Podcasts about Kaisers

“Behind every breakthrough are countless failures no one ever sees—but that's exactly what makes progress possible.” Dr. Thomas Kaiser. When I have scientists on the podcast: they're some of the coolest, smartest, funniest people, and they're always willing (and excited) to explain what they do in ways you can actually understand. Dr. Tom Kaiser is no exception. He lives and works in Durham, North Carolina, and brings together an impressive mix of scientist, physician, and entrepreneur. His work focuses on designing better medicines using cutting-edge technology. He began his career at Emory University in Dennis Liotta's lab, working on antiviral drug discovery, and later helped pioneer early machine learning approaches in drug design. His research spans RSV, cancer, and neurodegenerative diseases, and he went on to earn his medical degree from the University of Oxford. Tom is now the co-founder and Chief Scientific Officer of Avicenna Biosciences, where he's leading the development of innovative therapies aimed at improving and saving lives. And my favorite detail from his bio? He ends it by mentioning the love of his life, his wife. I'll be honest, when I first met him, I told Dr. Kaiser he seemed like someone who must have been in a movie. He's just that cool. His Company: Dr. Thomas Kaiser shares the story behind his company's name, Ibn Sina, also known as Avicenna a true Renaissance figure of the Islamic Golden Age. A physician, philosopher, and scientist, Ibn Sina embodied the kind of multidisciplinary thinking that still drives innovation today. It's a powerful reminder that the roots of modern medicine, and the spirit of discovery stretch back centuries. The Part We Don't Talk About Enough Science is not a straight line. Not even close. Experiments fail. Clinical trials don't work. Hypotheses fall apart after years of effort. Funding can disappear. Progress can stall in ways that are frustrating and sometimes heartbreaking especially when patients are waiting. Dr. Kaiser speaks about this with a clarity and calm that really stayed with me. Because the truth is: scientists have to keep going anyway. They carry the weight of those disappointments and start again. They adjust, rethink, rebuild, and try again. Over and over. And that persistence? That's where breakthroughs come from. From the outside, it's easy to celebrate the wins ... the new drug, the successful trial, the headlines. But behind every one of those moments are countless failures no one ever sees. For families like ours, waiting, hoping, advocating it matters to understand that this difficult process is also what makes progress possible. Living the Dream What if you actually got to live the dream you had as a kid? In this conversation, Dr. Thomas Kaiser shares something surprisingly personal: he feels lucky to be doing exactly what he dreamed of as a child. That early curiosity grew into a career designing new medicines and pushing the boundaries of science. From imagination to impact, his journey is a reminder that sometimes those childhood passions really can shape the future. Go to Dr. Kaisers website:  https://www.avicenna-bio.com Like, subscribe, and comment on our podcasts!Please consider making a donation: https://thebonnellfoundation.org/donate/The Bonnell Foundation website:https://thebonnellfoundation.orgEmail us at: thebonnellfoundation@gmail.com Watch our podcasts on YouTube: https://www.youtube.com/@laurabonnell1136/featuredNew: Shop our merchandise! https://thebonnellfoundation.org/product-shop/Thanks to our sponsors:Vertex: https://www.vrtx.comViatris: https://www.viatris.com/enRead us on Substack: https://substack.com/@lstb?utm_campaign=profile&utm_medium=profile-pageWatch our trailer of Embracing Egypt: https://youtu.be/RYjlB25Cr9Y

Kein anderer Kaiser des Mittelalters wurde so von den Hoffnungen und Wünschen des 19. Jahrhunderts verzerrt wie Friedrich I. Barbarossa. Die Herausforderung für eine moderne Interpretation des Kaisers besteht darin, sein Leben und seine Politik in den Handlungshorizont seiner Zeit zu stellen. Erst dann kommt die Fremdartigkeit des fernen 12. Jahrhunderts ans Licht. Ein Vortrag des Historikers Knut Görich vom 22.04.2026 im Schelling Forum der BAdW in Würzburg.

