Podcasts about rodin

“If you can only explain the arguments of the other side because they're mad or dangerous or dumb, the problem is with you.” — Turi Munthe On yesterday's show, the psychiatrist Sally Satel described how Americans imagine their own mental condition differently, depending on their politics and age. Which is a nice segue for today's conversation with the Anglo-French journalist turned media entrepreneur Turi Munthe. It's not just in our mental health self-evaluation, Munthe argues, that we hallucinate reality. Indeed, the French born Munthe often sounds like one of his post-structuralist compatriots in his defiantly slippery notion of ontological reality. In Why We Think What We Think: The Unexpected Origins of Our Deepest Beliefs, Munthe argues that our deepest convictions turn out to be shaped by genetics, brain shape and sometimes even by the agricultural legacy of our distant ancestors. Left and right thinkers, Munthe argues, are different political phenotypes — each hallucinating their own version of reality. Total relativism, then — the full French post-structuralist monty? Not quite. Here's where Munthe's Englishness kicks in. Following the Anglo-Russian philosopher Isaiah Berlin, Munthe insists pluralism and relativism are different. So Turi Munthe doesn't just think what he thinks because of his English or French origins. Borrowing from the cognitive scientists Dan Sperber and Hugo Mercier, Munthe defines thinking as a “contact sport”. So, for example, believing that the 2020 election was stolen is what Munthe calls a social commitment, because humans would rather be wrong together than right alone. Speaking of convenient segues, Munthe's thoughts on thinking set the scene for next Tuesday's conversation with Emily Eakin, author of The Frenchmen. It's her history of seductive post-structuralists like Foucault, Derrida and Lacan who corrupted a whole generation of literary American Ivy Leaguers (including Eakin) into hallucinating reality. Five Takeaways •       Pluralism Is Not Relativism. Munthe opens with Isaiah Berlin's distinction: registering the sincerity and value of opinions across the political, religious, and ethical spectrum does not relativize truth. That Charles Windsor is King of the United Kingdom is a statement of fact; whether you're a monarchist or a republican is where opinion begins. The book confines itself to the second category — beliefs, values, and opinions that cannot be factually proven — and asks what the nonrational influences on them actually are. The answer is humbling: genetics account for perhaps half of political persuasion, and the rest is shaped by everything from brain anatomy to the agriculture of our ancestors. •       Different Political Phenotypes. At the margins, left and right differ neurologically: right-leaners are on average more readily startled by loud noises and more attentive to threat, while left-leaners carry a slightly larger anterior cingulate cortex — the brain region where we process ambiguity and split hairs. That anatomy, Munthe argues, explains the ideological capture of academia and media better than any conspiracy: hair-splitters go where the hair-splitting is, and a conservative 22-year-old doesn't volunteer for a newsroom where 80% of colleagues think differently. We are, in his phrase, different political phenotypes, each hallucinating a different version of reality. •       Thinking as a Contact Sport. Drawing on Dan Sperber and Hugo Mercier's research, Munthe argues that reason didn't evolve for solitary contemplation — Rodin's Thinker is the wrong image — but for argument: to convince you to hunt the buffalo with me, I need reasons that look objective to you too. The evidence is everywhere, from the most impactful academic papers being written by pairs and groups to the creative density of small university towns. The implication is political: the people we disagree with are not obstacles to good thinking but the condition of it — the loyal opposition that helps us get out of ourselves. •       Wrong Together Rather Than Right Alone. Munthe's reading of January 6 and the stolen-election faith is social rather than psychiatric: an enormous number of our beliefs matter more for what they do than for what they say, and professing them is a commitment to a group. From an evolutionary perspective, believing what your village believes — even about the god who is a giant rock at the end of the field — is intelligent, because the ostracized lose the protection of the group. The terrifying data point is the marriage test: in the 1950s, around 4% of families would have objected to a child marrying across party lines; today it approaches 45%. That is affective polarization, and it can pull societies apart. •       The Problem Is With You. Munthe spent his twenties unable to fathom American gun rights — supporters had to be bought, dumb, or morally corrupt — until he did the work and found a tradition he now calls beautiful and heroic, whether or not he shares it. His rule of thumb: if you can only explain the other side's arguments as madness, danger, or stupidity, the problem is with you. This is not centrism — there was no middle ground on slavery or the Holocaust — but a defense of the clash itself: societies need the left to fix inequality and the right to defend the village, and we think best when the two are, in his words, continually bashed against each other. About the Guest Turi Munthe is a journalist and policy analyst turned media entrepreneur. He founded Demotix, which became the largest network of photojournalists in the world before its sale to Corbis in 2012, and Parlia, an encyclopedia of opinion. He has written for The Economist, The Guardian, the TLS, The Nation, and The Spectator, has sat on the boards of Index on Censorship, openDemocracy, and the Bureau of Investigative Journalism, and is a board member of the Italian media group GEDI, publisher of La Repubblica and La Stampa. He studied Arabic and History at Oxford. Why We Think What We Think: The Unexpected Origins of Our Deepest Beliefs (Penguin/Hutchinson Heinemann) is out now in the UK, with US publication early next year. References: •       Why We Think What We Think: The Unexpected Origins of Our Deepest Beliefs by Turi Munthe (Penguin/Hutchinson Heinemann, 2026). Timothy Garton Ash: “Thinking is a contact sport.” •       Isaiah Berlin — the Anglo-Russian philosopher whose insistence that pluralism and relativism are not the same thing frames the whole book. •       Dan Sperber and Hugo Mercier...

REDIFF - Enfant, Camille Claudel a toujours aimé pétrir la glaise, modeler des visages ou des corps. Muse indocile de Rodin, elle collabore avec lui sur des sculptures célèbres, mais toujours dans l'ombre. Elle s'émancipe pour affirmer son génie mais, isolée et bridée par une société patriarcale, consumée par son art, elle finit internée par sa famille. Plongez dans la vie tourmentée de Camille Claudel, une artiste trop longtemps oubliée. Crédits : Lorànt Deutsch, Valériane Cariou. Tout l'été, retrouvez l'inimitable Lorànt Deutsch pour vous révéler les secrets des personnages historiques les plus captivants !Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

REDIFF - Enfant, Camille Claudel a toujours aimé pétrir la glaise, modeler des visages ou des corps. Muse indocile de Rodin, elle collabore avec lui sur des sculptures célèbres, mais toujours dans l'ombre. Elle s'émancipe pour affirmer son génie mais, isolée et bridée par une société patriarcale, consumée par son art, elle finit internée par sa famille. Plongez dans la vie tourmentée de Camille Claudel, une artiste trop longtemps oubliée. Crédits : Lorànt Deutsch, Valériane Cariou. Tout l'été, retrouvez l'inimitable Lorànt Deutsch pour vous révéler les secrets des personnages historiques les plus captivants !Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

