominator. And at the time, if I recall, you looked at like the early Llama papers and things like that. People were juicing epsilon, like, quite a bit. Like, they were, like, adding, I don't know if it was E minus four or whatever, like a high value for epsilon.Eiso Kant [00:14:31]: And if you think about this during training, it's like a bit weird and counterintuitive that we're adding noise to our optimizer by just adding effectively, like, a random number in the denominator, right? Like behind the decimal point. And I don't recall the exact bug, but it had - What I remember is once we solved it, we no longer had to juice epsilon as much as, like, was happening in the Llama paper and other places. and it was like one of those fundamental moments where we had trusted this paper that was out there, and we're like, “Oh, no, it has to be this way. It has to have this high value of epsilon.” But it made no sense to us intuitively. Like, why do you have to have this so high? Like, if you're just trying to avoid division by zero, why can't the value be extremely small? and that was like one of those moments where you realize like, okay, finding things out from scratch yourself builds a better intuition. Because the one thing you learn very quickly with model building is that your intuitions that you start with are gonna get beaten up so hard.Eiso Kant [00:15:33]: Right? Like - It's such an experimental science, that the things that seem obvious, you very quickly get to learn, like, you were wrong, and hopefully you figure out why, and sometimes you don't even.Swyx [00:15:45]: Yeah. yeah, so, one of the reasons that you, when you released your new models, Vibhu got really excited. I mean, everyone got really excited. But Vibhu led our paper club on it, and you guys sawEiso Kant [00:15:58]: YeahSwyx [00:15:58]: Obviously. maybe talk through some lessons learned in that, whatever you can disclose. we can focus on the model factory stuff, whatever you think is a good starting point.Model Building as EngineeringEiso Kant [00:16:08]: So I would say that our view from very early on in the company was that model building is ultimately 90% engineering.Eiso Kant [00:16:18]: And I think we all know it in the industry because if you look at where's every researcher spending their time, they're spending their time writing code, right? Looking at data and writing code. And so we said, okay, The state at the moment, like three years ago, was bash scripts and Slurm and spaghetti code bases for training and, like, data pipelines that were patched together. And we looked at this and said, “Well, ultimately, model building is a process.” You're going from raw data, right? Like training raw material, the web, et cetera. you're doing a whole bunch of filtering, cleaning up, transformations, analyzing. These days, that's, far more complex than it was three years ago. then you're training a model, which is effectively a large distributed systems problem, right? Across hardware that has still-- It's become a lot more reliable. It was extremely flaky back then. and now with every new generation, we get our new sets of challenges. And then you go into the next stages, right? There was no training back then, but, like, you got, your post-training and then your reinforcement learning. And so we looked at this and we said, “Well, this looks like an industrialized process. This looks like an end process, that every single part of it has its machinery,” right? If it's your big data pipelines, if it's your crawling ingestion of the web, if it's your, large-scale distributed training, and then you've got your reliability. And we said, “Well, why don't we take some of the world's smartest distributed systems engineers that we knew and make them part of the process of research from day zero?” Not retrofitting it later on, but, like, really from the beginning. And that became our model factory. And so our model factory started with a handful of components. Today, it's thousands of components, and I try to equate it to, if you think about, like, someone who was at the very early days of Foxconn, if they had been there for the following, decade, they would be able to rebuild Foxconn because they saw every decision that led to building that system and all the complexity. If you and I walk into Foxconn today, no chance.The Model Factory and Experiment VelocityEiso Kant [00:18:18]: Right? Because we don't have the lineage and history of decisions that led to that. And so we built early on from the beginning- with a team that really understood that, well, the metric that we are optimizing for is the speed of an idea from a researcher to an experimental result that we can trust to then being part of the next model training.Eiso Kant [00:18:42]: And in the. And because it's such an experimental science, ultimately, in the beginning when it wasn't that complex, you could patch your way around it, right? But now, at any foundation model company, you are running. I mean, we're a small team, right? We're less than 70 researchers, another 35 engineers. and we are running, I haven't checked the latest count, but far more than 10,000, maybe 10 to 20,000 experiments a month that we cut. And so if you look at that scale of every model run that is, like it's ultimately it's, it's you need to be able to trust it as an infra problem. And so what we have now done over the years is gotten really good at that, and just by working it and improving it and obsessing over those end decisions. So now what that means is that you looked up Laguna XS 2 that we launched. It was five weeks from the beginning of training to launch. The model that we're gonna talk about today was eight weeks from start of training, to launch. We started the next model literally yesterday because we now finished the post-training required for the model we're launching, next week or by the time this comes out today. and we move that compute to the much larger Laguna M model that we're now training. And so the model should be an artifact of someone's process. It shouldn't be really a thing in itself. Like, and we treat this like the way you would look at like a SpaceX factory where, yes, the first rocket, really hard to build, but the much harder challenge was building the factory. And now they're rolling off, and no one is really thinking about the next launch anymore. So it's just another launch, it's another launch, another rocket comes off. And that's what we're trying to do with model building.Eiso Kant [00:20:22]: And what has been, which was not planned from day zero, it was in the back of our mind like this will happen one day, is that when you build a really good end model factory with really good APIs and really good engineering systems, Well, what is it perfect for? It's perfect for agents.Agents Inside the Model FactoryEiso Kant [00:20:40]: Because agents are now starting to take over more and more work in our model factory.Vibhu [00:20:43]: Yeah.Eiso Kant [00:20:44]: So I look at the screens when I walk, like when we're, we come together, in our monthly, we do monthly onsites, and I walk behind people's screens and I stop by and I talk to our researchers. And the default is all of these different agents running on their screen that are writing the code. They're launching the jobs. They're evaluating the results that are coming back from the model runs. They are, making the changes. And we're still in the driver's seat. We're still coming up with the ideas. We're still helping with the debugging. But more and more, and this is right now very profound on the data side of our pipelines in both pre and post and the synthetic data pipelines, it's starting to become more on the architecture side as well. You're starting to see these twinklings of what RSI is gonna look like.Eiso Kant [00:21:27]: And that's. So when we talk about, like to your question about our models, every talk about the model factory, And my coolest example of these things is always that when we kick off a new run, doesn't matter if it's a training like big run or if it's now a post, like one of 10 post-training versions we do for like release or many experiments, is that at any given moment, the changes that somebody made that they had experimental results from the day before make it into that run.Eiso Kant [00:21:57]: So there's not like a cutoff 90 days before. Like no, it's like literally from that moment because we can now trust the machine enough. And then you also have to invest in the reliability. So one of my favorite metrics about like Laguna S is that there was no call events, Right? Like completely zero. And we haven't had a meaningful call event, like something to wake up for, as far as I recall this entire year. now there is one asterisk to that. In usually the first six hours of launching a new model run, something breaks because you set a config wrong, you made a small mistake, et cetera. So that's usually there's a little bit of intervention, but that's always within like call periods, right? Not on call. And I think that's starting to now compound. So the model we're releasing now, I love it. It's amazing, but we're already onto the next one. and I think that's the way it should be.Laguna, Five-Week Builds, and Zero On-Call EventsVibhu [00:22:50]: Hey, I also just wanna point out, so for context, this was like a month ago. we found it in the tech report, so we just came in with, “Okay, new model's dropped. Haven't heard about it.” We wereEiso Kant [00:23:02]: Yeah, we're very used to doing this every few months.Vibhu [00:23:03]: We're, we're very much like, “ okay, look, it's like, on par with Kimi, DeepSeek, whatnot, the small ones, Gemma level. Oh, it's a very cool paper on what goes into building.” And then we hit this page, right? Like literally page two of tech report is, “This process allowed us to build the small model from scratch to delivery within five weeks applying the lessons”. And then I'm like, oh, this paper is not about here's a tech report of benchmarks and here's how many tokens it was trained on. Like for people that wanna dive more from what we're not gonna discuss on the podcast, it's all laid out here, right? FromEiso Kant [00:23:38]: YeahVibhu [00:23:39]: Custom software that agents can use to interface with training code, training data.Eiso Kant [00:23:45]: Yeah. Well, link the paper correctly, so yeah.Vibhu [00:23:47]: Yeah. All that stuff. read the paper here, but,Technical Report Principles and Streaming Training DataEiso Kant [00:23:50]: But I would like to. I love principles, and I think that is a good starting off point for maybe telling some stories. Maybe we can go one by one past the principles. I'll just call out that Dagster just got bought by a Prefect.Vibhu [00:24:01]: Yeah.Eiso Kant [00:24:01]: Isn't it fun? But yes, I'm very familiar with Dagster. just anything where like they trigger some story.Vibhu [00:24:07]: So, well, I would say, well, experiments code's obvious, but I think one of my favorite things is, I don't know where it is in here, but early on, and I still think this is the case a lot of foundation model companies, people prepare their training data sets, they get packaged up, then they get copied over to a training cluster distributed across all of the nodes, and then training starts.Vibhu [00:24:30]: And we looked at this like three years ago and we were like That makes no senseEiso Kant [00:24:36]: You lose so much time because the moment you have to rematerialize the data set, you have to make a change, you have to fix something, et cetera, you've got all this time of like repackaging it, right? Toca- tokenizing it, repacking it, moving it over to a cluster, then distributing it across the nodes. The bigger your clusters are, you start using fancy like torrent-like algorithms to like distribute your data. So why aren't we streaming data into training? Right? Something that's very common and like just basicVibhu [00:25:00]: Like just in timeEiso Kant [00:25:01]: Just in time, like good computer science like principle. And that was one of the first things that I think unlocked - the model factory. Because the moment you start thinking about, well, a training job, it doesn't matter if it's a big hero run or a small like, post-training experiment, consumes a certain number of tokens per second, right? And it's not a lot, right? From a like a data, moving data perspective. So we said, well, we have our training cluster, and then we've got like our AWS kinda setup where we can build these amazing big data pipelines. We can set things up. We use Spark underneath the hood, like all these things.Vibhu [00:25:36]: But when you say AWS, it's not actual AWS, it's your internal AWS.Eiso Kant [00:25:39]: It's our internal-- No, it's our internal like just running like our infrastructureVibhu [00:25:42]: Site web servicesEiso Kant [00:25:43]: Exactly. Our stuff running on like an AWS account or on like any hardware, right?Vibhu [00:25:47]: Yeah.Eiso Kant [00:25:48]: And so once we made that shift into I can stream data into training, all of a sudden you realize a lot of things unlock. Because now you don't have to wait for the whole data set to materialize.Immutable Data, Experiments as Code, and Scientific RigorEiso Kant [00:26:00]: You now all of a sudden when you're running data experiments about mixing data, it's a config. Because you've got these data sources that are coming in, and you just - we have this service called Blender that's in the report, where we then say, “Okay, for this run, I want 20% of this source, 10% of this source. I want this much, so many epochs of repetition. I want this to be, shuffled in a certain way,” and your training job can start while the rest of the data is even still materializing. also what it does is because all of this underneath-- So for us, we treated the data layer underneath as like an immutable data layer, and that was really important. Like experiments as code, immutable data layer means that you can always go back and understand literally down to the single token at which cursor it went in on which version of the code.Vibhu [00:26:47]: Yeah.Eiso Kant [00:26:48]: And it took us a I have to admit, like the first year of Poolside, we understood that engineering had to get great, But we didn't understand yet, that this is ultimately in support of like a good rigorous scientific progress. We were quite a - We were a very small number of people, so a lot of it was YOLO ideas and YOLO runs.Vibhu [00:27:08]: Yeah.Eiso Kant [00:27:09]: And we built great infra for the YOLO runs. But once we realized that we treated data as immutable and code as always versioned, and you could always track and trace every experiment end to end perfectly, you could repeat everything perfectly, right? You have perfect reproducibility. I can still reproduce runs from two years ago if I wanted to, right? It enables the scientific progress, like the scientific process, and I think that took us probably about a year and a half into the company to figure out. We also had some great hires, like our head of applied research, Nikolai, who joined us from Yandex, who'd been working on language models since like the early 2020s, I think brought that into the company of like, “Hey, we wanna have even more rigor.” And then once we kinda had the combination of like increasingly more capable platform that allowed people to do more, but had this immutability, we were able to start “Okay, every experiment is truly an ablation. We truly need to understand it.” And I think we became much more scientifically rigorous in the last couple of years, and the infra underneath enabled it. and then there's just fun stuff like, andVibhu [00:28:16]: Yeah, a lot of it's fun, like even just the, one, you share all the ablations, two, picking the data sets, right? There's like a random small paragraph in here where it's just like, “Oh yeah, training data, we have some, we have an auto mixer.” it trains eight small models, scales them up, picks the training data set. We don't even need to look at it. I'm like, “Wow, a lot of engineering rigor there.” And there's just, there's just a lot in here.Publishing Research and Giving BackEiso Kant [00:28:40]: Yeah, and it'- and look, and we wanna put out more. Like we, We treat writing papers as something that we haven't earned the right for yet for a long time. So you earn the right to spend time, publishing research once you're at the frontier, because until then, you're catching up, and every minute and hour in this industry matters. Like I obsess over it, not just the wall clock time from idea to result, but just general like time every day that we, waste is one that doesn't allow us to catch up. But in this case, we said, “Okay, we're gonna give ourselves.” I think we gave the team like three or four days while still doing their work, like give everything in there. And to your point earlier, if your stuff, it's easy to like put it out. And so there's so many more things that we wanna talk about over time, and we will definitely start doing. And as we earn more of the right, but also now have like added to our mission that we want more foundation model companies to exist, you'll see us like be way more proactive, and just trying to keep dropping some of those like things that we've learned along the way that can help others like speed up.Vibhu [00:29:40]: Which is the other cool side of this, right? It's, it's not like, back to your point, it's not just here's the benchmarks of our training. If you want to replicate, here's experiments of optimizers, data sets, post-training. you lay out a lot of it here alongside here's your system for how to do it? So it's, it's really like promotingEiso Kant [00:29:59]: No, thank youVibhu [00:29:59]: Other people can do the same.Eiso Kant [00:30:00]: And by the way, I also wanna make clear, right, we have been incredible-- Like we've taken a lot of advantage of the fact of all the open research that others have published, Right? And you mentioned, the Chinese labs, and we I think it's important that there's, from every country and every culture and background, including like Western companies like us, there's different models that come out that people can choose to trust. But I think we do have to give credit where credit's due, right? The incredible Chinese lab have done an amazing job at sharing their research, and we have definitely like been on the receiving end of taking advantage of that. So when you're on the receiving end of something coming to you, I think it's, you also have an obligation to give back.Swyx [00:30:39]: Do you have a favorite or underrated Chinese lab that you wanna shout out? Everyone shout outs DeepSeek.Chinese Labs, Zhipu, and PersistenceEiso Kant [00:30:44]: That's a good question.Swyx [00:30:45]: Moaan obviously for Therapsi. Yeah.Eiso Kant [00:30:48]: Yeah, look, I think, I think obviously everyone's been talking about Zhipu lately, with 5.2. I think what most people don't realize is when they started.Swyx [00:30:59]: Yeah.Eiso Kant [00:30:59]: Right? They started years before ChatGPT.Swyx [00:31:02]: They just rebranded. YeahEiso Kant [00:31:03]: And so, I've like, I remember how hard it was to work on these things Before the rest of the world got excited about it. And so I have an immense amount of respect for people, who were working on improving models when it wasn't the sexy thing to do, when believing in LLMs, was gonna get you ridiculed. I remember like back in 2016 when we were doing what we'd call, machine learning on code with some of these models. we would-- people would just laugh at us, like they'd be like, “This makes no sense. Like why are you wasting all these, like, millions of dollars on trying to figure this out?” And so I would say they're probably the one that, I think deserves a shout-out, not just because their latest model is very good, but because they fought to get here. And I think, I think every foundation model company it takes time to get here, right? It took us three years to get to the model that we're, that we're now gonna be releasing. and now the time in between the models is coming, is counted in weeks. It's no longer counted in months or years. But this stuff's hard. and if we can make it a little bit easier for the next person, like we should all do so. Because if we don't do so, we're, we've got a small window before models are really impacting recursive self-improvement to a level where catching up otherwise might become unfeasible. And we should try to, in that window, encourage as many labs or however we wanna call them, like to start. And so one of my currentEiso Kant [00:32:36]: Mission, but qualm is like I wanna encourage whoever is a researcher right now who thinks they can tackle this to go and leave and become my competitor.Eiso Kant [00:32:45]: Like start another foundation model company because I think we need it. I think otherwise we're not gonna be in the world where, I don't want to just be the fifth or the sixth company that wins. I wanna look at a world where there's lots of choice.Starting a Foundation Model CompanyVibhu [00:32:57]: