Podcasts about Beige

In this episode Gudrun speaks with Nadja Klein and Moussa Kassem Sbeyti who work at the Scientific Computing Center (SCC) at KIT in Karlsruhe. Since August 2024, Nadja has been professor at KIT leading the research group Methods for Big Data (MBD) there. She is an Emmy Noether Research Group Leader, and a member of AcademiaNet, and Die Junge Akademie, among others. In 2025, Nadja was awarded the Committee of Presidents of Statistical Societies (COPSS) Emerging Leader Award (ELA). The COPSS ELA recognizes early career statistical scientists who show evidence of and potential for leadership and who will help shape and strengthen the field. She finished her doctoral studies in Mathematics at the Universität Göttingen before conducting a postdoc at the University of Melbourne as a Feodor-Lynen fellow by the Alexander von Humboldt Foundation. Afterwards she was a Professor for Statistics and Data Science at the Humboldt-Universität zu Berlin before joining KIT. Moussa joined Nadja's lab as an associated member in 2023 and later as a postdoctoral researcher in 2024. He pursued a PhD at the TU Berlin while working as an AI Research Scientist at the Continental AI Lab in Berlin. His research primarily focuses on deep learning, developing uncertainty-based automated labeling methods for 2D object detection in autonomous driving. Prior to this, Moussa earned his M.Sc. in Mechatronics Engineering from the TU Darmstadt in 2021. The research of Nadja and Moussa is at the intersection of statistics and machine learning. In Nadja's MBD Lab the research spans theoretical analysis, method development and real-world applications. One of their key focuses is Bayesian methods, which allow to incorporate prior knowledge, quantify uncertainties, and bring insights to the “black boxes” of machine learning. By fusing the precision and reliability of Bayesian statistics with the adaptability of machine and deep learning, these methods aim to leverage the best of both worlds. The KIT offers a strong research environment, making it an ideal place to continue their work. They bring new expertise that can be leveraged in various applications and on the other hand Helmholtz offers a great platform in that respect to explore new application areas. For example Moussa decided to join the group at KIT as part of the Helmholtz Pilot Program Core-Informatics at KIT (KiKIT), which is an initiative focused on advancing fundamental research in informatics within the Helmholtz Association. Vision models typically depend on large volumes of labeled data, but collecting and labeling this data is both expensive and prone to errors. During his PhD, his research centered on data-efficient learning using uncertainty-based automated labeling techniques. That means estimating and using the uncertainty of models to select the helpful data samples to train the models to label the rest themselves. Now, within KiKIT, his work has evolved to include knowledge-based approaches in multi-task models, eg. detection and depth estimation — with the broader goal of enabling the development and deployment of reliable, accurate vision systems in real-world applications. Statistics and data science are fascinating fields, offering a wide variety of methods and applications that constantly lead to new insights. Within this domain, Bayesian methods are especially compelling, as they enable the quantification of uncertainty and the incorporation of prior knowledge. These capabilities contribute to making machine learning models more data-efficient, interpretable, and robust, which are essential qualities in safety-critical domains such as autonomous driving and personalized medicine. Nadja is also enthusiastic about the interdisciplinarity of the subject — repeatedly changing the focus from mathematics to economics to statistics to computer science. The combination of theoretical fundamentals and practical applications makes statistics an agile and important field of research in data science. From a deep learning perspective, the focus is on making models both more efficient and more reliable when dealing with large-scale data and complex dependencies. One way to do this is by reducing the need for extensive labeled data. They also work on developing self-aware models that can recognize when they're unsure and even reject their own predictions when necessary. Additionally, they explore model pruning techniques to improve computational efficiency, and specialize in Bayesian deep learning, allowing machine learning models to better handle uncertainty and complex dependencies. Beyond the methods themselves, they also contribute by publishing datasets that help push the development of next-generation, state-of-the-art models. The learning methods are applied across different domains such as object detection, depth estimation, semantic segmentation, and trajectory prediction — especially in the context of autonomous driving and agricultural applications. As deep learning technologies continue to evolve, they're also expanding into new application areas such as medical imaging. Unlike traditional deep learning, Bayesian deep learning provides uncertainty estimates alongside predictions, allowing for more principled decision-making and reducing catastrophic failures in safety-critical application. It has had a growing impact in several real-world domains where uncertainty really matters. Bayesian learning incorporates prior knowledge and updates beliefs as new data comes in, rather than relying purely on data-driven optimization. In healthcare, for example, Bayesian models help quantify uncertainty in medical diagnoses, which supports more risk-aware treatment decisions and can ultimately lead to better patient outcomes. In autonomous vehicles, Bayesian models play a key role in improving safety. By recognizing when the system is uncertain, they help capture edge cases more effectively, reduce false positives and negatives in object detection, and navigate complex, dynamic environments — like bad weather or unexpected road conditions — more reliably. In finance, Bayesian deep learning enhances both risk assessment and fraud detection by allowing the system to assess how confident it is in its predictions. That added layer of information supports more informed decision-making and helps reduce costly errors. Across all these areas, the key advantage is the ability to move beyond just accuracy and incorporate trust and reliability into AI systems. Bayesian methods are traditionally more expensive, but modern approximations (e.g., variational inference or last layer inference) make them feasible. Computational costs depend on the problem — sometimes Bayesian models require fewer data points to achieve better performance. The trade-off is between interpretability and computational efficiency, but hardware improvements are helping bridge this gap. Their research on uncertainty-based automated labeling is designed to make models not just safer and more reliable, but also more efficient. By reducing the need for extensive manual labeling, one improves the overall quality of the dataset while cutting down on human effort and potential labeling errors. Importantly, by selecting informative samples, the model learns from better data — which means it can reach higher performance with fewer training examples. This leads to faster training and better generalization without sacrificing accuracy. They also focus on developing lightweight uncertainty estimation techniques that are computationally efficient, so these benefits don't come with heavy resource demands. In short, this approach helps build models that are more robust, more adaptive to new data, and significantly more efficient to train and deploy — which is critical for real-world systems where both accuracy and speed matter. Statisticians and deep learning researchers often use distinct methodologies, vocabulary and frameworks, making communication and collaboration challenging. Unfortunately, there is a lack of Interdisciplinary education: Traditional academic programs rarely integrate both fields. It is necessary to foster joint programs, workshops, and cross-disciplinary training can help bridge this gap. From Moussa's experience coming through an industrial PhD, he has seen how many industry settings tend to prioritize short-term gains — favoring quick wins in deep learning over deeper, more fundamental improvements. To overcome this, we need to build long-term research partnerships between academia and industry — ones that allow for foundational work to evolve alongside practical applications. That kind of collaboration can drive more sustainable, impactful innovation in the long run, something we do at methods for big data. Looking ahead, one of the major directions for deep learning in the next five to ten years is the shift toward trustworthy AI. We're already seeing growing attention on making models more explainable, fair, and robust — especially as AI systems are being deployed in critical areas like healthcare, mobility, and finance. The group also expect to see more hybrid models — combining deep learning with Bayesian methods, physics-based models, or symbolic reasoning. These approaches can help bridge the gap between raw performance and interpretability, and often lead to more data-efficient solutions. Another big trend is the rise of uncertainty-aware AI. As AI moves into more high-risk, real-world applications, it becomes essential that systems understand and communicate their own confidence. This is where uncertainty modeling will play a key role — helping to make AI not just more powerful, but also more safe and reliable. The lecture "Advanced Bayesian Data Analysis" covers fundamental concepts in Bayesian statistics, including parametric and non-parametric regression, computational techniques such as MCMC and variational inference, and Bayesian priors for handling high-dimensional data. Additionally, the lecturers offer a Research Seminar on Selected Topics in Statistical Learning and Data Science. The workgroup offers a variety of Master's thesis topics at the intersection of statistics and deep learning, focusing on Bayesian modeling, uncertainty quantification, and high-dimensional methods. Current topics include predictive information criteria for Bayesian models and uncertainty quantification in deep learning. Topics span theoretical, methodological, computational and applied projects. Students interested in rigorous theoretical and applied research are encouraged to explore our available projects and contact us for further details. The general advice of Nadja and Moussa for everybody interested to enter the field is: "Develop a strong foundation in statistical and mathematical principles, rather than focusing solely on the latest trends. Gain expertise in both theory and practical applications, as real-world impact requires a balance of both. Be open to interdisciplinary collaboration. Some of the most exciting and meaningful innovations happen at the intersection of fields — whether that's statistics and deep learning, or AI and domain-specific areas like medicine or mobility. So don't be afraid to step outside your comfort zone, ask questions across disciplines, and look for ways to connect different perspectives. That's often where real breakthroughs happen. With every new challenge comes an opportunity to innovate, and that's what keeps this work exciting. We're always pushing for more robust, efficient, and trustworthy AI. And we're also growing — so if you're a motivated researcher interested in this space, we'd love to hear from you." Literature and further information Webpage of the group G. Nuti, Lluis A.J. Rugama, A.-I. Cross: Efficient Bayesian Decision Tree Algorithm, arxiv Jan 2019 Wikipedia: Expected value of sample information C. Howson & P. Urbach: Scientific Reasoning: The Bayesian Approach (3rd ed.). Open Court Publishing Company. ISBN 978-0-8126-9578-6, 2005. A.Gelman e.a.: Bayesian Data Analysis Third Edition. Chapman and Hall/CRC. ISBN 978-1-4398-4095-5, 2013. Yu, Angela: Introduction to Bayesian Decision Theory cogsci.ucsd.edu, 2013. Devin Soni: Introduction to Bayesian Networks, 2015. G. Nuti, L. Rugama, A.-I. Cross: Efficient Bayesian Decision Tree Algorithm, arXiv:1901.03214 stat.ML, 2019. M. Carlan, T. Kneib and N. Klein: Bayesian conditional transformation models, Journal of the American Statistical Association, 119(546):1360-1373, 2024. N. Klein: Distributional regression for data analysis , Annual Review of Statistics and Its Application, 11:321-346, 2024 C.Hoffmann and N.Klein: Marginally calibrated response distributions for end-to-end learning in autonomous driving, Annals of Applied Statistics, 17(2):1740-1763, 2023 Kassem Sbeyti, M., Karg, M., Wirth, C., Klein, N., & Albayrak, S. (2024, September). Cost-Sensitive Uncertainty-Based Failure Recognition for Object Detection. In Uncertainty in Artificial Intelligence (pp. 1890-1900). PMLR. M. K. Sbeyti, N. Klein, A. Nowzad, F. Sivrikaya and S. Albayrak: Building Blocks for Robust and Effective Semi-Supervised Real-World Object Detection pdf. To appear in Transactions on Machine Learning Research, 2025 Podcasts Learning, Teaching, and Building in the Age of AI Ep 42 of Vanishing Gradient, Jan 2025. O. Beige, G. Thäter: Risikoentscheidungsprozesse, Gespräch im Modellansatz Podcast, Folge 193, Fakultät für Mathematik, Karlsruher Institut für Technologie (KIT), 2019.

