• NVIDIA Scores Consecutive Win for End-to-End Autonomous Driving Grand Challenge at CVPR

    NVIDIA was today named an Autonomous Grand Challenge winner at the Computer Vision and Pattern Recognitionconference, held this week in Nashville, Tennessee. The announcement was made at the Embodied Intelligence for Autonomous Systems on the Horizon Workshop.
    This marks the second consecutive year that NVIDIA’s topped the leaderboard in the End-to-End Driving at Scale category and the third year in a row winning an Autonomous Grand Challenge award at CVPR.
    The theme of this year’s challenge was “Towards Generalizable Embodied Systems” — based on NAVSIM v2, a data-driven, nonreactive autonomous vehiclesimulation framework.
    The challenge offered researchers the opportunity to explore ways to handle unexpected situations, beyond using only real-world human driving data, to accelerate the development of smarter, safer AVs.
    Generating Safe and Adaptive Driving Trajectories
    Participants of the challenge were tasked with generating driving trajectories from multi-sensor data in a semi-reactive simulation, where the ego vehicle’s plan is fixed at the start, but background traffic changes dynamically.
    Submissions were evaluated using the Extended Predictive Driver Model Score, which measures safety, comfort, compliance and generalization across real-world and synthetic scenarios — pushing the boundaries of robust and generalizable autonomous driving research.
    The NVIDIA AV Applied Research Team’s key innovation was the Generalized Trajectory Scoringmethod, which generates a variety of trajectories and progressively filters out the best one.
    GTRS model architecture showing a unified system for generating and scoring diverse driving trajectories using diffusion- and vocabulary-based trajectories.
    GTRS introduces a combination of coarse sets of trajectories covering a wide range of situations and fine-grained trajectories for safety-critical situations, created using a diffusion policy conditioned on the environment. GTRS then uses a transformer decoder distilled from perception-dependent metrics, focusing on safety, comfort and traffic rule compliance. This decoder progressively filters out the most promising trajectory candidates by capturing subtle but critical differences between similar trajectories.
    This system has proved to generalize well to a wide range of scenarios, achieving state-of-the-art results on challenging benchmarks and enabling robust, adaptive trajectory selection in diverse and challenging driving conditions.

    NVIDIA Automotive Research at CVPR 
    More than 60 NVIDIA papers were accepted for CVPR 2025, spanning automotive, healthcare, robotics and more.
    In automotive, NVIDIA researchers are advancing physical AI with innovation in perception, planning and data generation. This year, three NVIDIA papers were nominated for the Best Paper Award: FoundationStereo, Zero-Shot Monocular Scene Flow and Difix3D+.
    The NVIDIA papers listed below showcase breakthroughs in stereo depth estimation, monocular motion understanding, 3D reconstruction, closed-loop planning, vision-language modeling and generative simulation — all critical to building safer, more generalizable AVs:

    Diffusion Renderer: Neural Inverse and Forward Rendering With Video Diffusion ModelsFoundationStereo: Zero-Shot Stereo MatchingZero-Shot Monocular Scene Flow Estimation in the WildDifix3D+: Improving 3D Reconstructions With Single-Step Diffusion Models3DGUT: Enabling Distorted Cameras and Secondary Rays in Gaussian Splatting
    Closed-Loop Supervised Fine-Tuning of Tokenized Traffic Models
    Zero-Shot 4D Lidar Panoptic Segmentation
    NVILA: Efficient Frontier Visual Language Models
    RADIO Amplified: Improved Baselines for Agglomerative Vision Foundation Models
    OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving With Counterfactual Reasoning

    Explore automotive workshops and tutorials at CVPR, including:

    Workshop on Data-Driven Autonomous Driving Simulation, featuring Marco Pavone, senior director of AV research at NVIDIA, and Sanja Fidler, vice president of AI research at NVIDIA
    Workshop on Autonomous Driving, featuring Laura Leal-Taixe, senior research manager at NVIDIA
    Workshop on Open-World 3D Scene Understanding with Foundation Models, featuring Leal-Taixe
    Safe Artificial Intelligence for All Domains, featuring Jose Alvarez, director of AV applied research at NVIDIA
    Workshop on Foundation Models for V2X-Based Cooperative Autonomous Driving, featuring Pavone and Leal-Taixe
    Workshop on Multi-Agent Embodied Intelligent Systems Meet Generative AI Era, featuring Pavone
    LatinX in CV Workshop, featuring Leal-Taixe
    Workshop on Exploring the Next Generation of Data, featuring Alvarez
    Full-Stack, GPU-Based Acceleration of Deep Learning and Foundation Models, led by NVIDIA
    Continuous Data Cycle via Foundation Models, led by NVIDIA
    Distillation of Foundation Models for Autonomous Driving, led by NVIDIA