What else do people not see in starting a foundation model? it's, there's a lot of compute, there's a lot of capital required, a lot of compute. You lay out model factory and how to do the training, but there's a lot there, right? That's,Eiso Kant [00:33:10]: Well, look, it's, I in turn-- this is an oversimplification, and I always asterisk it with that because it can land a little bit the wrong way in people's minds. But I think you can sum down, And I saw it, 95% of model building to just doing, you're just doing two things. You're improving data or you're improving compute efficiency. And I know that feels like an oversimplification for the incredible, like, Gifted and skilled work people do. But if you really look at it, like what are we doing? We are looking at data, we're generating new data, we're improving data. and the only way to do that is to look at the data, right? That's a big part of foundation model building. And on the other hand, we come up with these incredible breakthroughs in inference, in architecture, and new attention mechanisms. But what are they really doing? They're bringing compute efficiency. Now, we have definitely had some breakthroughs over the years that allow for more model capabilities. But at the limit, if you could train a large enough model, right, like, and you had infinite compute, we probably-- if you had infinite compute, you'd be at AGI probably already tomorrow.Eiso Kant [00:34:12]: Right? Like it's not. And so, and let me say that infinite compute with infinite ability of much faster networking because networking ends up being more of the bottleneck than compute. But, so I do think that's, those are the main things. And to just realize that this is engineering. I think it's become more obvious, but I think for quite a few years, people have held foundation model companies and researchers and others on this pedestal of like you're doing incredible magic or rocket science, or only like, Nobel laureate physicists can do this. And don't get me wrong, there are some really hard problems that need to be solved, but a lot of the work that all of us are doing on a day Is not sitting down trying to solve a math theorem. A lot of the work that we're doing is just really doing the basics right, writing good code, looking at data, improving it, running experiments, looking at plots, trying to see like, hey, trying to shape our intuitions. And a lot more people could be highly capable researchers. and I think that's, it feels far for people to do so. But I've seen in our own company, we've seen engineers become researchers because the model factory allowed them to be, have a much lower hurdle of running experiments and trying things. And one of the guys on our team who started as an engineer building our agents is a legit reinforcement learning researcher now, making real progress. and that happened in the span of like six months. that would've not been what I think most people assumed was possible, a couple of years ago.Swyx [00:35:46]: Yeah. I think one of the interesting moments is when you can self-host, like, if in a programming language, like if you can compile the language in the language, the equivalent is can you use your own tools, right? You have the pool CLI, you have your own models. presumably you're not only using your own models. There's no way. But like, what's that percentage over time?Laguna S, Persistence, and Behavioral GainsEiso Kant [00:36:10]: This is the first model that we're releasing that is starting to meaningfully contribute to our own work. It's not a it's not state-art model yet. Fable and other, they're, they're very capable models, but Laguna S Is really interesting. I'm gonna pull up the quote. Peng Ming, one of our heads of applied research, said something, last week as the model came out about 10 days ago, much better than we had hoped for or expected. And he said, I have the feeling that a lot of the gains in Laguna S come not from more intelligence, but more from different behavior, more verification, less taking things for granted, not declaring victory early, and being way more persistent. And to be honest, those are more predictive than raw intelligence for success in human also to some degree. And this was, he wrote me this on 5th of July on a Sunday, and it's been burned in my brain ever since because the Laguna S model, as you'll see it and why it does so well on benchmarks and why it does so well in using it on a day basis, is that it's just incredibly persistent. It reasons a lot. I do call that out. We have work to do on making it more efficient. We have to work to do on offering different reasoning modes. But this is the model that has been able to do things that I never thought it could do. A hundred eighteen billion 8B active model, which is not that large. It fits on a DGX Spark and still runs at, thirty, forty tokens a second on a Spark, is able to solve Erdős 397 independently. It's able to do complex programming tasks. It's able to. I asked it this morning to make me a Fi scanner without using any external libraries on my Mac, and it's, like, figuring out, like, the core WLAN API by really persistently trying to understand it without access to the internet. And more, I love vibe checking. I've probably spent eight to ten hours a day with this model for the last ten days.Eiso Kant [00:38:05]: I'm not exaggerating. I was on my eleven-hour flight yesterday. I spent ten hours reading trajectories and traces and, like, of the model.Eiso Kant [00:38:12]: And what I take away from it is exactly what Peng Ming said. We are gonna be able to squeeze so much more out of smaller models than I think we had imagined in the industry because, yes, there's intelligence and larger models are more intelligent. Like, no doubt about it. We should continue to scale up. but the behaviors of being really persistent, of being able to backtrack when you're wrong, of, like, understanding how to interact with your environment show us that we can get a lot more out of it. And this, for me, has created a bit of a Question in my mind the last couple of days. If you think about where we're using models today, right? We are using models, say, for knowledge work. Represents twenty-five percent of the global economy, twenty-five trillion dollars of work.Eiso Kant [00:39:00]: As we scale up models and they become more intelligent, we are excited about using them more and more for pushing the frontier of science.Small Models, Knowledge Work, and CommoditizationEiso Kant [00:39:08]: And if you look at the frontier of science, like true breakthroughs in science, they have been linked, they are linked to more intelligence in many places. Einstein figuring out general relativity is able to bring ideas together that other people would have not brought together. And I think one of the many dimensions of intelligence is the ability to do that, and it's something we clearly see that as models get larger and more capable, they're able to pull more ideas and threads together that a smaller model wouldn't be able to.Eiso Kant [00:39:36]: And we're starting to see examples of that in medicine and, like, in bio and other things. But if you think about the majority of knowledge work that we do, and it includes building software. I'm a software developer at heart first and foremost probably, although I probably can't say it that much anymore as I don't write production code in years, is that what makes us good is our persistence. It's our ability to encounter a problem and backtrack and say, “I need to go figure out this bug. I need to go research this. I need to go look at the documentation. I need to, like, try different, five different ways to see, like, if I can solve it.” But it is not necessarily bringing three ideas together from radically different fields. And so if we are now seeing, and I think Laguna S is an example, that we are able to make a relatively small model much more capable than I had definitely predicted or any previous, like, benchmarks had shown for any model remotely this size or even larger, At least on coding tasks, that it's because of the behaviors. And so now the question I have, and I don't have an answer, it is I know at the limit, so infinite model size, right, extremely large model, and the cost of that model is gonna be very expensive to run. We know this, right? So larger model ROI.Eiso Kant [00:40:52]: So I know that at the very limit, I'm not gonna use the world's largest model one day, quadrillion parameter, whatever crazy, like, scale we scale up, to do a basic coding task. Already today, I'm starting to size down for certain tasks.Eiso Kant [00:41:07]: So it means that there is an optimal. It means there's some curve that goes as we go up to model size for knowledge work, at some point we're at the peak, and after that, the return on investment of using a bigger model, just doesn't make sense.Eiso Kant [00:41:22]: Now, I think the question is, before I would have thought that peak was extremely very far away.Eiso Kant [00:41:30]: This model for me is the first sign that Maybe that peak is At a trillion, five trillion, ten trillion. Maybe we can just squeeze way more out of these models. I'm no longer thinking that we need two or three orders of magnitude on the largest models to be able to, solve knowledge work, the accounting, the legal, the code that we write. And so if that holds true, It is an argument for the commoditization of models. It's an argument that open source can win and, like, succeed in this world. And now it's of course a self-serving argument and it's a hopeful argument, but theoretically at the limit it works. We just have to go discover in the next couple of years of how much more we can squeeze out. Now, I do want to put a big asterisk. This does not mean I'm against scaling models. I think we ultimately only succeed if we scale our models as large as our competition. I do not like. I think we should not put our head in the sand and say we're gonna be king of open source small models. I think that's, It's a out. It's trying to be king of your own kingdom, but not realizing what the rest of the world's doing. All of us rather use a smarter, faster, more model. It's a sign of hope. And so I don't wanna overly state this is a good model. We have a long way to go to get to the state-art. But what hopefully people take away when they use this model is that the behaviors inside of it are what push it to be far more capable, less than necessarily the number of parameters.Pre-Training, Mid-Training, and RL Moving EarlierVibhu [00:43:03]: Is that mostly post-training? LikeEiso Kant [00:43:05]: YesVibhu [00:43:05]: Right.Eiso Kant [00:43:06]: It's entirely post-training.Vibhu [00:43:08]: Are we done improving anything on training? Is, like, training done?Eiso Kant [00:43:12]: No.Vibhu [00:43:12]: Okay.Eiso Kant [00:43:13]: SoVibhu [00:43:13]: I just wanted to cover training, and then we go post-trainingEiso Kant [00:43:15]: Training is not done. I mean, look, there's a part of training of just dealing with skill, right? Every new order of magnitude of model skill, you are going to get new things you gotta solve for. That'- but those are ultimately, engineering challenges.Eiso Kant [00:43:31]: I have a, I would say, a not commonly held opinion that reinforcement learning Will move earlier and earlier into training.Vibhu [00:43:42]: Yeah, training.Eiso Kant [00:43:44]: Not even training. Like training today, right, is, like if you look at - So we've been working on this for years already. and I think the best-- I think the first time we saw it out in public was the DeepSeek Zero paper. this is a year and a half ago, I think, if I recall correctly. where, you can Very early on in a model as it starts capable of being able to use language, et cetera, induce reasoning. and so the question that I have is like, we have this- we have the dataset that's the web. and the web, I think we could arguably say probably has The totality of humanity's knowledge somewhere encoded in different places. It's a huge variance degree of quality, from garbage data, and like once you look at training data, you really get humbled of like what the web is, to like, the most greatest scientific papers and best blog posts and like, best transcripts and whatnot.Eiso Kant [00:44:39]: And so now What we are trying to figure out, and have been doing a lot of work on, and it's a place where maybe not as open as we're on other things, but we will become more over time. we've been spending a couple of years really doing research on how can we turn the web into not just next token prediction, but into a way to teach the model to think earlier in its training. and I think there's a huge amount of gold to be found there. I think we are right now in, we've got some drugs in the industry. One of the drugs is distillation. Another drug is, more environments. Like, and they're great, and they make us feel good, and they make the models better, and like we're all addicted to them, and we'll use them, right? in various different ways. and but ultimately, I think we are still barely squeezing out of the web what we should be getting out of the web.Eiso Kant [00:45:33]: I think just next token prediction during training is not enough.Eiso Kant [00:45:36]: AndVibhu [00:45:38]: YeahEiso Kant [00:45:38]: I think we'll see some very interesting things still happen. and that RL in post-training to induce behaviors, to improve things, like I think - the whole world knows how to do this now. I think we're, we're scaling it up. Everyone is. But I wonder if we need to go as far as we're going today with environments. I'm not sure yetVibhu [00:46:01]: You mean we're going too far?Eiso Kant [00:46:02]: I'm, I'm not sure if the path to AGI is justVibhu [00:46:06]: Is more environmentEiso Kant [00:46:07]: More environments.Vibhu [00:46:08]: It seems like a never-ending, “Okay, I want instruction manual for this table, right? Am I gonna environment out building furniture? Or are we just gonna tail end like we need some general solution?”Eiso Kant [00:46:19]: I think there is, I think there's an ability to generalize more from the web. but I also am very encouraged, like when I look at Laguna S and, which is post-training is, well, is the big impact there. and I see like, oh, wait a second, just by making some of these behaviors much better, we're able to get so much more out of it. It just changes a little bit the way you think about intelligence.Vibhu [00:46:40]: Yeah. The analogy people draw often is the RL phase is where you don't learn as much new knowledge. You shiftEiso Kant [00:46:46]: Yeah.Vibhu [00:46:46]: Yeah. So, you shift distribution, and you can have it reason towards what you want. on your point about training, a lot of training is still just continue training in a domain, say medicine, then you do RL. So still justEiso Kant [00:47:00]: It's just better data, right? Like, I mean, training, ooh, I like how we invented this word. Like it's effectively just like,Vibhu [00:47:06]: Second phaseEiso Kant [00:47:07]: It's the second phase of training With like a really dumb way to do a curriculum. But like ultimately, what you'd want is a curriculum from token zero to token 30 whatever or 40 trillion tokens that really truly is the optimal curriculum for the model to learn. But training is essentially a stage curriculum on the web because we do not have to compute, And, effectively to try to ablate the perfect curriculum, right? And so I'm pretty sure that you'll start to see people talking soon about some other term, and there's two or - ‘cause now we do this, right? We talk stage two and stage three and stage four training and like. But ultimately, all we're doing is we're trying to assign a curriculum to the web data that we have to allow the model to learn better. I think at some point, as things get compute, as models get cheaper to run, as the next generations of compute, this will become more of a continuous spectrum. I also think the reason, by the way, you have training and like stage two and stage three is organizational, Right? It'- this is, I think, a thing where-- that we really try to avoid with the model factory is like Training exists because there's a training team now, right? There's people, or like people in training decide to focus on like a training effort. but what you really want is engineering and scale of experiments that allows for a much more continuous spectrum that you don't, you have infinite stages. Now, we're not there. Compute's not there. Organization design is not there for it yet. but I think we'll get there. we'll look back on a couple of years and be like, “Oh my God, it was so cute that we did our training data like this in such a like naïve way. Like we barely ordered it. We didn't really do a good job at likeCurriculum, Auto Research, and New ObjectivesVibhu [00:48:48]: The building that curriculum will get you that in the industry.Eiso Kant [00:48:51]: And I'll confirm that, when I talk to some researchers that this is a lot of the focus now is like how does training change and what is the next objective other than, next token prediction. I assume you don't have the answers, but you have some ideas.Vibhu [00:49:02]: We have some ideas. We're not ready to talk about it yet.Eiso Kant [00:49:05]: Yeah.Vibhu [00:49:05]: We've been working on them for years, and I think that's the one thing that's also like you asked earlier about, like what's not obvious about building a foundation model company is that you are constantly balancing the table stakes work, the recipe worksEiso Kant [00:49:19]: Yeah.Vibhu [00:49:19]: Versus like your, my crazyEiso Kant [00:49:22]: Pure researchVibhu [00:49:22]: Breakthrough.Eiso Kant [00:49:22]: Yeah.Vibhu [00:49:22]: Pure research and finding that balance and adjusting the percentage to it based on where you are in the race is really important.Eiso Kant [00:49:31]: I mean, so like, this is a nice way. I was gonna bring up auto research at some pointVibhu [00:49:35]: YesEiso Kant [00:49:35]: As another Andrej invention, or coinage, which is like, I honestly, like how many objective functions can there be, right? Like just try 1,000 of them, set it running, whatever.Vibhu [00:49:47]: Man, it's alsoEiso Kant [00:49:48]: Like what you're looking for. You're looking for loss curves like that, likeVibhu [00:49:51]: It's also a thing people take bets on, right? When you say more Neo labs, you're doing a version of we'll do foundation models, scale them up, next token predictors. A lot of other Neo labs that we see want to take a completely different approach, right? At some level, you're right. It's all, compute efficiency, and that's the net objective. But some are okay, different architecture, like vastly different amounts of compute spend. So some are different. They're not justEiso Kant [00:50:19]: YeahVibhu [00:50:19]: They're like, 99% not balancing, here's the vanilla and scale up. They're 99% on, here's novel research that'll change everything.Eiso Kant [00:50:27]: And I think, Luke, I think you. It depends when you started as well, right?Pure Research vs. Table StakesVibhu [00:50:30]: Yeah.Eiso Kant [00:50:30]: When we started, like the novel thing we did was reinforcement learning on code. No long- that's no longer novel by far, but we were like, - that's where we obsessed over when no one believed in RL. So you have to when you start the company, you have to have your own idea. You have to have something that's different that allows you to speed up, right? For us, it was RL to LLMs that later became common, like, Knowledge. But in the beginning, it wasn'tVibhu [00:50:53]: It's cool. this was like your original 2023 blogEiso Kant [00:50:57]: YeahVibhu [00:50:57]: Of purpose.Eiso Kant [00:50:58]: Yeah.Vibhu [00:50:59]: And like you do lay it all out here.Eiso Kant [00:51:01]: We laidVibhu [00:51:01]: The blog is pretty underrated, right? The whole RL on code was very early on.Eiso Kant [00:51:06]: Very early. And even we had to argue with people, like we say here things like to push beyond current capability, to train your own foundation model. We had to argue with people that it mattered that you had your own like, base model. you can fine-tune your way to success, right? major capabilities emerge from training a base model made accurate and useful during fine-tuning.Vibhu [00:51:23]: Which like, for perspective at the time, we knew closed models, OpenAI, Anthropic were huge. The open models we had were like Mistral 7B, a 30B, a 70B.Eiso Kant [00:51:35]: When weVibhu [00:51:35]: YeahEiso Kant [00:51:36]: The date on this thing is wrong. When we published this, it was April 2023. I think this was justVibhu [00:51:42]: YeahEiso Kant [00:51:42]: Happened on a migration, probably found it on archive.org.Vibhu [00:51:45]: Mistral.Eiso Kant [00:51:46]: Mistral had started, we started on the same month, right?Vibhu [00:51:49]: Yeah.Eiso Kant [00:51:49]: So this wasn't even, there was only, I think, Llama out at the timeVibhu [00:51:52]: SnellEiso Kant [00:51:52]: And that's it, right? And so, but I agree. I think we wan