Special discounts up for AIE Melbourne (LS discount) and AIE World's Fair (group discounts up to 25% - CFPs still open for Autoresearch and Vertical AI) Cya there!Abridge did not start as an “GPT wrapper”. It was founded in 2018, years before the Cambrian explosion of AI application layer companies. OpenAI launched ChatGPT publicly on November 30, 2022 and by then, Abridge had already spent years doing the unglamorous work of building trust for one of the highest context, most important workflows in healthcare: the conversation between a patient and a clinician.Abridge's original wedge was clinical documentation. Listen to the visit, generate the note, reduce the clerical burden, and let clinicians spend more time with patients instead of the EHR. By focusing on how doctors actually document, how health systems actually buy, how EHR integration actually works, how clinicians verify outputs, and how missing context during a visit turns into downstream friction across billing, prior authorization, quality, and follow-up, the adoption of LLMs became a force multiplier on a workflow already optimized for sensitive context gathering.The company has scaled fast: Abridge says it is projected to support 80M+ patient-clinician conversations this year across 250 large and complex U.S. health systems, with support for 28+ languages and 50+ specialties. It raised $300M at a $5.3B valuation in June 2025, after a $250M round earlier that year.Today, Janie Lee and Chaitanya “Chai” Asawa of Abridge join us for another crossover pod with Redpoint's Jacob Effron (who is on the board of Abridge) to dive into how Abridge is building the clinical intelligence layer for healthcare starting with ambient documentation, then expanding into clinical decision support, prior authorization, payer/provider/pharma workflows, and eventually real-time agents that act before, during, and after the patient conversation. We go inside the product, data, infra, evals, workflow, privacy, and org design choices behind bringing AI into one of the highest-stakes enterprise environments from 100M+ medical conversations and specialty-specific evals to real-time alerts, EHR integration, de-identification, clinician-scientist teams, and why healthcare may solve some of the hardest AI problems first.We discuss:* Why Abridge started with clinical documentation, “pajama time,” and saving clinicians 10–20 hours a week* The transition from ambient scribe to clinical intelligence layer: save time, save money, and save lives* Why conversations between patients and clinicians may be the most important workflow in healthcare (patient visit summary feature)* Chai's “healthcare-coded Glean” framing: context is king, but healthcare raises the stakes on safety, evals, and rollout* Why Abridge wants AI to feel like “air conditioning”: always in the background, but only interrupting when it truly matters* The prior authorization example: turning a denied MRI weeks later into real-time guidance while the patient is still in the room* Why payer policies, EHR data, medical literature, and hospital-specific guidelines make the problem hard, and also create the moat* How Abridge thinks about ambient form factors: mobile, desktop, in-room devices, nursing workflows, multimodality, and future AR* The multi-sided healthcare customer: CMIOs, CFOs, CIOs, clinicians, patients, payers, and pharma* The hardest AI problem at Abridge: high-quality, low-latency, low-cost real-time support in a high-stakes clinical setting* When Abridge uses frontier models vs proprietary models, and why its unique data from medical conversations matters* Why “every agent is a coding agent underneath,” and how the EHR can be thought of as a filesystem for healthcare agents* How Abridge approaches personalization across individual doctors, specialties, and health systems* Why “AI slop” is AI without context, and how edits, memories, and clinician preferences create a data flywheel* Abridge's eval stack: LFDs, LLM judges, in-house clinicians, third-party evaluators, specialty-specific evals, and progressive rollout* HIPAA, PHI, de-identification, one-way anonymization, customer contracts, and learning from healthcare data safely* What changes when you operate at 100M+ conversations: reliability, cost, post-training, model routing, and infrastructure optimization* Why the same clinical conversation can serve doctors, patients, payers, pharma, and future clinical-trial workflows* How Abridge works with EHRs, and why deep interoperability is table stakes for clinician adoption* Why healthcare AI has regulatory tailwinds, why 80/20 does not work here, and why high-stakes domains may drive AI forward* Why Abridge embeds “clinician scientists” into product and eval teams* What Chai learned from Glean about search, quality, and durable AI infrastructure* Why the future of AI infra may look like context layers, event-driven systems, Kafka, Temporal, sockets, CRDTs, and tools built for humans* Why Janie changed her mind on “PRDs are dead,” and why crisp written clarity matters more in complex AI products* How Abridge uses Claude Code, Cursor, and coding agents internallyAbridge:* Website: https://www.abridge.com/* X: https://x.com/AbridgeHQJanie Lee:* LinkedIn: https://www.linkedin.com/in/janiejleeChaitanya “Chai” Asawa:* LinkedIn: https://www.linkedin.com/in/casawaTimestamps00:00:00 Introduction and what Abridge does00:02:05 From ambient documentation to clinical intelligence00:04:04 Clinical decision support and context as king00:06:57 Alert fatigue, proactive intelligence, and prior authorization00:12:36 Ambient AI form factors and healthcare customers00:16:59 The hardest AI problems in healthcare00:18:26 Frontier models, proprietary data, and model strategy00:21:07 The EHR as a filesystem for agents00:24:03 Personalization, memory, and clinician preferences00:30:40 Evals, LLM judges, and progressive rollout00:36:47 HIPAA, de-identification, and privacy00:39:21 100M conversations and operating at scale00:44:10 EHR integration and the clinical intelligence layer00:46:39 Healthcare regulation, latency, and high-stakes AI00:50:11 Clinician scientists and long-tail quality00:53:04 Lessons from Glean and durable AI infrastructure00:57:03 The future of agentic healthcare workflows00:57:34 PRDs, product clarity, and building serious AI products01:03:11 AI coding tools at Abridge01:04:06 OutroTranscriptIntroduction: Abridge, Clinical Intelligence, and the Latent Space x Unsupervised Learning CrossoverSwyx [00:00:00]: Okay. This is a special crossover Latent Space Unsupervised Learning pod.Jacob [00:00:07]: Very excited to do this.Jacob [00:00:08]: At this point, we get together once a year.Swyx [00:00:10]: Once a yearJacob [00:00:11]: And this is a fun occasion to get to do it on.Swyx [00:00:13]: I really wanted to talk to Abridge but I felt very underqualified because healthcare is not something we cover very intensely. It just so happens that Redpoint's our big investors and supporters of Abridge.Jacob [00:00:27]: Anytime you want to have a portfolio company on your podcastJacob [00:00:29]: Please, by all means.Swyx [00:00:31]: So we'll introduce our guests. Chai and Janie, welcome to the pod.Janie [00:00:34]: Thanks for having us.Chai [00:00:35]: Thank you.Janie [00:00:35]: We're excited to be here.Chai [00:00:36]: Thank you.Swyx [00:00:36]: So for listeners, what do you guys do, just to situate you guys in the company?Janie [00:00:42]: Abridge is a clinical intelligence layer for health systems. We really started with documentation and building for clinicians and as we think about reducing the burden that clinicians have, they're spending 10 to 20 hours a week on documentation. There's a massive doctor shortage in the country. We also think that conversations between patients and clinicians are probably the most important workflow in healthcare. It's where care is given and received but if you think about the 20% of our GDP that goes towards healthcare, almost everything is a derivative of that conversation, whether it's the claim, the payment, the actual diagnosis given, the treatment. And we've started with a conversation to reduce the burden for doctors on documentation but we're really excited about the path ahead as we become this broader clinical intelligence layer.Chai [00:01:34]: I'm Chai. I work on clinical decision support at Abridge.Swyx [00:01:37]: Yes.Chai [00:01:37]: And so as Janie said, we're uniquely situated where we started off with the clinical note. What I'm really excited about and where we're expanding towards is what are all the things you can do before the conversation, during the conversation and after the conversation if you did have access to all the context about patients, payer guidelines, medical literature and put that together and to serve, how healthcare could look fundamentally different.Swyx [00:02:01]: And that's the context engine that you guys have?Chai [00:02:04]: Yes.Swyx [00:02:04]: Is that what it's called? Okay.Swyx [00:02:05]: So historically, as I understand it, the company started in 2018. A lot of people would be familiar with the AI voice notes form factor that doctors would be “Well, do you consent to being recorded?” It replaces handwriting and what have you. But it sounds like more recently there's been a big transition in the company. Tell me about the broader transition.From Documentation to Clinical Intelligence: Save Time, Save Money, Save LivesJanie [00:02:26]: So from a transition perspective, we really think about our journey as The first act was: how do we help save time? And that's where a lot of that original product was.Swyx [00:02:37]: By the way, one of those interesting statsSwyx [00:02:39]: On your landing page was, doctors spend time after hours.Janie [00:02:43]: They call it pajama time.Swyx [00:02:44]: Why is that pajama time?Janie [00:02:46]: Doctors after work in their pajamasSwyx [00:02:48]: In their pajamas. OhJanie [00:02:49]: At home are just writing and catching up on their notes every day.Janie [00:02:53]: Some of our favorite customer love stories, we have a Slack channel called Love Stories. We have clinicians telling us, “Abridge has helped us, from retiring early or we're now finally able toJanie [00:03:06]: go home and eat dinner with our kids for the first time.”Chai [00:03:08]: Save the marriage in some cases.Swyx [00:03:10]: One of the quotes was “We're not divorcing anymore.”Swyx [00:03:12]: I'm asking, “Why?”Swyx [00:03:14]: Because they're working too much.Janie [00:03:16]: But, in terms of where we're going and where we're expanding, we really think about our second and third acts around how do we help health systems save and make more money. Health systems are operating with record-low operating margins. It's getting harder and harder to serve patients and they have regulatory, some tailwinds but also a lot of headwinds coming their way and AI is ripe for helping on the saving and make-more-money piece. And then ultimately, how do we help save lives? The fact that our software and our product is open millions of times a week before, during and after a patient walks in the room, gives us massive opportunity with products like clinical decision support, which Chai is building but so many others to improve patient outcomes and probably one of the most important workflows and problems to be going after right now.From Glean to Healthcare: Context Is KingJacob [00:04:04]: One thing that's interesting, Chai, is you came over to Abridge from Glean and clinical decision support, which for our listeners is, in the context of a visit, helping a doctor figure out the right type of care. It's really a search problem in many ways, going through lots of different data sources. Very analogous to your previous role as one of the earliest engineers over at Glean. I'm sure a lot of our listeners are curious what's similar about the problems that you're going after now and what feels different, now that you're in healthcare.Chai [00:04:33]: Very similar. Taking a step back, with every wave, there's a lot of very similar patterns that happen across different products. A lot of social networking products look the same. A lot of credit-based products look the same. And we're seeing that very similar in the agent era with many companies, of course, in Redpoint's portfolio and so forth. And the key insight between both companies is that you have amazing models but context is king. Context is what puts them to work. So I see it in a lot of ways, a lot of similarities in this is a healthcare-coded version of Glean but the differences are really interesting. A couple things that come to mind. First and foremost, the rigor of the setting we're in. The downside risk is extremely high here in healthcare. It can be fatal in some cases. You prescribe something that the patient is allergic to for example. Whereas at Glean, it's “Oh, you got the question wrong.” It wasn't the end of the world in most cases. And so what does that mean? That shapes our evaluation strategy, both offline evaluation, progressive rollout and there's a lot more we could go into there. Second thing that comes to mind is, vertical versus horizontal. In both cases, there's a large variance but when Glean is, it's a much more horizontal company, there's a variance of personas, companies that you're working with. We also have a variance of personas, different types of specialties, different hospital systems. But the variance is a little more narrow. So from a product perspective, you're able to focus far more, especially when you have a maturing technology and you're building new products that never existed before. It lets you go after them much more easily and especially in healthcare where so many problems were solved with labor and process, that it's extremely ripe for AI to keep helping augment and enable. And the final thing that's really interesting, Abridge specifically compared to many other companies in the AI area, is the modality we started with where we're ambient and we're always listening in the background. And many more AI products will go that way but it's how we started. And that's the greatest form of AI we can create, AI that's seamless. You're not looking at your screen. It's always there. It's always helping you out and being proactive. The Jarvis vision that, every hackathon I went to over the past decade, there was always a Jarvis competitor. But Abridge very much started from the opportunity and continues to go that way.Ambient AI and Alert Fatigue: When Should the Product Interrupt?Jacob [00:06:57]: One thing that is super interesting then from a product perspective is you have this always-on seamless in the background and then you have to decide when you break the wall almost and say, “Hey, clinician, you might not have thought about X,” or whatever it is that you want to do. And in healthcare traditionally there's been this idea of alert fatigue and a million pop-ups and then a doctor just ignores all of them. It's probably a pattern that a lot of builders are thinking through now. How do you think about the right way to intervene or to pop up in a doctor visit?Janie [00:07:26]: It's such a good question. Alerts are notorious in healthcare specifically. Over 90% of alerts are ignored. The first and most important thing is context is everything, as Chai alluded to and I also think about how do we go from being reactive alerting to really proactive intelligence at the point at which it matters most. One thing we like to say is we want our product to feel like air conditioning. It should be in the background just making things better and if there is something that has great clinical risk and we're acutely aware that intervening now and not later is incredibly important, we should decide to act. But if you think about proactive versus reactive, instead of alerting a clinician during a visit when they're with their patient having a pretty serious and sensitive conversation, how do we prep a clinician before they walk into the room with that patient? And so historically, clinicians might have to manually go through charts with a patient that they've had over the course of months or years and they'll try to suss out what are the things they should be doing. You can imagine a world with Abridge. We'll summarize all of the most recent context for you, tell you based on the reason for a visit the patient is coming in for the types of things you should be discussing. And so you're going into that conversation prepped rather than walking in cold to that patient visit and then having this product interrupt you five or 10 times throughout the visit. And there might be times where it's really important to interrupt. We have a product called Prior Authorization and so this is when you may go into a doctor's office with knee pain. They'll prescribe you an MRI and so many of us have had this experience before, where in four weeks you'll get a call saying, “Hey, Sean, that MRI that you were prescribed wasn't approved and why don't you come back in? We'll figure it out.” In a world with Abridge, we might choose to quietly but still alert a doctor in that visit. And alert is probably not even the word we would want to use. Before a patient leaves, we would want to tell the doctor, “Hey, Doctor, before Sean leaves, you should ask him, has he had physical therapy and has his pain lasted for more than six weeks? Because the Aetna plan that he's on in California requires six things. We've already confirmed four of them have been met ‘cause we have all the context. But these two last criteria, if you can address with Sean before he leaves the room, we could guarantee that your MRI is approved before you leave.” And so when you think about clinical usefulness, impact to the patient, there are instances in which if we can catch a doctor while the patient is still in the room, as we think about save time, save money, save lives, we get to check all of those boxes. But when doctors have 15 minutes between visits, we have to be really thoughtful about when it matters.Prior Authorization: Reducing Latency in CareChai [00:10:23]: There's this interesting product opportunity AI has is reducing latency in the world. For example, prior authorization is an example of where care gets delayed and so great AI can reduce that. And the problem with alerts before partially is a technical problem: the quality of your alerts really matters. They're going to get ignored if you get alerts that... Similarly in engineering, where they're noisy alerts that you can't act on. But if you can make really high-quality alerts with both the context, as Janie said, and really high-quality models, then you can create a whole other game.Janie [00:10:53]: And I really like that experience because it starts to tease apart, what makes this so hard and unique. One, to make that prior authorization example possible, think about all the data that you need to have. You need to integrate with the electronic health record to know all of the patient context. Do we have access to your previous labs, previous imaging? And then to match you and to know that you're on Aetna, we have to collect all of the different payer policies and they vary by state. Some of these payer policies live on websites. Some of them live in unstructured 50-page PDF files.Jacob [00:11:31]: I thought this episode wasJacob [00:11:31]: To make sure we didn't scare people from healthcare.Janie [00:11:34]: But when you think about the things that make it hard, it also gives you the moat.Janie [00:11:39]: And then the second is the AI and the model quality we need to be able to hang our hat on. And so the bar, similarly when I worked at Opendoor, I worked on pricing models. Every outlier wiped out the margins of 30 and so similarly here in healthcare, the bar for accuracy is so high. And then I'd say the last is workflow is everything. If insurance companies deploy AI, it typically happens too late and this is when you have the notorious comical examples of AI just fighting each other when it's too late. But if we can pull forward the use of both the AI but also the ability to solve problems when the patient's in the room, you can start to collapse what typically takes weeks or months after your visit, ideally down to minutes or real-time. And it's where healthcare is both very difficult but also extremely rewarding if you can crack it.Product Form Factors: Mobile, Desktop, In-Room Devices, and ARSwyx [00:12:36]: Just to get some baseline on the form factors, because I've seen some videos on your website and stuff. You guys talk a lot about ambient AI. Is it primarily on the phone? Is there any other form factor that people get Abridge in? Is there an Abridge room setup where it's always on? I don't know.Jacob [00:12:55]: An Abridge podcast studio.Janie [00:12:58]: Primary form factor is mobile and desktop. UsuallyJanie [00:13:00]: Clinicians are walking in and out of rooms with mobile but at the end of the day, when they're closing out their notes or wanting to prep for the day ahead, they might use desktop. We have been having a lot of really interesting partnership conversations with a lot of these in-room device companies as you think about the power of multimodality and even more data, as you think about all of what is not captured today. It is fascinating to think about, especially even as we go into building and scaling our nursing product. It's one where nurses constantly, as they're walking in to check in on a patient for two minutes or maybe even 30 seconds,Janie [00:13:43]: Starting an Abridge experience is probably going to take longer than the visit. And so what can we do with in-room devices that are always on starts to raise really interesting and fun product questions.Swyx [00:13:54]: I was thinking, the way in tech companies we have all these Google MeetSwyx [00:13:58]: And other things, we might as well set up entire rooms with just Abridge tech.Chai [00:14:02]: Very much. AR glasses and related form factors are also relevant: how do we bring the information to the clinician in real-time without a screen, while still letting them focus on the patient?Swyx [00:14:18]: Do you think they want that? I'm skeptical of AR, but I'm curious what you've tried.Chai [00:14:26]: Admittedly, it's not a near-term product roadmapChai [00:14:29]: By any means. I'm being far-fetched.Jacob [00:14:31]: There's some sick AR stuff for surgeries.Swyx [00:14:33]: Really?Jacob [00:14:33]: When people are trying to visualize, you're about to make an incision but you want to see, what the cut might look or what the body might look like inside and they can layer in imaging.Swyx [00:14:43]: That's cool.Chai [00:14:45]: At some point in the future.Janie [00:14:46]: But there are a lot of our largest customers and at the largest health systems integrating already and so even as we think about building into it, unlocks a lot of product capabilities.Swyx [00:14:57]: And just to establish the terminology. Sorry, and I know I'm asking basic questions somewhat for myself but also for the audience who might beHealth Systems, Buyers, Clinicians, Patients, and PayersSwyx [00:15:05]: Less integrated. When you say health systems, it's like the Johns Hopkins, the Kaiser Permanentes.Janie [00:15:09]: Mayos, the Kaisers of the world.Swyx [00:15:10]: These are your customers, right? And the outcome that you deliver for them is happier doctors, reduced cost of processing, reduced mistakes. It's weird in a sense that I feel like there's also, a secondary customer, the customer of the customer and I don't know if you — do you think about it that way?Janie [00:15:28]: The other interesting and complex part of building product is we have our buyers, who are the chief medical information officersJanie [00:15:39]: The chief financial officers, the CIOs of these large health systems. Our users today are clinicians but if you think about who downstream is impacted, it's patients. And so as we build, with every product in mind, we think about who we're building for, who the secondary user is and what does that mean either in terms of experience, security compliance, ROI that we have to make tangible. And so like you said, time savings is one of them. But for CFOs, they care a lot more than just time savings. We have to show for every dollar you put into Abridge, because you have more compliant documentation or because you have fewer queries coming from your billing team, we save or add real dollars to your bottom line or top line, are things that we're constantly thinking about because of the dynamic across all three sets of users.Chai [00:16:32]: There's a whole other axis too with the payers and pharmaChai [00:16:35]: as well. Connecting all these three big stakeholders in healthcare isSwyx [00:16:39]: Do the payers ever see your data? Sorry, the payers meaning the insurers, right?Chai [00:16:44]: Yes.Swyx [00:16:44]: They also see Abridge data?Chai [00:16:47]: NoSwyx [00:16:47]: Like the direct integration to you guysChai [00:16:48]: They wouldn't see the raw Abridge data but when you're working together on something like prior authorization, whatever information they need, we'd communicate to them.Jacob [00:16:59]: That's cool. I would love to dig into the AI side. You still have a lot of problems on the AI side. And so maybe to start at the highest level, what's one of the hardest problems you have to solve in AI at Abridge today?The Hardest AI Problems: Quality, Latency, and CostChai [00:17:11]: To make things simple, let's take, building off the prior auth example. So one thing Janie talked about is okay, this data is all over the place and there's this combinatorial explosion of procedures, payer policies and even sometimes different health systems. There can be some cross-product of all of these different considerations you have to take into account. But what's really hard about this problem is doing it real-time in the conversation. So, in any AI product, usually the three KPIs you care about are quality, latency and cost. Now, what we're saying is we want you to do this real-time in the conversation, guiding the clinician. How do we do it in a way that does not break the bank? But we're using — But we also need very intelligent models because you're working with this cross-product of data and this, all this context layer as well. So you need high intelligence and high-quality because you don't want the alert fatigue but you also need to be fast and cost-effective. And so that's where a lot of clever engineering goes. It's okay, without getting into all the details here, can you model these policies in some intermediate representation or other things that you can do that can make this problem tractable? And of course, the Pareto frontier is always changing but we are also trying to do this now.Model Strategy: Third-Party Models, Proprietary Data, and Medical ConversationsJacob [00:18:26]: What implications has that had for what you take off-the-shelf and say, “ what? We don't need to be world-class at X. We'll just take this from the model providers or from some infrastructure player,” and what you're “No, this is where we spend most of our time focused on”?Chai [00:18:38]: This is, the fun challenge in AI?Jacob [00:18:42]: It changes every three months? SoChai [00:18:42]: Of course, with the shifting landscape, we try to be extremely thoughtful on predicting the trends of where third-party models are going and where we can uniquely go. And, sometimes when you talk about AI models, we're the models are just going to get infinitely better. But I don't think... It may be in the grandness of time you could say that but, within every month, every quarter, there's specific ways they're getting better. They're training on a lot more, coding data to be better coding agents, for example. And soChai [00:19:14]: We have to think about where are the things that won't — unique data that we're uniquely training on or to step back a little, where is a proprietary model bringing advantage to us is if it can give higher quality or lower cost and latency for similar quality, very similar to many other companies. And when we can do that is when we have proprietary data. So, for example, we have on the order of eighty million or hundreds of millions now getting close to of medical conversations.Jacob [00:19:44]: It's insane.Chai [00:19:45]: This is a unique data set. And this data set, it's very interesting because this data set is effectively a large part of the trace between the patient and the provider. That's where the quote-unquote debugging happens in healthcare. We have these traces at scale, as in as, our CEOs even called it, an exhaust that comes out of our product. And so when you have these traces, that's how you can train better agents on certain use cases, whether it's your transcription diarization use cases or so on or like note generation models and we can do that much cheaper and faster. But we're always also working with these third-party model providers. We closely collaborate with them and that's how we predict where the trends are going. The thing that I think about a lot is that, I know that the model providers are going to train much more on agentic workflows and so forth, so that's great, so that you have a better agentic harness. But the other thing that's interesting is that the model providers, because a large class of the consumer model providers is healthcare queries, that they might, optimize to train a lot of healthcare data to encode the knowledge in its weights. And this is just a great thing for us as well, where the off-the-shelf models can keep bett-getting better at general healthcare information, such that what our strategy is, we have a constellation of models, we can use something for this, that and, we only care about, at the end of the day, the best product experience.EHR as File System: Agentic Workflows and Real-Time InterfacesJacob [00:21:07]: And, you have, overall capabilities improving. I'm curious, as these models get better, is there something you look at and you're “, three months ago, we really couldn't do that but God, the the latest models really allow us to do it”?Chai [00:21:19]: So here's something interesting that I've, been toying with. So all models are... This wasn't super obvious a year ago but now it's become clear and clear that almost every agent is a coding agent underneath the hood? So you give it whatever file system, it can write its own code and so forth. So when you think about within healthcare and the use case that we have, you can think of the EHR effectively like a file system. It's just — it's a storage of all this information. It's a lot of information there that cannot fit into the context window, at least of today's models and you want to use that context effectively for all these product use cases we're talking about. And so if you have better agents that can, manipulate data, read that data, treat it as a file system as we see they're going and we know model companies are investing this way, then that very directly benefits us.Swyx [00:22:09]: Yeah. Okay, cool. Again, just establishing basic things. But we're going back to the model stuff. I'm really interested in double-clicking more on the real-time, element, which is pretty important for both of you. Is it — Is real-time just batches of every one minute, every five minutes? Is that how we do it? Or is there some more native, genuinely real-time in the sense that OpenAI has a real-time API or Gemini has a real-time API?Chai [00:22:35]: Yeah. Yeah. So today it is more on the on the batch basis but there's interestingChai [00:22:41]: Prototypes that we have that we're still not fully, full time, voice in text out or in that sense. But, can you trigger your models, your agents or agentic workflows, depending on the right times in the conversation?Chai [00:22:58]: And so you can imagine, different techniques to bring this latency down and, you want to bring the feedback loop down as much as you can. And so a lot of clever engineering there without fully... Maybe one day we'll do full voice in and text out, train a model to do something like that.Swyx [00:23:15]: You do — People don't want voice in voice out?Chai [00:23:18]: Now we aren't creating experiences that are, during the conversation, inter — It's almost likeSwyx [00:23:25]: Might be too disruptiveChai [00:23:26]: Too disruptive until, who knows, maybe eventually you could have full voice agents once we — the quality and we improve the