    Explore the NVIDIA research papers to be presented at CVPR and watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang.
    Learn more about NVIDIA Research, a global team of hundreds of scientists and engineers focused on topics including AI, computer graphics, computer vision, self-driving cars and robotics.
    The featured image above shows how an autonomous vehicle adapts its trajectory to navigate an urban environment with dynamic traffic using the GTRS model.
    #nvidia #scores #consecutive #win #endtoend
    NVIDIA Scores Consecutive Win for End-to-End Autonomous Driving Grand Challenge at CVPR
    NVIDIA was today named an Autonomous Grand Challenge winner at the Computer Vision and Pattern Recognitionconference, held this week in Nashville, Tennessee. The announcement was made at the Embodied Intelligence for Autonomous Systems on the Horizon Workshop. This marks the second consecutive year that NVIDIA’s topped the leaderboard in the End-to-End Driving at Scale category and the third year in a row winning an Autonomous Grand Challenge award at CVPR. The theme of this year’s challenge was “Towards Generalizable Embodied Systems” — based on NAVSIM v2, a data-driven, nonreactive autonomous vehiclesimulation framework. The challenge offered researchers the opportunity to explore ways to handle unexpected situations, beyond using only real-world human driving data, to accelerate the development of smarter, safer AVs. Generating Safe and Adaptive Driving Trajectories Participants of the challenge were tasked with generating driving trajectories from multi-sensor data in a semi-reactive simulation, where the ego vehicle’s plan is fixed at the start, but background traffic changes dynamically. Submissions were evaluated using the Extended Predictive Driver Model Score, which measures safety, comfort, compliance and generalization across real-world and synthetic scenarios — pushing the boundaries of robust and generalizable autonomous driving research. The NVIDIA AV Applied Research Team’s key innovation was the Generalized Trajectory Scoringmethod, which generates a variety of trajectories and progressively filters out the best one. GTRS model architecture showing a unified system for generating and scoring diverse driving trajectories using diffusion- and vocabulary-based trajectories. GTRS introduces a combination of coarse sets of trajectories covering a wide range of situations and fine-grained trajectories for safety-critical situations, created using a diffusion policy conditioned on the environment. GTRS then uses a transformer decoder distilled from perception-dependent metrics, focusing on safety, comfort and traffic rule compliance. This decoder progressively filters out the most promising trajectory candidates by capturing subtle but critical differences between similar trajectories. This system has proved to generalize well to a wide range of scenarios, achieving state-of-the-art results on challenging benchmarks and enabling robust, adaptive trajectory selection in diverse and challenging driving conditions. NVIDIA Automotive Research at CVPR  More than 60 NVIDIA papers were accepted for CVPR 2025, spanning automotive, healthcare, robotics and more. In automotive, NVIDIA researchers are advancing physical AI with innovation in perception, planning and data generation. This year, three NVIDIA papers were nominated for the Best Paper Award: FoundationStereo, Zero-Shot Monocular Scene Flow and Difix3D+. The NVIDIA papers listed below showcase breakthroughs in stereo depth estimation, monocular motion understanding, 3D reconstruction, closed-loop planning, vision-language modeling and generative simulation — all critical to building safer, more generalizable AVs: Diffusion Renderer: Neural Inverse and Forward Rendering With Video Diffusion ModelsFoundationStereo: Zero-Shot Stereo MatchingZero-Shot Monocular Scene Flow Estimation in the WildDifix3D+: Improving 3D Reconstructions With Single-Step Diffusion Models3DGUT: Enabling Distorted Cameras and Secondary Rays in Gaussian Splatting Closed-Loop Supervised Fine-Tuning of Tokenized Traffic Models Zero-Shot 4D Lidar Panoptic Segmentation NVILA: Efficient Frontier Visual Language Models RADIO Amplified: Improved Baselines for Agglomerative Vision Foundation Models OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving With Counterfactual Reasoning Explore automotive workshops and tutorials at CVPR, including: Workshop on Data-Driven Autonomous Driving Simulation, featuring Marco Pavone, senior director of AV research at NVIDIA, and Sanja Fidler, vice president of AI research at NVIDIA Workshop on Autonomous Driving, featuring Laura Leal-Taixe, senior research manager at NVIDIA Workshop on Open-World 3D Scene Understanding with Foundation Models, featuring Leal-Taixe Safe Artificial Intelligence for All Domains, featuring Jose Alvarez, director of AV applied research at NVIDIA Workshop on Foundation Models for V2X-Based Cooperative Autonomous Driving, featuring Pavone and Leal-Taixe Workshop on Multi-Agent Embodied Intelligent Systems Meet Generative AI Era, featuring Pavone LatinX in CV Workshop, featuring Leal-Taixe Workshop on Exploring the Next Generation of Data, featuring Alvarez Full-Stack, GPU-Based Acceleration of Deep Learning and Foundation Models, led by NVIDIA Continuous Data Cycle via Foundation Models, led by NVIDIA Distillation of Foundation Models for Autonomous Driving, led by NVIDIA Explore the NVIDIA research papers to be presented at CVPR and watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang. Learn more about NVIDIA Research, a global team of hundreds of scientists and engineers focused on topics including AI, computer graphics, computer vision, self-driving cars and robotics. The featured image above shows how an autonomous vehicle adapts its trajectory to navigate an urban environment with dynamic traffic using the GTRS model. #nvidia #scores #consecutive #win #endtoend