In this episode Gudrun speaks with Nadja Klein and Moussa Kassem Sbeyti who work at the Scientific Computing Center (SCC) at KIT in Karlsruhe. Since August 2024, Nadja has been professor at KIT leading the research group Methods for Big Data (MBD) there. She is an Emmy Noether Research Group Leader, and a member of AcademiaNet, and Die Junge Akademie, among others. In 2025, Nadja was awarded the Committee of Presidents of Statistical Societies (COPSS) Emerging Leader Award (ELA). The COPSS ELA recognizes early career statistical scientists who show evidence of and potential for leadership and who will help shape and strengthen the field. She finished her doctoral studies in Mathematics at the Universität Göttingen before conducting a postdoc at the University of Melbourne as a Feodor-Lynen fellow by the Alexander von Humboldt Foundation. Afterwards she was a Professor for Statistics and Data Science at the Humboldt-Universität zu Berlin before joining KIT. Moussa joined Nadja's lab as an associated member in 2023 and later as a postdoctoral researcher in 2024. He pursued a PhD at the TU Berlin while working as an AI Research Scientist at the Continental AI Lab in Berlin. His research primarily focuses on deep learning, developing uncertainty-based automated labeling methods for 2D object detection in autonomous driving. Prior to this, Moussa earned his M.Sc. in Mechatronics Engineering from the TU Darmstadt in 2021. The research of Nadja and Moussa is at the intersection of statistics and machine learning. In Nadja's MBD Lab the research spans theoretical analysis, method development and real-world applications. One of their key focuses is Bayesian methods, which allow to incorporate prior knowledge, quantify uncertainties, and bring insights to the “black boxes” of machine learning. By fusing the precision and reliability of Bayesian statistics with the adaptability of machine and deep learning, these methods aim to leverage the best of both worlds. The KIT offers a strong research environment, making it an ideal place to continue their work. They bring new expertise that can be leveraged in various applications and on the other hand Helmholtz offers a great platform in that respect to explore new application areas. For example Moussa decided to join the group at KIT as part of the Helmholtz Pilot Program Core-Informatics at KIT (KiKIT), which is an initiative focused on advancing fundamental research in informatics within the Helmholtz Association. Vision models typically depend on large volumes of labeled data, but collecting and labeling this data is both expensive and prone to errors. During his PhD, his research centered on data-efficient learning using uncertainty-based automated labeling techniques. That means estimating and using the uncertainty of models to select the helpful data samples to train the models to label the rest themselves. Now, within KiKIT, his work has evolved to include knowledge-based approaches in multi-task models, eg. detection and depth estimation — with the broader goal of enabling the development and deployment of reliable, accurate vision systems in real-world applications. Statistics and data science are fascinating fields, offering a wide variety of methods and applications that constantly lead to new insights. Within this domain, Bayesian methods are especially compelling, as they enable the quantification of uncertainty and the incorporation of prior knowledge. These capabilities contribute to making machine learning models more data-efficient, interpretable, and robust, which are essential qualities in safety-critical domains such as autonomous driving and personalized medicine. Nadja is also enthusiastic about the interdisciplinarity of the subject — repeatedly changing the focus from mathematics to economics to statistics to computer science. The combination of theoretical fundamentals and practical applications makes statistics an agile and important field of research in data science. From a deep learning perspective, the focus is on making models both more efficient and more reliable when dealing with large-scale data and complex dependencies. One way to do this is by reducing the need for extensive labeled data. They also work on developing self-aware models that can recognize when they're unsure and even reject their own predictions when necessary. Additionally, they explore model pruning techniques to improve computational efficiency, and specialize in Bayesian deep learning, allowing machine learning models to better handle uncertainty and complex dependencies. Beyond the methods themselves, they also contribute by publishing datasets that help push the development of next-generation, state-of-the-art models. The learning methods are applied across different domains such as object detection, depth estimation, semantic segmentation, and trajectory prediction — especially in the context of autonomous driving and agricultural applications. As deep learning technologies continue to evolve, they're also expanding into new application areas such as medical imaging. Unlike traditional deep learning, Bayesian deep learning provides uncertainty estimates alongside predictions, allowing for more principled decision-making and reducing catastrophic failures in safety-critical application. It has had a growing impact in several real-world domains where uncertainty really matters. Bayesian learning incorporates prior knowledge and updates beliefs as new data comes in, rather than relying purely on data-driven optimization. In healthcare, for example, Bayesian models help quantify uncertainty in medical diagnoses, which supports more risk-aware treatment decisions and can ultimately lead to better patient outcomes. In autonomous vehicles, Bayesian models play a key role in improving safety. By recognizing when the system is uncertain, they help capture edge cases more effectively, reduce false positives and negatives in object detection, and navigate complex, dynamic environments — like bad weather or unexpected road conditions — more reliably. In finance, Bayesian deep learning enhances both risk assessment and fraud detection by allowing the system to assess how confident it is in its predictions. That added layer of information supports more informed decision-making and helps reduce costly errors. Across all these areas, the key advantage is the ability to move beyond just accuracy and incorporate trust and reliability into AI systems. Bayesian methods are traditionally more expensive, but modern approximations (e.g., variational inference or last layer inference) make them feasible. Computational costs depend on the problem — sometimes Bayesian models require fewer data points to achieve better performance. The trade-off is between interpretability and computational efficiency, but hardware improvements are helping bridge this gap. Their research on uncertainty-based automated labeling is designed to make models not just safer and more reliable, but also more efficient. By reducing the need for extensive manual labeling, one improves the overall quality of the dataset while cutting down on human effort and potential labeling errors. Importantly, by selecting informative samples, the model learns from better data — which means it can reach higher performance with fewer training examples. This leads to faster training and better generalization without sacrificing accuracy. They also focus on developing lightweight uncertainty estimation techniques that are computationally efficient, so these benefits don't come with heavy resource demands. In short, this approach helps build models that are more robust, more adaptive to new data, and significantly more efficient to train and deploy — which is critical for real-world systems where both accuracy and speed matter. Statisticians and deep learning researchers often use distinct methodologies, vocabulary and frameworks, making communication and collaboration challenging. Unfortunately, there is a lack of Interdisciplinary education: Traditional academic programs rarely integrate both fields. It is necessary to foster joint programs, workshops, and cross-disciplinary training can help bridge this gap. From Moussa's experience coming through an industrial PhD, he has seen how many industry settings tend to prioritize short-term gains — favoring quick wins in deep learning over deeper, more fundamental improvements. To overcome this, we need to build long-term research partnerships between academia and industry — ones that allow for foundational work to evolve alongside practical applications. That kind of collaboration can drive more sustainable, impactful innovation in the long run, something we do at methods for big data. Looking ahead, one of the major directions for deep learning in the next five to ten years is the shift toward trustworthy AI. We're already seeing growing attention on making models more explainable, fair, and robust — especially as AI systems are being deployed in critical areas like healthcare, mobility, and finance. The group also expect to see more hybrid models — combining deep learning with Bayesian methods, physics-based models, or symbolic reasoning. These approaches can help bridge the gap between raw performance and interpretability, and often lead to more data-efficient solutions. Another big trend is the rise of uncertainty-aware AI. As AI moves into more high-risk, real-world applications, it becomes essential that systems understand and communicate their own confidence. This is where uncertainty modeling will play a key role — helping to make AI not just more powerful, but also more safe and reliable. The lecture "Advanced Bayesian Data Analysis" covers fundamental concepts in Bayesian statistics, including parametric and non-parametric regression, computational techniques such as MCMC and variational inference, and Bayesian priors for handling high-dimensional data. Additionally, the lecturers offer a Research Seminar on Selected Topics in Statistical Learning and Data Science. The workgroup offers a variety of Master's thesis topics at the intersection of statistics and deep learning, focusing on Bayesian modeling, uncertainty quantification, and high-dimensional methods. Current topics include predictive information criteria for Bayesian models and uncertainty quantification in deep learning. Topics span theoretical, methodological, computational and applied projects. Students interested in rigorous theoretical and applied research are encouraged to explore our available projects and contact us for further details. The general advice of Nadja and Moussa for everybody interested to enter the field is: "Develop a strong foundation in statistical and mathematical principles, rather than focusing solely on the latest trends. Gain expertise in both theory and practical applications, as real-world impact requires a balance of both. Be open to interdisciplinary collaboration. Some of the most exciting and meaningful innovations happen at the intersection of fields — whether that's statistics and deep learning, or AI and domain-specific areas like medicine or mobility. So don't be afraid to step outside your comfort zone, ask questions across disciplines, and look for ways to connect different perspectives. That's often where real breakthroughs happen. With every new challenge comes an opportunity to innovate, and that's what keeps this work exciting. We're always pushing for more robust, efficient, and trustworthy AI. And we're also growing — so if you're a motivated researcher interested in this space, we'd love to hear from you." Literature and further information Webpage of the group G. Nuti, Lluis A.J. Rugama, A.-I. Cross: Efficient Bayesian Decision Tree Algorithm, arxiv Jan 2019 Wikipedia: Expected value of sample information C. Howson & P. Urbach: Scientific Reasoning: The Bayesian Approach (3rd ed.). Open Court Publishing Company. ISBN 978-0-8126-9578-6, 2005. A.Gelman e.a.: Bayesian Data Analysis Third Edition. Chapman and Hall/CRC. ISBN 978-1-4398-4095-5, 2013. Yu, Angela: Introduction to Bayesian Decision Theory cogsci.ucsd.edu, 2013. Devin Soni: Introduction to Bayesian Networks, 2015. G. Nuti, L. Rugama, A.-I. Cross: Efficient Bayesian Decision Tree Algorithm, arXiv:1901.03214 stat.ML, 2019. M. Carlan, T. Kneib and N. Klein: Bayesian conditional transformation models, Journal of the American Statistical Association, 119(546):1360-1373, 2024. N. Klein: Distributional regression for data analysis , Annual Review of Statistics and Its Application, 11:321-346, 2024 C.Hoffmann and N.Klein: Marginally calibrated response distributions for end-to-end learning in autonomous driving, Annals of Applied Statistics, 17(2):1740-1763, 2023 Kassem Sbeyti, M., Karg, M., Wirth, C., Klein, N., & Albayrak, S. (2024, September). Cost-Sensitive Uncertainty-Based Failure Recognition for Object Detection. In Uncertainty in Artificial Intelligence (pp. 1890-1900). PMLR. M. K. Sbeyti, N. Klein, A. Nowzad, F. Sivrikaya and S. Albayrak: Building Blocks for Robust and Effective Semi-Supervised Real-World Object Detection pdf. To appear in Transactions on Machine Learning Research, 2025 Podcasts Learning, Teaching, and Building in the Age of AI Ep 42 of Vanishing Gradient, Jan 2025. O. Beige, G. Thäter: Risikoentscheidungsprozesse, Gespräch im Modellansatz Podcast, Folge 193, Fakultät für Mathematik, Karlsruher Institut für Technologie (KIT), 2019.