We've been running a bit of an Agent Cloud series surveying all the top inference/compute/cloud providers, from Databricks to Daytona to Railway and, even further back, E2B, but we're excited to conclude this series returning to Modal, which has just raised a monster $355M Series C.The cloud was built for developers. But agents are now changing that.The old infra stack was designed for a human who could read docs, reason through YAML, and understand dashboards to figure out what they need when something broke. While this was painful for developers, it worked since they could fill in missing context in their heads.However, agents don't have that luxury. Now in this new era of agents, everything has to be tighter.They need a place to write code, run it, inspect the output, change the environment, debug failures, and try again. Fast iteration and feedback loops with all the necessary context are crucial for agents to operate properly. Furthermore, sandboxes are a clear representation of this shift as agents can easily spin up isolated environments. This programmatic infra even extends to research:Two years ago, we were one of the first to cover Modal with CEO Erik Bernhardsson and Alessio designed our favorite LS thumbnail of all time:At the time, Modal was just a teeny little company with a $17M Series A.Today, fresh off their $355M Series C, Modal is one of the clearest examples of the agent cloud future being built in real time: a cloud platform moving past traditional web app assumptions toward the workloads AI actually creates such as elastic inference, sandboxes, GPU burst, post-training, background agents, and infrastructure that agents themselves can operate.In this episode, Modal CTO Akshat Bubna joins swyx and Vibhu to unpack why AI applications don't fit traditional cloud assumptions, why Kubernetes was never designed for bursty compute-heavy workloads, and why Modal is now shifting from developer experience to agent experience.We go deep on Modal's AI infra stack: serverless functions, decorator-based infrastructure, elastic inference for custom models, GPU snapshotting, DeFlash, speculative decoding, Auto Endpoints, sandboxes, persistent storage, networked containers, private IPv6, RDMA, multi-node training, and Modal's capacity pool across 17 cloud providers. Akshat also explains why RL rollouts can require 100,000 sandboxes, why production agents need hard guardrails, why observability may matter more than reading code, and why AI has made infrastructure exciting again.We discuss:* Why Kubernetes wasn't built for bursty AI workloads* How Modal started as a better runtime before becoming an AI cloud* Why Modal added GPUs before ChatGPT* The shift from developer experience to agent experience* Why observability matters when agents are writing the code* Elastic inference for custom models across audio, video, robotics, and comp bio* GPU snapshotting, cold starts, and why inference workloads are so bursty* Why RL rollouts can require 100,000 sandboxes* DeFlash, speculative decoding, and frontier-level inference performance* Auto Endpoints and making optimized inference easier to deploy* What Modal adds beyond vLLM, SGLang, and raw GPU rental* Modal's 17-cloud capacity pool and supercloud strategy* Networked sandboxes, sidecars, private IPv6, and RDMA* Serverless multi-node training for post-training and research workloads* Auto-research, model-guided sweeps, and agents launching GPU experiments* Compute strategy, capacity planning, and batch tiers* Why production agents need specialized sandboxes and hard guardrails* Modal's take on managed agents, CI, Gitpod/Ona, Python, TypeScript, and Modal BenchAkshat Bubna* LinkedIn: https://www.linkedin.com/in/akshat-bubna-188885103* X: https://x.com/akshat_bModal* Website: https://modal.comTimestamps00:00:00 Introduction00:00:39 Modal's origin and why Kubernetes wasn't enough00:04:32 Developer Experience → Agent Experience00:06:21 Modal's AI cloud primitives00:09:14 Sandboxes, agent loops, and proto-Cognition00:12:12 Elastic inference, GPU snapshotting, and 100,000 sandboxes00:15:24 DeFlash, speculative decoding, and Auto Endpoints00:19:59 Production-grade inference beyond raw GPUs00:22:00 Background agents, Ramp Inspect, and the agent lifecycle00:24:08 Modal's 17-cloud supercloud strategy00:26:40 Networked sandboxes, private IPv6, and RDMA00:32:48 Multi-node training, post-training, and auto research00:37:36 Compute strategy, capacity planning, and batch tiers00:40:55 Open models, real-time AI, and production agent infra00:43:06 Hard guardrails, managed agents, and specialized sandboxes00:46:06 Why AI made infrastructure exciting again00:48:30 Model APIs, differentiated products, and agentic video00:51:50 CI, coding-agent infra, SDKs, and Modal Bench00:57:28 Closing ThoughtsTranscriptIntroduction: Modal, Series C, and the Art PartySwyx [00:00:00]: We're here with Akshat, CTO of Modal, together with Vibhu. Congrats on your Series C.Akshat [00:00:10]: Thank you.Swyx [00:00:11]: Your party yesterday was amazing.Akshat [00:00:15]: Yeah.Swyx [00:00:15]: From all the photos and all the swag.Akshat [00:00:17]: We had a bunch of art installations, which was fun, seeing, like, our products on pedestals next to, like, Rodin.Swyx [00:00:25]: Very nice. Very nice. When you started, it was not the GPU inference company. Maybe it was in your mind. Take us back to the origin story.Modal's Origin: A New Runtime Beyond KubernetesAkshat [00:00:39]: I first met Eric, who's the CEO, through an investor. Back then Eric was already thinking about building, a new runtime, and he got there thinking through why are workflow orchestration products so hard to use. It's because you have to run them on Kubernetes. Kubernetes is hard to manage. It's not built for burstiness and, custom images,Swyx [00:01:03]: YeahAkshat [00:01:03]: It has a terrible developer experience.Swyx [00:01:05]: And I'll, I'll interjectAkshat [00:01:06]: YeahSwyx [00:01:07]: For listeners, who are new, we interviewed Eric two years ago, and there's a bit more of the story there from Spotify and all those things.Swyx [00:01:14]: And I came across Eric through Data Council because he did that talk on the serverless container stack that you guys did, which was like, that was my first like, “Okay, I need to take Modal very seriously” moment.Akshat [00:01:26]: Yeah.Swyx [00:01:26]: But it was still very unclear, like, do I need all this for just my data pipelines?Akshat [00:01:33]: Yeah. initially what we were thinking about was if we build a better runtime, it's a very useful primitive in itself. It's There's a lot of things that, get solved by serverless functions, like you can do, ETL stuff, you can do job queues, you can do all this, like, bursty processing, which it turns out every company had needs for. but then we also were thinking about this as like, this is a primitive that we can build a whole collection of products on, which are very verticalized. So perhaps data engineering would've been the first one, but we were thinking about inference. Back then it was more classical inference, like computer vision stuff and running XGBoosts and whatnot. But we added GPUs to the product a year before ChatGPT came out.From Serverless Containers to GPU WorkloadsSwyx [00:02:19]: Nice.Akshat [00:02:19]: We just didn't think it would be that big of a deal.Swyx [00:02:22]: Yeah, just like add A100.Vibhu [00:02:23]: Was there any, like, early key problem that really sparked off why you built it?Akshat [00:02:28]: Yeah. Primarily it's just, none of the tooling that was out there was built for, one, a really great developer experience, and also there's a general trend of, a lot of the workloads that we were seeing were very. I wish there was a better word for it, but compute-heavy. Like, they need, one, like, need a lot more resources, so you need to burst up and down a lot, versus like Kubernetes designed for, like, slow scaling and, more for, like, web server use cases. And also there's just a lot more specialization in, like, what kinds of environments these workloads run in. Like, we had sometimes they need accelerators, sometimes they need different kinds of images, and this is just like a consistent thing that we saw across a lot of companies. That would be the next step.Software-Defined Infrastructure and Decorator-Based DXSwyx [00:03:13]: Yeah. Yeah. Be nice. I don't know how much this factored into the early story, but I wrote a post when I was at Temporal about infrastructure, software-defined infrastructure or something like that.Akshat [00:03:22]: Yeah, the self-provisioningSwyx [00:03:23]: Self-provisioning.Akshat [00:03:24]: Yeah.Swyx [00:03:24]: Yeah. I can't even remember my own post.Swyx [00:03:26]: And then you put me on the landing page.Akshat [00:03:28]: Yeah. We really like, the term and so we stole it.Swyx [00:03:32]: Because you had the insight that everything can just be in decorators co-located with the code, right?Akshat [00:03:37]: Yeah.Swyx [00:03:37]: Was that a big part of the originalAkshat [00:03:39]: YesSwyx [00:03:39]: Story or it was just like a DX layer?Akshat [00:03:41]: That was, really important because we really didn't want people to spend, so much time, writing YAML, and it seemed like you could really condense the surface area of what you're doing, put it in code so you can operate on it just like you operate on other code, and like build stuff that's more expressive and dynamic. and so yeah, that was always a very important part.Swyx [00:04:04]: Then the pushback is this is a DSL.Akshat [00:04:07]: Yeah.Swyx [00:04:07]: It's you're closed source. I am locked into Modal.Akshat [00:04:11]: Yeah. We never really got pushback for that because the nice thing about Modal is you can bring whatever code you have, and sure, the DSL is at the configuration layer for, what hardware you're using, how you're scaling things up, but you still own the code.Akshat [00:04:27]: And that's, that's been an important, part of our story, even as we do inference now.Swyx [00:04:32]: Yeah.Vibhu [00:04:32]: How much of do you think still stays the same today? Like if you were to build something today, DevX very important, but I feel like, a lot of this has been changed with just hook it up to an agent, have Claude Code, have Codex implement a tool. there's very agent native primitives that are different than if I'm doing this myself, right?Developer Experience → Agent ExperienceAkshat [00:04:54]: We've changed our SDK team to think about agent experience instead of, developer experience and we think that the same benefits that apply for DX also apply for AX, which is why would you have an agent read through hundreds of Kubernetes files and like write YAML that's not even typed when it can make a couple of changes in a decorator and it gets this self-provisioning runtime of, being able to see its changes live in action? yeah, it just seems from the customers we talk to, they find Modal is much faster for agents to use versus operating on a different substrate.Swyx [00:05:34]: Yeah, because like you, again, you co-locate the infrastructure requirements to the code that runs it.Akshat [00:05:38]: Yeah.Swyx [00:05:38]: Well, the negative thesis now is that nobody's looking at their code anymore, so there's no point.Akshat [00:05:44]: Yeah, people aren't looking at code. one thing we still see is really important is observability.Swyx [00:05:51]: Yeah.Akshat [00:05:51]: Like how good is your dashboard? And of course, like we have, we push a lot of it to the CLI so the agents can do their own investigation, but you still need humans to go interpret what's going on and, make judgment calls and whatnot. and that's I feel like, Maybe more important now than looking at the code itself.Swyx [00:06:11]: Yes, because like, you can try to treat the code as a black box and then use, see the observable action that comes out of it, and then just prompt a change.What Modal Is For: AI Cloud PrimitivesAkshat [00:06:21]: Yeah.Swyx [00:06:22]: So I think it takes a bit of restraint to not specialize, to say, “I want to ship a new primitive,” and then just be general purpose.Swyx [00:06:31]: People ask you, “What are you for?” You're like, “ I don't know. We can do this, we can do that.”Vibhu [00:06:36]: Well, I'd be curious to see, like, okay, if we were to ask you, like, what is Modal for even at a high level? There's a lot you guys do, sandboxes, GPUs, everything. How do you answer?Akshat [00:06:46]: Modal is a cloud platform that's built for, where we've built the primitives from scratch for AI applications. and right now it covers, inference, training, batch processing, and sandbox workloads.Akshat [00:07:00]: But we're building a lot moreSwyx [00:07:02]: I noticed you didn't say web server, so there is still a role for, like, the always-on large-scale Kubernetes type things.Akshat [00:07:09]: Yeah, absolutely. We're, we're not trying to compete with the renders of the world, because yeah, we think the differentiator for us is the, are the workloads that need specialized compute, need to scale up and down a lot. yeah, they're, they're, they're just shaped differently.Working Alongside Frontier StartupsVibhu [00:07:26]: I think you're building a lot of it alongside the startups, right? They're innovating quite a bit, even in your, like, latest blog post. Like, even in the series C, the customers that you mention here, the cognitions, technical ones, ramps and whatnot, they're, they're innovating with you, right? And that's not something AWS is doing directly with.Akshat [00:07:45]: Yeah, absolutely. I think, this is again classic. We're a small team. We can move really fast. our engineers are working with our customers and figuring it out. Yeah.Swyx [00:07:54]: So my first week at Cognition, I walked in, there was someone wearing a Modal shirt. I was like, “What are you doing here?” They're like, “Yeah, I just. I am embedded inside of Cog.”Akshat [00:08:05]: Yeah, I think that was Peyton. We sent him overSwyx [00:08:07]: Yeah.Akshat [00:08:07]: Because, the latency of communication was too high otherwise.Swyx [00:08:12]: Yeah, distributed node, you have to - you have to place one and collocate.Vibhu [00:08:16]: Yeah.Swyx [00:08:16]: So I had a, I had direct personal experience, right? So I worked on smol developer three years ago. it was inspired by Claude 1. I think you onboarded me at some point, like, just before, and I was like, “Oh, like, I need some bursty compute. Like, I was just gonna try using Modal.” And it was a, it was a pretty pleasant experience. apparently, I showed up in the board meeting, like the analytics.smol developer, Sandboxes, and Proto-CognitionAkshat [00:08:39]: Yeah, you blew up on Hacker News and,Swyx [00:08:41]: YeahAkshat [00:08:41]: We got a big traffic spike. I. I think the way you used smol developer was Modal functions for running stuff, which was. Like, the, that was a good use case. but then, yeah.Swyx [00:08:53]: Yeah. That - So to me, that was proto-cognition.Akshat [00:08:55]: Right.Swyx [00:08:56]: If only I had, like, stuck to it.Swyx [00:08:58]: Like, that was like, if - did you say draw the tech treeAkshat [00:09:00]: AbsolutelySwyx [00:09:00]: You're just like, “Yeah, like, probably this will happen.”Akshat [00:09:02]: Yeah. Like, he was so close. You were just rebuilding upon usSwyx [00:09:04]: I just didn't realize.Akshat [00:09:05]: But the funny story there is at the same time, we were talking to a bunch of customers who needed something like sandboxing.Swyx [00:09:14]: Yeah.Akshat [00:09:14]: This is like twenty-three.Swyx [00:09:15]: Yeah.Akshat [00:09:16]: So we builtSwyx [00:09:17]: You introduced a new API right after that.Akshat [00:09:18]: Yeah.Swyx [00:09:19]: Yes.Akshat [00:09:19]: Like, we built sandboxes in May of twenty-three before anyone was even knew this was gonna be a thing. And the first example we published was, we took smol developerSwyx [00:09:28]: Smol developerAkshat [00:09:28]: And put it in a loop, so the agent can iterate on itself.Swyx [00:09:33]: Loops are hot these days.Vibhu [00:09:34]: It's the looper.Akshat [00:09:34]: Yeah.Vibhu [00:09:35]: Loops in. When was this, twenty-three?Akshat [00:09:38]: Yeah.Vibhu [00:09:39]: A small check.Akshat [00:09:39]: Yeah.Swyx [00:09:39]: It's like twenty-three. so the. the, those for listeners, like, the problem was the models are not built for any of this, right?Swyx [00:09:46]: Like, you're just trying to like. They're not post-training to understand, like, looping and, like, self-correction and tool calling was there, but, like, also not that great.Akshat [00:09:55]: Yeah.Akshat [00:09:55]: I don't remember if you used tool calling in this one, but yeah, the models would just diverge after like ten iterations and not produce anything meaningful.Swyx [00:10:03]: Yeah. But like, then. So okay, like now talking to myself three years ago, the answerVibhu [00:10:08]: Of course they will get betterSwyx [00:10:09]: Collect all the failures, build benchmark, and then collect all the, examples, build the RL environmentAkshat [00:10:15]: RightSwyx [00:10:15]: Sell it for like ten billion dollars to Meta.Swyx [00:10:17]: And then also train a model and then sell that for sixty billion dollars to Elon. And this isAkshat [00:10:23]: Yeah, of courseSwyx [00:10:23]: The funny machine. Like, it's like, it's about the hardware.Akshat [00:10:28]: It's hard to have that inherent conviction that the stuff will get that much better.Swyx [00:10:33]: In retrospect, it's so f*****g obvious.Akshat [00:10:36]: Fair enough.Swyx [00:10:37]: Like, what else were we doing back then? I don't know. anyway. Yeah. So this. That was the start of your sandboxing journey, right? I feel like it didn't blow up until, like, last year.Akshat [00:10:49]: Yeah.Swyx [00:10:50]: So there was like a couple years of quietness.Akshat [00:10:52]: Exactly, yeah. We wereVibhu [00:10:53]: I think very underrated product value. Like, my experience with Modal, Charles, before he had joined Modal, met this guy at a hackathon, and he really insisted we wanted to run some small model, not hosted anywhere, and he's like, “ there's this cool company, Modal. They'll like spin up a GPU sandbox, we can throw it on there. They'll take a Hugging Face link.” And like there's so much value just right there, right? Like instant hosting, spin it up, spin it down. It'll stay cold, but we run the demo a few days later, it'll come back up and like all this stuff in retrospect, like it's still what we needed like today.Akshat [00:11:27]: Yeah, it's still needed today. workload shapes have changed a lot as, we run stuff for people with really massive production scale and, there it's it's not about scaling from zero to one, but it's how do we scale really elastically, from like thousand to fifteen hundred GPUs very quickly in a given region. It's the same shape problem.Elastic Inference, GPU Autoscaling, and Custom ModelsVibhu [00:11:50]: Okay. So you look at, say, Cursor Composer, right?Akshat [00:11:53]: Yeah.Vibhu [00:11:53]: They had a. “We'll do RL on a model every couple hours.” you guys have a whole version of RL inference gym and whatnot.Vibhu [00:12:01]: When you look at workloads like that, you're doing train runs where you need to scale up, scale down every hour thousands of GPUs, right? That's the example for we do need it, right?Akshat [00:12:12]: Yeah. Well, so I'll, I'll take a step back and, maybe talk about like how people use Modal today. because our biggest use case is, elastic inference. And the thing we first found product market fit, with was inference for custom models. So we stayed away from the LLM space, and we were serving companies like Suno for audio, Runway for video, robotics, comp bio companies that train their own model elsewhere. But Modal is the best black box that for deployment, scaling to however many GPUs you need as your traffic pattern changes. And we saw all of them like have a very unpredict- predict- predictable, traffic pattern. it's like diurnal. It's Some days, like the company will do a launch and, they'll need like, way more. And it's not just one model that they deploy. They-- all these companies deploy, lots of different models in different regions, and so the autoscaling problem becomes even harder because then you have to scale within a certain region, and those cycles are offset. So different times you scale up in different regions.Akshat [00:13:20]: So that's like our sortVibhu [00:13:22]: And thatAkshat [00:13:22]: YeahVibhu [00:13:22]: That in and of itself is a huge category. There's a bunch of inference providers which, provide this fireworks, does this as a service together, whatnot, Base10. that's carved into its own niche for language models, at least right now.Akshat [00:13:36]: Yeah. the thing that we have specialized in is the autoscaling aspect.Vibhu [00:13:41]: Yeah.Akshat [00:13:41]: Because we found that it's not universally true that everyone else can autoscale, and we've gone deeper into it on the tech side by, we've incorporated GPU snapshotting into the product so we can take the GPU state, like your torch.compile model, snapshot it, and the next cold start is way faster. And so going back to your question, it's That's why you need a lot of burstiness for inference. But then people also do a lot of demand training, like for RL stuff, your rollouts are bursty, as you said. People also do a lot of batch jobs. So we'll see, a lot of companies, before they have a training run, they'll need thousands of GPUs to run encoding or something like that. And I think those things are much more bursty than. I agree that agents are not that bursty. sandboxes are, except when you're doing RL. RL is justRL, Batch Jobs, and 100,000 SandboxesVibhu [00:14:28]: Or commerceAkshat [00:14:28]: Insanely bursty.Vibhu [00:14:29]: Yeah.Akshat [00:14:30]: Yeah. Like when you're doing, rollouts, you sometimes need a hundred thousand sandboxes in your sandboxes.Vibhu [00:14:37]: Yeah. I'm curious if you've seen early sparks of continual learning. There are some people, like our friends, ngram, recently announced thisAkshat [00:14:45]: YeahVibhu [00:14:45]: They're, they're trying to do training. That also seems like a different workload, right? If you're doing training twenty-four/seven per se, there's a very weird dynamic of how you're using GPUs between people and whatnot, but seems like something you guys would work for.Akshat [00:15:00]: As you said, we're, we're fortunate to work with a number of, customers at the frontier and grab some of our customers. and they are taking the primitives we have, and trying to use them in very interesting ways, like continual learning. It's possible as the stuff gets better, some of that will be part of, our offering as well if, more people need it. but we're, we're just waiting to seeVibhu [00:15:23]: YeahAkshat [00:15:23]: How it shakes out.Vibhu [00:15:24]: Is there a primitive that you added after sandboxing that was the next step in the story?LLM Inference, DeFlash, and Speculative DecodingAkshat [00:15:32]: I guess we've been going much deeper into LLM inferenceVibhu [00:15:35]: YeahAkshat [00:15:35]: Because we realized that some of the advantages we have with like autoscaling, again, especially in different regions and whatnot, are, not present elsewhere. and the place where we had a gap was we weren't, working on the model layer itself. Like we were a black box. And, we realized that, we can get to frontier-level model performance, with, by having great people who work on this. And, we've been open sourcing a lot of our work, in terms of, Recently, we, shared our work on DeFlash, which is a block-based, speculator, and we've open sourced, all of it. So, you can - By using open source DeFlash, you can get the same performance as you would with one of the proprietary providers. And the next thing we're thinking about hereVibhu [00:16:23]: I thought this wasAkshat [00:16:24]: YeahVibhu [00:16:24]: An interesting blog post as well, right? Like, I think in here you make a claim that. Not a claim, just that how effective speculative deco-decoding really just get to.Akshat [00:16:33]: Yeah.Vibhu [00:16:33]: Anything you wanna point out from this around, what people should know?Akshat [00:16:39]: Yeah, absolutely. the high-level summary is, it would help to describe what speculative decoding is.Vibhu [00:16:44]: Yes.Akshat [00:16:44]: I will, yes.Vibhu [00:16:45]: I think, likeAkshat [00:16:46]: YeahVibhu [00:16:46]: So we've covered like Eagle and all thisAkshat [00:16:47]: YeahVibhu [00:16:47]: Like Hydra and all those things, but it was like two years ago.Akshat [00:16:51]: Yeah.Vibhu [00:16:51]: I think it doesn't hurt, right?Akshat [00:16:52]: Yeah. Speculative decoding is you have a smaller model, called a draft model, predict tokens ahead of the bigger model, and then you have the bigger model, verify all of this, all the tokens are predicted. And the reason it's faster is if you're predicting, one token at once, you're bound by memory bandwidth. But if you can batch the verification of, the draft model, then you're much more efficient using compute, and it's faster, and as long as your draft model is producing a lot of tokens that can get accepted, which is called the accept length, you can get a speed up that's, multiple times of, the original model speed. and well, that's what we highlight here. It's Like people talk a lot about we made these kernels faster and whatnot, but improving kernel will only give you like few percentage points of improvement, and, increasing accept length, literally is a multiplicative decreaseVibhu [00:17:47]: Like two to four X.Akshat [00:17:48]: Yeah, exactly.Vibhu [00:17:48]: Without much head-on performance.Akshat [00:17:50]: Yeah. I think it may - you are running a second model, right? So it may be something more expensive in the compute,Vibhu [00:17:57]: I meant quality performanceAkshat [00:17:58]: Probably not by muchVibhu [00:17:58]: But yeah. I thinkAkshat [00:17:59]: So there's no drop in quality performanceVibhu [00:18:01]: YeahAkshat [00:18:01]: Because you're always. You're never accepting a token that the big modelVibhu [00:18:04]: It's strictly betterAkshat [00:18:05]: YeahVibhu [00:18:05]: Or it's same.Akshat [00:18:06]: Exactly.Vibhu [00:18:07]: Right. Yeah.Akshat [00:18:08]: And so we've been working a bunch on DeFlash, which is a block-based speculator. so it's instead of predicting, one token at a time, it's predicting a block. And we've been open sourcing our work with it. The next thing for us here is for helping people train speculators and custom models. it's it's something that traditionally is very forward-deployed engineering driven, support deployed, engineer driven, like you work with customers and help them do that. And our vision for. This is why we launched Auto Endpoints, is we want to make frontier-level performance available to everyone. And so, we mentioned this in the announcement, we teased it. The next thing we're, we're launching is, as you run an auto endpoint, we shadow trafficAuto Endpoints and Frontier-Level PerformanceVibhu [00:18:54]: Do you want to explain what auto endpoints are?Akshat [00:18:57]: Yeah.Vibhu [00:18:57]: I lovely, yeah.Akshat [00:18:58]: Yeah. So, this is, I guess, going back to your Modal is you touch the code, but, sometimes people don't wanna touch the code, and they wanna get started with an endpoint that works and has all the great performance and, scalability that Modal has. So we've made that easier with, a way to create an endpoint from our UI, from the CLI, that has all of our optimizations that we talked about, like the DeFlash stuff already baked in, and there's full transparency. So we give you the code, you can go run it yourself, and if you want, you can eject out into the full Modal experience, which we see as people get sophisticated, they do wanna tweak the models, they wanna, fine-tune stuff. You can still do all of that. It's it's not a black box. And yeah, the next thing, as we teased later in the post, is how do we give you value even beyond this in terms of having your draft models evolve as your data distribution evolves, again, without having to talk to a person and, yeah.Vibhu [00:19:59]: I guess just to understand it directly, you have the GPUs, you have an endpoint that's compatible, you serve open model. If someone was to do this themselves, what's the delta that you guys provide? So you do a lot of open source great work on effective inference. how does it compare to, say, I take the same model, 5.2 FP8, take shelf inference engine, vLLM, SGLang, get compute of similar capacity, similar cost. What's the delta that plugging into something this, like this offers outside of the benefit of, scaling?Production Inference Beyond Raw GPUsAkshat [00:20:34]: It's interesting because we've taken the approach of open sourcing our contributions and upstreaming them. we work closely with the SGLang team. We want the improvements that our team, comes up with to be, there in open source for others to use, even outside of Modal. The benefit to us is we have a team that has significant expertise in terms of if you do have something that is not there, our team can help you get that performance, first. the other thing is with these endpoints, we are way more elastic, as you said, than, anyone else, and you have true scaling to zero. you have true, burstiness, and in practice, that matters a lot more to people than just finding, the GPU and, running Modal code on something.Vibhu [00:21:20]: Yeah. And I will say it's not that straightforward to just. like what I said is easier said than done, right?Akshat [00:21:26]: Yeah.Vibhu [00:21:27]: It's I think still for the average person, still hard to just gut check using different. There's, there's quite a bit of combinations you can make there. the trade-offs aren't really known at face value.Akshat [00:21:40]: Yeah. it's it's not just that. I think it's it's that running production-grade inference is a hard infer problem.Vibhu [00:21:49]: YeahAkshat [00:21:49]: Even if you subtract out the autoscalingVibhu [00:21:50]: YeahAkshat [00:21:51]: Is controlling things like tail latency and, making sure every, request is delivered at least once and whatnot.The Model and Agent LifecycleVibhu [00:22:00]: There's a lot of innovation that you can do here. I think, it's very interesting that you're starting to encroach on, like as you become a full cloud, you're starting to encroach on other people's turf.Vibhu [00:22:09]: What will you not do?Akshat [00:22:13]: Well, we wanna follow our users and, make sure they get like a platform that has everything that works well together. so right now we're focused on the model lifecycle and the agent, lifecycle. so both like going from data prep to training to inference, and then also if I want to deploy a background agent, let's say, sandbox, do persistent storage, a whole bunch of other stuff.Vibhu [00:22:38]: We talked to Cole, who did, OpenInspect. Yeah.Akshat [00:22:42]: Yeah.Vibhu [00:22:42]: And RealInspect also is on Modal.Akshat [00:22:44]: Yeah. So Ramp Inspect was a great example of a background agent that was really successful because they, were able to use some of the primitives like snapshotting and fast scaling to just have something that feels really reactive and works well.Ramp Inspect and Background AgentsVibhu [00:23:02]: Yeah. That's the new CTO of, Ramp right there.Akshat [00:23:05]: Yeah, Rahul.Vibhu [00:23:08]: It was really fun. yeah, okay, I think, all very bullish. Like, one of my reflections was also I did not originally. So when I met you guysThe Inference Inflection: CPU, GPU, and Co-LocationVibhu [00:23:19]: You weren't that much in the GPU game, and now you're all about, inference. And one of the points that I hinged on for Jensen's keynote at GTC this year was, what we're calling like the inference inflection, right? That let's say in AI workloads or machine learning workloads, it used to be like, let's call it eight to one GPU to CPU, and now it's more like one to one, which is like a interesting. Like, - because of how much agents are blocked or call out to this, to CPU heavy stuff the actual, like, limiting factor, like, swings back and forth from GPU to CPU a lot more than it used to be all GPU and then occasional CPU.Akshat [00:24:01]: Yeah.Vibhu [00:24:02]: GPU, CPU. And now it's like just constantly, and you just have to locate everything.Seventeen Clouds and the Supercloud StrategyAkshat [00:24:08]: Yeah. And that's one of the things that, again, we see as, something appealing about Modal, which is we've built this capacity pool that spans, 17 cloud providers, so we're, we're very good at Running on various kinds of cloud capacity across the worldSwyx [00:24:24]: You don't have your own data centers?Akshat [00:24:25]: We don't have our own data centers. We just run across a lot of neo cloudsSwyx [00:24:29]: Yeah. AreAkshat [00:24:30]: Metal providers.Swyx [00:24:30]: Yeah. Question mark.Swyx [00:24:31]: Yeah. You're, you're running the math, and you're like, “What's the cutover point where you're like.”Akshat [00:24:36]: Yeah, it's a good question. part of it is we see our differentiator in the software layer, and, being capital light and focusing on the software helps us move really fast. so far it's worked out well because there are so many other people building data centers that we're able to work effectively with them, and again, focus on what makes us, special.Swyx [00:24:55]: Yeah.Swyx [00:24:56]: 17 gets you into, like, the local providers sometimes. LikeAkshat [00:25:00]: The,Swyx [00:25:01]: Which was the most interesting one?Akshat [00:25:02]: There are a lot more neo clouds than you expect, and they all have various degrees of, various levels of reliability. And, that's why it's something we've invested a lot of time in, is building our own reliability layer on top. so if the GPU falls off the bus or something happens, we user workloads are not affected, and that lets us use a lot more capacity than,Swyx [00:25:30]: YeahAkshat [00:25:30]: You as a user would be able to.Swyx [00:25:32]: It's a useful thing to have because like now everyone knows, like, what layer you are and, like, you optimize for being the super cloud of all clouds.Akshat [00:25:41]: Yeah. That's, that's, that's the idea. and so I guess when you mentioned colocation, that's, that's another interesting thing where, one thing we've seen is people come to us when they want, very specifically located, CPUs or GPUs, like they wantSwyx [00:25:57]: Oh, they pin it in likeAkshat [00:25:58]: YeahSwyx [00:25:58]: EU?Akshat [00:25:59]: Exactly. Or EU, US.Swyx [00:26:01]: Right. Data resiliencyAkshat [00:26:02]: AustraliaSwyx [00:26:02]: Locality thing or performance or what?Akshat [00:26:04]: It's either data locality or latency, yeah.Swyx [00:26:07]: Yeah.Akshat [00:26:07]: Like, you want your. They're running sandboxes and model. They want them to be right next to aSwyx [00:26:10]: Yeah, it's easy thenAkshat [00:26:11]: YeahSwyx [00:26:12]: To. That is important in all those things. and so, like, you've accidentally, I don't know if it's accident, but, like, you've built the perfect primitive for agents to express themselves. And then, like, it's almost very funny how every extra development just involves more file system, just involves more CPU.Akshat [00:26:30]: Yeah.Swyx [00:26:31]: Just like the things that you already have. I don't know much about, if there's any, like, networking usages that are interesting, but you've also done some good work on networking.Networking, Sidecars, Private IPv6, and SandboxesAkshat [00:26:40]: Yeah, that's exactly right. Like, we're just taking compute storage and networking and building stuff on that layer, for, again, the stuff people need.Swyx [00:26:49]: YeahAkshat [00:26:50]: We see a few interesting networking things coming up. one is people want networked sandboxes. so we haveSwyx [00:26:57]: For like a Docker cluster type thing.Akshat [00:26:59]: Yeah.Swyx [00:26:59]: Sorry, Docker Swarm. Oh, f**k. What is it called?Akshat [00:27:02]: Compose.Swyx [00:27:03]: Compose type thing.Akshat [00:27:04]: Yeah. So if you want Docker Compose, our sandboxes now support, this thing called sidecars. So you can. A sandbox is a pod of containers, and you can run multiple containers in, a sandbox. also useful because, going back to networking, people want a lot of control over, outbound networking from a sandbox.Swyx [00:27:23]: Yeah.Akshat [00:27:23]: Like, they might wanna run a middle proxy for, like, maybe logging stuff for RL or, controlling how egress can happen to a domain, injecting credentials. and yeah. So we've, we've had to build a lot of that stuff ourselves.Swyx [00:27:38]: Yeah.Akshat [00:27:39]: But then also sometimes people want, sandboxes spanning multiple nodes to talk to each other, which is an emerging thing we're seeing. We have support for that for a different reason, and yeah, we'll see if that becomes stable.Swyx [00:27:52]: Like, just an open socket. It's a. This is directly like mTLS.Akshat [00:27:56]: We do support that, which is you can, expose a tunnel inside a sandbox.Swyx [00:28:01]: Yeah.Akshat [00:28:01]: And then you can either expose it to public internet or it can be, you can add like a HTTP, auth layer above it. But we have this thing called I6PN, which we haven't talked about, which is this, like, overlay network using IPv6 addresses. so if Modal containers, within the same workspace, when this is enabled, can address each other using this private IPv6 address, and no one else can.Akshat [00:28:28]: So it's like private networking, for containers. We built it because we needed it as a primitive for our distributed training product. so we have this other feature, which is you can add a decorator to a function, and you get a cluster of GPUs. and they have RDMA networking. so you can run a distributed training job, that's truly serverless. and we did the overlay network for that. But then we've seen that people are using it for other reasons, and, I'm intrigued to yeah, what would people do with it.Swyx [00:28:59]: Build primitives and let people figure it out, right?Akshat [00:29:01]: Yeah, exactly.Swyx [00:29:02]: You put out a pretty interestingAkshat [00:29:03]: They're like, they read the docs webpage. Let me use thatSwyx [00:29:06]: YeahAkshat [00:29:06]: Something they never intended to work. This is literally not even in our docs page. People somehow found it, and they're using it.RDMA, Memory Movement, and Distributed TrainingSwyx [00:29:12]: Huh.Swyx [00:29:14]: The way you portrayed it with, like, RDMA versus TCP, like, very well laid out, but just the transfer speed change at scale for RL, like yeah, you have it, you have it built in. I'm sure someone found it. It's found it to be a lot more efficient before you made a thing out of it, right?Akshat [00:29:32]: Yeah. And not to split hairs, I guess the overlay network is the TCP overlay network.Akshat [00:29:39]: The reason we have that is you need that to do the key exchange for RDMA before you set up the RDMA network on top of that. but then people found the TCP part.Swyx [00:29:48]: Can I tell you, this is like a big aha moment for me becauseAkshat [00:29:51]: YeahSwyx [00:29:51]: So I review 2,200 submissions for the World's Fair.Akshat [00:29:56]: Yeah.Swyx [00:29:57]: And then I got this from John OsterhoutAkshat [00:29:58]: HuhSwyx [00:29:59]: Who I don't know if. Do John Osterhout by name?Akshat [00:30:01]: The name sounds familiar.Swyx [00:30:02]: He published a. He's a well-known professor, published a lot of interesting software design books, and this is the talk he chose to submit, is on RDMA at Inference. And I'm like, you wouldn't think that this guy, who is like operating systems guy, would care about RDMA.Akshat [00:30:20]: I, it makes sense to me because I,Swyx [00:30:24]: This is the cloud, right? YeahAkshat [00:30:25]: Like, the way you move around your KV cache and how efficiently you can do it, how efficiently you move, your weights from your training GPUs to your inference GPUs in RL is there's a lot of degrees of freedom, and it is a systems problemSwyx [00:30:41]: YeahAkshat [00:30:41]: Moving memory aroundSwyx [00:30:42]: YeahAkshat [00:30:43]: Scheduling.Swyx [00:30:44]: This shows you how primitive my understanding of networking stuff is.Swyx [00:30:46]: Is this like the domain of WireGuard as well?Akshat [00:30:50]: Not quite.Swyx [00:30:51]: It's adjacent?Swyx [00:30:53]: Explain everything.Akshat [00:30:54]: Sure.Swyx [00:30:56]: How do we move memory around GPUs?Akshat [00:30:58]: Well, so sorry. Yeah, that is memory. Sorry, I was talking more, and maybe I was talking like five minutes back, about the private IPv6, addressing that you've set up.Swyx [00:31:09]: Yeah.Akshat [00:31:09]: Is it like it's a VPN?Swyx [00:31:10]: Yeah, it is like a VPN, and yeah, WireGuard is, yeah, you're right. It is,Akshat [00:31:16]: Right. Yeah, you already moved on to new topicsSwyx [00:31:17]: A similarAkshat [00:31:18]: OkaySwyx [00:31:19]: In the same space, WireGuard is, encrypted and this is,Akshat [00:31:23]: And you don't need encryption.Swyx [00:31:23]: Yeah.Akshat [00:31:24]: Yeah.Swyx [00:31:24]: This is not encrypted. that's the main difference. This is TCP and we have eBPF programs that will reject or allow the TCP connection based on whether you're allowed to do it.Akshat [00:31:35]: Used to involve a full sidecar, but now you have eBPF in the Linux kernel.Swyx [00:31:39]: Yeah.Akshat [00:31:40]: Yeah. I don't know if this is a natural follow-on to the topic of like my skepticism on distributed training is that while, like, people spend a lot of money on, like, cables to hook up GPUs, and even that is not, like, fast enough, and that's the bottleneck, is your networking fast enough?Swyx [00:31:59]: Yeah. So I guess you're talking about fully distributed training like, Dialog or something which is like cross data centerAkshat [00:32:06]: That would be, yes.Swyx [00:32:07]: That's the extreme.Akshat [00:32:08]: Yeah.Swyx [00:32:08]: You're in the middle, and then other people would have like the Mellanox cables up in, like, their actual data center.Akshat [00:32:14]: When you run multi-node training on Modal, RDMA, I think Mellanox, is, or InfiniBand is like a, is all seen as RDMA. but it's a way to bypass the TCP networking stack and, transfer, stuff much faster, between one node, to the other. And we have I think like 3 terabit per second, internal networkingSwyx [00:32:40]: OkayAkshat [00:32:40]: Which is the standard that's needed.Swyx [00:32:42]: Okay. So I misunderstood whatAkshat [00:32:43]: 50Swyx [00:32:43]: What part of the stack you wereAkshat [00:32:44]: 50 gigs overSwyx [00:32:45]: YeahAkshat [00:32:45]: If you wentSwyx [00:32:45]: YeahAkshat [00:32:46]: RDMA.Swyx [00:32:46]: Okay.Swyx [00:32:48]: Yeah. I, very impressive work.Multi-Node Training, Post-Training, and Auto ResearchSwyx [00:32:52]: So effectively you're extending like the model philosophy to the training cluster, like, yeah.Akshat [00:32:59]: Yeah. And we're, we're not going for like large scale training runs. the thing that we've built multi-node training for is, we see a lot of, smaller scale post-training. like, people are post-training like medium sized fund models, so they can, get higher quality on inference. this is a perfect fit, for something like that.Swyx [00:33:21]: Yeah. That is my impression of how a lot of these labs explore branches in post-training and then eventually merge whatever they find in.Akshat [00:33:31]: Yeah. The other use case we've seen for multi-node training is even if you have a big cluster, your researchers are still doing small runsSwyx [00:33:38]: YesAkshat [00:33:39]: Having elasticity thereSwyx [00:33:40]: Right, sureAkshat [00:33:40]: Matters a lot more.Swyx [00:33:41]: Yeah. the, like, this is like the current limiting factor for auto research, which is like you need to give your model some GPUs in order for it to completely run.Akshat [00:33:51]: We have a blog post on auto resource and model is,Swyx [00:33:55]: YeahAkshat [00:33:56]: Yeah, like, turns out to be pretty good substrate for that.Swyx [00:33:59]: So my impression is auto research means many things, likeAkshat [00:34:01]: YeahSwyx [00:34:01]: Anything that Andrej coins. Right now it's still science fair, right? Like not like, I don't know how many people are doing this.Akshat [00:34:08]: We're having a golf.Swyx [00:34:08]: Yeah.Akshat [00:34:09]: I thought the same thing.Swyx [00:34:11]: Yeah, you would know.Akshat [00:34:12]: We, like, our internal both training and inference teams use this the general shape of this quite a bit. like we have this one internal repo called auto inference, which essentially we've automated our own forward-deployed engineering efforts using, this harness, which is, the agent will just spin up a sweep of different things. It'll even run like, NVIDIA inside profiler and it'll like tweak configs and it'll arrive the right thing. it'll change your GPUs both from H200 to B200, and works really well.Swyx [00:34:47]: Nice.Akshat [00:34:47]: So yeah.Swyx [00:34:48]: By the way, I enjoy that your forward-deployed engineering is so technical that you have to do these things.Swyx [00:34:52]: It's very different from forward-deployed engineering from other people.Akshat [00:34:54]: Yeah. For our forward-deployed engineering team is, essentially they're like applied inference researchers or applied training researchers.Swyx [00:35:02]: Someone told me like they have to be able to build, but they also have to be able to sell. do they have to sell or are they like they're good, they're just like post-sale type of thing?Akshat [00:35:09]: It does, being able to talk to a customer and engage effectively with themSwyx [00:35:13]: YeahAkshat [00:35:13]: Matters a lot.Swyx [00:35:14]: They want the same thing.Akshat [00:35:15]: Yeah.Swyx [00:35:15]: ?Akshat [00:35:15]: But it's it's not really a sales, thing. We pair them with-- We have solution architects as well that are more on the sales side.Swyx [00:35:23]: Okay. Let's spend a bit more time on auto research. This is a big focus for for this year. Where does this go? like, have people explored enough? Like, there's all these beautiful charts of like improve and then level off a bit and then you find the next thing. Is this one abstraction up from normal training? Is that how we think about it, or do you think about it differently? Like model level training versus high, like driven hyperparameter search.Auto Inference and Modal BenchAkshat [00:35:51]: Yeah, like,Swyx [00:35:51]: Someone, some people call it like neural architecture search or whatever, right? Like.Akshat [00:35:54]: Yeah, - So the stuff I've seen people do with it is nowhere on the architecture level. It's pretty much tweaking parameters, but it's it's a hyperparameter sweep that's guided by some model intuition, so it's like much more efficient than, whatever other, sweep you would have.Swyx [00:36:12]: Yeah, it's just, it's just a question of where you want to spend your compute?Akshat [00:36:16]: Right.Swyx [00:36:16]: ‘Cause yeah, you can just throw infinite amounts of money on this and somehow you'll bang out Shakespeare?Akshat [00:36:22]: Yeah, infinite monkey.Swyx [00:36:24]: Yeah, so like the very good for model. and I think it's also very important that agents can spin up other agents, can spin up their infrastructure. Like very good for you. how good is our LLMs at generating model code? Like the benefit of existing LLMs is that you are in the data.Akshat [00:36:42]: Yeah. They're, they're surprisingly good. I think like pre Cloud 4 they were not, and then now they're able to shot, stuff out of the box. But we're playing around with releasing like a Modal Bench for like the harderSwyx [00:36:55]: YeahAkshat [00:36:55]: Things, that the LLMs cannot do yet and maybeSwyx [00:36:59]: What's an example of that?Akshat [00:37:01]: I think the things that- Sometimes agents struggle with, without right guidance and a skill is, how to, use the rest of our observability. Like how to. Something is failing, like how do you look at the logs and then update the right thing? It's reasoning about that. But they're able to shot, likeSwyx [00:37:23]: Yeah. You can just add a skill to it?Compute Strategy and Capacity PlanningAkshat [00:37:26]: Yeah. So we have a Modal skill now that. Which is why we built this Modal Bench. It's to find things like that, so we can address them in our tool.Swyx [00:37:35]: Tune a skill. Yeah.Akshat [00:37:36]: Yeah.Swyx [00:37:36]: No. it's it's good. are you facing any shortages? like we talk a lot about GPU shortages, but also CPU, also memory.Swyx [00:37:44]: Yeah.Akshat [00:37:45]: We have had a lot of growth, which means that, there's - we've had to be much better aboutSwyx [00:37:53]: PlanningAkshat [00:37:54]: Proactive capacity planning.Swyx [00:37:55]: Yeah.Akshat [00:37:55]: So we have,Swyx [00:37:57]: Which by the way, like it's like a MBA's like dreamAkshat [00:38:00]: YesSwyx [00:38:00]: Is like just planning this stuff. I think last time you and I talked about something maybe about this.Akshat [00:38:03]: Yeah. we have a really competent team of people that we call, The role is called compute strategy. so yeah, if anyone listening here or wants to work on thatSwyx [00:38:13]: Compute strategy?Akshat [00:38:13]: Yeah.Swyx [00:38:14]: I think,Akshat [00:38:14]: I feel like,Swyx [00:38:15]: I think the normies call it FP&A or something.Akshat [00:38:18]: Well, it's more It's it's not FP&A. It's it's There's a lot of interesting financial questions of like what is the blend between one year and three-year reservations? how do we forecast our own capacity? how do we. especially since our capacity is very fungible across different GPU types and different regions, like you have to model a lot of it. and you also have to have an opinion on how the supply chain is gonna evolve, and then you have to like, take bets,Swyx [00:38:49]: YeahAkshat [00:38:49]: Based on that.Swyx [00:38:50]: Tokenomics.Akshat [00:38:50]: Yeah.Swyx [00:38:51]: This is like probably a not a real point, but, I was trying to think about like what other industries. I was trying to think about like, we cannot be first to like these kinds of problems.Akshat [00:38:59]: Yeah.Swyx [00:39:00]: And what other industries have had this? And I was like, airlines with fuel and like they have to hedge their fuel and like, I think for a long time Southwest because they made like a hero fuel bet, they like were like super low cost becauseAkshat [00:39:12]: OhSwyx [00:39:12]: Compared to everyone else.Akshat [00:39:14]: Yeah. I hadn't thought about that.Vibhu [00:39:16]: We're at a fun time too?Akshat [00:39:18]: Yeah. It's. A lot of the compute business in general, for us is also about being very good about capacity management. That is how you have great unit, economics. but also over time it's how you can unlock more value for customers. Like, one of the things we're building now is like a way for customers to get, If they don't care about latency, like get much cheaper pricing and they'll get results back in like next 24 hours or something, like a batch tier essentially.Batch Tiers and Latency-Insensitive WorkloadsSwyx [00:39:47]: Yeah.Akshat [00:39:47]: And those are levers we have because we control the whole stack and scheduling and whatnot to give people a sufficientSwyx [00:39:53]: Yeah. I feel like they're not as popular. Like those, like the Frontier Labs have all those APIs. They're not as popular as they should be.Akshat [00:40:00]: The demand that we see for something like that is not for LLMs. although sometimes people wanna run evals andSwyx [00:40:08]: OkayAkshat [00:40:08]: Synthetic data prep and there it makes sense.Swyx [00:40:10]: Okay.Akshat [00:40:11]: But it's from a lot of LLM companies, like people who are doing computational bio, like they have to run really big batch jobs and they don't care about when they get it back.Swyx [00:40:22]: Yeah. And like they have a reasonable. It's it's also like a cousin to the stopping problem of like, will this finish in time?Akshat [00:40:30]: Yeah. You can bound it.Swyx [00:40:33]: Yeah.Akshat [00:40:33]: Like you can give peopleSwyx [00:40:34]: YeahAkshat [00:40:34]: SLAs on it.Swyx [00:40:35]: Yeah. I think what's, what's interesting is like the next phase of model.Swyx [00:40:38]: Like what, do people expect from you, now that you're established and you're like well-known compute player among all these leading companies. You had an inference launch week, and we talked a little bit about the launches. like what else? Like what else should people know?What Modal Builds NextAkshat [00:40:55]: We are building primitives that make our users' lives much easier. So, I think for example, with LLM inference, thousands more companies are gonna post-train their own models and, deploy open source models for inference. so we're thinking a lot about what is the best product shape for that. And, that involves everything from our training gym to, then, endpoints that get frontier-level performance. again, but I haven't talked to anyone. It looks somewhat different on other verticals. Like, we're also seeing a lot of real-time, audio-video stuff in there, which is why like, we're working on things like regional routing, with fallbacks. So you can get GPUs that are as close to users as possible. so you get like low latency for video streaming and whatnot. And then on the agent side, it's,Akshat [00:41:52]: We're still working very closely with our customers because stuff is changing so fast in terms of what they need. And, I think beyond sandboxes and persistent file systems, there's a lot of other things people will need from this agent stack as they build production agents. So yeah, we're thinking about those other things that fit in there.Swyx [00:42:13]: I want to ask what the other things are.Akshat [00:42:15]: Yeah. I probably should share right now.Swyx [00:42:17]: I think-- I think, okay, so, I do think a lot about the principal components of cloud, and you do talk about compute storage networking.Akshat [00:42:25]: Yeah.Swyx [00:42:25]: Because so far for me, it's fine. so far for the. the first couple generations of cloud, it's fine. What's different, qualitatively different about agents that you need some new permission level? Like a lot of people, okay, and I'll just kinda spew tokens at you until it like hopefully sparks something.Akshat [00:42:43]: Yeah.Swyx [00:42:44]: Like the new level now is whatever Claude Code does, which is dangerously scope permissions or like allow list by command or like whatever, right? And sometimes they're like, “Well, okay, we have like this adaptive thinking mode where like, just trust me, bro. I will make the calls for you.” Is that it? like mediated permissions.Hard Guardrails vs. LLM-Mediated PermissionsVibhu [00:43:03]: Now you're looping it with a goal and letting it roll.Akshat [00:43:06]: Yeah, I'm, I'm skeptical of LLM media permission for stuff that is at the sandbox level because you do want hard boundaries.Swyx [00:43:16]: Yeah.Akshat [00:43:16]: Otherwise, someone can exfiltrate stuff.Swyx [00:43:20]: But likeAkshat [00:43:20]: YeahSwyx [00:43:20]: Maybe that's old school thinking. Maybe we're the dinosaurs.Swyx [00:43:23]: Maybe the AI OS or the LLM OS is really the kernel is a goddamn LLM.Swyx [00:43:30]: Like it makes you feel uncomfortable.Akshat [00:43:31]: Yeah, I'm, I'm toldSwyx [00:43:32]: But that's what trusting the LLM is. Like imagine a spherical cow perfect LLM.Akshat [00:43:36]: Right.Swyx [00:43:37]: That it.Akshat [00:43:39]: Maybe.Swyx [00:43:41]: I wanna test the boundaries, right?Akshat [00:43:42]: Yeah.Swyx [00:43:42]: Like, and I don't believe that, but I wanna see where I'm wrong ‘cause that's, that's the consensus.Akshat [00:43:49]: Yeah. I think you always need hard guardrails when you want, And you can pair those with softer guardrails, right? And that's gonna be a lot of mediated.Managed Agents and Specialized SandboxesSwyx [00:44:00]: There. I'll also get you a end with a couple of your commentary on like the ecosystem outside of Modal. Manage agents. Everyone has one. Gemini, OpenAI, Claude, very useful for you, but also like it is their way of starting to edge into your space.Akshat [00:44:17]: Yeah.Swyx [00:44:17]: What's going on?Akshat [00:44:19]: Yeah, we're, very excited to partner with Anthropic and some of the other foundation labs, will not name who we're also working with. the way we see it is the manage agent thing is a great place to start if you're starting out building an agent and, But then when you get to, building something more production grade, like you're a company that's like Ramp that's building their own, Ramp also runs their accounting agent on us, so their external-facing agent. You need a lot more control over, your compute primitive on things like, what sort - how do you persist different files that the agent has access to, and how do you snapshot and restore? How do you control the networking? maybe you want GPUs. When you get to that point, you kinda want, a specialized sandbox provider, that gives you those things, and that's the role that we are trying to play.Swyx [00:45:15]: YeahAkshat [00:45:16]: We don't really have an opinion on the harness, whether it runs - it's a cloud-managed agent, and you hook it up to Model Sandbox, or you run the harness in Model Sandbox. We'll see where people converge with that.Swyx [00:45:26]: Yeah. Do you any opinions on like the meta harnesses, or just another layer on top of these things?Akshat [00:45:31]: You mean like the OpenPipeSwyx [00:45:33]: OpenPipe is one. I think Vercel had one, which I can't remember the name of right now. Fredshot had one. and then, to me, most recently was Data Databricks that had Omnigen. All these are meta harness. Like it's kinda pseudo agent cloud type things.Akshat [00:45:50]: I personally have not played around with them.Swyx [00:45:53]: Yeah.Akshat [00:45:53]: Build agents with them.Swyx [00:45:54]: Everything's bullish Modal, as long as it consumes more infra.Akshat [00:45:57]: That's why we're focusing on the infra layer. It's somewhere where our, relative competence is and, also it's a hard problem to solve.Swyx [00:46:06]: Yeah. I will say like just generally reflecting on that, I don't know if - if there's other topics on Modal, but like just generally reflecting as an infra person, not as intense as you, but in that field, this has like been the most exciting time in infra. Like it was boring for a while, and you couldn't really get people excited about data infrastructure. Like Eric would get on Data Console, everyone just watched the video and like say, “Look at how many sandboxes I can spin up,” and no one gave a crap.Why Infrastructure Became Exciting AgainAkshat [00:46:39]: Yeah.Swyx [00:46:40]: And like now everyone gives a crap.Akshat [00:46:42]: That's true. It is a very exciting time, and I think a lot of that's driven by just the amount of scale all of this stuff needs.Swyx [00:46:50]: I think the, like a lot of your initiatives or a lot of your like product directions make sense in retrospect, which is like the best kind, but I wouldn't necessarily have thought about it myself, which.Akshat [00:47:00]: We need the predictions.Swyx [00:47:02]: I think there's a lot that you just don't even see, right? Like you have the batch, you have the voice, you have the multimodal, but what else?Akshat [00:47:10]: What else is coming up for usSwyx [00:47:11]: Yeah. Where do you see things going?Akshat [00:47:13]: Yeah. I, in generalBiotech, Robotics, and Non-LLM AI WorkloadsAkshat [00:47:15]: It's it's clear that there's there's a huge shift happening. I think one thing that's not as obvious to people because LLM inference gets talked about so much and is also we work a lot of companies that are, doing things like drug discovery and computational bio, like the Chai Discoveries of the world. Big things are probably gonna happen there. we work a lot of robotics companies that are putting robots in like active deployments and getting good results out of them.Swyx [00:47:45]: Is there Air Gap Modal? Is there a version that is like prem air gapped whatever?Akshat [00:47:50]: No. We,Swyx [00:47:51]: You should cloud only.Akshat [00:47:51]: Yeah.Swyx [00:47:52]: Yeah. Okay. But yeah, so what you're saying is like because you're focused on primitives and they're good primitives, you find use cases in all these kinds of things.Akshat [00:48:01]: Yeah.Swyx [00:48:01]: Probably diversifies you a little bit away from LMS all the time.Akshat [00:48:05]: Yeah, absolutely. We're, we'- our goal isn't to only serve the LLM inference market.Swyx [00:48:10]: There are a lot just on the website, the audio,Akshat [00:48:12]: Yeah. We said both onSwyx [00:48:14]: Computational bio images. Yeah, there's a lot here. There's QTA TTS, customizing. Oh, Chatterbox. there was customizing Whisper.Akshat [00:48:24]: Okay. Yeah.Swyx [00:48:25]: This screen reminds me of a fallen competitor, which Replicate.Model APIs vs. Differentiated AI ProductsSwyx [00:48:31]: What's your postmortem on what happened?Akshat [00:48:34]: This is one thing we've stayed away from is providing an API for models because I think providing model APIs is some of it ends up serving like a really hobbyist market, which is much less sticky.Swyx [00:48:50]: Yeah.Akshat [00:48:50]: And we've always wanted to build for companies that are building products and need more flexibility that's not just an API.Swyx [00:48:57]: Which you can build an API for a model and this is clearly what it is. But you - but what you're saying, you can wrap it into a more fully functioning back end that you run.Akshat [00:49:06]: Yeah. So all of our examples, it's not that spin up this model, here's an API token, use it. They're all code.Swyx [00:49:13]: Okay.Akshat [00:49:13]: And so the point is that this is just an example.Swyx [00:49:16]: Starter code.Akshat [00:49:17]: Yeah. But you can tweak it however you want.Swyx [00:49:20]: Yeah.Akshat [00:49:21]: And if you're like a company building a product, like, computational bio whatnot, yeah.Swyx [00:49:26]: I guess I'm trying to tease out for listenersAkshat [00:49:28]: YeahSwyx [00:49:28]: When does it stop becoming, oh, you're just an API call and you're just a wrapper on API to becoming what you call a product, right?Swyx [00:49:36]: Like, what is that layer? Like what-- Like, more lines of code, but like beyond that, what is the substance that people add that qualifies it to be something more?Akshat [00:49:46]: I think there's a little bit of like a selection effect of like a lot of the companies who do wanna get deeper into that level are probably building something that's more differentiated. And, I think, an example is like - with LLM inference, originally we, worked with companies that were building their own post-training frameworks or they were, - Ramp early in the day was training their own tokenizer and like swapping out the tokenizer in Llama and whatnot. I'm not saying that's, that successful, in that case. But a better example is like, let's say Suno. because Suno, does not use Modal for training.Swyx [00:50:26]: Mikey on the pod. Yeah.Akshat [00:50:27]: But they use Modal for all their inference and that's because they have like a custom-- They have completely custom model architecture and that means that they have to be at the code level and tweak things that are not, just an API.Swyx [00:50:41]: It's interesting as well, like we had, Ethan, most recently on the xAI Groq team make a prediction that like the next tier in video gen is not a better video model, it's a better model or agent that orchestrates video models.Video Agents and Production WorkflowsAkshat [00:50:56]: Oh, interesting.Vibhu [00:50:56]: Language model backbone that can use toolsAkshat [00:50:58]: RightVibhu [00:50:59]: And write code.Akshat [00:51:00]: Like, yes, I can make my second video or my second video from Groq, but I want my minute video.Akshat [00:51:06]: And I'm not going there through normal video gen.Swyx [00:51:10]: Yeah, that's interesting. I - So we have GPU sandboxes and recently have seen a few companies doing agents that do video manipulation or,Akshat [00:51:22]: Yeah. Give it FFmpeg and just do it.Swyx [00:51:23]: Run FFmpeg. But likeAkshat [00:51:25]: That's not enough.Swyx [00:51:25]: Yeah.Akshat [00:51:26]: You need to give it Adobe.Swyx [00:51:27]: Yeah, I hadn't put it together with like it would be a video production thing. in my mind these things were going more towards editingAkshat [00:51:36]: Yeah.Vibhu [00:51:36]: Well, shout out Mantis.Akshat [00:51:37]: I think about this a lot.Swyx [00:51:38]: .Akshat [00:51:41]: Yeah. Sorry.Vibhu [00:51:41]: Luma. Luma Agent is a version of this for video production, but it's a off.Swyx [00:51:46]: I was gonna get your quick takes, on some other stuff that happensGitpod/Ona, CI, and Runtime SandboxesSwyx [00:51:50]: In recent news and just-just see if you have anything interesting. Gitpod, very li