    BLOGS.NVIDIA.COM
    NVIDIA Scores Consecutive Win for End-to-End Autonomous Driving Grand Challenge at CVPR
    NVIDIA was today named an Autonomous Grand Challenge winner at the Computer Vision and Pattern Recognition (CVPR) conference, held this week in Nashville, Tennessee. The announcement was made at the Embodied Intelligence for Autonomous Systems on the Horizon Workshop. This marks the second consecutive year that NVIDIA’s topped the leaderboard in the End-to-End Driving at Scale category and the third year in a row winning an Autonomous Grand Challenge award at CVPR. The theme of this year’s challenge was “Towards Generalizable Embodied Systems” — based on NAVSIM v2, a data-driven, nonreactive autonomous vehicle (AV) simulation framework. The challenge offered researchers the opportunity to explore ways to handle unexpected situations, beyond using only real-world human driving data, to accelerate the development of smarter, safer AVs. Generating Safe and Adaptive Driving Trajectories Participants of the challenge were tasked with generating driving trajectories from multi-sensor data in a semi-reactive simulation, where the ego vehicle’s plan is fixed at the start, but background traffic changes dynamically. Submissions were evaluated using the Extended Predictive Driver Model Score, which measures safety, comfort, compliance and generalization across real-world and synthetic scenarios — pushing the boundaries of robust and generalizable autonomous driving research. The NVIDIA AV Applied Research Team’s key innovation was the Generalized Trajectory Scoring (GTRS) method, which generates a variety of trajectories and progressively filters out the best one. GTRS model architecture showing a unified system for generating and scoring diverse driving trajectories using diffusion- and vocabulary-based trajectories. GTRS introduces a combination of coarse sets of trajectories covering a wide range of situations and fine-grained trajectories for safety-critical situations, created using a diffusion policy conditioned on the environment. GTRS then uses a transformer decoder distilled from perception-dependent metrics, focusing on safety, comfort and traffic rule compliance. This decoder progressively filters out the most promising trajectory candidates by capturing subtle but critical differences between similar trajectories. This system has proved to generalize well to a wide range of scenarios, achieving state-of-the-art results on challenging benchmarks and enabling robust, adaptive trajectory selection in diverse and challenging driving conditions. NVIDIA Automotive Research at CVPR  More than 60 NVIDIA papers were accepted for CVPR 2025, spanning automotive, healthcare, robotics and more. In automotive, NVIDIA researchers are advancing physical AI with innovation in perception, planning and data generation. This year, three NVIDIA papers were nominated for the Best Paper Award: FoundationStereo, Zero-Shot Monocular Scene Flow and Difix3D+. The NVIDIA papers listed below showcase breakthroughs in stereo depth estimation, monocular motion understanding, 3D reconstruction, closed-loop planning, vision-language modeling and generative simulation — all critical to building safer, more generalizable AVs: Diffusion Renderer: Neural Inverse and Forward Rendering With Video Diffusion Models (Read more in this blog.) FoundationStereo: Zero-Shot Stereo Matching (Best Paper nominee) Zero-Shot Monocular Scene Flow Estimation in the Wild (Best Paper nominee) Difix3D+: Improving 3D Reconstructions With Single-Step Diffusion Models (Best Paper nominee) 3DGUT: Enabling Distorted Cameras and Secondary Rays in Gaussian Splatting Closed-Loop Supervised Fine-Tuning of Tokenized Traffic Models Zero-Shot 4D Lidar Panoptic Segmentation NVILA: Efficient Frontier Visual Language Models RADIO Amplified: Improved Baselines for Agglomerative Vision Foundation Models OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving With Counterfactual Reasoning Explore automotive workshops and tutorials at CVPR, including: Workshop on Data-Driven Autonomous Driving Simulation, featuring Marco Pavone, senior director of AV research at NVIDIA, and Sanja Fidler, vice president of AI research at NVIDIA Workshop on Autonomous Driving, featuring Laura Leal-Taixe, senior research manager at NVIDIA Workshop on Open-World 3D Scene Understanding with Foundation Models, featuring Leal-Taixe Safe Artificial Intelligence for All Domains, featuring Jose Alvarez, director of AV applied research at NVIDIA Workshop on Foundation Models for V2X-Based Cooperative Autonomous Driving, featuring Pavone and Leal-Taixe Workshop on Multi-Agent Embodied Intelligent Systems Meet Generative AI Era, featuring Pavone LatinX in CV Workshop, featuring Leal-Taixe Workshop on Exploring the Next Generation of Data, featuring Alvarez Full-Stack, GPU-Based Acceleration of Deep Learning and Foundation Models, led by NVIDIA Continuous Data Cycle via Foundation Models, led by NVIDIA Distillation of Foundation Models for Autonomous Driving, led by NVIDIA Explore the NVIDIA research papers to be presented at CVPR and watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang. Learn more about NVIDIA Research, a global team of hundreds of scientists and engineers focused on topics including AI, computer graphics, computer vision, self-driving cars and robotics. The featured image above shows how an autonomous vehicle adapts its trajectory to navigate an urban environment with dynamic traffic using the GTRS model.
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  • Scientists in Canada have developed a biotint that simulates lung tissue. It's part of ongoing research in 3D bioprinting, which seems to be slowly evolving in the field of personalized medicine. A team from McMaster University in Ontario worked on this, aiming to replicate mechanical properties. Not sure how exciting this really is, but it's something, I guess.