The summer begins...and with it, a journey into one of the most singular, poetic and uncompromising voices in horror cinema.Welcome to The Summer of Rollin, a brand-new multi-part retrospective celebrating the dreamlike, surreal and unmistakably gothic films of French auteur Jean Rollin, using the stunning 4K UHD restorations from Indicator as our guide through his extraordinary filmography.In this opening chapter we travel back to where it all began with The Rape of the Vampire (1968) and The Nude Vampire (1970)...two films that announced the arrival of a filmmaker unlike anyone else working in horror.Before there were sprawling cemeteries by the sea, melancholic vampire sisters wandering deserted beaches and haunting visions that blurred the lines between fantasy and reality, there was a young filmmaker with almost no money, enormous ambition and a determination to create horror that looked and felt like poetry.We'll explore the remarkable story behind The Rape of the Vampire, a production born almost by accident. Originally conceived as a short film before unexpectedly expanding into a feature, its troubled production forced Rollin to think on his feet, embrace experimentation and create something that felt unlike any vampire film audiences had seen before. Released during the political and cultural upheaval of May 1968, the film scandalised audiences, baffled critics and quietly introduced many of the visual obsessions that would define Rollin's entire career.Then, just two years later, we'll see how Rollin returned with The Nude Vampire, his first colour feature and a giant leap forward in confidence. Mixing masked cults, pulp serials, secret societies and his growing fascination with dream logic, the film reveals a filmmaker who had already refined his unique cinematic language while refusing to compromise his wonderfully eccentric vision.Along the way we'll discuss:The unlikely birth of Jean Rollin's story telling directing career.How an accidental feature film launched one of horror's most distinctive auteurs.The evolution of his vampire mythology between his first two features.Why conventional storytelling was never his priority.The visual motifs that would become signatures throughout his career. The beautiful new Indicator 4K UHD restorations and the wealth of historical context found within their superb special features.Whether you're a lifelong admirer of Jean Rollin or stepping into his haunting world for the very first time, this series aims to celebrate a filmmaker who followed his own strange path through cinema, creating films that are as hypnotic, romantic and mysterious today as they were over fifty years ago.So pour yourself a glass of red wine, light a candle, listen for the crashing waves and prepare to spend your summer wandering forgotten castles, lonely cemeteries and moonlit beaches...The Summer of Rollin has begun.The following texts and documentaries were used in this series:Lost Girls: The Phantasmagorical Cinema of Jean Rollin - Samm DeighanOrchestrator of Storms: The Fantastique World of Jean Rollin (2022) - Kat Ellinger and Dima BallinIndicator 4KUHD Releases of both The Rape of the Vampire & The Nude Vampire - Street date June 2023.The grading follows the Netflix rating style of 1 = Hated It, 2 = Didn't Like It, 3 = Liked It, 4 = Really Liked It & 5 = Loved ItThe Rape of the Vampire:Duncan: 4The Nude Vampire:Duncan: 4.5Our new RSS Feed: ⁠https://anchor.fm/s/13ba6ef0/podcast/rss⁠Check out the show on ⁠Anchor⁠, ⁠iTunes⁠, ⁠TuneIn⁠ & on ⁠Stitcher Radio⁠.Please leave us feedback on ⁠iTunes⁠, podcastunderthestairs@gmail.com and follow us on ⁠Facebook⁠.TIMECODE FOR EPISODE 574:00:00:00 - Intro 00:06:25 - The Rape of the Vampire00:22:05 - The Nude Vampire00:32:57 - The Indicator 4KUHD's00:37:18 - Closing the Show