Le 1er février 2023, le rappeur toulousain Bigflo lançait son nouveau projet musical, sous un autre nom, “Bunshiin”. Ce mot japonais qui veut dire “l'autre soi”, en dit long sur la volonté de l'artiste de vouloir s'émanciper du duo BigFlo et Oli. C'est un moyen de retrouver la liberté de créer dans un autre style que celui auquel il nous a habitué, et en solo. Cela ne l'éloigne en rien du duo, qui continue à se produire sur scène dans toute la France, mais permet à l'artiste aux nombreux disques d'or de se différencier et d'oser se renouveler. Ce n'est pas la première fois qu'un artiste célèbre utilise un autre alias.  Pourquoi multiplier les noms d'artistes ? Certains artistes ne répondent-ils même plus officiellement à leur premier nom? Et quels sont ces artistes dont les vrais noms pourraient nous étonner ? Écoutez la suite dans cet épisode de "Maintenant vous savez - Culture". Un podcast Bababam Originals, écrit et réalisé par Carole Beaudouin. Première diffusion : mars 2023 A écouter aussi : ⁠Qui sont ces acteurs qui détestent leur rôle culte au cinéma ?⁠ ⁠Quels sont les 3 conseils pour lire plus souvent ?⁠ ⁠Qui est "Le Penseur" de Rodin ?⁠ Retrouvez tous les épisodes de ⁠"Maintenant vous savez - Culture"⁠. Suivez Bababam sur ⁠Instagram⁠. Learn more about your ad choices. Visit megaphone.fm/adchoices