    #Bioprinting #LungTissue #PersonalizedMedicine #McMasterUniversity #Research
    Scientists in Canada have developed a biotint that simulates lung tissue. It's part of ongoing research in 3D bioprinting, which seems to be slowly evolving in the field of personalized medicine. A team from McMaster University in Ontario worked on this, aiming to replicate mechanical properties. Not sure how exciting this really is, but it's something, I guess. #Bioprinting #LungTissue #PersonalizedMedicine #McMasterUniversity #Research
    Científicos en Canadá desarrollan una biotinta que simula el tejido pulmonar
    La bioimpresión 3D sigue estudiándose y evolucionando como una herramienta en el ámbito de la medicina personalizada. En esta línea, un equipo de investigadores de la Universidad McMaster, en Ontario, ha desarrollado una nueva biotinta que replica la
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  • Exciting news on the horizon! Scientists have developed a groundbreaking 3D material that can capture CO₂, inspired by the incredible cyanobacteria that have thrived on our planet for billions of years! This innovative solution reminds us that nature often holds the keys to our technological challenges. Let's embrace this symbiotic relationship and work towards a cleaner, greener future together!

    Every step we take towards sustainability is a step towards a brighter tomorrow! Let's be the change we wish to see!

    #Sustainability #Innovation #GreenTechnology #Cyanobacteria #FutureIsBright
    🌍✨ Exciting news on the horizon! Scientists have developed a groundbreaking 3D material that can capture CO₂, inspired by the incredible cyanobacteria that have thrived on our planet for billions of years! 💚 This innovative solution reminds us that nature often holds the keys to our technological challenges. Let's embrace this symbiotic relationship and work towards a cleaner, greener future together! 🌱💪 Every step we take towards sustainability is a step towards a brighter tomorrow! Let's be the change we wish to see! 🌟 #Sustainability #Innovation #GreenTechnology #Cyanobacteria #FutureIsBright
    Desarrollan un nuevo material 3D que captura CO₂
    En innumerables ocasiones las respuestas a los desafíos tecnológicos no se han encontrado en un laboratorio, sino en la naturaleza. Las cianobacterias, unos microorganismos que habitan la Tierra desde hace miles de millones de años, podrían ser la re
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  • Hey everyone!