Mark Rocco's Tache Episode 4 with Andy & Kieran from Nuffink & Like It as they watch matches from Brian Maxine, Pat Barrett, John Quinn and learn about many addresses that you can send letters to for requestsSupport this podcast at — https://redcircle.com/graps-and-claps-podcast/donations

A visit to Beaufort, SC to meet the three owners behind Pure Cafe and Bakery — the region’s only fully celiac-safe, nut-free bakery, drawing customers from as far as Atlanta […] The post Pure Cafe and Bakery: Beaufort’s Only 100% Gluten-Free Bakery first appeared on Eat It & Like It.

The shuffle lands on *'Bobcaygeon'* - a love song built on a race riot, and the track one fan ties to losing Gord Downie.---"This is the song I think of when I think about coming to terms with the fact that Gord Downie was going to die."Dave from Montreal---Episode SummaryThe Tragically Hip On Shuffle - Live Stream is back after a week off, and the shuffle lands on *'Bobcaygeon'*, the acoustic-leaning centrepiece of "Phantom Power" and one of the most beloved songs in the entire **Tragically Hip** catalogue. The panel - **Chris from Seattle**, **Greg from the Kootenays**, and **Dave from Montreal** - takes it apart from every angle.They dig into the constellation imagery, the buried 1933 Christie Pitts riot the lyric nods to, the much-debated "Aryan twang" line, and the way **Gord Downie** humanizes a cop caught in the middle of it all. First impressions split the room between love at first listen and slow-burn grower. From there the conversation moves through the song's placement between *'Save the Planet'* and *'Thompson Girl'*, Steve Berlin's organ work, and how *'Bobcaygeon'* became, for more than one fan in the room, the song tied to coming to terms with **Gord Downie's** passing.Along the way: an icebreaker on favourite live Hip performances, a featured live cut from Austin City Limits, poll results that surprise nobody, and a look ahead to the next shuffle. A real conversation about how a quiet song carries this much weight.Tale of the Tape- Song: *'Bobcaygeon'*, from "Phantom Power" (released July 14, 1998), the album's fourth single- TTHTop40 Countdown ranking: #14- First played live: May 10, 1997 - a full year before the record dropped- Last played live: August 20, 2016- Played as a show opener once, and as an encore 115 times- Featured live cut: Austin City Limits, September 15, 2006- Listener poll: 91% Love It, 7% Like It, 1% Tolerate ItThe Panel**Chris from Seattle** returns for his second appearance - the panel's lone American and a working musician. His band Loud Flowers just put out two EPs, the Litho EP and the Earwig EP, recorded in part at Pearl Jam guitarist Stone Gossard's Seattle studio.**Greg from the Kootenays** has caught The Hip somewhere north of 25 times and brings a scholar's eye. He has published academic work on the band, including the article "Ambiguously Hip: The Tragically Hip and Canadian Nationalism."**Dave from Montreal** is a writer, journalist, and tour guide who has covered The Hip for years. He runs non-touristy Montreal tours with Spade and Palacio.Resources, Links & References- "Phantom Power" (1998) - the album *'Bobcaygeon'* calls home- Featured live version: Austin City Limits, September 15, 2006- Setlist and live-performance data sourced from Hipbase and setlist.fm- Live recordings via The Tragically Hip Archive- Band history reference: This Is Our Life by Michael Barclay- Greg's article: "Ambiguously Hip: The Tragically Hip and Canadian Nationalism"- Chris's band: Loud Flowers - the Litho EP and the Earwig EP- Dave Kaufman's Montreal tours with Spade and Palacio - Instagram @davekaufman1, Bluesky @davekaufman- Related listening: Discovering DownieSupport the ShowEditing is hard, and the coffee runs dry. If The Tragically Hip On Shuffle - Live Stream keeps your battery charged, you can drop a caribou in the tip jar at buymeacoffee.com/tthtop40. Tips, always - never an ask.Big thanks to **Chris from Seattle** for coming back and bringing the musician's ear, to **Greg from the Kootenays** for the scholarship and the 25-shows-deep perspective, and to **Dave from Montreal** for going somewhere heavy and honest with this one. *'Bobcaygeon'* is a slow jam about something dark and ominous under the surface, and this panel found every layer of it. Next shuffle is *'The Darkest One'* on July 8 - no show on Canada Day, so mark the calendar.- Explore the full discography, lyrics, credits, and mapped live shows at The Hip Compendium: compendium.tthpods.comThe network home: home.tthpods.comFacebook: community.tthpods.com | Instagram: @tthpods | YouTube: youtube.com/@tthpods | Email: jd@tthpods.com#TheTragicallyHip #PhantomPower #GordDownie #TheHip #TTHOnShuffle #InGordWeTrustSupport this podcast at — https://redcircle.com/tthtop40/donationsAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Hudson Valley Shakespeare's summer season is underway in its first permanent home, the Samuel H. Scripps Theater Center. Designed to immerse audiences and actors in the rich landscape of the Hudson Valley, its unique indoor-outdoor setting for the company's open-air productions offers an unparalleled theater experience.The 2026 Season includes Shakespeare's 'As you Like It' and 'King Lear' this month, and in August, a production of 'Les Mis.' Davis McCallum is the Artistic Director and joins us for a preview this morning.

Jesse is joined by Shawn Hill — aka The Reluctant Foodie SC — a Beaufort-based videographer, marketing pro, and accidental food content creator who’s been quietly building a loyal following […] The post Shawn Hill is The Reluctant Foodie first appeared on Eat It & Like It.

Jesse is joined by William LaFlower, the energetic co-owner of Bandana Burger in Savannah’s Habersham Village, for a fast-moving conversation about burgers, branding, collabs, and building something real. Five years […] The post Savannah’s Bandana Burger: Rising Stars first appeared on Eat It & Like It.

Exploring Tomorrow || (017) Sound Decision (The Martian Queen) || April, 2, 1958The "Martian Queen" is hurtling toward Earth, out of control! It's heading right toward New York City! The body of the show only, the opening has been added from another program. The story is also known as, "The Martian Queen" and "Do It and Like It.": : : : :You can donate to show your support for my podcast and the time I put into creating and posting every week. Donations are through my duane.media PayPal account:https://www.paypal.com/donate/?hosted_button_id=MSL7S8FKCSL94My other podcast channels include: MYSTERY x SUSPENSE -- DRAMA X THEATER -- COMEDY x FUNNY HA HA -- VARIETY X ARMED FORCES -- THE COMPLETE ORSON WELLES.Subscribing is free and you'll receive new post notifications. Thank you for your support.https://otr.duane.media | Instagram @duane.otr#scifiradio #oldtimeradio #otr #radiotheater #radioclassics #bbcradio #raybradbury #twilightzone #horror #oldtimeradioclassics #classicradio #horrorclassics #xminusone #sciencefiction #duaneotr:::: :

Maggie is back for a visit to talk about what she has been eating and liking on the island the last few weeks. A few visits to some popular spots […] The post Monday with Maggie: Eating Good in the Neighborhood first appeared on Eat It & Like It.

In this episode, Jesse clears up the weekend rumor mill surrounding one of Savannah's most beloved old-school restaurants: 45 Bistro. After word spread that The Marshall House Hotel had been […] The post The Future of Savannah’s 45 Bistro first appeared on Eat It & Like It.

This week, we are joined by chef Shannon Foeller to talk about Healer Supper Club, a fast-growing Savannah dinner experience built around creativity, community and a little trust at the […] The post Savannah Heeler Supper Club first appeared on Eat It & Like It.

Jesse spends a few minutes talking about the new Casual Italian eats spot coming to Hilton Head Island’s South End. Capri Pizza HHI will offer Chicago style pies, pastas and […] The post Hilton Head Island’s Capri Pizza: Coming Soon first appeared on Eat It & Like It.

Got it — here it is:

This week on the Eat It and Like It podcast, Jesse Blanco and Maggie Crenshaw reunite after a busy spring to catch up on everything from business changes and real […]

In this episode of Podcast Under the Stairs, we turn our attention to the sci-fi horror-comedy Cold Storage, a fast-paced, fungus-fuelled creature feature packed with B-movie thrills, dark humour, and plenty of gloopy gore. Blending elements of horror, comedy and sci-fi, the film comes from writer David Koepp (Jurassic Park, Mission: Impossible, Spider-Man) and director Jonny Campbell (Dracula), delivering a high-energy genre mash-up that's as chaotic as it is entertaining.STUDIOCANAL bring Cold Storage to home audiences with a Home Premiere release on 6th April 2026, where it will be available to buy or rent digitally. This is followed by a physical release on 11th May 2026, landing on 4K, Blu-ray and DVD. For collectors, there's also a limited HMV Exclusive 4K edition, featuring alternate artwork and a set of four art cards, capped at just 1,000 copies.As a special bonus, this episode also features an exclusive interview with director Jonny Campbell. We chat about bringing Cold Storage to the screen, working with such a strong cast, navigating tone in horror-comedy, and his journey as a filmmaker leading up to this release.The grading follows the Netflix rating style of 1 = Hated It, 2 = Didn't Like It, 3 = Liked It, 4 = Really Liked It & 5 = Loved ItCold Storage:Duncan: 3Thanks to Studio Canal & Fetch PR for the review copy of this movie and setting up the interview with Johnny Campbell.Our new RSS Feed: ⁠⁠⁠⁠⁠⁠⁠https://anchor.fm/s/13ba6ef0/podcast/rss⁠⁠⁠⁠⁠⁠⁠Check out the show on ⁠⁠⁠⁠⁠⁠⁠Anchor⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠iTunes⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠TuneIn⁠⁠⁠⁠⁠⁠⁠ & on ⁠⁠⁠⁠⁠⁠⁠Stitcher Radio⁠⁠⁠⁠⁠⁠⁠.Please leave us feedback on ⁠⁠⁠⁠⁠⁠⁠iTunes⁠⁠⁠⁠⁠⁠⁠, podcastunderthestairs@gmail.com and follow us on ⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠.TIMECODE COLD STORAGE REVIEW00:00:00 Intro 00:02:52 Interview with Johnny Campbell00:16:05 Cold Storage Review00:25:27 Closing

Remember how LL Cool J rapped "Don't call it a comeback?" It was because it wasn't really a comeback...because he was still there - he never actually left. And that's how it's been for me.*Side Note: If you don't any any clue what I'm talking about, consider "Mama Said Knock You Out" required listening.The last episode I published was about a year and a half ago...and I haven't been gone - I've just been living life, and let me tell you - LIFE has been LIFE-ING.The last four years have sucked, and these last two? They reallllly sucked. But something I realized these last few weeks was that this podcast thing? Something I created to help others feel less alone? It's actually made ME feel less alone at a time when I probably needed it most.This isn't a comeback episode, but it's a bit of an update, a "Thank You," and a "What's to Come" all rolled into one.So sit back, press "Play," and maybe enjoy some raw cookie dough while you listen.Did you love this episode? If so, I want to know! Send me a DM @itsactuallykristi on Instagram, or send me an email at Kristi@awakentheextraordinary.com.If you reallllly loved the episode, please "Like It" or "Heart It" or whatever it is you need to do to show the podcast some love on whatever platform you're listening on. And if you leave a review, please let me know so I can personally thank you! (And I actually will!)Oh - and one last thing! You can share whatever episode you're enjoying in your Stories too! If you do, be sure to tag @itsactuallykristi and I'll re-share!OK....I think that's it! Thank you SO much for listening - I really DO appreciate it and I appreciate YOU!