comfort of the technology. But right now gra — that change is much more gradual and it's more text focus, text out.Janie [00:23:42]: And so much of currently what our product is trying to do is allow a clinician to focus on their patient and maybe at some point but right now patients, clinicians don't want a third voice, at least in a literal voice in that room. And so how do we be there with all the contacts and information ready at hand when there's the right moment?Personalization: Individual Doctors, Specialties, and Health SystemsJacob [00:24:03]: Jenny, one thing I'm curious about is how you think about, personalization in the product. I imagine, every doctor is a special snowflake in their own way, has their own way they like to do things. There are probably a bunch of different approaches you could take to doing that, both within the model layer itself but then also just with clever prompting or engineering. How do youJacob [00:24:20]: Deliver on that?Janie [00:24:21]: It's such a good question. Personalization is massive for us. We think about personalization at three levels. The first is at the individual, the second is at the specialty level and then the third is at the health system or the organization level. To your point, there are a lot of individual preferences. You-When a note is produced, it almost is a reflection that is so deeply personal of a doctor's work and how they give care. And so do they have preferences on things like style? They might want bullets versus paragraphs, really concise versus comprehensive. They also might have phrases that they really like to use or the templates that they want every note to be structured. And, we see it in our feedback all the time. We want two spaces in between sentences or I refuse to use this tool. And so that's something that we've had to build in. And the tricky part is how do you make sure that stylistic preferences don't interrupt accuracy and quality and that's something that we've really had to refine and hone over time. Second is at the specialty level. A cardiologist note or workflow is going to look very different from a dermatologist workflow.Jacob [00:25:32]: I assume cardiology notes are the highest stakes for you guys, given your CEO is a cardiologist.Jacob [00:25:36]: It's “Oh my God, make sure we get this one.”Janie [00:25:37]: Shiv, our CEO, is still a practicing cardiologist. He rounds once a month. And so, first call when we want just quick and easy user feedback too.Janie [00:25:46]: But, specialties require a lot of personalization, both in terms of what does the product look and so we make sure that as new users onboard, we catch that and the product proportionally reflects that. But also on the back end, evals at the specialty level, they are hard-earned to calibrate and get. What does a really great dermatology note look like? What makes it complete? What makes it compliant and billable is very different than a primary care doctor. And so it's not just about what does the product experience look but on the back end tuning and really deepening our understanding for the specialists. What does great output look like? And that's, a problem that we need to calibrate internally, externally, online, offline but, takes lots of cycles but is necessary in a high-stakes environment. And then at the health system level, for products like clinical decision support, you have health systems who've spent years or decades refining their best practices and they want to know, “Hey, we love your clinical decision support product but how do we embed our own hospital guidelines into them to inform clinicians before, during or after a visit what brest — best practices should look like?” And as you think about, deepening moats as well, when health systems, trust us with that data, allow us to productize it and directly into the clinical workflow, makes us a really great partner to health systems who want to build something that truly meets their needs, their practicing guidelines.AI Slop, Memory, and Product Data FlywheelsChai [00:27:23]: And I want to add onto that. The for the clinical documentation problem, it's very similar to AI writing that doesn't feel like your own and then we call that slop. But the way I describe one framing of slop is like AI without context. But we have all that context and both the clinicians, can have it and can guide it. And so part of the other interesting exhaust for us is, memory is, one of these new systems recordsChai [00:27:49]: Almost.Janie [00:27:50]: And we also have all the edits people make on our product and when you think about a data flywheel and how we get better over time becomes really powerful as a mechanism to just going deeper in personalization.Jacob [00:28:04]: It's interesting. I love this idea of working with systems on the guidelines they built up over a long time. I feel like so many of the best AI app companies today are... The question is: How do you take the expertise that a law firm or a bank has built up over many years and then add that as context and also a special sauce over, a an AI tool? And so seems like y'all are really doing that very effectively.Janie [00:28:24]: We're now starting to have our customers ask, “What are other customers doing?”Janie [00:28:28]: “And how are they doing it?”Janie [00:28:30]: And as we think about having visibility across such a large set of care being delivered right now, a really interesting place we could also partner.Swyx [00:28:40]: I'm just curious. I — This may be a nothing question but, how different are health system guidelines from each other? Don't they all converge to the same thing? And if not, where do they differ?Chai [00:28:52]: At a really high level, they're going to talk about very similar things but the difference is probably in some more of the details. “Oh, you should refer to specialists only when XYZ conditions are met,” or so forth and maybe different organizations have different practices and guidelines around that. But high level, talking about similar things but the details are what, of course, that shapes the context and the decisions you make.Swyx [00:29:15]: And this all goes into the context engine and it might affect the notes but maybe not.Chai [00:29:21]: The — For these local pathways, we're definitely thinking about it a little more for our clinical decision support product.Chai [00:29:26]: So yeah.Swyx [00:29:27]: Which is your stuff, yeah.Swyx [00:29:28]: And then the memory which you raised, let's just tell us more about that. What have you tried in memory? What's the structure of the memory? What works? What doesn't work?Chai [00:29:38]: There's, of course, many different ways you could do memory, where it's okay, can you bake it into the model weights or can you do it in some external store? For us, what's interesting is, of course, when you think the models are rapidly changing, whether it's in-house or third-party, baking into the model weights, sometimes you worry that it could be a little throwaway. And so, how do you... You need to find a way that you decompose the problem, the preferences from the underlying models and so forth. The thing we're right now most both that's easiest to start with and we're excited about is having, a separate store for memory, where you have, for example, a memory sub-agent that's, working in the background, figuring out what are the important parts of the clinician's actions that we want to remember for the long term. And then you can also imagine, other things where in the — you have background jobs that are running that are collating these, memories similar to Sleep, of course and what other pattern, patterns products do as well. Learning over all these action, all the action data we have, again, note edits, the conversations they did and the actual transcripts.Evals: LFD, LLM Judges, and Clinical SafetyJacob [00:30:40]: What about evals? How in the world do you... It is such a complex product surface area. We would love to hear you riff on that and also how has that evolved? I'm sure you've gotten better at it, so any learnings along the way.Janie [00:30:50]: From an evals perspective, we, from day one when we build any new product or feature, we think about, what does good look like? And there are table stakes things like clinical safety but then you start to get deeper into what does good quality look like. And when you go into something like our core product, there's stuff like style and completeness and there's things like does this note become something that can be billable, which is very high stakes for a health system. We have a number of ways in which we get confidence for this. We have, internal in-house clinicians who do what we call an LFD process to give us our very first pass at is this or isn't this a good enough output, look at the effing data.Jacob [00:31:41]: LFD?Chai [00:31:42]: That's why I was smiling. I was “Is Janie going to mention what it stands for?”Jacob [00:31:46]: I was not... There's like a million acronyms.Jacob [00:31:48]: How am I supposed to know that I don't? So “Oh yeah, of course, an LFD.”Swyx [00:31:51]: I've never heard of LFDs.Chai [00:31:53]: It's a bridge for sure.Janie [00:31:55]: I got through three days and then I had to ask someone.Janie [00:31:58]: I thought it was just me that didn't knowJanie [00:32:01]: It's our internal process.Swyx [00:32:02]: But look at the data as a meme in ML, ‘cause you tend to not look at it. You just want to look at number go up.Chai [00:32:06]: Exactly.Swyx [00:32:07]: But yes.Janie [00:32:08]: But so, we make sure we look at the data and then as we think about all of the components of good output, we, one, create LLM judges across all of these and we make sure with annotated data and either internal or external evaluators, we feel like these judges are calibrated. And then depending on the stakes, we also work with in-house and third-party evaluators across all of these before we ship any big change. And the goal is, in terms of evolution, how do you go from this process taking months, down to weeks, down to days? Some of it is, a true science and ML problem. A lot of it's also just, hard operational work. Have you planned ahead in terms of what you need? Have you really optimized the capacity that you need across all of the different specialties you need? Have you gotten a really good sense of which third parties are great to work with for what use cases? This takes a lot of domain, expertise and, lots of mistakes and errors in figuring that out. And so as much of it is an ML problem, so much of it has also been operational gains that are hugely important, where domain-specific expertise is everything.Specialty-Level Evaluation and Progressive RolloutsJacob [00:33:23]: But it's funny, ‘cause I feel like people talk about healthcare like it's one giant market and the reality isJacob [00:33:26]: It's, dozens and dozens of sub-markets. And so it feels like in your evals you have to build that up across the board, probably.Swyx [00:33:34]: And is specialization the primary cardinality at... That's the word that comes to mind.Janie [00:33:40]: Sometimes, depending on the product or the use case. And so if we're making a note improvement or feature for a particular specialty, definitely but we have products that are for nurses. We have products that, are really aimed at making the document or the output a lot more billable. And so we'll want to work with coding teams and not necessary clinicians. And so likeJacob [00:34:05]: Coding meaning healthcare coding.Janie [00:34:06]: Yes. Yes.Jacob [00:34:07]: NotChai [00:34:07]: Yes. I see you.Swyx [00:34:07]: Other kinds.Janie [00:34:09]: But is this output proportional to the work that was delivered? Is there sufficient documentation to justify the amount that a health system may end up charging? And so, specialty sometimes but also domain, very different across all of the different products that we're working for. And building out that network is, not easy and is where a lot of our operational investments have gone into.Chai [00:34:35]: And I view a lot of analogies to self-driving cars here, where, part of it is we really want progressive rollout of features to test in the real world is this useful? Is this going to work? One big difference compared to past lives is before I'd build a product, maybe I'd alpha it and then I'd like GA it the next week, ‘cause I'm “Go, move fast, ship,” and whatnot. But the mentality is like you... I want to make contact with the reality as quick as possible but I want a progressive rollout. Because as much as I get as large of an offline eval set, I want the distribution of that to match real-life distribution. And over time, by rolling out early, similar to Waymo has a tagline, “The world's most experienced driver,” another thing that can, at least linearly increase for us is, both the size of our evaluation offline and online, that and it all feeds back.Janie [00:35:25]: Something that's been earned over time, speaking of evolution, is just the trust we've gotten with customers. Historically, a lot of these health systems, when they bring on new vendors, their release cycles are quarters, sometimes twice a year. We've gotten our customers onto monthly release cycles, which is pretty fast for health systems but what is more exciting over the last, call it, few quarters, has been, a subset of our customers have said, “We want to innovate with you. We trust you,” and we have a pretty, decent chunk of our customers who say, “We'll develop with you outside of these monthly release cycles. We have a higher tolerance. We know that the stakes are very high but we want to be the first ones using these products, giving you feedback.” And so for a pretty substantial set of our customers, we've been able to convince them to be able to ship, in this gradual way before GA. Something we talk about a lot internally is, trust is earned in drops, earned in buckets and so we still can't do what I used to do when I worked at Loom. We had 30 million users. I'd just be, rolling out experiments left and. The bar is still quite high for iterative rollout but because of the trust we've earned, we're able to learn at pretty high volume very quickly.Privacy, HIPAA, and De-IdentificationSwyx [00:36:45]: Your scale is still pretty huge.Swyx [00:36:47]: One thing I want to... We were going to go into scale? In a sec. One thing I wanted to call up, follow up on evals, which, again, just coming from a generalist engineer point of view, just thinking through what would people be scared of in doing this, the privacy and HIPAAJacob [00:37:00]: Elements of this. I have zero experience in that. What do you have to do? What is surprisingly not that bad?Chai [00:37:06]: So one thing that's really important here from a compliance perspective is very much that any of the data we use needs to be de-identified, any real-world data we use as a basis of online eval sets we're learning from. And so you have to — And there's, very clear, government guidelines, what counts as PHI. And so we've even have built models that can take, for example, a clinical transcript and remove all the key PHI indicators and so you have a scrubbed/de-identified version. And then once you... And so one thing that's important is first you've got to get confidence in that model in the first place? And prove that out. Because, now you have, multiple probabilistic systems on top of each other.Chai [00:37:46]: But once you have that, then you can train on it use it for evaluation and so forth, provided one of the cool things also that you can do from a business side is the right data contracting as well with your partners.Jacob [00:37:57]: Is the anonymization one way? Once it's done, you cannot undo it? Or is there someoneChai [00:38:01]: YesJacob [00:38:02]: Who holds the master key that can... Yeah, okay. So it's one way.Chai [00:38:05]: It's one way. Yeah.Jacob [00:38:06]: That's how it works. I just wanted to... Because, there's a lot of this, learning from feedback and everything that, you would want to debug more but you can't because you just physically don't allow yourself to.Janie [00:38:17]: Some of it's also written in our customer contracts in terms of who can or can't access PHI data, how long do we retain it,Jacob [00:38:27]: Very goodJanie [00:38:27]: Before it gets de-identified. And so we have a pretty high bar for who can access that PHI data, just to make sure that we always respect our customer data and privacy. But that's something that we partner with our customers on too, to make sure that as we want full, as close to precision as possible in that qualityJanie [00:38:48]: We can still use it.Jacob [00:38:50]: But it'll be fascinating to see how that space evolves? Because you think about, I used to work at a company that, did a lot of healthcare data in the cancer space and if you asked, the average cancer patient, “Hey, do you want people, do you want other patients to be able to learn-”Chai [00:39:03]: Take it.Jacob [00:39:03]: “... Learn from your experience?”Chai [00:39:04]: Take it all.Jacob [00:39:05]: They're “Please.”Jacob [00:39:06]: “I'd love, nothing more than for other people to be able to learn fromJacob [00:39:10]: The experience that I had.” And so in the past it was a lot harder to do that learning. But with this technology, that might really be practical and so it'll be fascinating to see how that continues to evolve.Chai [00:39:21]: There's so much in our data set of 100 million conversations.Chai [00:39:26]: You can imagine things like insights that you can give to the clinician. How could you, oh, how could you have reacted to this? In coaching or insights around, which treatments are effective or, like... Because you have this, again, this data source that was never captured before but that's, where, intuition or experience is created from, going back to this idea that the conversation is the agent of truth.Operating at Scale: Reliability, Cost, and Token EfficiencyJacob [00:39:46]: Back to the 100 million conversations, I feel like you have this insane scale that maybe only a few other AI app companies have and everyone else dreams of. So not everyone has had to confront this yet but maybe just talk about some of the challenges of operating at that scale and what, our listeners have to look forward to if they ever get to this level of scale.Chai [00:40:05]: At large and larger in scale, so of course there's a general, infrastructure reliability. When you... In any given startup, you're building the plane while it's flying. So there's some notion of that. But what gets interesting on the AI and ML side for sure is this, as you get at more and more scale, so one, you have the data to first and foremost do this. But, you start thinking about costs or infrastructure in a whole different way at scale versus, a prototype.Chai [00:40:34]: You can use the most expensive model, you can burn as many tokens as you want but when you're doing 100 million conversationsJacob [00:40:41]: Token max on leaderboards are less upsetting than that context.Chai [00:40:45]: . When you're doing that and so that comes for we have the data and we also have the team that's able to post-train based on this and you can optimize for efficiency, especially in areas where you believe that maybe a lot of the quality headroom is less so and you don't expect the other off-the-shelf models to go that way, such that you want to do, efficiency maximization, in terms of compute and tokens.Jacob [00:41:08]: I feel like you guys live in the future in some way where most use cases today are really just in use case discovery mode, where it's “God, I really hope I can find something that can get to scale,” and so you're always going to use the most powerful model. And then the few things that do get to this level of scale, you start to do those optimizations.Chai [00:41:22]: It's a natural trajectory where it's like zero-to-one, we're not talking about any of these optimizations.Chai [00:41:26]: But when maybe we're in the one-to-100 or so forth, then we're in optimization mode and, what works out really well is you've got all this data from zero-to-one that lets you do this.What Comes Next: The Conversation as the Shared Healthcare PlatformJacob [00:41:36]: That's fascinating. I feel like one thing that's so interesting about the Abridge footprint is that you're in the doctor-patient visit in real-time. I always like to say, there's like probably 50 years' worth of product you could build on top of that. What gets each of you, I don't know, what are you most excited about building, either in the short term or medium term or even, long down the line?Janie [00:41:53]: Something that I get really excited about is that the same conversation can serve so many stakeholders. If you think about the conversation, a doctor needs to know what is the documentation, how do I make sure that this fully represent the care I gave? A patient needs to know, “What the heck just happened? This was really overwhelming. What are my next steps?” A payer needs to know, was this the proper and appropriate care given? A pharma company might want to know why isn't this drug being properly used or is there a good candidate for this clinical trial that I'm about to run? And where I get excited is that our product and our platform and our infrastructure can be the same product across all of those things and start to what's today, separate, very expensive, complex systems that serve each one of these stakeholders in very different ways, start to collapse all of that into a singular platform that enables not just more efficiency across the board but also better outcomes for everyone. And, all of us experience healthcare in probably very painful ways and knowing that there is a world in which we can simplify a lot is really exciting to me and it all starts with the conversation.Chai [00:43:15]: It's interesting. Of it very similar to going back to the KPIs that any AI product cares about. How do you increase quality of care? How do you reduce latency to care? And how do you reduce costs? Which is a huge, in healthcareJacob [00:43:28]: They call it the triple aim in healthcare.Chai [00:43:30]: But very similar to building AI products and the thing that really excites me is when we talk about that latency piece, we talked about one example earlier of prior authorization, can you reduce the latency to care? But you can imagine so much more. Oh, as soon as the lab value gets updated, do you have like a background agent that, kicks off and uses all the context to be “Oh, hey, the patient should do this next,” for example. And of flagging that to the clinician who's always in the loop but reducing that latency, to care. And then you can imagine this is much further down the road but it's like even connecting that to the direct patient and the consumer. And so how can you, how can you build a bridge to all of these things?EHR Partnerships and the Clinical Intelligence LayerJacob [00:44:10]: Very cool. The connections piece is just an ever-growing thing. And one of the key partners is the EHR and I wonder what that relationship is like. Will they, look at this as, something that is valuable enough that they want to own someday?Janie [00:44:29]: Our partnerships with the EHR is, we know that we have to be extremely close partners with all the EHRs who we partner with. Being able to not only pull and push all of the data into the right places is, not only table stakes, if we can't do that, health systems don't want to use us. The second and the reality of today is clinicians spend a lot of their days in the EHR. So much of what allowed us to win in the largest health systems was pretty direct and, very close partnerships with some of the largest electronic health records that allowed us to pull and push data with APIs that weren't ready out of the box. And clinicians want to save clicks. Anytime we introduce a new product that, adds two clicks for them in their day, they're “We're not going to use it.”Janie [00:45:21]: They have 15-minute back-to-back appointments with their patients. They're spending, hours during pajama time doing documentation. Every second and every minute counts and so we really think about being deeply integrated into the EHR as also table stakes to getting real usage and adoption. And anything that we build or introduce, we really talk about earn the right internally a lot, which is we have to provide so much value or save so much time that people will use us. But those are the two things that are close to us, is we know that the product won't be used unless it is deeply interoperable.Chai [00:46:01]: And strategically, to your point, it's like what does EHR want to own versus us? EHRs are really focused on the clinical workflows and so forth but some of the things that we're talking about here, I do these traditionally are outside of the domain where it's oh, connecting pairs and providers together with provider policies or the clinical trial matching, as Janie brought up. And so these are, entirely — we position ourselves as building this entirely new intelligence, clinical intelligence layer across, again, providers, pharma and, payers.Chai [00:46:33]: And so that's a it's a whole different ballgame that we try to playChai [00:46:36]: In combination with them.Jacob [00:46:37]: But it's like a different layer of scope.Healthcare AI Regulation, Technical Depth, and What Changed Their MindsJacob [00:46:39]: I'm curious, you are both relatively newcomers to healthcare. People have these, there's lots of futuristic healthcare AI takes of “Oh, everything will look different.”, now that you've been in healthcare for a bit, you live at the edge of AI, what have you, changed your mind on around this, as you think about what healthcare looks like in ten, 20 years? Any updates to your mental model from the time being close to the problems?Chai [00:47:02]: One thing that IChai [00:47:04]: Was hesitant about before and it's a common thing when I'm trying to recruit engineers that people ask me around, is definitely oh, healthcare, heavily regulated space. And it is, rightfully so. You want to keep, the patients at the end of the day safe. But one of the interesting things that, is a that surprised me how much it is coming to the company is there's a lot of really favorable regulatory tailwinds as well. Where you think about, government really wants interoperability between all these systems that we talked about and so agents can access this information. The government just in January, the FDA released updated guidance on clinical decision support, what I work on in such a way that they used to have guidance from like 2022 that required you to have, mention all these options and do all these other things but it's a very forward and forward-looking way. And so for me, what's been really cool to work on is this, there's this very special moment both in AI in general, we all know that but there's a special moment also regulatory in healthcare as well.Janie [00:48:05]: One thing I would call out is for the very reasons things are higher stakes or, potentially considered more difficult in healthcare, it's where some of the hardest AI problems will get solved first, just because the bar is so high. When I first joined, I was “Oh, this is where we'll be on the tail end of where, all of the AI innovation will be able to be applied.” But when you think about, zero error evals or multi-step workflows that have really low tolerance, a lot of the innovation will happen here just because we have to or else we can't ship.Jacob [00:48:42]: ‘Cause like in other domains, you'd much rather just solve the 80%-is-good-enough problems firstJanie [00:48:46]: 80/20 doesn't work hereChai [00:48:48]: And building off that, traditionally, there was a bit of stigma that, oh, healthcare companies are not that interesting from a technical perspective or I've seen that or faced that myself. But these are really hard and fun problems from a pure technical perspective beyond just the impact. How do you bring the latency of this thing down and make it really high-quality?Reducing Latency: Clinical Workflows, Agents, and Implementation RealityJacob [00:49:07]: How do you bring the latency of things down?Chai [00:49:10]: Yeah. Yeah. Yeah. So okay, let's answer the latency question. And maybe hopefully not too redundant with some of the things I've said earlier but some part of it is with any latency, you have to like what is, what is really your bottleneck. In a lot of workflows, it's sometimes it's the model itself. And so that's where like our data flywheel, our post-training team and so forth come in so that can you make the models far more efficient. So that's one aspect of latency. But there's whole other aspects of latency where it's okay, on top of that, if you use a constellation of different models, can you use — can you first use like a — it's like thinking fast and slow. Can you use a cheap, fast model that triages and hands it off to a larger model where you get more intelligence and so forth and so all theseChai [00:49:56]: Clever tricks to make it work.Chai [00:49:58]: And by the way, we are totally — we also realize that the parameter frontier is changing and so these tricks will — may not get us to where we want to be in five years but we need to if we want to build a useful product right now.Jacob [00:50:11]: Should we go to the quick-fire or you want to ask more about Abridge? We can stuff everything that's not Abridge into the quick-fireSwyx [00:50:16]: I don't mind. I was — I feel like Janie was on the topic of more long tail stuff, which isSwyx [00:50:21]: Not the eighty/twenty thing and that really matters. And I'll —, if you have any tips or cool stories or just general approaches that have worked for you that's interesting to dig into.Janie [00:50:32]: One of them is even just how we staff our teams looks different than a traditional software engineering team, I'd say.Swyx [00:50:40]: Let's go.Clinician Scientists, Edge Cases, and Evals at ScaleJanie [00:50:41]: We have a bunch of folks with different roles who are clinicians and so we have this role called the clinician scientist and I heard one of our leaders refer to them as mutants recently. But they are people who've had clinical backgrounds, so MDs typically, who are also deeply technical, somewhere, on the spectrum of like a full stack engineer all the way to like extremely scrappy prompter. But having each of these people embedded within our teams instantly raises the bar for everything that we build because not only are they determining, is this product clinically useful but they're deeply embedded in our whole evals process. And so when we talk about LFDs, when we talk about what is our actual evaluation criteria, you don't want Chai or me creating what those are because we don't have clinical background. But is probably unique to Abridge but has been game changing. And when you think about where the puck is going, you have people build with clinical backgrounds who are technical and where AI tools are going, they just becomeJanie [00:51:53]: More and more, critical and like the killers of the team. And so that's one. And then the second is just the scale at which we do evals to catch that long tail up front before anything ever gets into production is something that we've pretty much like really started to fine-tune, both from a scale but when do we know we need to get several hundred versus several thousand offline responses, what helps us make that quick decision and make this less of an art and as much of a science as possible. But that's also been something we've had to tune over time.Swyx [00:52:27]: And you have partners who opted in to give you those evals.Janie [00:52:31]: So we work either internally or with third-party for offline evals and then we have customers who also agree to give us, whether it's like thumbs up, thumbs down to like choose this or that, a lot of data to get us to what is as close to fully confident as possible.Swyx [00:52:51]: The term that comes to mind isSwyx [00:52:53]: Like active learning on things where you're weak. I feel like it's a lost artSwyx [00:52:58]: Is a lot of the polish that comes into doing something like this.Janie [00:53:02]: Really.Chai [00:53:03]: Hundred percent.Lessons from Glean: Technical Foundations and AI App InfrastructureJacob [00:53:04]: Maybe, on a totally unrelated note, Chai, you had a very, storied run at Glean b