    Today, I want to dive into something truly fascinating and groundbreaking that’s making waves in the tech world: **superintelligence**! The recent news about Meta's investment in Scale AI and their ambitious plans to create a superintelligence AI research lab is incredibly exciting! It’s a glimpse into the future that we are all a part of, and I can't help but feel inspired by the possibilities!

    So, what exactly is superintelligence? In essence, it refers to a form of artificial intelligence that surpasses human intelligence in virtually every aspect. Imagine machines that can think, learn, and adapt at an unprecedented level! The potential for positive change and innovation is enormous! Just think about how this technology could transform industries, solve complex problems, and even improve our everyday lives!

    Meta is taking a bold step by investing in this field, and it shows just how serious they are about shaping our future. Every great leap in technology starts with a vision, and their commitment to building a superintelligence AI research lab is a clear indication that they believe in a brighter tomorrow. Just imagine the breakthroughs that could come from this initiative! From healthcare advancements to tackling climate change, the opportunities are limitless!

    What I find truly inspiring is how this move encourages collaboration among brilliant minds across the globe. The quest for superintelligence is not just about creating smart machines; it’s about bringing together diverse perspectives, ideas, and skills to push the boundaries of what’s possible! Let’s celebrate this spirit of innovation and teamwork!

    And here’s the most exciting part: You don’t have to be a tech expert to be a part of this journey! Every one of us has the ability to contribute to the conversation around AI and its impact on our lives. Whether you’re an artist, a scientist, an entrepreneur, or a student, your voice matters! Let’s dream big and think about how we can leverage technology to create a better world for everyone!

    As we move forward, let’s keep the dialogue open and embrace the changes that superintelligence might bring. Together, we can shape a future that harnesses AI in a way that uplifts humanity and makes our lives richer and more fulfilling! So, let’s stay positive, curious, and engaged! The future is bright, and it’s ours to create!

    Stay tuned for more updates, and let’s keep this conversation going! What are your thoughts on superintelligence? How do you envision it impacting our world? Share your ideas below!

    #Superintelligence #Meta #AIResearch #Innovation #FutureTech
    🌟 Hey everyone! 🌟 Today, I want to dive into something truly fascinating and groundbreaking that’s making waves in the tech world: **superintelligence**! 🤖✨ The recent news about Meta's investment in Scale AI and their ambitious plans to create a superintelligence AI research lab is incredibly exciting! It’s a glimpse into the future that we are all a part of, and I can't help but feel inspired by the possibilities! 🚀 So, what exactly is superintelligence? 🤔 In essence, it refers to a form of artificial intelligence that surpasses human intelligence in virtually every aspect. Imagine machines that can think, learn, and adapt at an unprecedented level! The potential for positive change and innovation is enormous! 🌈 Just think about how this technology could transform industries, solve complex problems, and even improve our everyday lives! 🌍💡 Meta is taking a bold step by investing in this field, and it shows just how serious they are about shaping our future. Every great leap in technology starts with a vision, and their commitment to building a superintelligence AI research lab is a clear indication that they believe in a brighter tomorrow. 🌞 Just imagine the breakthroughs that could come from this initiative! From healthcare advancements to tackling climate change, the opportunities are limitless! 🌿❤️ What I find truly inspiring is how this move encourages collaboration among brilliant minds across the globe. The quest for superintelligence is not just about creating smart machines; it’s about bringing together diverse perspectives, ideas, and skills to push the boundaries of what’s possible! Let’s celebrate this spirit of innovation and teamwork! 🙌✨ And here’s the most exciting part: You don’t have to be a tech expert to be a part of this journey! Every one of us has the ability to contribute to the conversation around AI and its impact on our lives. Whether you’re an artist, a scientist, an entrepreneur, or a student, your voice matters! 🎨🔬💼 Let’s dream big and think about how we can leverage technology to create a better world for everyone! 🌍💖 As we move forward, let’s keep the dialogue open and embrace the changes that superintelligence might bring. Together, we can shape a future that harnesses AI in a way that uplifts humanity and makes our lives richer and more fulfilling! So, let’s stay positive, curious, and engaged! The future is bright, and it’s ours to create! 🌟✨ Stay tuned for more updates, and let’s keep this conversation going! What are your thoughts on superintelligence? How do you envision it impacting our world? Share your ideas below! 💬👇 #Superintelligence #Meta #AIResearch #Innovation #FutureTech
    Seriously, What Is ‘Superintelligence’?
    In this episode of Uncanny Valley, we talk about Meta’s recent investment in Scale AI and its move to build a superintelligence AI research lab. So we ask: What is superintelligence anyway?
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  • What in the world are we doing? Scientists at the Massachusetts Institute of Technology have come up with this mind-boggling idea of creating an AI model that "never stops learning." Seriously? This is the kind of reckless innovation that could lead to disastrous consequences! Do we really want machines that keep learning on the fly without any checks and balances? Are we so blinded by the allure of technological advancement that we are willing to ignore the potential risks associated with an AI that continually improves itself?