CELÝ ROZHOVOR V DÉLCE 54 MIN. JEN NA ⁠HTTPS://HEROHERO.CO/CESTMIR⁠⁠⁠⁠ A ⁠HTTPS://FORENDORS.CZ/CESTMIR „Měl jsem pocit, že ulice patří mně. A že můžu cokoliv.“ Herec Jan Cina popisuje moment, kdy poprvé vyšel ven jako drag queen - v podpatcích, paruce a kostýmu - a najednou se cítil jinak. Ne jako někdo cizí, ale jako ostřejší, odvážnější a svobodnější verze sebe sama. „Jste to pořád vy. Ale zvětšení, posílení a zvýraznění,“ říká. Drag se k němu dostal přes film Chica Checa, ve kterém hraje mladého muže vracejícího se za matkou s pravdou o tom, že je gay a že se živí jako drag queen. Jenže po natáčení v něm tahle zkušenost zůstala a dnes už dokonce mluví o své dragové personě La Chica Pala Santa i o tom, proč ho nebaví dvě hodiny líčení, ale miluje sílu, kterou mu převlek dává. V rozhovoru popisuje, že už nechce být „hodnej Honza“, který sebou nechá vláčet, ale spíš člověk, který se snaží být dobrý, otevřený a citlivý. Právě citlivost je pro něj i smyslem herectví. Umění podle něj může člověka přimět, aby se díval jinak, aby hned neodmítal to, čemu nerozumí a aby se aspoň na chvíli zastavil. Cina popisuje i cestu do New Yorku, kam odjel po rozchodu a kde chtěl být chvíli mimo všechny role, které má doma - herce, syna, známé tváře i vítěze StarDance. „Najednou tam jste trochu nikdo,“ vzpomíná. Řeč přichází i na politiku, veřejnoprávní média, Slovensko a zrušené queer představení Měsíční kámen ve Slovenském národním divadle. Cina říká, že ho současná situace ve světě spíš než k velkým gestům vede k otázce, co může udělat sám. „Jediné, na co jsem přišel, tak se snažit být dobrý člověk,“ říká. Zároveň ale nezůstává jen u bezmoci - kvůli volbě ombudsmana a dřív i kvůli manželství pro všechny dokonce psal i Andreji Babišovi. Velmi osobně mluví také o samotě, rozchodu, depresi a touze po rodičovství. Po návratu z Ameriky ho podle jeho slov dohnala těžká fáze, začal brát léky a některé věci se mu přeskládaly. Právě od té doby je pro něj silné téma rodiny a dítěte. „Je to hodně aktuální věc,“ říká a dodává, že když vidí své přátele s dětmi, vnímá obrovskou náročnost, ale i „pevný bod“, kolem kterého se život začne skládat jinak. A i když pořád hledá, jak by se k téhle touze mohl postavit, mluví o ní jako o něčem, co mu začalo dávat smysl života mnohem konkrétněji než dřív. Co mu drag dovoluje ukázat, když běžný Jan Cina ještě váhá? Proč se v něm cítí silnější a ostřejší? Jak ho proměnil New York a co mu ukázal návrat domů? A proč se mu právě teď tak silně vrací touha po dítěti? I to se dozvíte v rozhovoru s Janem Cinou.