Send us a textIn this episode of Oldish: Conversations on Aging in the 21st Century, co-hosts Dr. Janet Price and Gregg Kaloust have a wide-ranging conversation with Liz Kitchens, author of Be Brave, Lose the Beige, Finding Your Sass After 60! Isn't it about time to be true to your more colorful self?You can find Liz Kitchens' book at www.bebravelosethebeige.comat your local bookstore, or at the Oldish Book Store on Bookshop.org. If you buy this or any of our favorite books from Bookshop, Oldish may get a small commission, and Bookshop will send a portion of the purchase price to an independent book store of your choice.Support the showConnect with Janet at https://drjanetprice.comGregg has a new substack newsletter where he's publishing writings old and new: poems, short pieces, works in progress, opinions and notes.You can email Gregg at gregg@kannoncom.com Gregg is now an ambassador for Revolin Sports Pickleball Paddles. If you are in the market for a new paddle, for any playing level, Revolin is made in the USA from sustainable materials, with the finest engineering and quality. Enter the code pickleballnomad at checkout for 10% discount. Gregg wears Tyrol pickleball shoes, the only company that makes shoes just for pickleball. He has been wearing the same pair of Velocity V model shoes for almost a year, and he plays a lot! Click here to purchase Tyrol Pickleball shoes (note, if you purchase Tyrol pickleball shoes after clicking this link Oldish may receive a commission. Thanks for helping to support our podcast!)Comments, suggestion, requests: oldish@kannoncom.comThanks to Mye Kaloustian for the music.