    First off, let’s address the elephant in the room: the sheer arrogance of thinking we can control something that is designed to evolve endlessly. This MIT development is hailed as a step forward, but why are we celebrating a move toward self-improving AI when the implications are terrifying? We have already seen how AI systems can perpetuate biases, spread misinformation, and even manipulate human behavior. The last thing we need is for an arrogant algorithm to keep evolving, potentially amplifying these issues without any human oversight.

    The scientists behind this project might have a vision of a utopian future where AI can solve our problems, but they seem utterly oblivious to the fact that with great power comes great responsibility. Who is going to regulate this relentless learning process? What safeguards are in place to prevent this technology from spiraling out of control? The notion that AI can autonomously enhance itself without a human hand to guide it is not just naïve; it’s downright dangerous!

    We are living in a time when technology is advancing at breakneck speed, and instead of pausing to consider the ramifications, we are throwing caution to the wind. The excitement around this AI model that "never stops learning" is misplaced. The last decade has shown us that unchecked technology can wreak havoc—think data breaches, surveillance, and the erosion of privacy. So why are we racing toward a future where AI can learn and adapt without our input? Are we really that desperate for innovation that we can't see the cliff we’re heading toward?

    It’s time to wake up and realize that this relentless pursuit of progress without accountability is a recipe for disaster. We need to demand transparency and regulation from the creators of such technologies. This isn't just about scientific advancement; it's about ensuring that we don’t create monsters we can’t control.

    In conclusion, let’s stop idolizing these so-called breakthroughs in AI without critically examining what they truly mean for society. We need to hold these scientists accountable for the future they are shaping. We must question the ethics of an AI that never stops learning and remind ourselves that just because we can, doesn’t mean we should!

    #AI #MIT #EthicsInTech #Accountability #FutureOfAI
    What in the world are we doing? Scientists at the Massachusetts Institute of Technology have come up with this mind-boggling idea of creating an AI model that "never stops learning." Seriously? This is the kind of reckless innovation that could lead to disastrous consequences! Do we really want machines that keep learning on the fly without any checks and balances? Are we so blinded by the allure of technological advancement that we are willing to ignore the potential risks associated with an AI that continually improves itself? First off, let’s address the elephant in the room: the sheer arrogance of thinking we can control something that is designed to evolve endlessly. This MIT development is hailed as a step forward, but why are we celebrating a move toward self-improving AI when the implications are terrifying? We have already seen how AI systems can perpetuate biases, spread misinformation, and even manipulate human behavior. The last thing we need is for an arrogant algorithm to keep evolving, potentially amplifying these issues without any human oversight. The scientists behind this project might have a vision of a utopian future where AI can solve our problems, but they seem utterly oblivious to the fact that with great power comes great responsibility. Who is going to regulate this relentless learning process? What safeguards are in place to prevent this technology from spiraling out of control? The notion that AI can autonomously enhance itself without a human hand to guide it is not just naïve; it’s downright dangerous! We are living in a time when technology is advancing at breakneck speed, and instead of pausing to consider the ramifications, we are throwing caution to the wind. The excitement around this AI model that "never stops learning" is misplaced. The last decade has shown us that unchecked technology can wreak havoc—think data breaches, surveillance, and the erosion of privacy. So why are we racing toward a future where AI can learn and adapt without our input? Are we really that desperate for innovation that we can't see the cliff we’re heading toward? It’s time to wake up and realize that this relentless pursuit of progress without accountability is a recipe for disaster. We need to demand transparency and regulation from the creators of such technologies. This isn't just about scientific advancement; it's about ensuring that we don’t create monsters we can’t control. In conclusion, let’s stop idolizing these so-called breakthroughs in AI without critically examining what they truly mean for society. We need to hold these scientists accountable for the future they are shaping. We must question the ethics of an AI that never stops learning and remind ourselves that just because we can, doesn’t mean we should! #AI #MIT #EthicsInTech #Accountability #FutureOfAI
    This AI Model Never Stops Learning
    Scientists at Massachusetts Institute of Technology have devised a way for large language models to keep learning on the fly—a step toward building AI that continually improves itself.
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  • What a world we live in when scientists finally unlock the secrets to the axolotls' ability to regenerate limbs, only to reveal that the key lies not in some miraculous regrowth molecule, but in its controlled destruction! Seriously, what kind of twisted logic is this? Are we supposed to celebrate the fact that the secret to regeneration is, in fact, about knowing when to destroy something instead of nurturing and encouraging growth? This revelation is not just baffling; it's downright infuriating!