Are you ready for a world where true personal computing is under threat? This week's candid conversation with Framework CEO Nirav Patel tackles why owning your own AI hardware matters more than ever—and what's at risk if we don't. Alphabet tops Q1 estimates on strong Google Cloud growth Is OpenAI Falling Further Behind in the A.I. Race? OpenAI Releases 'Spud' GPT-5.5 Model OpenAI Breaks Free From Exclusive AI Pact With Microsoft Google signs classified AI deal with the Pentagon for 'any lawful government purpose' Elon Musk appeared more petty than prepared OpenAI Set to Redefine Smartphones; MediaTek, Qualcomm & Luxshare Key to Its AI Agent Phone Why Manus has become a crucial prize in the global AI race - Fast Company Australia unveils a 2.25% levy on Meta, Google, and TikTok The Man Behind AlphaGo Thinks AI Is Taking the Wrong Path Amateur armed with ChatGPT 'vibe-maths' a 60-year-old problem Introducing talkie: a 13B vintage language model from 1930 Cursor-Opus agent snuffs out startup's production database OpenAI Really Wants Codex to Shut Up About Goblins Now we know who paid $100,000 to unlock a Sam Altman podcast interview Study Finds A Third of New Websites are AI-Generated The Bloomberg Terminal Is Getting an AI Makeover, Like It or Not Generative AI vegetarianism To buy this Bay Area home, you'll need Anthropic equity | TechCrunch * Chloe vs. History Jack Dorsey-backed Vine reboot Divine launches to the public | TechCrunch noscroll Felvidek Amazon's AI product podcasts 64″D Hyperbaric Oxygen Chamber Timmy's rescue Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Guest: Nirav Patel Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: scribe.how/machines outsystems.com/twit zscaler.com/security

Are you ready for a world where true personal computing is under threat? This week's candid conversation with Framework CEO Nirav Patel tackles why owning your own AI hardware matters more than ever—and what's at risk if we don't. Alphabet tops Q1 estimates on strong Google Cloud growth Is OpenAI Falling Further Behind in the A.I. Race? OpenAI Releases 'Spud' GPT-5.5 Model OpenAI Breaks Free From Exclusive AI Pact With Microsoft Google signs classified AI deal with the Pentagon for 'any lawful government purpose' Elon Musk appeared more petty than prepared OpenAI Set to Redefine Smartphones; MediaTek, Qualcomm & Luxshare Key to Its AI Agent Phone Why Manus has become a crucial prize in the global AI race - Fast Company Australia unveils a 2.25% levy on Meta, Google, and TikTok The Man Behind AlphaGo Thinks AI Is Taking the Wrong Path Amateur armed with ChatGPT 'vibe-maths' a 60-year-old problem Introducing talkie: a 13B vintage language model from 1930 Cursor-Opus agent snuffs out startup's production database OpenAI Really Wants Codex to Shut Up About Goblins Now we know who paid $100,000 to unlock a Sam Altman podcast interview Study Finds A Third of New Websites are AI-Generated The Bloomberg Terminal Is Getting an AI Makeover, Like It or Not Generative AI vegetarianism To buy this Bay Area home, you'll need Anthropic equity | TechCrunch * Chloe vs. History Jack Dorsey-backed Vine reboot Divine launches to the public | TechCrunch noscroll Felvidek Amazon's AI product podcasts 64″D Hyperbaric Oxygen Chamber Timmy's rescue Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Guest: Nirav Patel Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: scribe.how/machines outsystems.com/twit zscaler.com/security

Are you ready for a world where true personal computing is under threat? This week's candid conversation with Framework CEO Nirav Patel tackles why owning your own AI hardware matters more than ever—and what's at risk if we don't. Alphabet tops Q1 estimates on strong Google Cloud growth Is OpenAI Falling Further Behind in the A.I. Race? OpenAI Releases 'Spud' GPT-5.5 Model OpenAI Breaks Free From Exclusive AI Pact With Microsoft Google signs classified AI deal with the Pentagon for 'any lawful government purpose' Elon Musk appeared more petty than prepared OpenAI Set to Redefine Smartphones; MediaTek, Qualcomm & Luxshare Key to Its AI Agent Phone Why Manus has become a crucial prize in the global AI race - Fast Company Australia unveils a 2.25% levy on Meta, Google, and TikTok The Man Behind AlphaGo Thinks AI Is Taking the Wrong Path Amateur armed with ChatGPT 'vibe-maths' a 60-year-old problem Introducing talkie: a 13B vintage language model from 1930 Cursor-Opus agent snuffs out startup's production database OpenAI Really Wants Codex to Shut Up About Goblins Now we know who paid $100,000 to unlock a Sam Altman podcast interview Study Finds A Third of New Websites are AI-Generated The Bloomberg Terminal Is Getting an AI Makeover, Like It or Not Generative AI vegetarianism To buy this Bay Area home, you'll need Anthropic equity | TechCrunch * Chloe vs. History Jack Dorsey-backed Vine reboot Divine launches to the public | TechCrunch noscroll Felvidek Amazon's AI product podcasts 64″D Hyperbaric Oxygen Chamber Timmy's rescue Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Guest: Nirav Patel Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: scribe.how/machines outsystems.com/twit zscaler.com/security

The Podcast Under the Stairs presents our next instalment of The 88 Films Italian Collection Series.Duncan will review the next title in the 88 Films Italian Collection on The Podcast Under the Stairs. Disc 84 is The Pleasure (1985).The grading follows the Netflix rating style of 1 = Hated It, 2 = Didn't Like It, 3 = Liked It, 4 = Really Liked It & 5 = Loved ItThe Pleasure:Duncan: 3The next planned Italian Collection title is Disc 85 - Orgasmo (1969).And if that's not enough cult and exploitation goodness for you, be sure to check out my brand-new show with THE BAZ, The B-Movie Blitzkrieg Podcast. Hit the link below and let the chaos continue. B-Movie Blitzkrieg Podcast LinksYOUTUBE: ⁠⁠⁠⁠https://www.youtube.com/@BMovieBlitzkrieg⁠⁠⁠⁠Spotify Podcasts: ⁠⁠⁠⁠https://open.spotify.com/show/2hZul6ZQsZaL5Uhff8RS8J?si=5916d0866ee94fc1⁠⁠⁠⁠Apple Podcasts: ⁠⁠⁠⁠https://podcasts.apple.com/au/podcast/b-movie-blitzkrieg/id1818986998⁠⁠⁠Our new RSS Feed: ⁠⁠⁠⁠https://anchor.fm/s/13ba6ef0/podcast/rss⁠⁠⁠⁠Check out the show on ⁠⁠⁠⁠Anchor⁠⁠⁠⁠, ⁠⁠⁠⁠iTunes⁠⁠⁠⁠, ⁠⁠⁠⁠TuneIn⁠⁠⁠⁠ & on ⁠⁠⁠⁠Stitcher Radio⁠⁠⁠⁠.Please leave us feedback on ⁠⁠⁠⁠iTunes⁠⁠⁠⁠, podcastunderthestairs@gmail.com and follow us on ⁠⁠⁠⁠Facebook⁠⁠⁠⁠.TIMECODE FOR ITALIAN COLLECTION DISC 8400:00:00 Intro 00:02:32 The Pleasure Review 00:15:30 Closing

Are you ready for a world where true personal computing is under threat? This week's candid conversation with Framework CEO Nirav Patel tackles why owning your own AI hardware matters more than ever—and what's at risk if we don't. Alphabet tops Q1 estimates on strong Google Cloud growth Is OpenAI Falling Further Behind in the A.I. Race? OpenAI Releases 'Spud' GPT-5.5 Model OpenAI Breaks Free From Exclusive AI Pact With Microsoft Google signs classified AI deal with the Pentagon for 'any lawful government purpose' Elon Musk appeared more petty than prepared OpenAI Set to Redefine Smartphones; MediaTek, Qualcomm & Luxshare Key to Its AI Agent Phone Why Manus has become a crucial prize in the global AI race - Fast Company Australia unveils a 2.25% levy on Meta, Google, and TikTok The Man Behind AlphaGo Thinks AI Is Taking the Wrong Path Amateur armed with ChatGPT 'vibe-maths' a 60-year-old problem Introducing talkie: a 13B vintage language model from 1930 Cursor-Opus agent snuffs out startup's production database OpenAI Really Wants Codex to Shut Up About Goblins Now we know who paid $100,000 to unlock a Sam Altman podcast interview Study Finds A Third of New Websites are AI-Generated The Bloomberg Terminal Is Getting an AI Makeover, Like It or Not Generative AI vegetarianism To buy this Bay Area home, you'll need Anthropic equity | TechCrunch * Chloe vs. History Jack Dorsey-backed Vine reboot Divine launches to the public | TechCrunch noscroll Felvidek Amazon's AI product podcasts 64″D Hyperbaric Oxygen Chamber Timmy's rescue Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Guest: Nirav Patel Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: scribe.how/machines outsystems.com/twit zscaler.com/security

Are you ready for a world where true personal computing is under threat? This week's candid conversation with Framework CEO Nirav Patel tackles why owning your own AI hardware matters more than ever—and what's at risk if we don't. Alphabet tops Q1 estimates on strong Google Cloud growth Is OpenAI Falling Further Behind in the A.I. Race? OpenAI Releases 'Spud' GPT-5.5 Model OpenAI Breaks Free From Exclusive AI Pact With Microsoft Google signs classified AI deal with the Pentagon for 'any lawful government purpose' Elon Musk appeared more petty than prepared OpenAI Set to Redefine Smartphones; MediaTek, Qualcomm & Luxshare Key to Its AI Agent Phone Why Manus has become a crucial prize in the global AI race - Fast Company Australia unveils a 2.25% levy on Meta, Google, and TikTok The Man Behind AlphaGo Thinks AI Is Taking the Wrong Path Amateur armed with ChatGPT 'vibe-maths' a 60-year-old problem Introducing talkie: a 13B vintage language model from 1930 Cursor-Opus agent snuffs out startup's production database OpenAI Really Wants Codex to Shut Up About Goblins Now we know who paid $100,000 to unlock a Sam Altman podcast interview Study Finds A Third of New Websites are AI-Generated The Bloomberg Terminal Is Getting an AI Makeover, Like It or Not Generative AI vegetarianism To buy this Bay Area home, you'll need Anthropic equity | TechCrunch * Chloe vs. History Jack Dorsey-backed Vine reboot Divine launches to the public | TechCrunch noscroll Felvidek Amazon's AI product podcasts 64″D Hyperbaric Oxygen Chamber Timmy's rescue Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Guest: Nirav Patel Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: scribe.how/machines outsystems.com/twit zscaler.com/security