The first 17 minutes of this episode are free! Subscribe to our Patreon to hear the full pod.We're back with our weekly one on one pod to discuss spring weather, the Loveless patio, people pretending to work at cafes, Que Ling Restaurant, La Salumeria, Kaisers, Cootie Catcher at Low Bar, house shows, 107 Shaw, Tim Mcready's NXNE parties, Angel Dust at Danforth United, Cock Sparrer, Graham Hunt, Amigo's bar, Goldeneye 007, DJing with Martyn Bootyspoon, Dannys Next Door, the Mile End Kicks trailer and much more!Josh McIntyreNick Marian----COLD POD

Meeting-Marathons, Deadlines und schwierige Kollegen: Der moderne Arbeitsalltag gleicht oft einem Schlachtfeld. Doch wie wäre es, wenn du inmitten des Chaos die Ruhe eines römischen Kaisers bewahren könntest? In dieser Folge tauchen wir tief in die Welt des Stoizismus ein. Du erfährst, warum die Lehren von Mark Aurel und Epiktet über 2.000 Jahre später die ultimative Lösung gegen Burnout und Überforderung im Job sind. Hör auf, dich von deinen Umständen kontrollieren zu lassen, und werde zum Gestalter deiner eigenen Gelassenheit. Vertiefe dein Wissen: Du möchtest stoische Gelassenheit zu deiner Superkraft im Beruf machen? In meinem Hörbuch „Der Stoizismus-Hack für den Berufsalltag“ erfährst du alles über die praktischen Strategien von Mark Aurel und Epiktet für deinen Gamechanger im Alltag. Du findest den Titel ab Februar 2026 überall da, wo es Hörbücher gibt. Aber vielleicht möchtest du auch gleich mit mir sprechen. Dann kannst du dich hier für ein kostenloses Beratungsgespräch anmelden: https://lemper-pychlau.youcanbook.me Kontakt: info@lemper-pychlau.de