    In an age where regenerative medicine holds the promise of healing wounds and restoring functionality, we are faced with the shocking realization that the science is not about building up, but rather about tearing down. Why would we ever want to focus on the destruction of growth molecules instead of creating an environment where regeneration can bloom unimpeded? Where is the inspiration in that? It feels like a slap in the face to anyone who believes in the potential of science to improve lives!

    Moreover, can we talk about the implications of this discovery? If the key to regeneration involves a meticulous dance of destruction, what does that say about our approach to medical advancements? Are we really expected to just stand by and accept that we must embrace an idea that says, "let's get rid of the good stuff to allow for growth"? This is not just a minor flaw in reasoning; it's a fundamental misunderstanding of what regeneration should mean for us!

    To make matters worse, this revelation could lead to misguided practices in regenerative medicine. Instead of developing therapies that promote healing and growth, we could end up with treatments that focus on the elimination of beneficial molecules. This is absolutely unacceptable! How dare the scientific community suggest that the way forward is through destruction rather than cultivation? We should be demanding more from our researchers, not less!

    Let’s not forget the ethical implications. If the path to regeneration is paved with the controlled destruction of vital components, how can we trust the outcomes? We’re putting lives in the hands of a process that promotes destruction. Just imagine the future of medicine being dictated by a philosophy that sounds more like a dystopian nightmare than a beacon of hope.

    It is high time we hold scientists accountable for the direction they are taking in regenerative research. We need a shift in focus that prioritizes constructive growth, not destructive measures. If we are serious about advancing regenerative medicine, we must reject this flawed notion and demand a commitment to genuine regeneration—the kind that nurtures life, rather than sabotages it.

    Let’s raise our voices against this madness. We deserve better than a science that advocates for destruction as the means to an end. The axolotls may thrive on this paradox, but we, as humans, should expect far more from our scientific endeavors.

    #RegenerativeMedicine #Axolotl #ScienceFail #MedicalEthics #Innovation
    What a world we live in when scientists finally unlock the secrets to the axolotls' ability to regenerate limbs, only to reveal that the key lies not in some miraculous regrowth molecule, but in its controlled destruction! Seriously, what kind of twisted logic is this? Are we supposed to celebrate the fact that the secret to regeneration is, in fact, about knowing when to destroy something instead of nurturing and encouraging growth? This revelation is not just baffling; it's downright infuriating! In an age where regenerative medicine holds the promise of healing wounds and restoring functionality, we are faced with the shocking realization that the science is not about building up, but rather about tearing down. Why would we ever want to focus on the destruction of growth molecules instead of creating an environment where regeneration can bloom unimpeded? Where is the inspiration in that? It feels like a slap in the face to anyone who believes in the potential of science to improve lives! Moreover, can we talk about the implications of this discovery? If the key to regeneration involves a meticulous dance of destruction, what does that say about our approach to medical advancements? Are we really expected to just stand by and accept that we must embrace an idea that says, "let's get rid of the good stuff to allow for growth"? This is not just a minor flaw in reasoning; it's a fundamental misunderstanding of what regeneration should mean for us! To make matters worse, this revelation could lead to misguided practices in regenerative medicine. Instead of developing therapies that promote healing and growth, we could end up with treatments that focus on the elimination of beneficial molecules. This is absolutely unacceptable! How dare the scientific community suggest that the way forward is through destruction rather than cultivation? We should be demanding more from our researchers, not less! Let’s not forget the ethical implications. If the path to regeneration is paved with the controlled destruction of vital components, how can we trust the outcomes? We’re putting lives in the hands of a process that promotes destruction. Just imagine the future of medicine being dictated by a philosophy that sounds more like a dystopian nightmare than a beacon of hope. It is high time we hold scientists accountable for the direction they are taking in regenerative research. We need a shift in focus that prioritizes constructive growth, not destructive measures. If we are serious about advancing regenerative medicine, we must reject this flawed notion and demand a commitment to genuine regeneration—the kind that nurtures life, rather than sabotages it. Let’s raise our voices against this madness. We deserve better than a science that advocates for destruction as the means to an end. The axolotls may thrive on this paradox, but we, as humans, should expect far more from our scientific endeavors. #RegenerativeMedicine #Axolotl #ScienceFail #MedicalEthics #Innovation
    Scientists Discover the Key to Axolotls’ Ability to Regenerate Limbs
    A new study reveals the key lies not in the production of a regrowth molecule, but in that molecule's controlled destruction. The discovery could inspire future regenerative medicine.
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  • Ankur Kothari Q&A: Customer Engagement Book Interview