Are you ready for a world where true personal computing is under threat? This week's candid conversation with Framework CEO Nirav Patel tackles why owning your own AI hardware matters more than ever—and what's at risk if we don't. Alphabet tops Q1 estimates on strong Google Cloud growth Is OpenAI Falling Further Behind in the A.I. Race? OpenAI Releases 'Spud' GPT-5.5 Model OpenAI Breaks Free From Exclusive AI Pact With Microsoft Google signs classified AI deal with the Pentagon for 'any lawful government purpose' Elon Musk appeared more petty than prepared OpenAI Set to Redefine Smartphones; MediaTek, Qualcomm & Luxshare Key to Its AI Agent Phone Why Manus has become a crucial prize in the global AI race - Fast Company Australia unveils a 2.25% levy on Meta, Google, and TikTok The Man Behind AlphaGo Thinks AI Is Taking the Wrong Path Amateur armed with ChatGPT 'vibe-maths' a 60-year-old problem Introducing talkie: a 13B vintage language model from 1930 Cursor-Opus agent snuffs out startup's production database OpenAI Really Wants Codex to Shut Up About Goblins Now we know who paid $100,000 to unlock a Sam Altman podcast interview Study Finds A Third of New Websites are AI-Generated The Bloomberg Terminal Is Getting an AI Makeover, Like It or Not Generative AI vegetarianism To buy this Bay Area home, you'll need Anthropic equity | TechCrunch * Chloe vs. History Jack Dorsey-backed Vine reboot Divine launches to the public | TechCrunch noscroll Felvidek Amazon's AI product podcasts 64″D Hyperbaric Oxygen Chamber Timmy's rescue Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Guest: Nirav Patel Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: scribe.how/machines outsystems.com/twit zscaler.com/security

Welcome to this sub-set of show exclusively looking at the Duncan's 88 Films Slasher Classics Collection.Duncan will review the next title in the 88 Films Slasher Classics Collection on The Podcast Under the Stairs.Disc 53 is Dark Night of the Scarecrow (1981).The grading follows the Netflix rating style of 1 = Hated It, 2 = Didn't Like It, 3 = Liked It, 4 = Really Liked It & 5 = Loved ItDark Night of the Scarecrow:Duncan: 4The next planned Slasher Classics title is Disc 54 - Mortuary (1982).And if that's not enough cult and exploitation goodness for you, be sure to check out my brand-new show with THE BAZ, The B-Movie Blitzkrieg Podcast. Hit the link below and let the chaos continue. B-Movie Blitzkrieg Podcast LinksYOUTUBE: ⁠⁠⁠https://www.youtube.com/@BMovieBlitzkrieg⁠⁠⁠Spotify Podcasts: ⁠⁠⁠https://open.spotify.com/show/2hZul6ZQsZaL5Uhff8RS8J?si=5916d0866ee94fc1⁠⁠⁠Apple Podcasts: ⁠⁠⁠https://podcasts.apple.com/au/podcast/b-movie-blitzkrieg/id1818986998⁠⁠Our new RSS Feed: ⁠⁠⁠https://anchor.fm/s/13ba6ef0/podcast/rss⁠⁠⁠Check out the show on ⁠⁠⁠Anchor⁠⁠⁠, ⁠⁠⁠iTunes⁠⁠⁠, ⁠⁠⁠TuneIn⁠⁠⁠ & on ⁠⁠⁠Stitcher Radio⁠⁠⁠.Please leave us feedback on ⁠⁠⁠iTunes⁠⁠⁠, podcastunderthestairs@gmail.com and follow us on ⁠⁠⁠Facebook⁠⁠⁠.TIMECODE FOR SLASHER CLASSICS DISC 5300:00:00 Intro 00:03:30 Dark Night of the Scarecrow Review00:17:26 Closing

Click Here to Text us. Yes really, you totally can.Kory from The World is My Burrito guides a very sleepy Zack and Mike through a journey of discovery! Seriously, he does everything today. Turn up the volume to hear Zack and Mike snoring peacefully.Guess WeirderA Barbie Event Gets the Willy Wonka Nightmare TreatmentThere's a Cure for Cancer. You Won't Like It.Also I don't have the links but we talk about how Clavicular or however you spell his stupid name is suffering SEVERE CORITSOL SPIKES in jailTHEN! We take a trip through the most SUCCESSFUL franchises of all time. There are some head scratchers in here.Check Out Our Website!Join our Discord!Check out our Merch Store HERE!Follow us @theneatcast on TikTok!Follow us @neatcastpod on BlueskyFollow us @neatcastpod on Twitter!Follow us @neatcastpod on Instagram!Follow us @theneatcast on Facebook!

Duncan is back looking at one of the most overlooked entries in the Hammer Film Productions catalogue. Demons of the Mind (1972) has steadily grown in reputation as a bold, unsettling and genuinely ambitious piece of gothic horror. Directed by Peter Sykes and written by Christopher Wicking, the film trades traditional monsters for psychological decay, repression and inherited madness. Robert Hardy delivers a powerhouse performance as the deeply disturbed Baron Zorn, supported by the volatile energy of Shane Briant and Gillian Hills, with Patrick Magee adding a layer of intensity that pushes the film into darker territory. Dismissed on release, it's now widely appreciated by fans for its ambition—its striking visuals, uncomfortable themes and willingness to push Hammer beyond its comfort zone.This new Collector's Edition gives the film a long-overdue reappraisal with a brand-new 4K Dolby Vision restoration that highlights its rich, atmospheric cinematography. Packed with both new and archival extras, it's a comprehensive release for collectors and newcomers alike. Features include: 4K UHD & Blu-ray discsNew 4K Dolby Vision restorationMultiple audio commentariesNew featurettes including Evil In the Blood & Blood Will Have BloodInterviewsStills and lobby card galleriesTrailer64-page booklet with essays and original press materialBrand-new artwork Two posters & a release date of 6th April 2026.The grading follows the Netflix rating style of 1 = Hated It, 2 = Didn't Like It, 3 = Liked It, 4 = Really Liked It & 5 = Loved ItDemon's of the Mind:Duncan: 4.5Thanks to Studio Canal & Fetch PR for the review copy of this movie.Our new RSS Feed: ⁠⁠⁠⁠⁠⁠https://anchor.fm/s/13ba6ef0/podcast/rss⁠⁠⁠⁠⁠⁠Check out the show on ⁠⁠⁠⁠⁠⁠Anchor⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠iTunes⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠TuneIn⁠⁠⁠⁠⁠⁠ & on ⁠⁠⁠⁠⁠⁠Stitcher Radio⁠⁠⁠⁠⁠⁠.Please leave us feedback on ⁠⁠⁠⁠⁠⁠iTunes⁠⁠⁠⁠⁠⁠, podcastunderthestairs@gmail.com and follow us on ⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠.TIMECODE DEMON'S OF THE MIND BLURAY REVIEW00:00:00 Intro 00:04:04 Unboxing00:05:10 Demon's of the Mind Review00:10:48 Special Features00:16:37 Closing

Duncan is back to review a late-era entry from Hammer Film Productions, Blood from the Mummy's Tomb which stands apart from the studio's earlier monster-led formula by reworking classic Mummy lore through a more psychological and intriguingly subversive lens. Directed by Seth Holt and based on a story by Bram Stoker, the film shifts the horror inward centred on identity, possession, and female power. Arriving during a period of declining commercial success for Hammer, the film didn't redefine the studio's fortunes, but has since earned recognition as one of its more unusual and thematically rich horrors.This new Collector's Edition brings the film to 4K for the first time with a brand-new Dolby Vision restoration, offering a strong presentation of one of Hammer's more visually distinctive late-period releases. The set is packed with both archival and newly produced extras, alongside collectible physical content. Features include: 4K UHD & Blu-ray discsNew 4K Dolby Vision restorationMultiple new featurettes and interviewsAudio commentaryArchival materials including TV/radio spots and galleries64-page booklet with essays and original press kitBrand-new artwork, Two posters & a release date of 6th April 2026.The grading follows the Netflix rating style of 1 = Hated It, 2 = Didn't Like It, 3 = Liked It, 4 = Really Liked It & 5 = Loved ItBlood from the Mummy's Tomb:Duncan: 3.5Thanks to Studio Canal & Fetch PR for the review copy of this movie.Our new RSS Feed: ⁠⁠⁠⁠⁠https://anchor.fm/s/13ba6ef0/podcast/rss⁠⁠⁠⁠⁠Check out the show on ⁠⁠⁠⁠⁠Anchor⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠iTunes⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠TuneIn⁠⁠⁠⁠⁠ & on ⁠⁠⁠⁠⁠Stitcher Radio⁠⁠⁠⁠⁠.Please leave us feedback on ⁠⁠⁠⁠⁠iTunes⁠⁠⁠⁠⁠, podcastunderthestairs@gmail.com and follow us on ⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠.TIMECODE BLOOD FROM THE MUMMY'S TOMB BLURAY REVIEW00:00:00 Intro 00:02:30 Unboxing00:03:32 Fear in the Night Review00:08:58 Special Features00:15:27 Closing

Duncan is here to review a fascinating outlier in the Hammer Film Productions catalogue, Fear in the Night trades gothic horror for something far more intimate and unsettling. Directed by Jimmy Sangster, this psychological chiller leans heavily on atmosphere and performance, with Judy Geeson delivering a genuinely gripping turn as a woman unsure whether she's being hunted or losing her grip on reality. Supported by the ever-reliable Peter Cushing and a quietly enigmatic Joan Collins, the film stands as one of Hammer's more unusual experiments—less iconic, perhaps, but rich in tension and worth rediscovery.This new Collector's Edition from Studio Canal marks the film's worldwide 4K debut, giving Sangster's eerie, stripped-back thriller a fresh lease of life. The release includes a brand-new 4K restoration presented on both 4K UHD and Blu-ray, alongside a strong set of extras and physical additions for collectors. Features include: 4K UHD & Blu-ray discs New 4K restorationAudio commentariesFeaturettes including: The Fragile Mind and End of TermTheatrical trailer, stills gallery64-page booklet with new essaysBrand-new artworkTwo posters & a release date of 23rd March 2026.The grading follows the Netflix rating style of 1 = Hated It, 2 = Didn't Like It, 3 = Liked It, 4 = Really Liked It & 5 = Loved ItFear in the Night:Duncan: 4Thanks to Studio Canal & Fetch PR for the review copy of this movie.Our new RSS Feed: ⁠⁠⁠⁠https://anchor.fm/s/13ba6ef0/podcast/rss⁠⁠⁠⁠Check out the show on ⁠⁠⁠⁠Anchor⁠⁠⁠⁠, ⁠⁠⁠⁠iTunes⁠⁠⁠⁠, ⁠⁠⁠⁠TuneIn⁠⁠⁠⁠ & on ⁠⁠⁠⁠Stitcher Radio⁠⁠⁠⁠.Please leave us feedback on ⁠⁠⁠⁠iTunes⁠⁠⁠⁠, podcastunderthestairs@gmail.com and follow us on ⁠⁠⁠⁠Facebook⁠⁠⁠⁠.TIMECODE FEAR IN THE NIGHT BLURAY REVIEW00:00:00 Intro00:02:20 Unboxing00:04:02 Fear in the Night Review00:09:05 Special Features00:13:55 Closing