Im Auftrag des Kaisers macht er Paris heller, weiter, kontrollierbarer. Als rücksichtsloser Stadterneuerer. Am 11.1.1891 stirbt Georges-Eugène Haussmann. Von Andrea Klasen.

Meeting-Marathons, Deadlines und schwierige Kollegen: Der moderne Arbeitsalltag gleicht oft einem Schlachtfeld. Doch wie wäre es, wenn du inmitten des Chaos die Ruhe eines römischen Kaisers bewahren könntest? In dieser Folge tauchen wir tief in die Welt des Stoizismus ein. Du erfährst, warum die Lehren von Mark Aurel und Epiktet über 2.000 Jahre später die ultimative Lösung gegen Burnout und Überforderung im Job sind. Hör auf, dich von deinen Umständen kontrollieren zu lassen, und werde zum Gestalter deiner eigenen Gelassenheit. Vertiefe dein Wissen: Du möchtest stoische Gelassenheit zu deiner Superkraft im Beruf machen? In meinem Hörbuch „Der Stoizismus-Hack für den Berufsalltag“ erfährst du alles über die praktischen Strategien von Mark Aurel und Epiktet für deinen Gamechanger im Alltag. Du findest den Titel ab Februar 2026 überall da, wo es Hörbücher gibt. Aber vielleicht möchtest du auch gleich mit mir sprechen. Dann kannst du dich hier für ein kostenloses Beratungsgespräch anmelden: https://lemper-pychlau.youcanbook.me Kontakt: info@lemper-pychlau.de

Das Burgtheater in Wien ist mehr als eine Bühne. Es ist ein Mythos, ein Ort der Selbstvergewisserung der Habsburgermonarchie – und der Beginn einer der ungewöhnlichsten Beziehungen der österreichischen Geschichte.In dieser Folge von Habsburg to go! reisen wir nach Wien an die Ringstraße, ins 1888 eröffnete Burgtheater, die Hofbühne der Habsburger. Hier begegnet Kaiser Franz Joseph einer Frau, die sein Leben nachhaltig verändern wird: Katharina Schratt.Geboren 1853 in Baden bei Wien, wird Schratt zur gefeierten Schauspielerin des Burgtheaters – nicht als Diva, sondern als kluge, präzise und außergewöhnlich moderne Künstlerin. Ihre Spielweise ist leise, menschlich, unpathetisch. Und genau das fasziniert den Kaiser.Was zwischen Franz Joseph und Katharina Schratt entsteht, ist keine Affäre, sondern eine tiefe, vertrauensvolle Freundschaft. Eine Verbindung, die dem Kaiser etwas gibt, das ihm sonst fehlt: Normalität, Zuhören, emotionale Entlastung.Bemerkenswert: Kaiserin Elisabeth (Sisi) erkennt diese Konstellation früh – und fördert sie bewusst. Ohne Eifersucht. Ohne Skandal.Die Treffen sind offen, nicht heimlich: Spaziergänge in Schönbrunn, Aufenthalte in Bad Ischl, Gespräche fernab von Politik und Macht. Katharina Schratt nimmt keinen Einfluss, stellt keine Forderungen, bleibt diskret – auch nach dem Tod des Kaisers 1916.Und genau darin liegt ihre Größe: Keine Memoiren. Keine Enthüllungen. Kein Kapital aus der Nähe zur Macht. Stattdessen Rückzug, Würde und Stille bis zu ihrem Tod 1940 in Wien. +++

Böses, kleines Gedicht gegen die Alimentierung des geflohenen deutschen Kaisers durch die Weimarer Republik (Weltbühne, 1.12.1925).

Im November 2025 wurde bekannt, dass ein Teil der Juwelen des österreichischen Kaiserhauses in Kanada wieder aufgetaucht sind. Anlassbezogen beschäftigen wir uns daher in dieser Folge mit der Geschichte der Schatzkammer in der Wiener Hofburg, mit den Stücken, die darin aufbewahrt und zu sehen sind: darunter ein Erzherzoghut und die Reichinsignien des Kaisers des Heiligen Römischen Reichs Deutscher Nation und die Rudolfskrone, die 1804 österreichische Kaiserkrone wurde.

Gedanken zum Evangelium von Kardinal Christoph Schönborn, am 23. November 2025Lk 23,35b-43Im Gespräch zwischen Pontius Pilatus und Jesus geht es um die großen Fragen: Was ist Macht? Was ist Wahrheit? Woher kommt die Macht? Wer gibt sie? Wozu dient sie? Jesus steht als Gefangener vor Pilatus, dem Vertreter des mächtigsten Herrschers der damaligen Welt, des Kaisers von Rom. Jesus ist angeklagt.

Die Schmuckstücke haben eine Debatte über die Bedeutung des Kaiserhauses für die österreichische Identität ausgelöst - und das mehr als hundert Jahre nach dem Ende der Monarchie. Soll die Republik Österreich die Restitution verlangen? Können die Erben des ehemaligen Kaisers nach Belieben über die Juwelen aus der Kaiserzeit verfügen? Dazu zu hören sind die Historiker Oliver Rathkolb (Universität Wien), Martin Mutschlechner (Schönbrunn Group), Ilsebill Barta (Möbelmuseum Wien) und Matthias Dusini, Leiter des Feuilleton-Ressorts beim Falter. Hosted on Acast. See acast.com/privacy for more information.

Es ist leicht und fröhlich und freundlich und stimmungsvoll, einen schönen Martinsabend zu erleben: in die Kirche gehen zur Eröffnung des Martinszuges, dann mit Laternen und Gesang und Feuerwehrmusikzug durchs Städtchen flanieren, am Marktplatz angekommen das Martinsspiel schauen und von der Geschichte beeindruckt sein, Glühwein oder Kinderpunsch trinken und einen Stutenkerl, einen Weckmann, einen Klosmann geschenkt bekommen und erfreut und beschwingt nach Hause gehen. Wir Christen denken heute an einen Mann, der als junger Soldat gemacht hat, was er auf keinen Fall machen durfte. Er hat keinem Befehl gehorcht, sondern seinem Herzen! Wo gibt es denn sowas? Wo kämen wir hin, wenn selbst Befehlen gehorchen nicht mehr funktioniert. Das hätte bei Martin ziemlich ins Auge gehen können. Er hat den einzelnen frierenden Bettler von seinem hohen Ross aus, nicht übersehen, obwohl es viele frierende Bettler in jener Zeit gab, um die sich die Regierung gefälligst hätte kümmern können. Er hat sein Schwert gezückt und den Mantel geteilt, der ihn selbst und das Pferd bedeckt und warmgehalten hat. Der Haken an der Sache: der Mantel und das Schwert und das Pferd gehörte nicht ihm, sondern dem Kaiser und es war bei Strafe verboten etwas, was dem Kaiser gehörte, einfach wegzugeben oder sogar zu zerstören. Und die Legende, die sich im Volk bis heute gehalten hat, sagt, dass in der Nacht darauf, Christus dem Nichtchristen Martin erschienen ist, bekleidet mit dem halben Mantel und dem Dank für das offene Herz und den geteilten Mantel. Sehr viel später kann Martin den Dienst im Gefolge des Kaisers endlich quittieren und Nachfolger dieses Jesus Christus werden, der frierend und bettelnd an den Straßen der Welt sitzt und auf Hilfe wartet. Und er wird ein sehr anderer Christ und Bischof als viele andere vor und nach ihm. Er lebt in einer einfachen Holzhütte am Rand der Stadt und müht sich, durch die Gründung von Kirchen und Klöstern die Christianisierung des Landes zu festigen. Von Sulpitius Severus stammt die Aussage: „Durch Martins Tugenden und sein Glaubensbeispiel ist der Glaube in einem solchen Maß gewachsen, dass es heute keinen Ort gibt, der nicht voll ist von Kirchen und Klöstern.“ Die Glaubenskraft eines einzelnen Menschen kann so groß sein, dass sie ganze Länder und Generationen begeistert und zum Glauben bewegt. 

Ya tenemos serio candidato a convertirse en nuestro disco instrumental favorito del año. Los responsables son I. Jeziak and the Surfers, banda de la localidad de Gdansk, en el Norte de Polonia, junto a la costa del mar Báltico. En su debut -editado por Hi Tide Recordings- hacen gala de un excelente manejo de influencias y referentes con los que dan forma a 18 temas originales que parecen traídos de la edad dorada de la música surf.Playlist;(sintonía) I. JEZIAK and THE SURFERS “Pajama Party”I. JEZIAK and THE SURFERS “Night owls”I. JEZIAK and THE SURFERS “Maze”I. JEZIAK and THE SURFERS “Under the wave”THE TORMENTOS “Empire”DR TRITÓN feat JUANITO WAU “Bolillo fantasma”THE PHANTOM SURFERS “La Llorona”Versión y Original, TRÍO TARIÁCURI “La Llorona” (1941)LOS STRAITJACKETS “Two steps ahead”NICK LOWE and LOS STRAITJACKETS “Love starvation”SURF SCHOOL DROPOUTS “I thank you”LORD ROCHESTER “Don’t drink that vinegar”THEE HEADCOATEES “He’s gonna kill that girl”HOLLY GOLIGHTLY “My get back”THE GNOMES “Flippin’ stomp”THE KAISERS “Hey Lulu”LOS LOBOS “Will the wolf survive”Escuchar audio

Ein Schützenverein im Oktoberfestumzug, ein beiläufiger Kommentar im Fernsehen – und schon ist Thomas Krug auf Spurensuche: Was steckt hinter der Sendlinger Mordweihnacht von 1705?Gemeinsam mit Markus Knapp führt uns diese Folge mitten hinein in den Spanischen Erbfolgekrieg, in eine Zeit, in der Bayern zwischen Habsburg und Frankreich zerrieben wurde.Im Mittelpunkt stehen zwei Männer, deren Schicksale untrennbar mit diesem Konflikt verbunden sind:

Baronin Louise von Sturmfeder erlebte Kaiser Franz Joseph aus Perspektiven, die nur wenigen Menschen gegeben waren. Als Baby, als Kleinkind, aber auch als Herrscher eines großen Reiches. Die Aufzeichnungen der Kinderfrau des "kleinen Franzi", wie er in der Familie genannt wurde, geben intime Einblicke in seine ersten Lebensmonate, lassen uns Erzherzogin Sophie als junge Mutter erleben und Kaiser Franz II./I. als verspielten Großvater. Die teils unorthodoxen Erziehungsmethoden der Baronin Sturmfeder trafen nicht auf ungeteilte Zustimmung am Wiener Hof, doch entwickelte sich zwischen Kind und Kinderfrau eine tiefe Zuneigung, die bis zum Tod der Baronin 1866 ungebrochen blieb. Höre hier mehr über das kindliche Leben des späteren Kaisers von Österreich, und seine unkonventionelle Erzieherin.