Rafael Peña, socio fundador de Olea Gestión, analiza el rendimiento de los bonos europeos y americanos en este momento de gran incertidumbre provocado por la política comercial de Donald Trump. Sobre esto, el invitado destaca que “el Bund ha rebotado del 2,40 al 2,80 por el incremento en el gasto en defensa”. Sobre el mercado en Estados Unidos, el analista destaca que “el comportamiento del bono americano ha sido muy errático como en el resto de las Bolsas”. Según el libro Beige de la FED y también Christine Lagarde, el mercado de los bonos ya está descontando un empeoramiento de las perspectivas económicas por la guerra comercial. Para Rafael Peña, “lo que están avanzando es que no ven claro la senda de recortes de tipos”, sobre todo por esta política arancelaria de Trump. Tampoco ayuda, según él, que China esté vendiendo gran cantidad denominados en dólares. Esto provoca gran volatilidad. ¿Con qué calendario trabaja Olea Gestión en cuanto a los próximos movimientos de tipos de interés? Desde Olea Gestión opinan que no va haber recorte de tipos en la próxima cita de la Reserva Federal, sobre todo por el conflicto entre el presidente estadounidense y el mandatario de la FED, Jerome Powell. En cuanto a Europa, el invitado opina que “la senda está más clara” ya que la inflación se acerca al 2%, lo que desemboque “seguramente en una bajada de tipos”

Rafael Peña, socio fundador de Olea Gestión, analiza el rendimiento de los bonos europeos y americanos en este momento de gran incertidumbre provocado por la política comercial de Donald Trump. Sobre esto, el invitado destaca que “el Bund ha rebotado del 2,40 al 2,80 por el incremento en el gasto en defensa”. Sobre el mercado en Estados Unidos, el analista destaca que “el comportamiento del bono americano ha sido muy errático como en el resto de las Bolsas”. Según el libro Beige de la FED y también Christine Lagarde, el mercado de los bonos ya está descontando un empeoramiento de las perspectivas económicas por la guerra comercial. Para Rafael Peña, “lo que están avanzando es que no ven claro la senda de recortes de tipos”, sobre todo por esta política arancelaria de Trump. Tampoco ayuda, según él, que China esté vendiendo gran cantidad denominados en dólares. Esto provoca gran volatilidad. ¿Con qué calendario trabaja Olea Gestión en cuanto a los próximos movimientos de tipos de interés? Desde Olea Gestión opinan que no va haber recorte de tipos en la próxima cita de la Reserva Federal, sobre todo por el conflicto entre el presidente estadounidense y el mandatario de la FED, Jerome Powell. En cuanto a Europa, el invitado opina que “la senda está más clara” ya que la inflación se acerca al 2%, lo que desemboque “seguramente en una bajada de tipos”

House Hunting, Self Help Over Fantasy F*ck Books & A Meaty Beige What?The Round UpFantasy F*ck Books & Self HelpHistory Or Her StoryRed Light Green LightHotlines Hosted on Acast. See acast.com/privacy for more information.

Season 3 continues, again with just the boys, as Mrs AuDHD rests... Episode 188 covers ADHD and self-care, which is very clearly one of James's strengths. As usual, Alex, the Psycho…….education Monkey vomits up the research behind the subject; Alex and James offer personal reflections on self-care , and in part three, answer listeners' questions. 'What has James lost, forgotten or mislaid this week?" returns with the scores level at 2-2 (we think). James is a bit out of his depth with this topic and the title of Alex's sex tape is ‘5 Shades of Beige'...Written by Alex Conner, Samantha Brown and James Brown.Produced by James Brown and JBHD Ltd.Social media contacts: @theadhdadultsMusic by James Brown and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Sessionz⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠If you would like to support the podcast you can subscribe to extra content here⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠You can submit a message, question or future topic to the podcast here⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠You can support and get help from the charity that the show raises money for here ⁠⁠⁠

In this episode of The Make It You Podcast, I'm answering your top spring style questions—from what bras actually work under those tricky dresses to how to break out of your beige wardrobe rut without losing your personal style. Whether you're refreshing your closet for spring or navigating a major life shift, this Q&A-style episode gives you real advice with zero overwhelm.

What's your partner's beige flag? "He finishes everything to about 90% and then leaves it. Painting projects, construction, you name it." "My boyfriend always hits the curb, anywhere." "Leaves the lights on everywhere in the house!" Learn more about your ad choices. Visit podcastchoices.com/adchoices

What's your partner's beige flag? "He finishes everything to about 90% and then leaves it. Painting projects, construction, you name it." "My boyfriend always hits the curb, anywhere." "Leaves the lights on everywhere in the house!" Learn more about your ad choices. Visit podcastchoices.com/adchoicesSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

NEW FREE RESOURCE: The “Bitch, You ARE The Authority” Challenge CLICK HERE! 