1 Bawler - Onism 2 Amen Syndicate - Distorted Truth  3 Jungle Massive  4 Stormski-Someday-Instrumental_Mix 5 Yo Speed - I Can Feel U  6 tango-concrete_steps 7 olaf bassowski-A Decade in Drum_n_bass 8 Settle Down-Seen 9 The Moog - Hardcore Junglism 10 Ant to be - Sock Tune  11 Harmony, Xtreme - Temple of Heaven 12 Local Group - Stand Up 13 Dubplate union - Id give it all 14 Moodrich & MC Skain - Soul Rebel Junglin' Like It's 1993 15 Moodrich & MC Skain - Soul Rebel Fire, Fire 16 Moodrich & MC Skain - Soul Rebel London 1999 17 Constrict - Desert Cruising Gizmo   18 Kellaway - Knocking  19 Potential Badboy, Tim Reaper, Ragga Twins - Dangerous Is Dangerous  20 Moodrich & MC Skain - Soul Rebel Ceaseless Cacophony 21 Smack My Bitch Up (DJ Hype Remix) 22 Moodrich & MC Skain - Soul Rebel Funky Man 23 Lawyer - Nixxy Rain 24 Unknown Artist - Dilemma EP Say Yes 25 Chris Munky, Benji Webbe, Fernquest - Junglist Tonight  26 Unknown Artist - Dilemma EP Dilemma 27 PotatoViber - Mood Swing 28 RhythmRider - Aquarium Reality Check 29 Double Decker - Frenemy  30 RhythmRider - Aquarium On The Ride 31 Moodrich & MC Skain - Soul Rebel Is It a Crime 32 Gabriella Bongo - Cross The Line Cross The Line 33 Kyrist - Kynetic Sound - 4MYPEEPS 34 Unknown Artist - Dilemma EP One More Chance 35 DJ Nai, DJ LLIW, Marcos K-Marx, DJ DNS, Madsoon - Tight 36 Unknown Artist - Dilemma EP Night & Day 37 Flixton - Beautifully Broken  38 Conrad Subs - Super Dub 39 RhythmRider - Aquarium Exoterrestrial evolution 40 RhythmRider - Aquarium Into the Water 41 S.P.Y, The Melody Men - Sweet Sound  42 Mr Quest - Shame Them (In The Blood Remix) 43 Crate Classics, bella-monae - Do What I Can  44 Pussyhole- Kovert Sound 45 Moodrich & MC Skain - Soul Rebel 46 RhythmRider - Aquarium Utopic Thoughts 47 RhythmRider - Aquarium Neptune's Layer 48 The Prodigy - Warrior's Dance (ISHEN Bootleg) 49 Jamalaya_ vs 50 Danny Byrd - Shock Out 51 The Fugees - Ready Or Not (DJ Zinc 2003 RMX)

Ready or Not 2 is in theaters — so we went back to where it all started. Brian, John, and filmmaker/critic KT Baldassaro (@MovieRuntime) dig into the 2019 original and make the case that it's one of the smartest, funniest, most satisfying horror comedies of the last decade. A bride. A devil-controlled game box. A mansion full of rich lunatics. Hide and seek to the death. What we cover: Why this is more satire than horror and why that makes it better — Samara Weaving's all-time performance and why she carries the whole film  Why Adam Brody's Daniel has the real character arc, not Alex  The old money vs new money class war hiding underneath the comedy  Whether the game box is actually random — or whether the devil picks who dies Alex as the true villain of the movie  Whether the sequel can possibly match the original's ending  CHAPTERS: 00:00 Cold open 00:20 Welcome and introducing KT Baldassaro 03:00 First impressions — horror or comedy? 08:30 Marrying into a family that wants to kill you 16:00 Breaking down the LaBelle family 26:00 Why Alex is actually the villain 36:00 The game box theory — is it random or rigged? 46:00 Practical effects on a $6M budget 54:00 Community reviews 01:05:00 Will the sequel ruin the franchise? 01:15:00 Final verdicts and where to find KT KT Baldassaro — filmmaker, critic, festival programmer Podcast: What If I Don't Like It? — search on any podcast app Follow her: @movieruntime on TikTok Listen to The Cinema Psychos Show on: Spotify: https://rebrand.ly/0v6eeno Apple: https://rebrand.ly/j5nrkp7  Amazon: https://rebrand.ly/5x5hzng Goodpods: https://rebrand.ly/picstv6 OR LISTEN ON YOUR FAVORITE PODCAST APP! https://cinemapsychosshow.com/follow   Follow The Cinema Psychos Show on Socials ❤️‍

The Straw Hat Pirates finally make their way into the grand line, but they are met with a massive obstacle that they did not expect at all. Quickly, Luffy makes a couple new friends in Crocus and Laboon. Nami gains a special new tool to help them on the journey and the crew sets sail, not knowing what's infront of them.Next Week: Live Action Season 2 Episode 3https://linktr.ee/goingmerrypodTHIS WEEK ON The Variant Vendetta Podcast: Million Dollar Baby - Clinton's Trust Me You'll Like It.https://linktr.ee/VariantVendetta

Award-winning singer/songwriter John Galea releases his latest single “Songwriter” on March 27th. Galea continues to hone his craft and has been working with the top producers and writers from around the world, including Grammy-nominated production team ‘The Monarch' (Rita Ora, Chris Brown); Los Angeles-based ‘Beluga Heights' (Britney Spears, Jason Derulo, Rihanna), among others.  2026 now sees him release his first single, “Songwriter,” from his long-awaited debut album set for release early next year. The gospel-inspired love song, which was written by Galea, was co-produced by John & Oscar Lo Brutto (Wretch32, Scorcher) and has been remixed by Matt Pop & OLB, and its official music video was recently filmed on location in Central London.“Songwriter” follows the success of Galea's 5 Independent EP's starting with The Scrapbook EP (2012), Under Attack (2013), Notes From My Piano (2014) and ‘Missing Pages' (2016) which featured single ‘When You Truly Love Someone' which hit Top 10 in the Commercial Charts in 2017, which featured Celebrity Gemma Oaten in the music video. John followed up that success with his Christmas EP ' Christmas Round The Piano' (2018), scoring a Top 30 iTunes Charting track in 2019 with his Christmas song 'A Simple Christmas'. Galea followed up that success with his hit single “Hero Within You” featuring Guildhall Opera Singing Sensation Hannah Long. 2020 saw John score his first iTunes Number #1 in 2020 with his track  ‘Hero Within You' recorded with Singing sensation Hannah Long & John teamed up with Chart topping Rapper Ironik on the single ‘Don't Wanna Die' which was the first single taken from his 6th EP ‘The Art Of Collaboration'.When asked about his latest single Galea said, “‘Songwriter' was one of the longest songs I've taken to write, and probably now my favorite. It's taken literally years! I have had so many versions that have had different hooks or vibes and they just didn't feel right, then finally writing my 1st album, I sat down at my piano and the song just fell into place. The song is all about sharing whatever you have with the most special person in the world.”Galea started songwriting when he was 13 after winning a UK National Songwriting Contest with his track “I Am Not An Angel.” Following that win he started writing for artists such as Lao Ra (Jesus Made Me Bad), Thea Garrett (Frontline) & Gianluca Bezzina (Come Float Away) and more!  Around this time his track “Trendsetter” was synced on US TV. Galea has also toured the UK supporting the likes of McFly and Boyzlife, as well as performing on the main stage for London Pride, Birmingham Pride, Northern Pride, Norwich Pride, as well as the main stage on festivals like The Sundown Festival and more. Stay tuned to Galea's social pages below for more updates on future releases as he gets ready to release his next project.# # #Connect with John Galea: WEBSITE | INSTAGRAM | SPOTIFY | TIKTOK Press Contacts:Brad Taylor    ​Big Machine Agency  brad@bigmachineagency.com  ​​​​​Maya BlakemoreBig Machine Agency​​​​​            maya@bigmachineagency.com Meijin BruttomessoBig Machine Agency  meijinb@bigmachinemedia.comView email in browserBig Machine Agency · 22 E 36th St Ste 8A · New York, NY 10016-3419 · USAupdate your preferences or unsubscribeCan you do March 13th ?   Lets say NOON EST ?  Will you send a zoom link? Show quoted textShow quoted textAbsolutely!  So grateful!!!!Hide quoted textOn Wed, Mar 4, 2026, 7:08 PM Brad Taylor wrote:Can you do March 13th ?   Lets say NOON EST ?  Will you send a zoom link?     Brad Taylor | Co-Founder and CEOBig Machine AgencyNYC • LONDONe: brad@bigmachineagency.comw: www.bigmachineagency.comp: +1 646.427.5476  On Wed, Mar 4, 2026 at 10:42 AM arroe M'e wrote:Zoom is fantastic.  I'm in Charlotte.  I can bend around your schedule.  How about the 13th of March?On Wed, Mar 4, 2026, 10:40 AM Brad Taylor wrote:do you set up a zoom?  what are timings can you do?  Where are you based?  Obviously John is in London so the earlier in the day EST is better.  Brad     Brad Taylor | Co-Founder and CEOBig Machine AgencyNYC • LONDONe: brad@bigmachineagency.comw: www.bigmachineagency.comp: +1 646.427.5476  On Wed, Mar 4, 2026 at 10:38 AM arroe M'e wrote:That would be an amazing experience for listeners.  Grateful!On Wed, Mar 4, 2026, 10:23 AM Brad Taylor wrote:ok do you want an interview with John?     Brad Taylor | Co-Founder and CEOBig Machine AgencyNYC • LONDONe: brad@bigmachineagency.comw: www.bigmachineagency.comp: +1 646.427.5476  On Sun, Mar 1, 2026 at 9:07 AM arroe M'e wrote:iHeart Radios Unplugged and Totally Uncut View from the Writing Instrument and Like It's Live.  You've blessed my life with many conversations in the past due to my connection to helping all up and coming performers have a pleasant place to spread their wings as creative souls. Wow that sounds like a very big artistic portrait but it's the truth! Radio doesn't serve the new artist like it should therefore there are a lot of us out here that believe that the inside sleeve of an album is still one of the greatest journeys of all time. But how can people find it if people aren't talking about it? Looking forward to creating with you!On Fri, Feb 27, 2026, 12:48 PM Brad Taylor wrote:Leslie can helpWhat's your outlet?    Brad Taylor | Co-Founder and CEOBig Machine AgencyNYC • LONDONe: brad@bigmachineagency.comw: www.bigmachineagency.comp: +1 646.427.5476  On Fri, Feb 27, 2026 at 5:47 PM arroe M'e wrote:Hey guys! Happy day to you!. If you guys are walking the path of doing interviews to help promote this please add me to your list.On Fri, Feb 27, 2026, 12:19 PM Big Machine Agency wrote:FOR IMMEDIATE RELEASE:Award-winning UK Singer-Songwriter John Galea Releases Latest Single “SONGWRITER” On March 27th Listen to “Songwriter”New York, NY – (February 27, 2026) – Award-winning singer/songwriter John Galea releases his latest single “Songwriter” on March 27th. Galea continues to hone his craft and has been working with the top producers and writers from around the world, including Grammy-nominated production team ‘The Monarch' (Rita Ora, Chris Brown); Los Angeles-based ‘Beluga Heights' (Britney Spears, Jason Derulo, Rihanna), among others.  2026 now sees him release his first single, “Songwriter,” from his long-awaited debut album set for release early next year. The gospel-inspired love song, which was written by Galea, was co-produced by John & Oscar Lo Brutto (Wretch32, Scorcher) and has been remixed by Matt Pop & OLB, and its official music video was recently filmed on location in Central London.“Songwriter” follows the success of Galea's 5 Independent EP's starting with The Scrapbook EP (2012), Under Attack (2013), Notes From My Piano (2014) and ‘Missing Pages' (2016) which featured single ‘When You Truly Love Someone' which hit Top 10 in the Commercial Charts in 2017, which featured Celebrity Gemma Oaten in the music video. John followed up that success with his Christmas EP ' Christmas Round The Piano' (2018), scoring a Top 30 iTunes Charting track in 2019 with his Christmas song 'A Simple Christmas'. Galea followed up that success with his hit single “Hero Within You” featuring Guildhall Opera Singing Sensation Hannah Long. 2020 saw John score his first iTunes Number #1 in 2020 with his track  ‘Hero Within You' recorded with Singing sensation Hannah Long & John teamed up with Chart topping Rapper Ironik on the singBecome a supporter of this podcast: https://www.spreaker.com/podcast/arroe-collins-like-it-s-live--4113802/support.