(Záznam z Konference pro ženy 2025) Marie je manželkou Joshe Ehlerse a mámou tří dětí. Studovala teologii a hudbu na Spurgeon's College a Union University. Momentálně spolu s manželem zakládají sbor Kostel Jinak v Olomouci, kde slouží především v oblasti chval a práce se ženami. Olomouc vnímají s manželem jako strategické město – historické univerzitní centrum plné mladých lidí hledajících smysl a komunitu. Věří, že právě zde může vzniknout církev, která bude autentická a zakořeněná v Boží pravdě. Článek Ženy, seberte odvahu v rodině / Marie Ehlers se nejdříve objevil na KOSTEL Jinak.

Episode: 1595 In which Alfred Stieglitz and 291 anticipate Modern.  Today, Stieglitz and photography, art and reality.

Happy Pride! It's the perfect time to discuss the listener requested HEDWIG AND THE ANGRY INCH, a loud, in-your-face musical experiment that has sparked one of the more philosophical episodes in our history. Joining us is the talented Matt Rodin (BEAU THE MUSICAL, COMPANY) who reflects on his transformative time with the musical and, along with Jeff, uses more pronouns and pronunciations than Hedwig could dream of. Learn more about Matt by visiting mattrodin.com and get ready for your newest obsession by playing his brand-new Theater Games platform. Interested in hearing from John Cameron Mitchell? Check out our episode THE SECRET GARDEN with Daisy Eagan & John Cameron Mitchell. Join us at ⁠⁠⁠⁠⁠PATREON!⁠⁠⁠⁠⁠ for bonus episodes, contests, and conversations all while supporting the show for only a few dollars each month! Share our posts and videos on ⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠TikTok⁠⁠⁠⁠⁠. If you're feeling like giving back, check out our ⁠⁠⁠⁠⁠TeePublic Store⁠⁠⁠⁠⁠. The profits we receive are donated to ⁠⁠⁠⁠⁠Broadway Cares/Equity Fights AIDS⁠⁠⁠⁠⁠. And check out our Spotify playlist featuring one song from each episode we've covered! More than anything, thank you for being part of this wonderful podcasting community. Learn more about your ad choices. Visit megaphone.fm/adchoices

Maintenant Vous Savez, c'est aussi ⁠Maintenant Vous Savez - Santé⁠ et ⁠Maintenant Vous Savez - Culture⁠. Auguste Rodin est l'un des sculpteurs les plus importants. Son oeuvre Le Penseur est aussi populaire que mystérieuse. Dans cet épisode, on vous en dit plus sur cette fameuse statue. Œuvre incontestablement la plus célèbre d'Auguste Rodin, Le Penseur, dont le nom originel était Le Poète, représente un homme en pleine méditation, et semblant confronté à un terrible dilemme. Si la pose de cet homme est très connue et a fait le tour du monde, peu de monde connaît la genèse de cette œuvre, ni même le symbole qu'elle représente. Qui est Le Penseur en tant qu'œuvre d'art ? Que représente-il ? Quel est l'importance du Penseur dans la culture populaire ? Ecoutez la suite dans cet épisode de "Maintenant vous savez - Culture". Un podcast Bababam Originals, écrit et réalisé par Thomas Deseur. Première diffusion : septembre 2022 A écouter aussi : ⁠Quels sont les plus grands plagiats dans la chanson ?⁠ ⁠Pourquoi Picasso fait-il polémique aujourd'hui ?⁠ ⁠Quels sont les 5 faux raccords les plus fous du cinéma ?⁠ Retrouvez tous les épisodes de ⁠"Maintenant vous savez - Culture"⁠. Suivez Bababam sur ⁠Instagram⁠. Learn more about your ad choices. Visit megaphone.fm/adchoices

La trayectoria de Camille Claudel estuvo marcada por su talento y por las dificultades de un entorno dominado por figuras masculinas. Su relación con Rodin y su situación personal condicionaron su reconocimiento en vida. Con el tiempo, su obra ha sido reivindicada como una aportación clave dentro de la escultura moderna. Y descubre más historias extraordinarias en National Geographic y Disney+. Learn more about your ad choices. Visit podcastchoices.com/adchoices

The broken windows theory suggests that one broken window can cause a neighbourhood to descend into disrepair. But is it true?  Today, with the award-winning professor Leidy Klotz, we investigate the broken windows theory and explain how environments shape our behaviour.  --- Become an FSB member: https://get.fsb.org.uk/nudge/ Leidy's book Subtract: https://amzn.to/4df4duk Leidy's latest book In a Good Place: https://amzn.to/4tzjCvE  Join 11,934 readers of the Nudge Newsletter: https://www.nudgepodcast.com/mailing-list Unlock the Nudge Vaults: https://www.nudgepodcast.com/vaults Connect on LinkedIn: https://www.linkedin.com/in/phill-agnew/  --- Today's sources:  Brown, G., & Baer, M. (2011). Location in negotiation: Is there a home field advantage? Organizational Behavior and Human Decision Processes, 114(2), 190–200. Cialdini, R. B. (2016). Pre-suasion: A revolutionary way to influence and persuade. Simon & Schuster. Langer, E. J., & Rodin, J. (1976). The effects of choice and enhanced personal responsibility for the aged: A field experiment in an institutional setting. Journal of Personality and Social Psychology, 34(2), 191–198. Pinsker, H., Kupfermann, I., Castellucci, V., & Kandel, E. R. (1970). Habituation and dishabituation of the gill-withdrawal reflex in Aplysia. Science, 167(3926), 1740–1742. Rajecki, D. W. (1974). Effects of prenatal exposure to auditory or visual stimulation on postnatal distress vocalizations in chicks. Behavioral Biology, 11(4), 525–536. Rodin, J., & Langer, E. J. (1977). Long-term effects of a control-relevant intervention with the institutionalized aged. Journal of Personality and Social Psychology, 35(12), 897–902. Wells, M. M. (2000). Office clutter or meaningful personal displays: The role of office personalization in employee and organizational well-being. Journal of Environmental Psychology, 20(3), 239–255.

Ovládá Česko několik málo nejbohatších rodin? O oligarchii se Zdislavou Pokornou by Alarm

Host: advokátka Gabriela Donati. Dotazy posílejte na adresu: dvojka@rozhlas.cz. Moderuje Patricie Strouhalová.

Host: advokátka Gabriela Donati. Dotazy posílejte na adresu: dvojka@rozhlas.cz. Moderuje Patricie Strouhalová.Všechny díly podcastu Káva o čtvrté můžete pohodlně poslouchat v mobilní aplikaci mujRozhlas pro Android a iOS nebo na webu mujRozhlas.cz.