Es ist die spannendste Zeit des Uhren-Jahres: die Woche der Watches & Wonders. Eine Woche lang schaut die gesamte Uhrenwelt nach Genf, um zu sehen, welche Neuheiten die großen Uhrenhersteller herausbringen und welche Markttrends sich abzeichnen. Eine Marke steht dabei in den Tagen immer besonders im Fokus. Wie jedes Jahr geben wir Euch hier im UhrTalk einen tagesaktuellen Überblick der Rolex Neuheiten. Denn Chris hatte heute bereits alle neuen Modelle am Handgelenk und schildert seine Eindrücke. Wie ihm die neue Rolex Land-Dweller gefallen hat und warum das Kaliber 7135 eine technische Revolution ist, erfahrt Ihr in dieser Episode des UhrTalks. Wir wünschen wie immer gute Unterhaltung!Uhren in der Folge​Rolex Land-Dweller in 36mm und 40mm - erhältlich in Edelstahl / Rolesor, Everose Gold und Platin​Rolex GMT-Master II 126729VTNR mit Weißgold-Gehäuse und grünem Cerachrome Blatt​Rolex Perpetual 1908 in 18k Gelbgold mit siebenreihigem Gliederband​Neue Oyster Perpetual 28/ 31/ 34/ 36 und 41 mit neuen Blattvarianten - u.a. Pistachio, Beige und Lavendel​Rolex Daytona mit türkisblauem Blatt​Rolex GMT-Master II mit Tigereisen Blatt​Rolex Sky-Dweller in 18k Gelbgold mit grünem Blatt Die UhrTalk Community auf Telegram: https://t.me/uhrtalkAlle Episoden auf allen Plattformen:https://linktr.ee/uhrtalkDer UhrTalk auf Instagram:  / uhrtalk  #uhrtalk #audiowristcheck  Schreibt uns gerne auch einzeln über Instagram an:Wristwatches_de  / wristwatches_de  Mr. NiceWatch  / mr.nice.watch  

In episode 212, Dean and Deron discuss their recent plays (Monumental & The Vale of Eternity) and share their top beige board games. If you enjoy our podcast, please consider rating us and giving us a review. If you like our YouTube channel, please consider subscribing. If you have questions you would like us to answer on the podcast, please email us at meepletownmail@gmail.com. To support us further, check out www.patreon.com/meepletown or www.buymeacoffee.com/meepletown9. Join us on Discord: https://discord.gg/uasmBx326h  00:00     Intro 03:04     Monumental 09:31     The Vale of Eternity 17:00     Top 5 Beige Board Games Thanks for coming down to MeepleTown!

Story #423 – Beige Fagslaugh – Exec. Prods, nodebit, voidzero, Baron Spudthemitey, Lala – Fletcher talks to Lala about holes, rocks, whales and much more! Skittletits NOTES Whale Brush https://noauthority.social/@radix023/114180303916923263 Arizona Haze https://www.12news.com/article/news/education/board-censures-educators-for-hamilton-high-hazing-scandal-feb-2020/75-9f4d3472-1dc0-4adf-9db3-227c069ce5e8 GW High School https://www.kltv.com/2023/02/18/gladewater-holds-walk-down-memory-lane-tour-high-school-before-planned-redevelopment/

Steve Berger and Suave Golf's Kyle Surlow congregate to discuss Adam Schupack's article in Golfweek, discussing feedback from players after their initial tests of a rolled back golf ball. Before that, Kyle and Beige recap the Arnold Palmer Invitational and LIV Hong Kong. They also discuss this week in golf history and discuss some of this week's top headlines in golf. Hosts: Kyle Surlow and Steve 'Beige' Berger Proudly presented by SUAVE GOLF

In this episode, Kate, Jeff, and Nidhi dive into the latest developments shaping economics, media, technology, and entertainment in 2025. From tariffs impacting trade to the evolution of streaming platforms and AI innovation, we explore how industries are navigating uncertainty and embracing change. Highlights include insights from the US Federal Reserve Beige Book, Oscars viewership trends, YouTube's app redesign, and updates from the Morgan Stanley TMT Conference.Segments(00:00) Introduction(00:28) Global Economics Overview(01:32) Beige Book Insights(02:45) US Consumer Spending Trends(03:30) Tariffs and Price Increases(05:02) F1 Viewership Insights(07:13) European Media Owners Report(08:55) Linear TV Trends in Europe(09:56) Germany's Cable TV Shift(11:00) Streaming vs. Linear TV(14:52) Out-of-Home Advertising Growth(15:32) Programmatic Advertising in OOH(16:18) YouTube's Redesign & Aggregation(17:04) The Battle for the Living Room(19:41) Morgan Stanley TMT Conference Highlights(20:10) Fox's DTC Strategy(22:31) Netflix's Ad Business Growth(24:00) Disney's Focus on Advertising(24:34) Warner Bros. Content Strategy(25:55) Weekend Plans & Closing RemarksSome links:GroupM's This Year Next Year 2024 End of Year Report: https://www.groupm.com/this-year-next-year-2024-global-end-of-year-forecast/US Federal Reserve Beige Book: https://www.federalreserve.gov/monetarypolicy/files/BeigeBook_20250305.pdf Thanks for tuning in! If you enjoyed this episode, don't forget to hit the follow button, and rate us on your favorite podcast platform. And we'd love to hear from you—drop a comment or share your thoughts with us on LinkedIn.

Han har i livet pendlat mellan total kontroll och fullständig hopplöshet. Vem är Claes Eriksson utan sin berömda kreativitet? Lyssna på alla avsnitt i Sveriges Radio Play. Claes Eriksson är den kreativa motorn i Galenskaparna och After Shave, som i många decennier underhöll svenska folket med sin alldeles egna, underfundiga typ av humor. Med tv-serier som Macken och En himla många program, föreställningar som Stinsen brinner och filmer som Leif skapade dom humorhistoria.Claes Eriksson är manusförfattaren som legat bakom det mesta. Och på senare år har han fortsatt skapa även på egen hand. Men nu börjar idéerna ta slut – till och med för honom. Programledare: Martin WicklinProducent: Filip BohmKontakt: sondagsintervjun@sr.se

Things look different depending on the backdrop. Beige can look white--until you see it in the snow.Life lived is life learned. Every experience has facts, concepts and applications.  These arestories from the eclectic life of Lonnie Jones, Licensed ProfessionalCounselor, Minister, SWAT Team Chaplain, Outdoor Enthusiast and Quixotic Jedi. Support this podcast at https://anchor.fm/lonnie-jones/support--- Support this podcast:https://podcasters.spotify.com/pod/show/lonnie-jones/support  Please subscribe and share. Want lonnie to speak at yourevent?  Contact:  lonjones@bellsouth.net Check out YouTube for thelive eye view while the episode was being recorded.  Also look for archived lessons, Skits, and videosshowing/explaining some of the rope stuff we talk about.  YouTube.com/@LonnieJones Visit www.lonniejones.org  to find links tooriginal art, swag, 550guys and the following books:"Cognitive SpiritualDevelopment: A Christ Centered Approach to Spiritual Self Esteem";"Grappling With Life. Controlling Your Inside Space";"Pedagogue" The Youth Ministry Book by Lonnie Jones; "If I Werea Mouse" a children's story written and illustrated by Lonnie Jones;"The Selfish Rill, a story about a decision" A fantasy parableby Lonnie Jones.   T-shirts, stickers, prints and other art at www.teespring.com/stores/lonnie-jones-art https://lonnie-jones-art.creator-spring.com/listing/buy-podcast-swag?products=46  #www.worldchristian.org#tkminc2001@twlakes.net #www.hcu.edu #hpcitizensfoundation.orgFaulkner.edu/kgst  graduateenrollment@faulkner.edu   