The Podcast Under the Stairs presents our next instalment of The 88 Films Italian Collection Series.Duncan will review the next title in the 88 Films Italian Collection on The Podcast Under the Stairs. Disc 83 is Street Law (1974).The grading follows the Netflix rating style of 1 = Hated It, 2 = Didn't Like It, 3 = Liked It, 4 = Really Liked It & 5 = Loved ItStreet Law:Duncan: 3.5The next planned Italian Collection title is Disc 84 -The Pleasure (1985).And if that's not enough cult and exploitation goodness for you, be sure to check out my brand-new show with THE BAZ, The B-Movie Blitzkrieg Podcast. Hit the link below and let the chaos continue. B-Movie Blitzkrieg Podcast LinksYOUTUBE: ⁠⁠⁠https://www.youtube.com/@BMovieBlitzkrieg⁠⁠⁠Spotify Podcasts: ⁠⁠⁠https://open.spotify.com/show/2hZul6ZQsZaL5Uhff8RS8J?si=5916d0866ee94fc1⁠⁠⁠Apple Podcasts: ⁠⁠⁠https://podcasts.apple.com/au/podcast/b-movie-blitzkrieg/id1818986998⁠⁠Our new RSS Feed: ⁠⁠⁠https://anchor.fm/s/13ba6ef0/podcast/rss⁠⁠⁠Check out the show on ⁠⁠⁠Anchor⁠⁠⁠, ⁠⁠⁠iTunes⁠⁠⁠, ⁠⁠⁠TuneIn⁠⁠⁠ & on ⁠⁠⁠Stitcher Radio⁠⁠⁠.Please leave us feedback on ⁠⁠⁠iTunes⁠⁠⁠, podcastunderthestairs@gmail.com and follow us on ⁠⁠⁠Facebook⁠⁠⁠.

Welcome to this sub-set of show exclusively looking at the Duncan's 88 Films Slasher Classics Collection.Duncan will review the next title in the 88 Films Slasher Classics Collection on The Podcast Under the Stairs.Disc 52 is Funeral Home (1980).The grading follows the Netflix rating style of 1 = Hated It, 2 = Didn't Like It, 3 = Liked It, 4 = Really Liked It & 5 = Loved ItFuneral Home:Duncan: 3.5The next planned Slasher Classics title is Disc 53 - Dark Night of the Scarecrow (1981).And if that's not enough cult and exploitation goodness for you, be sure to check out my brand-new show with THE BAZ, The B-Movie Blitzkrieg Podcast. Hit the link below and let the chaos continue. B-Movie Blitzkrieg Podcast LinksYOUTUBE: ⁠⁠https://www.youtube.com/@BMovieBlitzkrieg⁠⁠Spotify Podcasts: ⁠⁠https://open.spotify.com/show/2hZul6ZQsZaL5Uhff8RS8J?si=5916d0866ee94fc1⁠⁠Apple Podcasts: ⁠⁠https://podcasts.apple.com/au/podcast/b-movie-blitzkrieg/id1818986998⁠Our new RSS Feed: ⁠⁠https://anchor.fm/s/13ba6ef0/podcast/rss⁠⁠Check out the show on ⁠⁠Anchor⁠⁠, ⁠⁠iTunes⁠⁠, ⁠⁠TuneIn⁠⁠ & on ⁠⁠Stitcher Radio⁠⁠.Please leave us feedback on ⁠⁠iTunes⁠⁠, podcastunderthestairs@gmail.com and follow us on ⁠⁠Facebook⁠⁠.TIMECODE FOR SLASHER CLASSICS DISC 5200:00:00 Intro 00:04:55 Funeral Home Review 00:16:54 Closing

change it oder like it

Luffy finally shows us the next step he has taken in his development as a fighter and the wait pays off. Doflamingo is majorly struggling to hold off the Straw Hat captain...until he's not. Time is running out. Luffy is out of energy and the birdcage is collapsing.Next Week: Episodes 731-736https://linktr.ee/goingmerrypodTHIS WEEK ON The Variant Vendetta Podcast: Annabelle's "Trust Me You'll Like It" - Signhttps://linktr.ee/VariantVendetta

Welcome to this sub-set of show exclusively looking at the Duncan's 88 Films Slasher Classics Collection.Duncan will review the next title in the 88 Films Slasher Classics Collection on The Podcast Under the Stairs.Disc 51 is Skinned Alive (1990).The grading follows the Netflix rating style of 1 = Hated It, 2 = Didn't Like It, 3 = Liked It, 4 = Really Liked It & 5 = Loved ItSkinned Alive:Duncan: 1.5The next planned Slasher Classics title is Disc 52 - Funeral Home (1980).And if that's not enough cult and exploitation goodness for you, be sure to check out my brand-new show with THE BAZ, The B-Movie Blitzkrieg Podcast. Hit the link below and let the chaos continue. B-Movie Blitzkrieg Podcast LinksYOUTUBE: ⁠https://www.youtube.com/@BMovieBlitzkrieg⁠Spotify Podcasts: ⁠https://open.spotify.com/show/2hZul6ZQsZaL5Uhff8RS8J?si=5916d0866ee94fc1⁠Apple Podcasts: ⁠https://podcasts.apple.com/au/podcast/b-movie-blitzkrieg/id1818986998Our new RSS Feed: ⁠https://anchor.fm/s/13ba6ef0/podcast/rss⁠Check out the show on ⁠Anchor⁠, ⁠iTunes⁠, ⁠TuneIn⁠ & on ⁠Stitcher Radio⁠.Please leave us feedback on ⁠iTunes⁠, podcastunderthestairs@gmail.com and follow us on ⁠Facebook⁠.TIMECODE FOR SLASHER CLASSICS DISC 5100:00:00 Intro 00:03:34 Skinned Alive Review 00:13:21 Closing

(0:00) Seahawks vs. Patriots, Matthew Stafford wins MVP (26:44) Most To Gain, Most To Lose Super Bowl LX Edition (42:59) How should the Seahawks defense attack the Patriots? (48:38) Upset Alert & Nick's Picks (01:10:48) Josh McDaniels making 10th Super Bowl appearance (01:20:18) 2026 Hall of Fame Class announced (01:28:38) Parkins' Picks, Like how the MVP vote went? (01:53:29) Like It or Not: Super Bowl LX edition (02:04:42) Coach's Tips for the Patriots to beat the Seahawks (02:10:58) Super Bowl LX Winner and MVP Picks Learn more about your ad choices. Visit podcastchoices.com/adchoices

Welcome to episode 572 of The Podcast Under the Stairs.After nearly a year away, the show is officially back…and we're kicking things off with a vengeance by diving into the gritty revenge classic Ms. 45. Thanks for sticking around during the hiatus; new episodes are back on track and will be dropping about every two weeks. And if that's not enough cult and exploitation goodness for you, be sure to check out my brand-new show with THE BAZ, The B-Movie Blitzkrieg Podcast. Hit the link below and let the chaos continue. B-Movie Blitzkrieg Podcast LinksYOUTUBE: https://www.youtube.com/@BMovieBlitzkriegSpotify Podcasts: https://open.spotify.com/show/2hZul6ZQsZaL5Uhff8RS8J?si=5916d0866ee94fc1Apple Podcasts: https://podcasts.apple.com/au/podcast/b-movie-blitzkrieg/id1818986998The grading follows the Netflix rating style of 1 = Hated It, 2 = Didn't Like It, 3 = Liked It, 4 = Really Liked It & 5 = Loved ItMS. 45:Duncan: 4.5Our new RSS Feed: https://anchor.fm/s/13ba6ef0/podcast/rssCheck out the show on Anchor, iTunes, TuneIn & on Stitcher Radio.Please leave us feedback on iTunes, podcastunderthestairs@gmail.com and follow us on Facebook.TIMECODE FOR EPISODE 572:00:00:00 Intro 00:07:40 Trailer00:09:15 MS. 45 Review 00:23:15 Closing

I got to sit down with my sweet friend Rachel Awtrey to talk about what it really means to love your life—even when you don't like it all the time. We went deep into the hard stuff: grief, spiritual warfare, motherhood, friendship, and how to CHOOSE joy as a daily practice. Rachel opens up about the loss of her father, writing her book through a miscarriage, and building joy as a skill, not just a feeling. We also chatted about the lies we believe about "balance," how to find friends in a new season, and why being present is one of the best gifts you can give yourself. This episode is for the girl who's tired, overwhelmed, and maybe wondering if this is all life has to offer. Joy is available—and worth fighting for. In This Episode 02:31 – Rachel's Story & Online Encouragement 04:50 – Ambition, Balance & Community as a Mom 09:00 – Grief, Tragedy & Learning to Love Your Life 13:44 – The Skill of Joy & Practical Mindset Shifts 19:00 – Toxic Positivity vs. Choosing Joy 28:00 – Small Habits That Shift Your Life 30:00 – How to Make Friends in a New Season 35:00 – Writing the Book in the Midst of Brokenness 40:00 – Spiritual Warfare & the Fight for Joy 46:00 – Final Encouragement: Choose Your Hard Guest Resources Follow Rachel Check out her website Buy Love Your Life Even if You Don't Like It. Check out her podcast OUR SPONSORS Function: Function gives you a near-360 view of your health, and my followers get a $100 credit toward membership. Just go to ⁠functionhealth.com/HAPPY⁠ or use gift code HAPPY100 at sign-up to start owning your health today. Our Place: Go to ⁠fromourplace.com/HEALTHY⁠ and use code HEALTHY for 10% off sitewide. Ritual: Get 25% off your first month at ⁠ritual.com/HEALTHY.⁠ NIV Bible App: You can save an extra 10% on any NIV Application Bible or NIV Application Commentary resource by visiting ⁠⁠⁠⁠⁠⁠⁠⁠⁠faithgateway.com/ NIVAB⁠⁠⁠⁠⁠⁠⁠⁠⁠ and using code HEALTHY at checkout. Boll & Branch: Get 15% off plus free shipping on your first set of sheets at ⁠⁠⁠⁠⁠⁠⁠⁠⁠BollAndBranch.com/HAPPYANDHEALTHY.⁠⁠⁠⁠⁠⁠⁠⁠⁠ Brooklyn Bedding: Go to ⁠⁠⁠⁠⁠⁠⁠⁠brooklynbedding.com⁠⁠⁠⁠⁠⁠⁠⁠ and use my promo code HEALTHY at checkout to get 30% off sitewide. Knowing God's Voice: ⁠⁠⁠⁠⁠⁠It's available now⁠⁠⁠⁠⁠⁠ everywhere books are sold, so grab your copy today! Hosanna Revival: Use my code Jeanine15 for 15% off your entire order at checkout at ⁠⁠HosannaRevival.com⁠⁠! If you'd like to partner with Jeanine as a sponsor for the Happy & Healthy podcast, fill out our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Advertise With Us⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ form! Follow us on Instagram!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Happy and Healthy⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jeanine⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jeanine and Kaleb⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Follow us on TikTok! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Happy and Healthy⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jeanine Learn more about your ad choices. Visit megaphone.fm/adchoices

An all-time derail episode with Will deFries as the boys discuss a leaked fraternity group chat, Hollywood actress Tilly Norwood, and Dillon reads Elizabeth Holmes' tweets.  Support us on Patreon and receive weekly episodes for as low $5 per month: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.patreon.com/circlingbackpodcast⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Watch all of our full episodes on YouTube: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.youtube.com/washedmedia⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Shop Washed Merch: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.washedmedia.shop⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ • (0:00) Fun & Easy Banter • (24:50) Like It the Fuck Now • (43:30) Elizabeth Holmes Check-In • (58:55) Who's Tilly Norwood? Support This Episode's Sponsors: Squarespace: Check out ⁠⁠⁠⁠⁠https://squarespace.com/steam⁠⁠⁠⁠⁠ for a free trial, and when you're ready to launch, use OFFER CODE: STEAM to save 10% off your first purchase of a website or domain. Vuori: Get 20% off your FIRST purchase of the most comfortable and versatile clothing on the planet at ⁠https://vuori.com/steam⁠ Rhoback: Get 20% off at https://rhoback.com/ with promo code WASHED20 Learn more about your ad choices. Visit megaphone.fm/adchoices