ON TODAYS PROGRAM…   KIMI WINS 5 IN A ROW WITH A CHERIE ON TOP! PIERRE GASLY ROBBED OF PODIUM HADJAR KEEPS HIS PODIUM… CADILLAC LOOSES FIRST POINTS TO PENALTY.   SINCE LECLERC GOT MARRIED HIS PERFORMANCE HAS DECLINED…SORRY CHARLIE! SINCE GEORGE SIGNED HIS NEW CONTRACT AND GOT HIS FIRST PAYCHECK HIS PERFORMANCE HAS DECLINED!   THIS WEEK'S NASIR HAMEED CORNER WE HAVE: A MOMENT IN MOTORSPORTS HISTORY…AN INTERVIEW WITH BOBBY UNSER… SOME TRIVIA ON THE GRAND PRIX OF TURKEY AND TECH TALK WITH TIM! LCH GETS INTRODUCED TO A LOS ANGELES LOW RIDER!! Kimi Antonelli It's an incredible feeling to win in Monaco. It's such a special weekend and one I'll remember for a long time. Today was one of those days where everything just clicked; I had a lot of confidence in the car, felt strong throughout, and to bring the win home in a place like this makes it even more meaningful. From a race perspective, there were definitely some key moments to manage. The starts are still an area we're working on, but I've made good progress. My first one was solid, and although the second was a bit more challenging with the tyres, it's positive to see improvement. The red flag added a bit of stress, especially knowing the restart could change everything, but we handled it well. In the final laps, I really enjoyed myself out there, even though I still had to carefully manage the tyres. This track demands a lot of focus, you have to find the right balance between pushing and not making mistakes, and once you settle into that rhythm, everything starts to come together. At the same time, I know there's still a lot to learn and improve. I just want to keep pushing, keep building on this momentum, and most importantly, keep enjoying the journey. That's what makes moments like this so rewarding. ISACK HADJAR  "It's been an outstanding result and weekend considering how it started in FP1! The race was difficult and I had to dig very deep. We got off to a clean start and were managing our race, and then within the first 10 to 15 laps I started having big drivability issues. If there's one track you don't want that, it's here, so that was incredibly challenging having to cover 60 laps. There was then uncertainty about what was going to happen with the red flag and you need to get your head back again in focus. Even towards the end, I was still lacking power on the restart. It really was the longest race of my life but now it's finished we got the podium. Whatever happens with the stewards, it's now completely out of my control. I celebrated and had my podium and I will always have that. My moment with the lads. Huge thank you to the Team, I trust these guys. Whatever happens, the emotions on the podium have already happened and I am proud of the Team." MAX VERSTAPPEN - DNF "We don't know what happened today but we think the issue was due to an engine problem. During the formation lap I could feel that something was off and the pre-start was terrible. There was no consistency and then, at the start, the engine just dropped out. I dropped the clutch and it went dead and had no power. When I got a bit more power back, unfortunately it was messed up so I had to bring it back slowly. It was such a shame for us as everything was going really well up to that point. We felt great in the car all weekend and to come out with no points and to finish the race like this when you do everything so well as a Team is of course disappointing." George Russell Firstly, congratulations to Kimi. He did an amazing job today and over the weekend and is a well-deserving winner. On my side, the race was very difficult. I had managed to get to P4 but the penalty for speeding in the pitlane is difficult to understand. I was under the limit but then that was compounded by us not serving the penalty at my second stop; that ultimately cost me a lot and left me with zero points again. It's tough to take but I'm not going to give up. Across the last two races, I've effectively lost around 40 points. It's incredibly frustrating but the rest of the season can still look very different. We saw that last year and, in many seasons previous. It's unfortunate how things have played out so far but I'm aiming to bounce back in Barcelona. I believe in myself and I know what I'm capable of. LAURENT MEKIES - CEO & Team Principal "Mixed emotions today, as Isack and the Team did a great job to get him to the podium, overcoming some technical issues on the car, but on the other side of the garage, we lost Max's car straightaway with an engine issue. It was hard to take as he had incredible pace all weekend. It's frustrating when you miss out on a big points score, but that's part of the game, and we can only apology to him. For Isack it was a very intense battle in the car considering the number of issues he had to deal with. It was also an intense battle for the team in the garage as they worked to keep his car alive to the finish. In that context, making it to the podium is a very strong result. The most important lesson we take away from Monaco is that the underlying performance of the car keeps improving." Badoer earns maiden F3 victory in Monte Carlo. Brando Badoer launched off the line and into the lead and didn't look back, taking his first FIA Formula 3 victory for Rodin Motorsport.  The Italian beat pole-sitter Théophile Nael off the line and on the run to Turn 1, with the Frenchman having to settle for second place at the chequered flag. Freddie Slater completed the podium for TRIDENT.  AS IT HAPPENED  Nael was immediately passed by Badoer while Slater took to the escape road at the opening corner and filtered in behind the top two up the hill, with the remainder of the top five staying as they were on the grid.  Van Amersfoort Racing's Bruno del Pino was able to make up a place, getting ahead of MP Motorsport's Alessandro Giusti for P6 at Turn 1, but for the Frenchman's teammate, his race was over soon after. Tuukka Taponen found the barriers at the penultimate corner after an attempted pass by Maciej Gladysz left the Finn nowhere to go. That incident brought out the Safety Car on Lap 2.  With the MP cleared, racing resumed going onto Lap 5, with Badoer able to gap Nael comfortably, with the Frenchman under attack from Slater on the run to Turn 3. By Lap 10, Badoer had escaped out of DRS range to the Campos driver behind, while Slater, Ugo Ugochukwu and Ernesto Rivera remained within a second of the car ahead.  Drivers inside the top 10 began to back off on some laps in order to generate enough space to attempt a fastest lap for the additional point. Slater was very happy with the balance of his TRIDENT, praising the car over team radio. Lap 18 and Badoer looked unflappable out front, now two seconds clear of the field.  Further back in the pack, Nandhavud Bhirombhakdi was coming under serious pressure from Enzo Deligny in the fight for P15. The Thai driver had to defend into Turn 1 on Lap 21, and later missed the Turn 10-11 chicane, skipping across the run-off as the Frenchman behind turned the screw.  Nael spent the final five laps closing the gap to the leader back down to under a second, but the Rodin driver would not be denied, earning his first win in the Championship around the Principality. Slater completed the podium behind Nael while Ugochukwu and Rivera ensured all three Campos' were in the top five.  Bruno del Pino finished sixth for Van Amersfoort, followed by Giusti in P7, Pedro Clerot in eighth, Sprint Race winner Gerrard Xie in P9 and Noah Stromsted completing the points in 10th.  KEY QUOTE – Brando Badoer, Rodin Motorsport  “I was studying the start all evening with the guys yesterday and I executed it perfectly. I jumped to P1 at Turn 1 and then led the 27 laps. It was a very long race, I was hoping it ended a bit earlier and it felt long in the car, but winning in Monaco is one of my dreams come true! Really happy with the team and my performance. Thanks to everyone.”  THE CHAMPIONSHIP STANDINGS  Ugo Ugochukwu retains the lead of the Drivers' Championship going onto 43 points. Bruno del Pino is P2 on 35, just a single point ahead of Freddie Slater in third. Brando Badoer's win moves him up to P4 on 28 points, while Théophile Nael rounds out the top five drivers with 22 points.  Campos Racing extend their advantage at the top of the Teams' Standings, moving onto 75 points. Van Amersfoort Racing are P2 with 47, while Rodin Motorsport jumps TRIDENT into third place, 44 points to 43. ART Grand Prix complete the top five with 31 points.  León dominates in lights-to-flag victory in Monte Carlo F2. Noel León led every lap of the Monte Carlo Sprint Race on his way to claiming a dominant second victory of the season. Starting from pole, the Campos Racing driver managed the race expertly before going on to win by over three seconds. DAMS Lucas Oil driver Roman Bilinski achieved his maiden F2 podium in P2 ahead of MP Motorsport's Gabriele Minì in third.  AS IT HAPPENED  It was a good start from León, who kept the lead ahead of Bilinski, while Minì kept P3 ahead of Joshua Duerksen. In the battle for P11 Ritomo Miyata and Oliver Goethe went wheel-to-wheel through the hairpin and Mirabeau. However, they made slight contact which caused the MP Motorsport driver to pit, dropping him to the back of the field.  Out in front, León was struggling to pull away from Bilinski with the DAMS driver consistently within DRS range of the Mexican during the opening laps. The top four drivers of León, Bilinski, Minì and Duerksen were pulling away from the rest of the field, and by Lap 5 just two seconds separated the quartet.  Down the field, Laurens van Hoepen, who started in P21 was up to 15th by Lap 8. However, the TRIDENT driver's charge was halted when he was given a 10-second time penalty for leaving the track and gaining an advantage at the start. On to Lap 11 of 30, the drivers entered management mode, but the top four were still close, and were covered by 2.7s.  As the race reached the halfway point, Dino Beganovic had closed the gap to Duerksen and was now within DRS range of the Invicta Racing driver. Miyata, who had been running with a broken front wing since his contact with Goethe on the opening lap, was looking to make a move past Tasanapol Inthraphuvasak at Tabac, but found the door closed on Lap 17.  By the next lap the top two of León and Bilinski had pulled a three-second gap to Minì, as they continued to battle for the lead. The Italian driver was now running on his own having built a 2.3s gap to Duerksen in P4, with Beganovic right on the back of the Invicta driver on Lap 20.  Miyata's pressure on Inthraphuvasak finally paid off on Lap 22 as he dived to the inside of the ART Grand Prix driver on the run to Tabac. On the next lap, the Hitech driver was putting pressure on Nikola Tsolov for P10, while behind them, Mari Boya went around the outside of van Hoepen at the hairpin for P15.  With five laps to go, Inthraphuvasak retired to the pitlane with an issue. At the front of the field, León was now 2.4s ahead of Bilinski with Minì having closed the gap on the Polish rookie, just over a second away on Lap 27. The Campos driver continued to pull away and by the start of the final lap he was over three seconds clear of the rest of the field and would go on to win for the second time this season.  Bilinski held off Minì's charge to take his maiden podium, with Duerksen in P4 ahead of Beganovic. Stenshorne finished sixth ahead of Kush Maini, as Rafael Câmara rounded out the points in eighth.  KEY QUOTE – Noel León, Campos Racing  “Feels great to win in Monaco, my second win in a row on a weekend and in a Sprint. I feel very happy to be honest. Yesterday we missed a bit, we missed pole, but luckily it put me in a position to start on the front row today, to get the 10 points, and for the championship it is great. I have a great opportunity tomorrow to score again good points, that's the goal for this weekend and I am very happy that every weekend we are stronger and stronger and qualifying is going to get there at some points, so very happy.”  THE CHAMPIONSHIP STANDINGS  Gabriele Minì continues to lead the Drivers' Championship with 63 points, while Noel León has jumped up second, 20 points adrift of his rival. Martinius Stenshorne is third on 38 points, with Rafael Câmara a further point in fourth, as Nikola Tsolov rounds out the top five with 36.  In the Teams' Standings, Campos Racing have taken over at the top with 79 points, while MP Motorsport slip to second with 75. Rodin Motorsport are third with 68 points, with Invicta Racing a further 10 points behind in fourth, as DAMS Lucas Oil sit fifth on 38.  UP NEXT  The drivers have one more chance to hit the jackpot in Monte Carlo with Sunday's Feature Race set to start at 09:25 local time.  2026 FIA Formula 2 - Monte Carlo -  Provisional Classification, Sprint Race |   | DRIVER | LICENCE | TEAM | | 1 | Noel Leon | MEX | Campos Racing  | | 2 | Roman Bilinski | POL | DAMS Lucas Oil  | | 3 | Gabriele Mini | ITA | MP Motorsport | | 4 | Joshua Durksen | PAR | Invicta Racing  | | 5 | Dino Beganovic | SWE | DAMS Lucas Oil  | | 6 | Martinius Stenshorne | NOR | Rodin Motorsport | | 7 | Kush Maini | IND | ART Grand Prix | | 8 | Rafael Camara | BRA | Invicta Racing  | | 9 | Alexander Dunne | IRL | Rodin Motorsport | | 10 | Nikola Tsolov | BUL | Campos Racing  | | 11 | Ritomo Miyata | JPN | Hitech | | 12 | Nico Varrone | ARG | Van Amersfoort Racing | | 13 | Sebastian Montoya | COL | PREMA Racing  | | 14 | Mari Boya | ESP | PREMA Racing  | | 15 | Colton Herta | USA | Hitech | | 16 | Rafael Villagomez | MEX | Van Amersfoort Racing | | 17 | Emerson Fittipaldi | BRA | AIX Racing  | | 18 | Cian Shields | GBR | AIX Racing  | | 19 | Laurens van Hoepen | NED | TRIDENT | | 20 | John Bennett | GBR | TRIDENT | NOT CLASSIFIED | DNF | Tasanapol Inthraphuvasak | THA | ART Grand Prix | | DNF | Oliver Goethe | GER | MP Motorsport | OVERALL FASTEST LAP  |   | Nikola Tsolov | BUL | Campos Racing  |               1:22.100 (Lap 23)   OVERALL FASTEST LAP FOR POINTS  |   | Nikola Tsolov | BUL | Campos Racing  |               1:22.100 (Lap 23)     FIA Pit lane speed trap Monaco 

The Thinker And The Gates Of HellThere's a statue most of us have seen at some point, even if we can't immediately place where. Auguste Rodin's The Thinker has become one of the most recognized images in Western culture, and for good reason. The figure is strong, capable, self-possessed. He sits alone, deep in thought, as if the answers to life's greatest questions are just one more moment of reflection away. He is the ideal of the post-Enlightenment man: guided by reason, defined by his own greatness, needing nothing outside himself to become everything he was meant to be.It's a compelling image. Many of us have, at one point or another, seen ourselves in it.But the longer we live, the more that image fails us.Careers plateau. Marriages are harder than we imagined. The beauty and strength we once had quietly fades. We look inside for the strength to overcome, and we find more disappointment than we expected. The rugged individual who can think his way to his best life turns out to be a myth, and we feel that in our bones even when our culture keeps selling it to us.This is exactly where Ephesians 2 begins. Paul doesn't ease into the bad news. He leads with it. “You were dead in your trespasses and sins.” Not lost. Not broken. Not misunderstood. Dead. It's the most severe word he could choose, and he means for us to feel the weight of it, because dead people cannot heal themselves. Dead people cannot improve themselves or save themselves. A dead person needs someone else to do all the work.That is the diagnosis. And it matters, because good news only lands with power after the bad news has hit.Then come two of the most important words in all of Scripture: But God.“But God, who is rich in mercy, because of his great love that he had for us, made us alive with Christ, even though we were dead in trespasses.”The whole passage turns on that pivot. Before it, the focus is on us, our condition, our failure, our death. After it, the focus shifts entirely to God. And that shift is the entire point of the gospel.Look at who does the acting in this passage. God loved. God showed mercy. God made us alive. God saves. Christianity is not a religion that puts God at the top of a mountain and hands you a list of things to accomplish if you want to reach Him. It's the story of God coming down the mountain to find you where you are.That's grace. It's a gift, not a wage. Not something earned. Paul is explicit: “For you are saved by grace through faith. This is not from yourselves, it is God's gift. Not from works, so that no one can boast.”Faith, simply put, is trust in a person. It's the posture of someone who stops white-knuckling their own life and leans into the arms of a Father who is strong enough to carry them. If you've been trying to manage your sin, outrun your shame, or earn your standing before God through sheer effort, this passage has a word for you: lay it down. You're laboring under a burden you were never meant to carry.And here's where the story of The Thinker takes a turn that matters.What most people don't know is that Rodin never considered The Thinker his masterpiece. That statue was actually designed to sit at the top of a much larger work: The Gates of Hell, a massive, towering set of doors covered in more than 180 individual figures. The Thinker wasn't made to stand alone. He was always part of something bigger.So are we.Ephesians 2:10 says we are God's workmanship, created for good works He prepared in advance. The point of salvation isn't self-actualization. It's being placed by a master artist into a story far larger than ourselves. The people around us aren't background scenery. They're the good works God has already prepared for us.The gospel isn't a monument to human achievement. It's a monument to divine mercy. And the life that flows from it isn't about becoming the best version of yourself. It's about stepping, freely and joyfully, into the work God has already set before you.

Matt Rodin joins the podcast for an invigorating conversation about stepping out of traditional boxes and forging an authentic, sustainable path in the entertainment industry. He shares the remarkable story of his wedding day, which pulling double duty included marrying his husband in Central Park just hours before delivering his high-stakes final callback for the national tour of Company. Matt opens up about the perspective this gave him, detailing how a 360-degree view of the business—shaped by his time as a digital producer at Broadway.com and his husband's work as a talent agent—allows him to navigate the highs and lows of the theater world without taking the rejection personally. The discussion also dives deep into Matt's passion for technological innovation and community building. He pulls back the curtain on his latest venture, theater.games, explaining how his curiosity with AI code tools allowed him to develop daily theater puzzles like Spike and Curtain that have rapidly captured tens of thousands of players globally. From his early days creating the "Red Carpet Challenge" with a selfie stick to preparing for a whirlwind 12-hour recording session for the Beau cast album, Matt emphasizes the power of self-reliance, creativity, and the joy of creating work with friends rather than waiting for gatekeepers to open doors. Matt Rodin is a Drama Desk and Outer Critics Circle Award-nominated actor, creator, and creative consultant. His extensive stage credits include starring as Jamie in the national tour of the Tony-winning revival of Company, Roger in Rent at Paper Mill Playhouse, and the title role in Hedwig and the Angry Inch at Milwaukee Rep, alongside leading the off-Broadway premiere of Adam Gwon's All The World's A Stage with Keen Company. A prominent digital pioneer within the Broadway community, he is the mastermind behind the viral "Red Carpet Challenge," writer of the industry newsletter The Fourth Wall, and the founder of the digital puzzle platform theater.games. This episode is powered by WelcomeToTimesSquare.com, the billboard where you can be a star for a day. Connect with Matt: Instagram: @whoismattrodin TikTok: @whoismattrodin Platform: theater.games Connect with The Theatre Podcast: Support the podcast on Patreon and watch video versions of the episodes: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Patreon.com/TheTheatrePodcast⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Instagram: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@theatre_podcast⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook.com/OfficialTheatrePodcast⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TheTheatrePodcast.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Alan's personal Instagram: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@alanseales⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Email me at feedback@thetheatrepodcast.com. I want to know what you think. Learn more about your ad choices. Visit megaphone.fm/adchoices

L'exposition « Corps Vivants » proposée par le Louvre réunit plus de 200 œuvres de marbre, de bronze, et de plâtre sculptés par Michel-Ange et Auguste Rodin. Des sculptures si fidèles à leurs modèles qu'on attend qu'elles s'animent sous nos yeux. Les productions sont issues des collections du Louvre, du musée Rodin et d'importants prêts de grands musées internationaux.  Chloé Ariot, conservatrice du patrimoine au Musée Rodin et Marc Bormand, conservateur général du patrimoine au département des Sculptures du musée du Louvre, étaient les invités de Nathalie Amar sur RFI. L'exposition « Corps vivants » est à retrouver au Louvre.   ► Chronique : Les pionnières de la culture  Marjorie Bertin nous parle d'Anita Conti, pionnière de l'océanographie française.   ► Reportage :  Solène Gardré s'est rendue aux Rencontres chorégraphiques internationales de Seine-saint-Denis, festival de danse contemporaine. Elle a notamment rencontré les danseuses et chorégraphes Tatiana Gueria Nade et Dafne Bianchi.   ► Playlist du jour : - Ezra Collective feat Pa Salieu - Only Love - Himra - Bara Bara.