Steve Berger and Suave Golf's Kyle Surlow discuss Beige's recent trip to Scottsdale and try to fiigure out what makes it so popular for stag parties. Then they discuss a new idea on how pro golf could update its dress code to make it more representative of the courses they play, recap the Mexico Open, Thailand LPGA event and the past week of TGL action. Then they touch on the recent meeting at the White House with Donand Trump, Tiger Woods, Jay Monahan and Yasir Al-Rumayyan, before trying to figure out if AimPoin is really an issue as it relates to slow play. Hosts: Kyle Surlow & Steve 'Beige' Berger Nice Grass Nice People is proudly presented by Suave Golf

Beige on Beige : "have you joined a cult?" Being Spurs, Spy Peacoat

This episode is sponsored by Taptap Send Remittance App.Fast Transfers & Great Rates . Use promo code CHEATCODERS to get a bonus added to your first send!DOWNLOAD TAPTAP SEND: ⁠https://taptapsend.onelink.me/Lrab/CHEATCODERS⁠ Cash Bonus:Australia: $30US/Canada: $20UK - 10GBP

Unexpected Horseradishing. Oh No! Where Did I Park My Phone?! Dropping Bombs Like a TIE Fighter. Craftsman Wounds vs Dumbass Wounds. Mom's Sewing Scissors Are Sacred. Cockpit toobs. What are you a HOBO? Bean juice in my cuts. A Broken President is Right Twice a Term. Frogpants Transparency Office. Badass vs Stupid. They only knew the doot doot. Nickel For Your Thoughts. Migration, All I've Ever Wanted with Tom. The Spag does not want to Go Low with Nicole and more on this episode of The Morning Stream. Hosted on Acast. See acast.com/privacy for more information.

Unexpected Horseradishing. Oh No! Where Did I Park My Phone?! Dropping Bombs Like a TIE Fighter. Craftsman Wounds vs Dumbass Wounds. Mom's Sewing Scissors Are Sacred. Cockpit toobs. What are you a HOBO? Bean juice in my cuts. A Broken President is Right Twice a Term. Frogpants Transparency Office. Badass vs Stupid. They only knew the doot doot. Nickel For Your Thoughts. Migration, All I've Ever Wanted with Tom. The Spag does not want to Go Low with Nicole and more on this episode of The Morning Stream. Hosted on Acast. See acast.com/privacy for more information.

In this episode I talk about the recent release of the Nike SB Dunk Low Pro B Parachute Beige.  Then I get into what SB's I'm suddenly feeling and some upcoming (and currently available) pairs. Thanks as always for listening AFS Squad! Shoutout to the Patrons: Kyle M, Kingsley G, Tristan S, Brian D, Joshua N, John You can support this podcast, get your name listed above and get early access to episodes (paid tier) at: Patreon.com/ActualFanOfSneakers

Ned and Meg talk about #fff8e7, the hexadecimal index of the color Cosmic Latte. And what is a cosmic latte? Why, it's the average color of all the light emitted in the universe, or close to it! We chat about how this color came to be known in 2002 and the guys who discovered it. We also talk about physics jokes, free will and the double slit experiment, deterministic universes, and coffee. Because of course we talk about coffee. Thanks for listening, wash your hands, and don't be a dick!

Do we have a doozy for you today! I am here sans Rob & Kevin, but not alone. Joined by some old friends from my days of wanting to be a rapper, first we have Josh Dahlquist aka Beige or nowyoureshattered on socials. Stick-and-poke tattoo master based out of the Seattle area. Beige is the lead vocalist of the group Triceracorn with producer IG88 aka Branden Clarke, who is guest number 2 on today's episode. The Bran Man is a wonderful producer and video game sound designer who you may recognize from five previous episodes.Guest #3 is none other than the swarthy pen wielding producer, Chance Random aka Kaleb Gubernik. Besides making some of the most intentional music in the Pacific Northwest, Kaleb is an amazing author writing short stories on his social media that are a beautiful screenshot of moments often overlooked and under appreciated in our daily lives. Our final guest is the wonderful Spike Daely. Linguistic expert and world traveler, Spike has used his abundance of life experiences to create some of the most intricate lyrics I've ever heard. We've got a few songs for you throughout the episode from our wonderful guests, as well as some brand new products! So stay tuned til the end. You can find all the social media and music links to these gentleboiz' work in the episode description. And make sure you go back through the Nostalgia Pit of old, and listen to the close to 10 episodes that these dudes have previously helped contribute to. Much love and thanks to them.EtsyPatreonLinktreeAraless - BandcampTriceracorn - BandcampChance Random - BandcampPretty Killers - And Whatnot...Instagram:@raggedchance@nowyoureshattered@ig88music@ruining_your.childhood@feral_williams@aralessbmn@strangeloopanimation@madshroommc

Jon and Rex talk about all things NY Sports

Two Amazon influencers are in a legal battle over whether or not one has appropriated the other's aesthetic. The Verge's Mia Sato breaks down the claims, and legal intellectual property expert Alexandra Roberts tells us what the lawsuit could mean for the future of content creation. This episode was produced by Hady Mawajdeh, edited by Amina Al-Sadi, fact-checked by Laura Bullard, engineered by Andrea Kristinsdottir and Rob Byers, and hosted by Noel King. Transcript at vox.com/today-explained-podcast Support Today, Explained by becoming a Vox Member today: http://www.vox.com/members Sydney Nicole Gifford and her mother, Laura, film a video promoting autumn decor from Amazon. Photo by Liam James Doyle.  Learn more about your ad choices. Visit podcastchoices.com/adchoices

Send us a text2024 - a bland, beige year for Emily and I. we decided beige years are boring but necessary. We talked about women turning 40 and the challenges but glory of it and somehow went on an appreciation tangent about our little brother, Craig from southern charm. I turn 40 this year and this podcast made it a little easier to look forward to it. Don't forget to subscribe wherever you listen to podcasts so you don't miss an episode!Follow me on socials: @justmewendyv on tiktok and instagram Join my Facebook group! https://www.facebook.com/share/qvAVdWrtDqC6UwFd/?mibextid=K35XfPJoin Patreon for more! https://www.patreon.com/rss/Hairapywithwendyv?auth=HHq03fSHTnN_10AgAjJXriabw6d3gaK4

Heroes of Humility is a show about social behavior as told through the eyes of real pals during their hangs. They use their comradery to contend with life's ordeals and podcast their meetings in the hopes it helps others do the same. After a hiatus due to real life difficulties, the HoHs return to laugh and find life's truths in the studio. In this one Red, Beige and Pierce tackle a classic human error in trying to achieve real happiness through the acquisition of things. How do our purchases affect us? Find Heroes of Humility on Instagram, Facebook, and YouTube. Follow on your podcast app for updates to avoid the critical mistake of missing the next show. 