Otto von Bismarck gilt als die Überfigur des 19. Jahrhunderts und des Deutschen Kaiserreichs. Und obwohl das Deutsche Reich ein Kaiserreich war, steht dessen Namensgeber Kaiser Wilhelm I. im tiefen historischen Schatten des „Eisernen Kanzlers“. Wilhelm, so die gängige Erzählung, sei ein schwacher Monarch gewesen, nicht mehr als eine Symbolfigur für das neue Reich, während Bismarck als dessen eigentlicher Architekt gilt. Zu dieser Wahrnehmung trug – vermeintlich – nicht zuletzt der Kaiser selbst selbst bei: Soll er doch geäußert haben, es sei nicht leicht, unter Bismarck Kaiser zu sein. Doch entspricht dieses Bild der historischen Realität? Neue Forschungen werfen Zweifel auf. Der Historiker Dr. Jan Markert hat den bislang weitgehend unerschlossenen Nachlass Wilhelms I. ausgewertet und zeichnet das Bild eines Kaisers, der weit mehr war als nur ein Statist der Geschichte. Wir haben mit ihm gesprochen. Den Originalbeitrag und mehr finden Sie bitte hier: https://lisa.gerda-henkel-stiftung.de/lisa_am_telefon_markert_wilhelm_bismarck_kaiserreich

Otto von Bismarck gilt als die Überfigur des 19. Jahrhunderts und des Deutschen Kaiserreichs. Und obwohl das Deutsche Reich ein Kaiserreich war, steht dessen Namensgeber Kaiser Wilhelm I. im tiefen historischen Schatten des „Eisernen Kanzlers“. Wilhelm, so die gängige Erzählung, sei ein schwacher Monarch gewesen, nicht mehr als eine Symbolfigur für das neue Reich, während Bismarck als dessen eigentlicher Architekt gilt. Zu dieser Wahrnehmung trug – vermeintlich – nicht zuletzt der Kaiser selbst selbst bei: Soll er doch geäußert haben, es sei nicht leicht, unter Bismarck Kaiser zu sein. Doch entspricht dieses Bild der historischen Realität? Neue Forschungen werfen Zweifel auf. Der Historiker Dr. Jan Markert hat den bislang weitgehend unerschlossenen Nachlass Wilhelms I. ausgewertet und zeichnet das Bild eines Kaisers, der weit mehr war als nur ein Statist der Geschichte. Wir haben mit ihm gesprochen. Den Originalbeitrag und mehr finden Sie bitte hier: https://lisa.gerda-henkel-stiftung.de/lisa_am_telefon_markert_wilhelm_bismarck_kaiserreich

Rund um die namensgebende Kirche "Mariahilf" bewegen wir uns in dieser Episode. Vom Apollokino aus besuchen wir das Cafe Ritter und das ehemalige Hotel Kummer, fahren mit dem Taxi kurz zum Prater und mit dem Autobus durch die Kärnterstraße zurück und überlegen, wie Autofreiheit und offene Verkaufssonntage und die Kutschenfahrten des Kaisers die Mariahilfer Straße bewegen.

Martin Andree ist seit 2018 Professor für Medienwissenschaften an der Universität Köln. Er studierte in Köln, Münster, Cambridge und Harvard ,war Marken-Manager bei Henkel. ist regelmäßiger Gast in Talk-Shows und wird häufig von führenden Wirtschaftsmedien zitiert und interviewt zum Thema Macht der Medien. Er veröffentlichte 2020 den hoch angesehenen “Atlas der digitalen Welt”,2023 schrieb er das Buch “Big Tech muss weg” und vor wenigen Tagen erschien sein neuestes Buch “Krieg der Medien” … mit einem sehr großen Medienecho. Martin sagt: „Die Mechanismen, die unsere Demokratie zerstören, sind dieselben, die auch unsere Wirtschaft zerstören.“ „Marken sind längst nicht nur Kunden von Big Tech – sie liefern den Treibstoff für Monopole und schwächen damit ihre eigene Kraft.“ Jetzt geht es für ihn ums Ganze: Zum einen geht es um unsere Demokratie und Gesellschaft – die Gefahr, dass Big Tech Monopole den öffentlichen Diskurs bestimmen, zu ihren Zwecken diese Macht wirtschaftlich mißbrauchen und gleichzeitig unsere Demokratie zerstören. Zum anderen geht es auch um den Selbstschutz von Marken, die aus seiner Sicht betrogen und erpresst werden und große Mengen an Geld verschwenden. Denn über 60 % der weltweiten Media-Investitionen landen heute im digitalen Raum, über 40% davon in Social Media und damit auf den Plattformen von Meta, Google & Co. Meta verspricht seit neuestem, sogar dass in Zukunft gar keine Werbeagenturen mehr gebraucht werden. Mark Zuckerberg sagt: Gebt uns einfach das Geld, wir liefern die Kunden. Aber: Die Effektivität von Kampagnen – gemessen an Brand-Effects und Large Scale Business Effekts, ist heute trotz dieser massiv gestiegenen Investitionen in digitale Werbung deutlich schlechter als noch vor 15 Jahren. Wie kann das sein? Martins These: Wir finanzieren mit unseren Budgets Strukturen, die uns schwächen – und ähnlich wie in der Erzählung von “des Kaisers neue Kleider” spricht es niemand offen aus.

Marc spricht mit Dr. Andrea Panzer-Heemeier von ARQIS über ihren Weg von der Ruhr-Universität Bochum zur Mitgründerin und Managing Partnerin der heute 75-köpfigen Kanzlei, über frühe Stationen bei einer Großkanzlei, den Wechsel in eine Arbeitsrechtsboutique und die Motivation, ARQIS als multidisziplinäres Spin-off aufzubauen. Unter anderem geht es um ihr spektakulärstes Mandat: die arbeitsrechtliche Flankierung des Kaisers-Tengelmann-Deals, bei dem eine Ministererlaubnis die kartellrechtlichen Bedenken überwog. Sie schildert, wie strategische Beratung, Politik und Verhandlungsgeschick verschmelzen, warum Arbeitsrecht mehr als Brot-und-Butter-Geschäft sein kann und weshalb Anwälte auch Verkäufer sein müssen. Nachwuchsjuristen erfahren, welche Vorkenntnisse ARQIS erwartet, welche No-Gos im Bewerbungsprozess gelten und wie Dr. Panzer-Heemeier Partnerinteressen balanciert, um ihre Kanzlei zukunftsfähig zu führen. Wie übt man einen Ministerauftritt mit einem Unternehmer? Weshalb kann ein Doktortitel besonders Frauen im Arbeitsrecht helfen? Welche Rolle spielen Persönlichkeit, Auslandserfahrung und Dienstleistungsmentalität für den Berufseinstieg? Antworten auf diese und viele weitere Fragen erhaltet Ihr in dieser Folge von IMR. Viel Spaß!

Leute, diesmal war der Start ungewohnt holprig. Steckte uns die harte Vorbereitung noch hörbar in den Beinen, der lange Sommer in von der Sonne ausgeblichenen Knochen. Die Zungen noch schwer nach sechs Wochen Pause, die Gehirne noch auf dem Sonnendeck. Eine Folge wie Pokal. Erste Runde, als Favorit kurz vor dem Aus. Pointen wie Fehlpässe, mehr Hallervorden als Didi-Man. So konnten wir uns mit Mühe und Not in die Werbung retten, dann lief Musik und wir fanden, gerade noch rechtzeitig, zu alter Stärke zurück. Schließlich konnten wir uns dann doch auf unsere Standards verlassen. Auf Trump und Infantino, auf Adeyemi und Matthias Sammer. Und vor allem auf Hoeneß und die Bayern, das große Sommertheater um den großen Sommertransfer. Die Hoffnung auf einen, der die Hoffnung trägt. Denn während der Supercup nun endlich den Namen des Kaisers trägt, wird dieses Transferfenster eher nicht nach Max Eberl benannt werden. Denn auch die Bayern greifen zunehmend ins falsche Regal, oder frei nach Uli: The Trend is Rob Friend. Nun ja. Es ist hier, wie bei Nick Woltemade, eben noch reichlich Luft nach oben. Aber nach dem Pokal ist vor der Bundesliga. Und wer sich deshalb nicht ganz zu Unrecht fragt, was eigentlich mit all den anderen Klubs ist, mit Heidenheim und Wolfsburg und Hoffenheim, dem legen wir ans Herz, doch bitte die volle Distanz zu gehen, denn gerade hintenraus werden nahezu alle Fragen beantwortet. Wirklich! In diesem Sinne: viel Vergnügen mit dieser neuen Folge. FUSSBALL MML - denn anders als der Geburtstag von Lamine Yamal ist das hier am Ende doch ein Riesenspaß!

Die EU ist blank und Deutschland sowieso. Unsere Wirtschaft steht nackt auf offener Weltbühne, ebenso wie unsere moralisch entblößten Politiker. Die Realität hat sie eingeholt, sie wollen es nur noch nicht wahrhaben. Es sind „des Kaisers neue Kleider“… Darum geht es heute: Benjamin Gollme und Marcel Joppa, die Jungs von Basta Berlin, präsentieren heute zwei große Aufreger: Die Aufrüstung und die Grünen. Und beides hängt unmittelbar miteinander zusammen. Während Bündnis 90/ die Olivgrünen aktuell im Osten lautstark in die Opferrolle schlüpfen, hat Ursula von der Leyen im Hinterzimmer das Land bereits an Donald Trump verhökert.

Er ist der Sohn eines gefeierten Kaisers, Erbe eines riesigen Weltreichs - und der Anfang vom Ende des goldenen Zeitalters Roms. Commodus wächst im Schatten seines Vaters Mark Aurel auf, einem Philosophenkaiser, der Ordnung und Vernunft verkörperte. Doch was passiert, wenn auf Weisheit Wahnsinn folgt?Schon früh wird klar: Das Imperium liegt einem jungen Mann zu Füßen, bei dem die Politik zur Bühne wird.Wir begleiten Commodus in seinem Aufstieg zur absoluten Macht: durch ein Netz aus Intrigen, gescheiterten Attentaten und brutalen Racheakten. Ein Kaiser, der sich selbst als Gott sieht, Gladiatorenkämpfe liebt, Skandale auslöst, einen Hofstaat mit Blut und Misstrauen regiert und schließlich als historische Vorlage im Hollywood Blockbuster "Gladiator” landet.

Passend zur Landesausstellung über Marc Aurel in Trier spricht Philosophie-Professor Jörn Müller in den Viehmarktthermen über das Denken des römischen Kaisers. „Das Glück deines Lebens hängt von der Beschaffenheit deiner Gedanken ab“, lautet einer seiner berühmtesten Sätze, wie Müller im Gespräch mit SWR Kultur am Mittag sagt.

Kinder – die Zukunft wird golden! Was freuen wir uns, dass wir Euch nach ein paar wohlverdienten Wochen Urlaub im Juli endlich wieder in den Arm nehmen können: Und das in komplett neuem Outfit! KSS macht eine „Frischzellen-Kühr“ und kommt zurück in des Kaisers neuen Kleidern! Wir werden angesagter als Dubai-Schokolade in das neue Zeitalter starten und dabei komplett unsere Wurzeln vergessen .. Zwinkersmiley. Heute trefft Ihr noch exklusiv ein aller letztes Mal auf den alten Dominik und den noch älteren Hendrik – aber in ein paar Wochen werdet Ihr Euren Ohren nicht trauen. Freut Euch heute auf ESC, USA, Nationalfeiertage und auf zwei bestens gelaunte alte Hasen, die bald als ganz neue „super-Karnickel“ zurückkehren werden.