L'exposition « Corps Vivants » proposée par le Louvre réunit plus de 200 œuvres de marbre, de bronze, et de plâtre sculptés par Michel-Ange et Auguste Rodin. Des sculptures si fidèles à leurs modèles qu'on attend qu'elles s'animent sous nos yeux. Les productions sont issues des collections du Louvre, du musée Rodin et d'importants prêts de grands musées internationaux.  Chloé Ariot, conservatrice du patrimoine au Musée Rodin et Marc Bormand, conservateur général du patrimoine au département des Sculptures du musée du Louvre, étaient les invités de Nathalie Amar sur RFI. L'exposition « Corps vivants » est à retrouver au Louvre.   ► Chronique : Les pionnières de la culture  Marjorie Bertin nous parle d'Anita Conti, pionnière de l'océanographie française.   ► Reportage :  Solène Gardré s'est rendue aux Rencontres chorégraphiques internationales de Seine-saint-Denis, festival de danse contemporaine. Elle a notamment rencontré les danseuses et chorégraphes Tatiana Gueria Nade et Dafne Bianchi.   ► Playlist du jour : - Ezra Collective feat Pa Salieu - Only Love - Himra - Bara Bara.

Centrum rodinné mediace Vysočina v Jihlavě nabízí rodinám pomoc při rozvodech a konfliktech. Do řešení zapojuje i hlas dítěte.Všechny díly podcastu Dobré dopoledne můžete pohodlně poslouchat v mobilní aplikaci mujRozhlas pro Android a iOS nebo na webu mujRozhlas.cz.

Heather Webb is the USA Today and international bestselling author of eleven novels, including her upcoming The Hope Keeper and her other recently published Queens of London, The Next Ship Home, and Christmas with the Queen. In 2015, Rodin's Lover was a Goodread's Top Pick, and in 2018, Last Christmas in Paris won the Women's Fiction Writers Association STAR Award. Meet Me in Monaco, was selected as a finalist for the 2020 Goldsboro RNA award in the UK, as well as the 2019 Digital Book World's Fiction prize. Three Words for Goodbye was a Prima Magazine's 2022 Book of the Year. To date, Heather's books have been translated to twenty languages. She lives in New England with her family and two mischievous cats.Killer Women Podcast is copyrighted by Authors on the Air Global Radio Network#podcast #author #interview #authors #KillerWomen #KillerWomenPodcast #authorsontheair #podcast #podcaster #killerwomen #killerwomenpodcast #authors #authorsofig #authorsofinstagram #authorinterview #writingcommunity #authorsontheair #suspensebooks #authorssupportingauthors #thrillerbooks #suspense #wip #writers #writersinspiration #books #bookrecommendations #bookaddict #bookaddicted #bookaddiction #bibliophile #read #amreading #lovetoread #daniellegirard #daniellegirardbooks #heatherwebb #sourcebooks

Heather Webb is the USA Today and international bestselling author of eleven novels, including her upcoming The Hope Keeper and her other recently published Queens of London, The Next Ship Home, and Christmas with the Queen. In 2015, Rodin's Lover was a Goodread's Top Pick, and in 2018, Last Christmas in Paris won the Women's Fiction Writers Association STAR Award. Meet Me in Monaco, was selected as a finalist for the 2020 Goldsboro RNA award in the UK, as well as the 2019 Digital Book World's Fiction prize. Three Words for Goodbye was a Prima Magazine's 2022 Book of the Year. To date, Heather's books have been translated to twenty languages. She lives in New England with her family and two mischievous cats. Killer Women Podcast is copyrighted by Authors on the Air Global Radio Network #podcast #author #interview #authors #KillerWomen #KillerWomenPodcast #authorsontheair #podcast #podcaster #killerwomen #killerwomenpodcast #authors #authorsofig #authorsofinstagram #authorinterview #writingcommunity #authorsontheair #suspensebooks #authorssupportingauthors #thrillerbooks #suspense #wip #writers #writersinspiration #books #bookrecommendations #bookaddict #bookaddicted #bookaddiction #bibliophile #read #amreading #lovetoread #daniellegirard #daniellegirardbooks #heatherwebb #sourcebooks

„To, že na sebe tlačíme, že se často snažíme všechno zvládnout samy, je vzor, který nám daly naše mámy a babičky. Musely bychom do naší historie sáhnout hodně hluboko, abychom našli kořeny toho, kdo vlastně jsme,“ říká polská novinářka Joanna Kuciel Frydryszak.Všechny díly podcastu Houpačky můžete pohodlně poslouchat v mobilní aplikaci mujRozhlas pro Android a iOS nebo na webu mujRozhlas.cz.

Do letošní Muzejní noci se zapojuje celá řada muzeí, galerií a památkových objektů, také budova Českého rozhlasu Plzeň bude otevřena. Na akci zvou zástupci dvou velkých institucí: Západočeského muzea a Západočeské galerie v Plzni.

„To, že na sebe tlačíme, že se často snažíme všechno zvládnout samy, je vzor, který nám daly naše mámy a babičky. Musely bychom do naší historie sáhnout hodně hluboko, abychom našli kořeny toho, kdo vlastně jsme,“ říká polská novinářka Joanna Kuciel Frydryszak.

Před 80 lety začal v Praze proces s K. H. Frankem, někdejším státním tajemníkem Protektorátu Čechy a Morava, který se zodpovídal ze zločinů spáchaných na českém národě. O dobovém kontextu i nově zpřístupněných rozhlasových nahrávkách jednání si Jan Pokorný povídal s historikem Vojtěchem Kynclem. „Byla to mimořádná událost z hlediska práva i z pohledu vyrovnání se s důsledky války.“ Co všechno záznamy odhalují o poválečné spravedlnosti? A jak se proces podařilo zaznamenat?Všechny díly podcastu Host Radiožurnálu můžete pohodlně poslouchat v mobilní aplikaci mujRozhlas pro Android a iOS nebo na webu mujRozhlas.cz.

Před 80 lety začal v Praze proces s K. H. Frankem, někdejším státním tajemníkem Protektorátu Čechy a Morava, který se zodpovídal ze zločinů spáchaných na českém národě. O dobovém kontextu i nově zpřístupněných rozhlasových nahrávkách jednání si Jan Pokorný povídal s historikem Vojtěchem Kynclem. „Byla to mimořádná událost z hlediska práva i z pohledu vyrovnání se s důsledky války.“ Co všechno záznamy odhalují o poválečné spravedlnosti? A jak se proces podařilo zaznamenat?Všechny díly podcastu Host Radiožurnálu můžete pohodlně poslouchat v mobilní aplikaci mujRozhlas pro Android a iOS nebo na webu mujRozhlas.cz.

Před 80 lety začal v Praze proces s K. H. Frankem, někdejším státním tajemníkem Protektorátu Čechy a Morava, který se zodpovídal ze zločinů spáchaných na českém národě. O dobovém kontextu i nově zpřístupněných rozhlasových nahrávkách jednání si Jan Pokorný povídal s historikem Vojtěchem Kynclem. „Byla to mimořádná událost z hlediska práva i z pohledu vyrovnání se s důsledky války.“ Co všechno záznamy odhalují o poválečné spravedlnosti? A jak se proces podařilo zaznamenat?

Le 18 aout 1850, le grand Honoré de Balzac meurt à Paris. Très vite, il est décidé d'ériger une grande statue à l'auteur de la Comédie Humaine. Auguste Rodin se voit confier cette prestigieuse tâche. Il faudra attendre 65 ans avant de la voir enfin érigée. C'est cette incroyable aventure que raconte la romancière Clélia Renucci dans son livre Le Chef D'œuvre maudit, paru aux éditions Albin Michel. Merci pour votre écoute Un Jour dans l'Histoire, c'est également en direct tous les jours de la semaine de 13h15 à 14h30 sur www.rtbf.be/lapremiere Retrouvez tous les épisodes d'Un Jour dans l'Histoire sur notre plateforme Auvio.be :https://auvio.rtbf.be/emission/5936 Intéressés par l'histoire ? Vous pourriez également aimer nos autres podcasts : L'Histoire Continue: https://audmns.com/kSbpELwL'heure H : https://audmns.com/YagLLiKEt sa version à écouter en famille : La Mini Heure H https://audmns.com/YagLLiKAinsi que nos séries historiques :Chili, le Pays de mes Histoires : https://audmns.com/XHbnevhD-Day : https://audmns.com/JWRdPYIJoséphine Baker : https://audmns.com/wCfhoEwLa folle histoire de l'aviation : https://audmns.com/xAWjyWCLes Jeux Olympiques, l'étonnant miroir de notre Histoire : https://audmns.com/ZEIihzZMarguerite, la Voix d'une Résistante : https://audmns.com/zFDehnENapoléon, le crépuscule de l'Aigle : https://audmns.com/DcdnIUnUn Jour dans le Sport : https://audmns.com/xXlkHMHSous le sable des Pyramides : https://audmns.com/rXfVppvN'oubliez pas de vous y abonner pour ne rien manquer.Et si vous avez apprécié ce podcast, n'hésitez pas à nous donner des étoiles ou des commentaires, cela nous aide à le faire connaître plus largement. Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Episode: 1573 Donatello: Of his age or for all time?  Today, we ask: Of an age, or of all time?

Dr Sophie Matthiessen, Senior Curator of International Art at Auckland Art Gallery nous présente l'exposition "Facing Modernity" au Shepparton Art Museum qui se tiendra à partir du 23 mai. Cette exposition réunit des œuvres de Picasso, Degas, Matisse, Cézanne, Dali, Rodin et d'autres artistes, jamais exposées auparavant en Australie. Les oeuvres proviennent de la Galerie d'art d'Auckland Toi o Tāmaki.

Případ malé Viktorky, kterou svěřil soud do péče biologických rodičů a letos v březnu ji otec zavraždil, v nové epizodě Ve stínu odkrývá, pod jakým tlakem se ocitají úřady. To může vést k ponechávání dětí v rizikovém prostředí. „My prostě musíme dávat děti do biologických rodin, a to i v horších případech, než jste vy,“ zdůvodnila soudkyně benešovského soudu Sandra Kimmelová, když loni 9. října rušila pěstounskou péči a svěřovala dvouapůlletou Viktorku biologickým rodičům. Pět a půl měsíce poté otec Viktorku zavraždil. Případ, který ukazuje velké systémové selhání v péči o ohrožené děti, rekonstruujeme ve speciální podcastové sérii Viktorka. Dnešní, pátá epizoda přináší mimo jiné pohled odborníků z praxe. Hlasujte pro Ve stínu v anketě Podcast roku.

Případ malé Viktorky, kterou svěřil soud do péče biologických rodičů a letos v březnu ji otec zavraždil, v nové epizodě Ve stínu odkrývá, pod jakým tlakem se ocitají úřady. To může vést k ponechávání dětí v rizikovém prostředí.„My prostě musíme dávat děti do biologických rodin, a to i v horších případech, než jste vy,“ zdůvodnila soudkyně benešovského soudu Sandra Kimmelová, když loni 9. října rušila pěstounskou péči a svěřovala dvouapůlletou Viktorku biologickým rodičům. Pět a půl měsíce poté otec Viktorku zavraždil.Případ, který ukazuje velké systémové selhání v péči o ohrožené děti, rekonstruujeme ve speciální podcastové sérii Viktorka. Dnešní, pátá epizoda přináší mimo jiné pohled odborníků z praxe.Hlasujte pro Ve stínu v anketě Podcast roku.

durée : 00:18:12 - Les interviews d'Inter - par : Ali Baddou, Marion L'Hour - L'invité du Grand Entretien est Marc Bormand, conservateur général du patrimoine au département des Sculptures du musée du Louvre et co-commissaire de l'exposition "Michel-Ange Rodin-Corps vivants", au Louvre du 15 avril au 20 juillet 2026. - invités : Marc Bormand Conservateur en chef au département des Sculptures du musée du Louvre . Vous aimez ce podcast ? Pour écouter tous les épisodes sans limite, rendez-vous sur Radio France

Proč nejsou v Česku veřejné politiky přizpůsobeny slaďování rodinného a pracovního života? Jak důležitá je práce Evropského soudu pro lidská práva a  je ohrožena v Česku svoboda slova? A z čeho má soudkyně Kateřina Šimáčková radost?

durée : 00:05:31 - Classic & Co - par : Anna Sigalevitch - Anna Sigalevitch nous parle, ce matin, du concert de l'ensemble Les Métaboles dirigé par Léo Warynski ce mercredi 15 avril pour l'inauguration de l'exposition “Michel-Ange, Rodin. Corps vivants” au musée du Louvre. Vous aimez ce podcast ? Pour écouter tous les épisodes sans limite, rendez-vous sur Radio France

In this Artist Episode Matt Rodin from the national tour of company and MTCA Director Charlie Murphy discuss:

Viaceré vlny konsolidácie vidia ľudia na výplatných páskach. Podľa Rady pre rozpočtovú zodpovednosť na to doplácajú pracujúce rodiny s deťmi a nízkopríjmoví živnostníci, ktorí môžu prísť aj o viac než tisíc eur ročne. Niektorých však takáto suma šokuje naraz - napríklad po ročnom zúčtovaní dane alebo pri podávaní daňového priznania. Takýmto prípadom je aj pani Zdena, zdravotná sestra z Trnavy.Na príbeh pani Zdeny z Trnavy, ktorá sama živí tri deti, dnes upozornili Aktuality. Aby zvládla zaplatiť nájomné, musí chodiť aj do druhej práce, kde sa stará o ležiacich seniorov. Vďaka druhému príjmu presiahla hranicu tzv. milionárskej dane a Ficova konsolidácia ju obrala aj o daňový bonus na deti. V jej prípade sa síce stretlo viacero negatívnych faktorov, ale fakticky dokazuje zaujímavý paradox - čím viac pracuje, aby uživila rodinu, tým viac musí zaplatiť štátu na daniach. Nikto pritom nezohľadňuje, že z jej príjmov musia žiť štyria členovia domácnosti.V dnešnom videopodcaste uvidíte pani Zdenu a ekonóma z Rady pre rozpočtovú zodpovednosť Martina Šustra. Nahrával Peter Hanák. Na tejto téme sa podieľali aj Michaela Paulovič, Katarína Runnová, Marek Orihel a Michaela Jónová.