This week on Dopey! After years of Pursuit we finally got chemist, author, TV host, Documentarian and Director - Hamilton Morris of Vice and HBO's trailblazing show Hamilton's Pharmacopia to come to my Dad's house! He tells of how he became a PSYCHONAUT and also why he hates the term PSYCHONAUT among tons of other stuff psychedelic and chemical.  PLUS Adversity Advantage host Doug Bopst is back to talk New Years Resolutions, fitness and more! On this brand new episode of the good old Dopey Show! There are a few Dopeywood Tickets left: https://buytickets.at/thedopeyfoundation/1484803 Join Patreon at: https://www.patreon.com/dopeypodcast Here is what AI said: Dopey Podcast Episode Show Notes:

What happens when you put a skinny boy on broadway and put beige pants on him? Logan and Sammie answer that question today as they discuss two iconic, but vastly different, musicals in Newsies and Spongebob the Musical! --- Support this podcast: https://podcasters.spotify.com/pod/show/logan-keller/support

Suave Golf's Kyle Surlow and Steve Berger convene to recap TNT's made-for-TV golf match between Rory McIlroy and Scottie Scheffler against Brooks Koepka and Bryson DeChambeau. Afterwards, the guys talk about what happens when you make an ace at the simulator club, does traditional ace etiquette apply? Then Beige shares his pretournament power rankings for this weekend's PNC Championship. Nice Grass Nice People is proudly presented by Suave Golf Hosts: Kyle Surlow & Steve 'Beige' Berger

• Our Black Friday sale is still on! Get 20% off annual Patreon support for The Bunker. Beige against the machine – Mocked by left and right in the 2010s, Centrist Dad had the last laugh. Now he bestrides our politics like gilet-clad colossus – he's even Prime Minister. But what makes him tick? How is he adjusting to power? What is Centrist Mum like? Authors of The Centrist Dad Handbook, friend of the pod Jason Hazeley and pal Nico Tatarowicz, talk to Andrew Harrison about the man at the centre of it all.  • Support us on Patreon for early episodes and more - www.patreon.com/bunkercast • We are sponsored by Indeed. Go to Indeed.com/bunker for £100 sponsored credit.   Presented by Group Editor Andrew Harrison. Audio production by Simon Williams and Robin Leeburn. Music by Kenny Dickinson. Managing Editor Jacob Jarvis. THE BUNKER is a Podmasters Production www.podmasters.co.uk Learn more about your ad choices. Visit podcastchoices.com/adchoices

What do we do with Cultural Beige? This week, Aaron and Joey talk about cultural homogenization, algorithms, local commerce, international culture, outliers and Charli XCX. They don't talk about Christian Bale or J. G. Ballard. references Empire Of The Sun "Walking On A Dream" Empire Of The Sun "Alive" @ The Hollywood Bowl 11/23/24 Sabrina Carpenter "Espresso" terroir Sammy McCormack: "How Janet Jackson Made 'If'" Sammy McCormack: "How Britney Spears Made 'Break The Ice'" Froggy Fresh Timbaland feat. OneRepublic "Apologize" Cam'ron and Mase: It Is What It Is 

Kyle and Beige are back to discuss each other's nicotine habits on the golf course, and golf's relationship with tobacco, among other things. They also discuss Scottie Scheffler winning the Hero World Challenge, Joaquin Niemann winning the Saudi International, terrifying golf travel bag stories, and Patrick Reed's comments about player tour eligibility. Hosts: Steve Berger & Kyle Surlow Nice Grass Nice People is proudly presented by SUAVE GOLF 

Kyle and Beige return after their respective sabbaticals to Spain and Bandon Dunes. Each recaps their time away before diving into the business of professional golf. Topics include Kevin Kisner being named NBC's lead golf analyst for 2025, Mollie Marcoux Samaan stepping down as LPGA commissioner, and Jay Monahan getting paid way too much money. Hosts: Steve Berger & Kyle Surlow Nice Grass Nice People is proudly presented by SUAVE GOLF  Signups are officially open for Suave Golf's 2025 Bandon Spring Jamboree - March 12-16, 2025. Learn more and signup.

We enter into the world of the Latter Day Saints by speed-rounding the origins of the church, including Joseph's exodus from the east coast and his soon after murder.Know of a missing woman's case that needs attention? Contact us at someplaceunderneith@gmail.com.Some Place Under Neith produced and edited by Ryan Connor and Last Podcast Network. Artwork by Kevin Conor Keller, intro song "Subway" by Lunachicks, remixed by Devin Castaldi-Micca. Subscribe to SiriusXM Podcasts+ on Apple Podcasts to listen to ad-free new episodes.

In today's episode of Beyond the Bump, the beautiful Luka McCabe from Boob to Food is back on the poddy! We're chatting all about toddlers eating family meals and sharing loads of tips and tricks that are super approachable and not too overwhelming. We get it—so many parents feel shame or guilt around what their toddlers eat (or don't eat!), and this episode is all about easing that pressure. Tune in for practical advice, plenty of laughs, and a fresh perspective on tackling toddler mealtimes with confidence!  Thanks for joining us, legends and as always we hope you enjoy this episode!   Resource Links: Boob to Food Chip & Dip Tray   Beyond the Bump is a podcast brought to you by Jayde Couldwell and Sophie Pearce! A podcast targeted at mums, just like you! A place to have real conversations with honest and authentic people.   Follow us on Instagram at @beyondthebump.podcast to stay up to date with behind the scenes and future episodes.  Join our Facebook chat Beyond the Bump Community Chats! Sign up to our newsletter HERE  Email us HERE   This episode is proudly sponsored by iL Tutto! Head over to iltutto.com.au. Use Presale20 before November 19th for the exclusive listener discount, or catch the big sale starting on the 20th. But don't wait too long—this is one of those sales where things fly off the shelves!

0:09-Introductions 4:00-Petty 101 5:20-Sweet Feet 16:00-Pierre petty bouncing 20:00-Intermission 21:00-Jules vs Abdul 27:00-Ginn Mill 31:30-Beige and avocados 37:00-Pierre petty with Bj 42:00-Trap house Jules 48:30-Brothers being petty 53:20-Gift No Bloopers Follow the Podcast: YouTube: What Can Go Wrong Podcast Instagram: WhatCanGoWrongPodcast TikTok: WhatCanGoWrongPodcast Snapchat: wcgwcast Twitter: @wcgwcast Follow the Co-Host: Instagram: Lodo_Watcher TikTok: Lodo_Watcher

0:09-Introductions 4:00-Petty 101 5:20-Sweet Feet 16:00-Pierre petty bouncing 20:00-Intermission 21:00-Jules vs Abdul 27:00-Ginn Mill 31:30-Beige and avocados 37:00-Pierre petty with Bj 42:00-Trap house Jules 48:30-Brothers being petty 53:20-Gift No Bloopers Follow the Podcast: YouTube: What Can Go Wrong Podcast Instagram: WhatCanGoWrongPodcast TikTok: WhatCanGoWrongPodcast Snapchat: wcgwcast Twitter: @wcgwcast Follow the Co-Host: Instagram: Lodo_Watcher TikTok: Lodo_Watcher

Steve and Kyle converge to talk all about Beige's recent golf trip to Ocean City, Maryland, discuss Dream Golf setting up shop in the Florida panhandle, and try to figure out if Bernhard Langer is one of the greatest golfers of all time.   Hosts: Steve Berger & Kyle Surlow Nice Grass Nice People is proudly presented by SUAVE GOLF  Signups are officially open for Suave Golf's 2025 Bandon Spring Jamboree - March 12-16, 2025. Learn more and signup.