Graham and Joe return after an end-of-season holiday hiatus to discuss what's been happening over the last fortnight at Leeds. 49ers, Rangers, Kaisers, 'furry creatures', transfers, contracts and returnees. Watch, share and subscribe now.This podcast is brought to you by Tailwind - a video production company. Visit: https://www.tailwind.group

Una ensalada con muchos sabores de rock’n’roll, todos procedentes de la cosecha de discos de 1995. Una buena añada.Playlist;(sintonía) THE SATAN’S PILGRIMS “Spoke” (Soul pilgrim)THE NEANDERTHALS “Arula Mata Gali” (The last menace to the human race)SOUTHERN CULTURE ON THE SKIDS “Voodoo cadillac” (Dirt track date)FLAT DUO JETS “Goin’ to a town” (Introducing the…)BEN VAUGHN “Rock is dead” (Rambler’65)OBLIVIANS “Sunday you need love” (Soul food)THE GORIES “You little nothing”THE KAISERS “Watcha say” (Beat it up)THE SWINGIN' NECKBREAKERS “Wait” (Shake break!)THE FLESHTONES “Let’s go” (Laboratory of sound)ROCKET FROM THE CRYPT “On a rope” (Scream Dracula Scream)SUPERSUCKERS “The thing about that” (The sacrilicious sounds of...)THE LAZY COWGIRLS “Frustration, tragedy and lies” (Ragged soul)RANCID “Journey to the end of the East Bay” (...And out come the wolves)MR T. EXPERIENCE “Ba ba ba ba ba” (Love is dead)RIVERDALES “Back to you” (ST)THE MUFFS “End it all” (Blonder and blonder)LOS IMPOSIBLES “Epílogo” (En el país del niño mosca)Escuchar audio

Auf Adolf Hitlers Selbstmord und die Kapitulation der deutschen Wehrmacht im Mai folgt die Kapitulation des japanischen Kaisers im August: Schrittweise endet der Zweite Weltkrieg im Jahr 1945.**********Ihr hört in dieser "Eine Stunde History":00:15:15 - Der Historiker Christian Stein beschreibt den langen Rückzug der deutschen Wehrmacht an der Ostfront.00:26:11 - Die Hagener Historikerin Janine Fubel erläutert die Auflösung und Evakuierung des Konzentrationslagers Sachsenhausen.00:37:51 - Der Buchautor Volker Heise hat Berichte und Zeitzeugenerinnerungen über die letzten Monate des Krieges und die ersten Monate des Friedens zusammengefasst.**********Mehr zum Thema bei Deutschlandfunk Nova:Holocaust: Die Befreiung des Vernichtungslagers AuschwitzNationalsozialismus: Euthanasie im NS-Staat - Die Aktion T4Trauma: Die Kinder der Nachkriegszeit**********Den Artikel zum Stück findet ihr hier.**********Ihr könnt uns auch auf diesen Kanälen folgen: TikTok und Instagram .**********In dieser Folge mit: Moderation: Markus Dichmann Gesprächspartner: Dr. Matthias von Hellfeld, Deutschlandfunk-Nova-Geschichtsexperte

Im November 1095 ruft Papst Urban II. zur bewaffneten Pilgerfahrt auf – und entfesselt damit eine Bewegung, die ganz Europa erschüttert. Was als Hilfsbitte eines bedrängten Kaisers beginnt, endet in einem religiös aufgeladenen Massenaufbruch nach Jerusalem. Zehntausende folgen dem Ruf ins Heilige Land – Adelige, Ritter, Bauern, Fanatiker. Und schon lange bevor sie ankommen, fließt das erste Blut. Die „expeditio“ wird zur Ideologie – mit tödlichen Folgen, auch in deutschen Städten. Was hat die Menschen damals bewegt? Und warum hallt dieser „Heilige Krieg“ bis heute nach?Du hast Feedback oder einen Themenvorschlag für Joachim und Nils? Dann melde dich gerne bei Instagram: @wasbishergeschah.podcastQuellen:Die Kreuzzüge – Der Krieg um das Heilige Land von Thomas AsbridgeGeschichte der Kreuzzüge von Hans Eberhard MayerUnsere allgemeinen Datenschutzrichtlinien finden Sie unter https://art19.com/privacy. Die Datenschutzrichtlinien für Kalifornien sind unter https://art19.com/privacy#do-not-sell-my-info abrufbar.

12. Exciting time to enjoy fantastic fresh new rockin' tunes with DJ Del Villarreal! Tuesday night's 2-hour rock n' roll fiesta thrills with a big batch of incedible vintage 50's era songs sure to make you twitch in your blue suede shoes! The Aztec Werewolf is here for you in the Motorbilly Studio LIVE and sharing cuts from JS and the Lockerbillies (with Darrel Higham!), The Kaisers, The Booze Bombs, Los Rebeldes, Murry Robe, Urban Zotel, Pat Winn & The Losers and even the Helltown Sinners! Jump in a dig the sounds sure to energize and excite you on a chilly Tuesday night! "Go Kat, GO! The Rock-A-Billy Show!" is ready to go! Good to the last bop!™Please follow on FaceBook, Instagram & Twitter!

32.005  Let's rock it up, tear it up and RIP it up on a Tuesday nite! Join DJ Del Villarreal this evening on Rockabilly Radio's greatest LIVE rockin' 50's music program,  "Go Kat, GO! The Rock-A-Billy Show!" broadcasting from the world-famous Motorbilly Studio! Loads of hot new tracks to share on a frosty Winter night. Excited to hear music from Jared Petteys & Ronnie Crucher, The Diamond Daddies, Wild May West, Fatboy, The Kaisers, The Lucky Devils, Tornado Beat and The Shakers! PLUS we're celebrating Phil Everly's 86th birthday with some choice songs written & performed by the legendary Everly Brother. Email requests: del@motorbilly.com OR drop a comment below! Good to the last bop!™Please follow on FaceBook, Instagram & Twitter!

Gerade dachte man, die Liebe zu seiner Lebensgefährtin Claudia hätte ihn besänftigt. Doch jetzt hatte Prinz Ernst August von Hannover schon wieder einen Ausraster. Diesmal in einem Nobel-Restaurant in Madrid. Fällt der Ex-Mann von Caroline von Hannover nun in alte Muster zurück? In der neuen Folge BUNTE Menschen spricht Lilly Burger mit Adelsressortleiter Stefan Blatt über die skandalreiche Vorgeschichte des Urenkels des letzten deutschen Kaisers. Außerdem: Unsere Highlights der glamourösen Golden Globes Verleihung. Die besten Roben, die heißtesten Küsse und die berührendsten Auftritte. Und im Horoskop fragen wir die Sterne, wie sie für die neue Liebe von Hugh Jackman.

Am 7. Januar 2024 hielt die Fußballwelt den Atem an. Die Nachricht vom Tod Franz Beckenbauers, des Kaisers, des Architekten des Sommermärchens, eines Mannes, der den deutschen Fußball prägte wie kein Zweiter, löste weltweite Bestürzung aus. Rund 50.000 Menschen versammelten sich wenige Tage später in der Münchner Allianz Arena, um einem Mann die letzte Ehre zu erweisen, der weit mehr war als ein Fußballstar. Sein Freund Uli Hoeneß brachte es auf den Punkt: Er ist die größte Persönlichkeit, die der FC Bayern jemals hatte. Als Spieler, Trainer, Präsident, Mensch: unvergesslich. Niemand wird ihn jemals erreichen. Malte Asmus und Sportjournalismus-Urgestein Werner-Johannes Müller (Kicker, ...Du möchtest deinen Podcast auch kostenlos hosten und damit Geld verdienen? Dann schaue auf www.kostenlos-hosten.de und informiere dich. Dort erhältst du alle Informationen zu unseren kostenlosen Podcast-Hosting-Angeboten. kostenlos-hosten.de ist ein Produkt der Podcastbude.Gern unterstützen wir dich bei deiner Podcast-Produktion.

Segunda entrega de nuestro repaso al 2024 a través de cien canciones favoritas.(Foto del podcast por Joshua Black Wilkins; JD McPherson)Playlist;(sintonía) THE FUZILLIS “Pickle swap”MFC CHICKEN “Beer size skeeters”THE KAISERS “That kind of fun”THE COURETTES “Keep dancing”JD McPHERSON “Just like summer”NATHANIEL RATELIFF and THE NIGH SWEATS “Heartless”AISHA KHAN feat BIG JOE LOUIS “Good morning middnight”THE VELVET CANDLES “Hello stranger”CHARLIE HIGHTONE and THE ROCK-IT’S “Little angel”LA LUZ “Poppies”PERROSKY “La ola”DREAM PONY “Synthetic love”CAROLINA DURANTE “Hamburguesas”ANNA DUKKE “My lifeline”THE HILLBILLY MOON EXPLOSION “Sometimes late at night”THE WYLDE TRIFFLES “I can’t get enough of your love”THE DEALERS “No me convences ya”Escuchar audio

Das Jahr 1902 ist eine Zeit, in der Pferdekutschen noch das Straßenbild dominieren und das Automobil ein exotisches Gadget ist. Kaiser Wilhelm II. wird oft das Zitat zugeschrieben: „Ich glaube an das Pferd. Das Auto ist nur eine vorübergehende Erscheinung.“ Doch hat der Kaiser das wirklich gesagt? Und war er tatsächlich so technikfeindlich, wie die Legende nahelegt?Quellen:Die Herrschaft des letzten Kaisers von Christopher ClarkThe Kaiser and His Court: Wilhelm II and the Government of Germany von John C. G. Röhl+++ Alle Infos und Streaming-Link zu unseren Werbepartnern findest du hier: LINK +++++ NEU: Wir sind jetzt auch auf Instagram! Hier gehts direkt zum Profil: @wasbishergeschah.podcast ++Unsere allgemeinen Datenschutzrichtlinien finden Sie unter https://art19.com/privacy. Die Datenschutzrichtlinien für Kalifornien sind unter https://art19.com/privacy#do-not-sell-my-info abrufbar.

Gladiatorenspiele, Tierkämpfe und Schiffsschlachten - die Veranstaltungen im Kolosseum sollten unterhalten und die Macht des Kaisers feiern. Genauso wie der Bau - ein architektonisches Meisterwerk der Antike. Von Lukas Grasberger (BR 2020)

In this episode of the Building HVAC Science podcast, co-hosts Bill Spohn and Eric Kaiser are joined by Eric's father, Mark Kaiser, for a special father-son discussion. Mark shares his experiences with building and improving a unique energy-efficient home in Carlinville, Illinois. His journey began in the late 1970s, when he retrofitted a modest house to reduce energy consumption using insulation, solar energy, and a variety of unconventional methods. Mark talks about his motivation for energy efficiency, stemming from his role overseeing utilities at Blackburn College, where he gained valuable insights into energy management and building systems. Throughout the conversation, Mark delves into the construction techniques he employed, including double wall construction for added insulation, using solar heat gain, and even creating a thermal mass storage system with water-filled milk jugs to retain heat. He explains how he balanced various heating systems, such as solar, wood, and natural gas, and how his hands-on approach—digging around the foundation, raising the roofline, and using sustainable materials—resulted in a home that remains energy-efficient to this day. The Kaisers also touch on innovative electrical systems, such as 12-volt and 24-volt setups, and how these have helped keep energy costs low. Mark's deep understanding of thermal mass, energy usage, and alternative construction methods highlights the importance of thoughtful, sustainable home design. As the discussion wraps up, Mark reflects on the lessons learned from maintaining and improving his home over the years, emphasizing the ongoing challenges of perfecting energy-efficient construction. The conversation offers listeners a unique blend of family history, practical tips, and a deep dive into the technical aspects of home energy management. The DC Freezer Mark mentioned www.sundanzer.com The paper on the Lo-Cal House may be found here: https://www.ideals.illinois.edu/items/54705   This episode was recorded in October 2024.

En el segundo tramo del programa retrocedemos a los años 50 iluminados por la compilación “Interstate Rockabilly box”, caja de ocho singles de vinilo que rescata oscuras grabaciones de rockabilly repartidas por sellos de diferentes estados norteamericanos. Entre las novedades actuales encontramos lo último del británico Rob Heron, el californiano James Intveld, los sevillanos Lojo and the Mojos o ese nuevo proyecto ideado por George Kaiser Miller llamado The Kaiserinas.Playlist;ROB HERON and THE TEA PAD ORCHESTRA “Good loving” (Feet first)ROB HERON and THE TEA PAD ORCHESTRA “Six month sleeper” (Feet first)JAMES INTVELD with THE VELVET CANDLES “Love you still”CHARLIE HIGHTONE and THE ROCK-IT’S “Haunted rhythm” (Haunted rhythm EP)LOJO and THE MOJOS “Hey Johnny” (Bumblebee EP)THE KAISERS “Cruelty” (More from The Kaisers)THE KAISERINAS “Don’t come back”JAKE LABOTZ “Hair on fire” (Hair on fire)WILLIE PHELPS “Yes siree, yes siree” (Interstate Rockabilly box)TRAIL BLAZERS “Grandpa’s rock” (Interstate Rockabilly box)JIMMY PRITCHETT “That’s the way I feel” (Interstate Rockabilly box)HAROLD and THE OFFBEATS “Three years” (Interstate Rockabilly box)TEDDY REDELL “Gold dust” (Interstate Rockabilly box)BOBBY BROWN “Please please baby” (Interstate Rockabilly box)AL FERRIER “Kiss me baby” (Interstate Rockabilly box)TOMMY STRANGE “Nervous and shakin all over” (Interstate Rockabilly box)THE GAYE SISTERS with REM WALL and GREEN VALLEY BBOYS “Oh Ricky” (Interstate Rockabilly box)WILD BILL TAYLOR and THE CLEFS “Little jewell” (Interstate Rockabilly box)DICKIE BIRD NEWMAN with THE JIMMY HEAP ORCHESTRA “Pearly Mae” (Interstate Rockabilly box)Escuchar audio