Le nom de Rodin résonne aujourd'hui comme celui d'un maître incontesté...Pourtant, avant le temps de la reconnaissance, le jeune Auguste a traversé des années d'échecs, loin des salons et des honneurs.Plongez dans les prémices de sa carrière. Découvrez les origines modestes de cet artiste hors du commun, son parcours semé d'embûches et les rencontres déterminantes qui ont forgé son talent.Franck Ferrand nous emmène au cœur du Paris du Second Empire, dans la boutique d'épicerie de la famille Rodin. C'est là que le jeune Auguste, fasciné par les gravures qu'il découvre, comprend sa vocation pour le dessin et la sculpture. Malgré les réticences de son père, il parvient à entrer à l'école impériale de dessin, où il développe un style personnel, loin des canons académiques.Ses premiers pas dans le monde de l'art ne sont pourtant pas de tout repos. Trois fois recalé à l'école des Beaux-Arts, Rodin se voit contraint de travailler comme artisan, modelant des décors de plâtre pour les immeubles haussmanniens. Mais sa rencontre avec Rose Beuret, qui deviendra sa compagne dévouée, ainsi que son expérience en Belgique, vont être déterminantes pour la suite de sa carrière.À travers ce passionnant récit, vous découvrirez comment les années de jeunesse de Rodin, faites de défis et de révélations, ont façonné le génie qui allait révolutionner la sculpture. Laissez-vous emporter par cette odyssée captivante.Plongez dans l'histoire des grands personnages et des évènements marquants qui ont façonné notre monde ! Avec enthousiasme et talent, Franck Ferrand vous révèle les coulisses de l'histoire avec un grand H, entre mystères, secrets et épisodes méconnus : un cadeau pour les amoureux du passé, de la préhistoire à l'histoire contemporaine.Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Découvrez l'histoire de Rose Beuret, la compagne de l'artiste Auguste Rodin pendant plus de 50 ans. Malgré les infidélités de Rodin, Rose a été une figure essentielle dans la vie et l'œuvre du sculpteur.Plongez dans l'histoire des grands personnages et des évènements marquants qui ont façonné notre monde ! Avec enthousiasme et talent, Franck Ferrand vous révèle les coulisses de l'histoire avec un grand H, entre mystères, secrets et épisodes méconnus : un cadeau pour les amoureux du passé, de la préhistoire à l'histoire contemporaine.Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Jedna z nejhranějších českých skladatelek se narodila před 111 lety v Brně. I přes její krátký život ukončený nemocí stihla obdržet Smetanovu cenu za její Vojenskou symfonietu a prorazila do maskulinního světa dirigování. Osudu Vítězslavy Kaprálové se filmově věnoval dokumentarista Petr Záruba. „Byla první studentkou brněnské konzervatoře, která vystudovala skladbu a dirigování,“ popisuje v Hovorech Českého rozhlasu Plus.

Nous sommes le 24 décembre 1898. En feuilletant « Le Figaro », sous la plume de Gustave Larroumet, historien d'art, écrivain et haut fonctionnaire, on peut lire ceci : « Hier matin, au premier coup d'œil jeté sur le journal, j'éprouvais cette secousse de surprise et de douleur, si fréquent, dans la vie de Paris, où l'on apprend la mort de ses amis avant de les savoir malades. Georges Rodenbach vient d'être enlevé, brusquement, en pleine force, à quarante-trois ans. Il y a quelques jours, il me parlait de son dernier livre et, sachant en quelle estime je tenais son talent, il me quittait sur ces mots : « Parlerez-vous de moi ? » Je lui promis, et je tiens ma promesse avec ces lignes qu'il ne lira pas. Georges Rodenbach avait reçu l'adoption des lettres françaises, grâce au Figaro. Il n'était connu que dans les cénacles, lorsque la publication de « Bruges-la-morte », dans ce journal, vint apprendre son nom au grand public. La poésie de la mort lui ouvrait la vie littéraire. Il contractait ainsi une dette envers l'impitoyable créancière, une dette qu'il paye à bien courte échéance. » Larroumet revient dans la suite de son article sur le parcours et les qualités littéraires de son ami et conclut ainsi : « Il s'est endormi, loin de Bruges, le soir de Noël, à l'heure où le cloches tintent pour la dernière fois, avant le repos de la nuit. Qu'il soit couché dans la terre de France ou que la Belgique réclame son enfant mort, il ne sera pas exilé. Il avait deux patries, celle de son berceau et de celle de sa tombe. » C'est dix ans avant sa disparition que Georges Rodenbach monte à la capitale française. Il devient un parfait dandy, noue des amitiés avec Mallarmé, Mirbeau, Rodin, le jeune Proust et beaucoup d'autres. Chroniqueur de la Belle Epoque, il était un personnage complexe et paradoxal. Tentons d'en percer les secrets … Invité : Marc Quaghebeur, docteur en Philosophie et Lettres Sujets traités : Georges Rodenbach, Figaro, Paris, symbolisme, poésie , dandy, Mallarmé, Mirbeau, Rodin, Proust, Belle Epoque Merci pour votre écoute Un Jour dans l'Histoire, c'est également en direct tous les jours de la semaine de 13h15 à 14h30 sur www.rtbf.be/lapremiere Retrouvez tous les épisodes d'Un Jour dans l'Histoire sur notre plateforme Auvio.be :https://auvio.rtbf.be/emission/5936 Intéressés par l'histoire ? Vous pourriez également aimer nos autres podcasts : L'Histoire Continue: https://audmns.com/kSbpELwL'heure H : https://audmns.com/YagLLiKEt sa version à écouter en famille : La Mini Heure H https://audmns.com/YagLLiKAinsi que nos séries historiques :Chili, le Pays de mes Histoires : https://audmns.com/XHbnevhD-Day : https://audmns.com/JWRdPYIJoséphine Baker : https://audmns.com/wCfhoEwLa folle histoire de l'aviation : https://audmns.com/xAWjyWCLes Jeux Olympiques, l'étonnant miroir de notre Histoire : https://audmns.com/ZEIihzZMarguerite, la Voix d'une Résistante : https://audmns.com/zFDehnENapoléon, le crépuscule de l'Aigle : https://audmns.com/DcdnIUnUn Jour dans le Sport : https://audmns.com/xXlkHMHSous le sable des Pyramides : https://audmns.com/rXfVppvN'oubliez pas de vous y abonner pour ne rien manquer.Et si vous avez apprécié ce podcast, n'hésitez pas à nous donner des étoiles ou des commentaires, cela nous aide à le faire connaître plus largement. Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

VŠECHNY EPIZODY V NEZKRÁCENÉ VERZI SLEDUJTE NA HEROHERO.CO/STUDION Když se po sociálních sítích začalo šířit video ženy v těžké životní situaci, Patrik Buday v ní poznal vlastní mámu. Ve veřejné výzvě pak lidi poprosil, aby nesbírali lajky na cizím neštěstí. Ve Studiu N vypráví o dětství po boku matky alkoholičky a násilného otce závislého na automatech, o vlastním propadu i rozhodnutí žít jinak. Chlapec, který v pěti letech skončil v Klokánku a vyrůstal v pěstounské péči, má dnes vlastní rodinu a věnuje se práci s dětmi – má skejtovou školu a dělá přednášky v dětských domovech. „Ve všem negativním se snažím najít něco pozitivního. Jsem jak zas*anej Robin Hood,“ směje se Buday. V rozhovoru přiznává, že dlouho trpěl pocitem, že v jeho životě nic není fér. „Musel jsem si dojít ke klidu, lásce a pocitu, že můžu být šťastný. Na Vánoce jsem se díval do cizích oken a říkal jsem si: ‚To už budu do konce života sám?‘ Záviděl jsem jsem kamarádům jejich rodiny. Ale bylo pro mě důležité je vidět a být v nich. Jaký kluk si nechá v devatenácti vytetovat symbol rodiny na kůži? Cítil jsem, že to chci a potřebuju.“ O svých rodičích mluví ve Studiu N bez idealizace. „Na tátu nemám dobré vzpomínky, proto jsem ho odstřihl. Za celý život jsem u něj necítil dobrotu,“ říká. „Pokud vyčerpáte všechny strategie, jak udržet s rodiči kontakt, aniž by vám ubližovali, pak jediná možnost, abyste byli šťastní, je odstřihnout je. Není jiná volba.“ S mámou se dodnes stýká, ale museli si nastavit jasné hranice. „I když to v životě pos*ala, moje láska vychází z ní. Chlapi ji rubali, chodila nakalená tak, že nemohla mluvit, na hlaváku chodila vyzývavě oblečená a chlapi po ní řvali. Pamatuju si, že jsem se na ně ve čtyřech letech otočil a začal řvát, ať na ni tak nemluví. Měl jsem ochranářský pud už v tak nízkém věku. Máma nás ale hodně milovala. Pamatuju si, jak nás budila, lehla si k nám a říkala: miláčku, vstávej.“ Jak si nastavit hranici s rodiči, kteří propadli alkoholu nebo gamblerství? Kde se v něm vzala síla veřejně sdílet svůj příběh? A kdy si uvědomil, že už se sám dostává do problémů? Podívejte se na celé Studio N na herohero.co/studion

It's a little-known fact that appraisers on GBH's Antiques Roadshow are not paid to appear on the show. What keeps them on-set for 10+ hour days season after season? The special excitement from coming face-to-face with a once-in-a-lifetime object. So when a guest brought what they thought to be Rodin's sculpture “Eternal Spring” to the show in Fort Worth, TX, would the piece of art turn out to be an extraordinary find or a fake? Join host Adam Monahan as he uncovers the surprising story of the sculpture and the lasting mark left on two appraisers.

Attaché à sculpter « l'essence des choses », Constantin Brancusi aura bouleversé l'art moderne grâce à ses formes épurées dont s'inspireront les designers du monde entier.Né en 1876 dans un petit village roumain, Brancusi quitte très jeune son foyer pour explorer le pays, avant de prendre la route de Paris, la capitale des arts.

"One Day in Paris: How to See the Best of the City in 24 Hours"—ever wondered if you could really experience Paris in just one day? In this action-packed episode of Join Us in France, host Annie Sargent sits down with Rick McGuirk, a seasoned Paris visitor who turned a quick layover into an unforgettable adventure. Whether you're squeezing in a solo day, showing a first-timer the highlights, or just love efficient travel, this episode is your ultimate guide to maximizing every minute in the City of Light. Listen to this episode ad-free Rick shares his real-time, fast-paced itinerary, starting with a sunset stroll through Luxembourg Gardens and Saint-Sulpice Church—a hidden gem with stunning art and history. The next morning, he kicks off at Trocadéro with a croissant, soaking in Eiffel Tower views before diving into a walking marathon that includes the Louvre Courtyard, Notre-Dame, and a riverside picnic at Square du Vert-Galant. No stuffy museums or endless lines here—just smart choices, like visiting the Musée de Rodin (no crowds!) and ending with Monet's Water Lilies at the Musée de l'Orangerie after dark. Annie adds her signature tips: where to skip the queues, how to navigate like a local, and why comfortable shoes are your best friend. You'll hear how Rick logged 32,000 steps, dodged Paris traffic (Olympic prep chaos!), and still found time for ice cream at Berthillon, a Seine River cruise with wine, and a late-night crêpe. Spoiler: His secret weapon? A mix of walking, strategic Ubers, and knowing which attractions stay open late. Annie also reveals her favorite off-the-beaten-path spots, like the Courre de Commerce alleyway, and why the Batobus river taxi might just save your tired feet. Perfect for travelers with tight schedules, this episode proves you don't need a week to fall in love with Paris—just a well-planned day, a charged phone, and a sense of adventure. Rick's story is packed with practical advice, from ordering food in French (even badly!) to avoiding taxi scams at the airport. Plus, Annie's magazine segment dishes on what French presidents actually eat—hint: it's not all foie gras! Subscribe now to Join Us in France for more insider tips, hidden gems, and stories that make you feel like you're exploring France with a friend. Whether you're planning a trip or just dreaming of Paris, this episode will inspire you to see more, stress less, and savor every moment. Hit follow on Apple Podcasts, Spotify, or wherever you listen—and get ready to turn your next short trip into a memorable French escape!

A personal guide from us - smaller, quieter museums we genuinely love, chosen for their intimacy and character rather than hype. None of these are in the top 15 most-visited museums in Paris. PS: The music from this episode is an original from Pres Maxson called Guimard's Abbesses. Here's the list of museums mentioned in the episode. For the full list with addresses, details, websites, etc, check out my website and Substack.  1. Musée Rodin 2. Musée des Archives Nationales 3. Maison de Balzac 4. Musée de la Chasse et de la Nature  5. Musée Yves Saint Laurent Paris (currently closed) 6. Musée Nissim de Camondo (currently closed) Future Bonus: Musée Hector Guimard (opening 2027ish) *********** The Earful Tower exists thanks to support from its members. For just $10 a month you can unlock almost endless extras including bonus podcast episodes, live video replays, special event invites, and our annually updated PDF guide to Paris.  Membership takes only a minute to set up on Patreon, or Substack. Thank you for keeping this channel independent.  For more from the Earful Tower, here are some handy links: Website  Weekly newsletter  Walking Tours

In "Via Francigena: Slow Travel, History, and Self-Discovery on Foot," host Annie Sargent chats with Olivier Andrieu about his incredible 100-day journey along the Via Francigena. Olivier, a former corporate sales director, decided to quit his job and walk from Canterbury, England, to Rome, Italy. He wanted a fresh start and a challenge, and the Via Francigena provided both. Listen to this episode ad-free Olivier shares the highs and lows of his adventure. He walked an average of 25 kilometers per day, staying in convents, monasteries, and Airbnbs along the way. He met people from all over the world, discovered hidden historical gems, and immersed himself in the beauty of slow travel. Olivier's journey took him through England, France, Switzerland, and Italy, offering a rich tapestry of landscapes and cultures. One of the highlights of Olivier's journey was the historical discoveries he made. He learned about a young World War I soldier whose name was engraved in a church near his home. He visited the statue of Rodin in Calais and discovered convents just an hour's drive from his home that he had never seen before. These discoveries added depth and meaning to his journey, connecting him to the history and culture of the places he visited. Annie and Olivier also discuss practical tips for anyone considering a similar journey. Olivier recommends a 35-liter backpack and high-quality gear. He used Akileine Nok cream to prevent blisters and had minimal injuries throughout his journey. His packing tips and advice on finding accommodations are invaluable for anyone planning a long-distance walk. In the magazine segment, Annie critiques The New York Times' "36 Hours in Toulouse" article, emphasizing the importance of experiencing the city beyond a quick checklist. She also dives into the intricate work behind Paris's Christmas windows and updates listeners on the success of free-flow tolling on the A13 motorway. If you love travel stories, historical adventures, or are dreaming of exploring France on foot, this episode is for you. Subscribe to Join Us in France for more inspiring stories and practical tips on exploring France. Whether you're planning your own adventure or just love to travel vicariously, Annie Sargent and her guests offer a wealth of knowledge and inspiration. Happy travels! Table of Contents for this Episode [00:00:16] Introduction and Guest Welcome [00:00:32] Today on the podcast [00:01:06] Podcast supporters [00:01:37] Magazine segment [00:02:39] Via Francigena with Olivier Andrieu [00:02:46] The Bold Decision to Walk Across France [00:04:02] Family Reactions and Support [00:04:34] Preparing for the Journey [00:05:08] Exploring the Via Francigena [00:08:30] Daily Routine and Experiences [00:13:12] Historical Discoveries and Reflections [00:18:56] Challenges and Physical Demands [00:23:44] Packing Tips and Final Thoughts [00:24:11] Packing Essentials for Long Walks [00:24:32] Choosing the Right Footwear [00:25:49] Dealing with Blisters and Injuries [00:27:07] Daily Routines on the Walk [00:27:41] Historical Discoveries Along the Way [00:28:50] Emotional Impact of World War Memorials [00:32:59] The Beauty of Slow Travel [00:33:32] Using Apps to Document the Journey [00:37:02] Unexpected Encounters and Local Stories [00:41:36] Cost and Accommodation Tips [00:43:22] Future Walking Plans and Reflections [00:45:56] Thank you Patrons [00:46:26] VoiceMap Tours [00:48:15] 36 Hours in Toulouse [00:50:20] Christmas Windows [00:53:33] Free Flow Tolling on the A13 [00:56:19] Next week on the podcast More episodes about active vacations in France #JoinUsInFrance, #FrancePodcast, #TravelFrance, #FrenchCulture, #ExploreFrance, #DiscoverFrance, #FranceTravelTips, #RealFrance, #Francophile, #FranceAdventures, #ViaFrancigena, #SlowTravelFrance, #WalkingFrance, #TravelingFranceOnFoot, #PilgrimageJourney, #HikingInFrance, #FrenchHistory, #TravelLikeALocal, #AdventureTravel, #HiddenGemsFrance

In today's episode Jordan Rodin joins us to chat about life lessons and hazing gleaned from Derek Hynd, make a case for heavier surfboards, explain his 5 year hiatus from getting barreled, why you should be stripping down used boards and reshaping them, what famous sculptors of centuries past can teach us about surfing, why sometimes the smallest movements can translate to the biggest things. Enjoy! Learn more about your ad choices. Visit megaphone.fm/adchoices