You've probably found yourself reaching for this wine on a regular basis. You don't have to think about it. You order it when you aren't sure what else you want. It's safe. It's comfy. And you don't need to put much effort into it. BUT, wine is sexy friends and you don't want to find yourself in the boring rut of always reaching for this wine. Want to know what it is and how you can break out of this habit? Press play now and start listening to this week's episode! And don't forget to hit subscribe so that you never miss an episode of The Wine CEO Podcast! Today's episode is best enjoyed on my youtube channel: https://youtu.be/Iei_CETLKlM ------ Sign up for The Wine CEO newsletter and get a free guide to Food & Wine Pairing: thewineceo.com Email: Sarah@thewineceo.com Instagram: @thewineceo  

Guy Adami and Liz Young Thomas from SoFi dissect the latest market trends, including rising 10-year yields and their impact on housing. They explore Goldman's surprising decade-long bearish forecast for U.S. stocks and discuss upcoming earnings from major companies. The hosts also touch on election speculations, China's economic stimulus efforts, and their implications on markets. Key highlights include in-depth analyses of the gold market, energy stocks, and the relationship between Bitcoin trends and tech stocks. Subscribe to our newsletter: https://riskreversalmedia.beehiiv.com/subscribe — About the Show: On The Tape is a weekly podcast with CNBC Fast Money's Guy Adami, Dan Nathan and Danny Moses. They're offering takes on the biggest market-moving headlines of the week, trade ideas, in-depth analysis, tips and advice. Each episode, they are joined by prominent Wall Street participants to help viewers make smarter investment decisions. Bear market, bull market, recession, inflation or deflation… we're here to help guide your portfolio into the green. Risk Reversal brings you years of experience from former Wall Street insiders trading stocks to experts in the commodity market. — Check out our show notes here See what adding futures can do for you at cmegroup.com/onthetape. — Shoot us an email at OnTheTape@riskreversal.com with any feedback, suggestions, or questions for us to answer on the pod and follow us @OnTheTapePod on Twitter or @riskreversalmedia on Threads — We're on social: Follow @GuyAdami on Twitter Follow Danny Moses @DMoses34 on Twitter Follow Liz Thomas @LizThomasStrat on Twitter Follow us on Instagram @RiskReversalMedia Subscribe to our YouTube page The financial opinions expressed in Risk Reversal content are for information purposes only. The opinions expressed by the hosts and participants are not an attempt to influence specific trading behavior, investments, or strategies. Past performance does not necessarily predict future outcomes. No specific results or profits are assured when relying on Risk Reversal. Before making any investment or trade, evaluate its suitability for your circumstances and consider consulting your own financial or investment advisor. The financial products discussed in Risk Reversal carry a high level of risk and may not be appropriate for many investors. If you have uncertainties, it's advisable to seek professional advice. Remember that trading involves a risk to your capital, so only invest money that you can afford to lose. Derivatives are not suitable for all investors and involve the risk of losing more than the amount originally deposited and any profit you might have made. This communication is not a recommendation or offer to buy, sell or retain any specific investment or service.

The holidays are almost upon us... come join our Healthy Through the Holidays Program (starts Nov. 1st) to get workouts, recipes, and the community you need to help you stay on track during the busy holiday season! Join here:https://healthycatholicmoms.teachable.com/p/chasing-greatnessTry my FREE 3 Day Pregnancy Workout Challenge here:https://mailchi.mp/3544a2978243/threedaypregnancyprogramGet the FREE GUIDE to Exercising Postpartum!https://mailchi.mp/4e93de16eeaf/q047rmh7veMy pregnancy and postpartum programs are ALWAYS available right here:https://www.healthycatholicmoms.com/services/Get your FREE 3 Steps to Fat Loss Checklist instantly here: https://mailchi.mp/83c78e2a2d39/5fscogioxyShop Healthy Catholic Moms merch here! Mugs, shirts, and more...https://www.healthycatholicmoms.com/shop/Join my email list here: https://www.healthycatholicmoms.com/____________________________________________________________________________________Schedule a 30 minute coaching call with me here:https://www.healthycatholicmoms.com/services/The BEST organic meat (delivered right to your door!).Try this beautiful family-owned farm, Blustery Bovine (our family LOVES it!).Use code HEALTHYCATHOLICMOMS10 for $60 off!https://www.blusterybovine.com/new-products____________________________________________________________________________________For recipes, workouts, and tips- follow me on:Instagram: https://www.instagram.com/healthycatholicmoms/Facebook: https://www.facebook.com/healthycatholicmomsEmail: brittany@healthycatholicmoms.com

Today we dove into Red, Beige and Green “Flags” in a relationship! We talked about our personal “flags” and what we think you should look out for when dating someone and then went through a list of “flags” you all sent in and wow, there were some funny ones haha Have you ever ended a relationship because of glaring red flags? Let us know in the comments!  Love you guys! Shawn & Andrew Listen to our “Worst Dates” Episode ▶ https://podcasts.apple.com/us/podcast/reacting-to-your-worst-date-stories-of-all-time/id1485740243?i=1000664610493 Follow our podcast Instagram ▶ https://www.instagram.com/shawnandandrewpods/ Subscribe to our newsletter ▶ https://www.familymade.com/newsletter Follow My Instagram ▶ https://www.instagram.com/ShawnJohnson Follow My Tik Tok ▶ https://www.tiktok.com/@shawnjohnson Shop My LTK Page ▶ https://www.shopltk.com/explore/shawnjohnson  Like the Facebook page! ▶ https://www.facebook.com/ShawnJohnson Follow Andrew's Instagram ▶ https://www.instagram.com/AndrewDEast Andrew's Tik Tok ▶ https://www.tiktok.com/@andrewdeast?lang=en Learn more about your ad choices. Visit megaphone.fm/adchoices

Step into the world of creativity with Beige, the ultimate Uber for Creatives!

Last week, Jen saved the show by lending her comfort bra to Kristin….and now Kristin can't stop making fun of it. Tune in as we talk about how important it is to be prepared and proactive…not just while traveling but with our health too. Get your boobs checked ladies, and enjoy today's episode! Hosted on Acast. See acast.com/privacy for more information.

Lev is joined by comedians Derek Drescher and Harry Settel! They discuss why Harry decided to drop his stage name, Lev's weight loss competition, getting into golf, their NFL picks, and so much more!The Lev Fer Show is a comedy podcast hosted by New York City comedian Lev Fer. Join Lev as he invites his favorite comedian friends on twice a week to chop it up and laugh about any and everything.Original Air Date: 9.4.24SEE LEV LIVEhttps://levfercomedy.com/LIVESTREAM Mondays & Fridays at 6:30PM E ONLY on GaS DigitalOr catch The YouTube Premiere the following Friday at 12PM Ehttps://GaSDigital.com/LIVESign up to the Gas Digital Network with promo code LEV and get a discount on your membership which includes access to full episodes of all our shows days before the public, FULL HD livestreams, join live chat, and the entire GaS Digital library, On-Demand and in HD!https://GaSDigital.comFOLLOWThe Lev Fer Showhttps://instagram.com/levfershowLev FerInstagram: https://instagram.com/levferTwitter: https://twitter.com/thelevfershowGaS Digital NetworkInstagram: https://instagram.com/gasdigitalTwitter: https://twitter.com/gasdigitalSEND LEV MAIL:GaS Digital Studios Attn: Lev Fer151 1st Ave # 311New York, NY 10003#LevFer #GaSDigital #Podcast #ComedySee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.