El viernes 13 de septiembre se lanza en todo el planeta el disco “Indoor safari” (Yep Roc), nuevo álbum de Nick Lowe con Los Straitjackets. Un día antes lo presentamos en exclusiva, escuchando en primicia esta nueva colección de canciones a cargo de uno de las más brillantes compositores que ha dado el pop y el rock’n’roll de los últimos 55 años.Estrenamos también el primer adelanto del próximo álbum de los suizos The Jackets, disco que se editará a mediados de octubre bajo el título “Intiution”.(Foto del podcast por Bobby Fisher)Playlist;NICK LOWE and LOS STRAITJACKETS “Went to party” (Indoor safari, 2024)NICK LOWE and LOS STRAITJACKETS “Crying inside” (Indoor safari, 2024)NICK LOWE and LOS STRAITJACKETS “A quiet place” (Indoor safari, 2024)NICK LOWE and LOS STRAITJACKETS “Blue on blue” (Indoor safari, 2024)NICK LOWE and LOS STRAITJACKETS “Tokyo Bay” (Indoor safari, 2024)NICK LOWE and LOS STRAITJACKETS “Jet pac boomerang” (Indoor safari, 2024)NICK LOWE and LOS STRAITJACKETS “Raincoat in the river” (Indoor safari, 2024)NICK LOWE and LOS STRAITJACKETS “Don’t be nice to me” (Indoor safari, 2024)THE KAISERS “Voodoo Lily” (More from The Kaisers, 2024)THE JACKETS “Intiution” (adelanto del álbum “Intuition”)THE KNIGHT SHADES “Up, down, in, way-out” (single, 2023)THE FLESHTONES “The consequences” (adelanto del álbum “It's getting late (...and more songs about werewolves)”)THE STEMS “For always” (Official Live Recording, 2024)JAMIE TURNER “How lost I would be without you” (single 2023)TED HAWKINS “Sorry you’re sick” (Watch your stop, 1982)Escuchar audio

Cäsars Ziehsohn gelingt, woran dieser scheiterte: Augustus stürzt die Republik und stirbt am 19.08.0014 als erster römischer Kaiser - weil er einen Fehler Cäsars vermeidet.

Where else can you find both Phish and The Muppets (Animal) going Head 2 Head covering a classic by The Surfaris? Right here on Catching A Wave! We also hear #3 and #2 in our Top 5 Favorite Dick Dale Song Countdown! Beth Riley has a tune related to The Beach Boys in her Surf's Up: Beth's Beach Boys Break. There's a song by The Kaisers celebrating it's 30th anniversary in our Good Time segment and we drop a coin in the Jammin' James Jukebox to hear our selection of the week (Duane Eddy)! Plus, there's songs from Ichi-Bons, The Scimitars, the Lake Devils, Magnatech, The Rebel Set, The Other Timelines, Marco Di Maggio, Jenny Don't & The Spurs, Punk Fiction, Ultra Lights, dayaway and Shriek If You Know What I Did Last Friday The 13th!    Intro music bed: "Catch A Wave"- The Beach Boys   Magnatech- "Departure Hall" the Lake Devils- "Seizures"   Favorite Dick Dale Song Countdown: #3 Dick Dale- "Nitro"   Ichi-Bons- "Snake Eyes" Ultra Lights- "Nostalgia"   Good Time segment: The Kaisers 30th anniversary of "In Step With The Kaisers" (1994 No Hit Records) The Kaisers- "Squarehead"   The Rebel Set- "Bummer City" The Scimitars- "Taverna"   Surf's Up- Beth's Beach Boys Break: Kenny & Cadets- "What Is A Young Girl Made Of" Follow "Surf's Up: Beth's Beach Boys Break" HERE   Shriek If You Know What I Did Last Friday The 13th- "El Tormento's Theme"   Favorite Dick Dale Song Countdown: #2 Dick Dale- "The Wedge"   dayaway- "rogue wave" Jenny Don't & The Spurs- "War Cry!"   Head 2 Head: Phish- "Wipe Out" The Muppets (Animal)- "Wipe Out"   Jammin' James Jukebox selection of the week: Duane Eddy & The Rebels with The Rebelettes- "Your Baby's Gone Surfin'"   Marco Di Maggio- "Okyo Affair" The Other Timelines- "Public Access '66 Theme" Punk Fiction- "Jungle Boogie"   Outro music bed: Link Wray- "Apache"

We may be heading to the end of summer but it’s not the end of great music. Once again, the new release episode for this month has been expanded into a two part extravaganza. Tonight’s first part features a number of “friends of the show”, including monthly singles by White Rose Motor Oil and Rob Moss & Skin-Tight Skin. There Realpunkradio’s Greg Lonesome with his Intrusive Thoughts project, a teaser from Tamar Berk’s upcoming record, a couple of new tracks from Big Stir Records, and plenty of others that so graciously keep me on their mailing list!   Of course, that’s not all. We have the return of X with reportedly their final album. There’s the first new Kaisers album in 246 months! Jack White is also represented with his surprise new release that I’m not afraid to say is his best music since the demise of The White Stripes. Plus so much more! Along with these releases are the usual mix of punk, garage, power pop, and much more! Also, please head to YouTube and subscribe to our channel – Public Domain Classics 888. We have close to 500 classic films from over 110 years of releases!  For more info, including […]

We may be heading to the end of summer but it's not the end of great music. Once again, the new release episode for this month has been expanded into a two part extravaganza. Tonight's first part features a number of “friends of the show”, including monthly singles by White Rose Motor Oil and Rob Moss & Skin-Tight Skin. There Realpunkradio's Greg Lonesome with his Intrusive Thoughts project, a teaser from Tamar Berk's upcoming record, a couple of new tracks from Big Stir Records, and plenty of others that so graciously keep me on their mailing list!   Of course, that's not all. We have the return of X with reportedly their final album. There's the first new Kaisers album in 246 months! Jack White is also represented with his surprise new release that I'm not afraid to say is his best music since the demise of The White Stripes. Plus so much more! Along with these releases are the usual mix of punk, garage, power pop, and much more! Also, please head to YouTube and subscribe to our channel – Public Domain Classics 888. We have close to 500 classic films from over 110 years of releases!  For more info, including […]

Echamos un vistazo por el retrovisor para ofrecerte una sesión con algunos de nuestros discos favoritos editados en lo que llevamos de este 2024.(Foto del podcast; Shannon and The Clams)Playlist;(sintonía) FIFTY FOOT COMBO “Golden hour”AISHA KHAN feat BIG JOE LOUIS “Good morning midnight”THE VELVET CANDLES “Hello stranger”ANNA DUKE “My lifeline”THE PEAWEES “Banana tree”SHANNON and THE CLAMS “Big Wheel”THE LOONS “Daffodils or despair”THE KAISERS “Tremblin’”CHUCO y SUS CARRUCHAS “Cumbia del perro viejo”LOS ESTANQUES “¡Ay que no me pique el tábano”THE MELLOWS “Satisfy your soul”EELS “Time”LA LUZ “Poppies”PERROSKY “La ola”DREAM PONY “Synthetic love”KELLEY STOLTZ “Hide in a song”THE HANGING STARS “Let me dream of you”Escuchar audio

Today's conductors on the June 2024 New Music train are headed for a mix of retro and modern, as Bill Mulligan and Adam Coop discuss new tunes from The Scimitars, The Kaisers and Tiny Stills. Rockin' the Suburbs on Apple Podcasts/iTunes or other podcast platforms, including audioBoom, Spotify, Google Podcasts, Amazon, iHeart, Stitcher and TuneIn. Or listen at SuburbsPod.com. Please rate/review the show on Apple Podcasts and share it with your friends. Visit our website at SuburbsPod.com Email Jim & Patrick at rock@suburbspod.com Follow us on the Threads, Facebook or Instagram @suburbspod If you're glad or sad or high, call the Suburban Party Line — 612-440-1984. Theme music: "Ascension," originally by Quartjar, covered by Frank Muffin. Visit quartjar.bandcamp.com and frankmuffin.bandcamp.com.

Desde su formación a comienzos de los años 90 los escoceses The Kaisers fueron los más fieles y talentosos herederos del sonido y las formas del beat por su lado más energético. Tras su separación en 2002 volvieron a reaparecer en 2015 para recordar su legado a las nuevas generaciones paseándose por los mejores festivales de rock’n’roll de Europa. Ahora, por fin, lanzan el álbum con el que consolidan esta segunda etapa, “More from The Kaisers”, uno de los mejores discos de beat de las últimas décadas el cual hemos elegido como nuestro Disco Subterráneo del Verano.Playlist;THE KAISERS “Guillotine twist” (More from The Kaisers, 2024)THE KAISERS “The kind of fun” (More from The Kaisers, 2024)THE KAISERS “Tremblin’” (More from The Kaisers, 2024)THE KAISERS “Keep walking that way” (More from The Kaisers, 2024)THE KAISERS “Shaking and stomping” (More from The Kaisers, 2024)YOUNG FRESH FELLOWS “Good times rock’n’roll” (Because we hate you, 2021)FASTBACKS “Come on” (adelanto del álbum “For what reason”)THE MYSTERY LIGHTS “Purgatory” (adelanto próximo álbum)BENNY TROKAN “It’s time” (Do you still think of me, 2024)THE REBEL SET “Evil eyes” (Bummer City, 2024)THE MOCKS “Same old day” (single, 2022)THE MAHARAJAS “You’re gonna need me when I’m gone” (adelanto próximo álbum)THE WYLDE MAMMOTHS “Enough of your love” (Go baby go, 1985)WYLDE MAMMOTHS “Hooked” (Go baby go, 1985)THE HANGING STARS “Let me dream of you” (On a golden shore, 2024)BIZNAGA “Imaginación política” (adelanto próximo álbum)MELOPEA “Amante de olas” (Hoy me siento retro, 2019)Escuchar audio

Wir springen in dieser Folge ins Jahr 1915 und sprechen über eine chemische Verbindung, die in den USA zum Teil einer Verschwörung wurde: Phenol. Ein Stoff, der nicht nur als Desinfektionsmittel Verwendung fand, sondern auch als Basis von Kunststoffen, Aspirin und Sprengstoff. Nach Ausbruch des Ersten Weltkriegs wurde in den USA das Phenol knapp, weil die Importe aus Europa versiegten. Das rief nicht nur den Erfinder Thomas Edison auf den Plan, sondern auch den deutschen Botschafter und seine Geheimagenten. //Literatur - Lindsey Fitzharris: Der Horror der frühen Medizin. Joseph Listers Kampf gegen Kurpfuscher, Quacksalber & Knochenklempner. - Diarmuid Jeffreys: The Extraordinary Story of a Wonder Drug. // Erwähnte Folgen - GAG23: Ziemlich beste Feindschaft oder Die Anfänge der Bakteriologie https://gadg.fm/23 - GAG168: Carl Laemmle und die Anfänge Hollywoods https://gadg.fm/168 - GAG207: William Stewart Halsted und die Chirurgie des 19. Jahrhunderts https://gadg.fm/207 - GAG320: In 72 Tagen um die Welt – Journalistin Nellie Bly https://gadg.fm/320 - GAG361: Gustave Trouvé - der vergessene Erfinder https://gadg.fm/361 - GAG406: Die SMS Wolf und die Piraten des Kaisers https://gadg.fm/406 - GAG444: Die Erfindung von Heroin und Aspirin https://gadg.fm/444 Das Episodenbild zeigt einen Ausschnitt einer Skizze der Freiheitsstatue: The Great Bartholdi Statue. Schwer zu erkennen, aber auf dem Bild stehen Menschen auf der Aussichtsplattform der Fackel, die seit der Black-Tom-Explosion für Publikum gesperrt ist. //Aus unserer Werbung Du möchtest mehr über unsere Werbepartner erfahren? Hier findest du alle Infos & Rabatte: https://linktr.ee/GeschichtenausderGeschichte //Wir haben auch ein Buch geschrieben: Wer es erwerben will, es ist überall im Handel, aber auch direkt über den Verlag zu erwerben: https://www.piper.de/buecher/geschichten-aus-der-geschichte-isbn-978-3-492-06363-0 Wer Becher, T-Shirts oder Hoodies erwerben will: Die gibt's unter https://geschichte.shop Wer unsere Folgen lieber ohne Werbung anhören will, kann das über eine kleine Unterstützung auf Steady oder ein Abo des GeschichteFM-Plus Kanals auf Apple Podcasts tun. Wir freuen uns, wenn ihr den Podcast bei Apple Podcasts oder wo auch immer dies möglich ist rezensiert oder bewertet. Wir freuen uns auch immer, wenn ihr euren Freundinnen und Freunden, Kolleginnen und Kollegen oder sogar Nachbarinnen und Nachbarn von uns erzählt!

Großadmiral, Marineminister, Strippenzieher. Einflüsterer des Kaisers, versessen nach Weltgeltung: die Karriere des eigentlich Bürgerlichen Alfred Tirpitz ist atemberaubend. Von Edda Dammmüller.

Am 1.2.1394 wurde er als Sohn des Kaisers von Japan geboren - ohne Ansprüche, seine Mutter war Konkubine. Ein Mönch, der in Freudenhäusern verkehrt und Gedichte schreibt. Von Claudia Belemann.