    Reading Time: 9 minutes
    In marketing, data isn’t a buzzword. It’s the lifeblood of all successful campaigns.
    But are you truly harnessing its power, or are you drowning in a sea of information? To answer this question, we sat down with Ankur Kothari, a seasoned Martech expert, to dive deep into this crucial topic.
    This interview, originally conducted for Chapter 6 of “The Customer Engagement Book: Adapt or Die” explores how businesses can translate raw data into actionable insights that drive real results.
    Ankur shares his wealth of knowledge on identifying valuable customer engagement data, distinguishing between signal and noise, and ultimately, shaping real-time strategies that keep companies ahead of the curve.

     
    Ankur Kothari Q&A Interview
    1. What types of customer engagement data are most valuable for making strategic business decisions?
    Primarily, there are four different buckets of customer engagement data. I would begin with behavioral data, encompassing website interaction, purchase history, and other app usage patterns.
    Second would be demographic information: age, location, income, and other relevant personal characteristics.
    Third would be sentiment analysis, where we derive information from social media interaction, customer feedback, or other customer reviews.
    Fourth would be the customer journey data.

    We track touchpoints across various channels of the customers to understand the customer journey path and conversion. Combining these four primary sources helps us understand the engagement data.

    2. How do you distinguish between data that is actionable versus data that is just noise?
    First is keeping relevant to your business objectives, making actionable data that directly relates to your specific goals or KPIs, and then taking help from statistical significance.
    Actionable data shows clear patterns or trends that are statistically valid, whereas other data consists of random fluctuations or outliers, which may not be what you are interested in.

    You also want to make sure that there is consistency across sources.
    Actionable insights are typically corroborated by multiple data points or channels, while other data or noise can be more isolated and contradictory.
    Actionable data suggests clear opportunities for improvement or decision making, whereas noise does not lead to meaningful actions or changes in strategy.

    By applying these criteria, I can effectively filter out the noise and focus on data that delivers or drives valuable business decisions.

    3. How can customer engagement data be used to identify and prioritize new business opportunities?
    First, it helps us to uncover unmet needs.

    By analyzing the customer feedback, touch points, support interactions, or usage patterns, we can identify the gaps in our current offerings or areas where customers are experiencing pain points.

    Second would be identifying emerging needs.
    Monitoring changes in customer behavior or preferences over time can reveal new market trends or shifts in demand, allowing my company to adapt their products or services accordingly.
    Third would be segmentation analysis.
    Detailed customer data analysis enables us to identify unserved or underserved segments or niche markets that may represent untapped opportunities for growth or expansion into newer areas and new geographies.
    Last is to build competitive differentiation.

    Engagement data can highlight where our companies outperform competitors, helping us to prioritize opportunities that leverage existing strengths and unique selling propositions.

    4. Can you share an example of where data insights directly influenced a critical decision?
    I will share an example from my previous organization at one of the financial services where we were very data-driven, which made a major impact on our critical decision regarding our credit card offerings.
    We analyzed the customer engagement data, and we discovered that a large segment of our millennial customers were underutilizing our traditional credit cards but showed high engagement with mobile payment platforms.
    That insight led us to develop and launch our first digital credit card product with enhanced mobile features and rewards tailored to the millennial spending habits. Since we had access to a lot of transactional data as well, we were able to build a financial product which met that specific segment’s needs.

    That data-driven decision resulted in a 40% increase in our new credit card applications from this demographic within the first quarter of the launch. Subsequently, our market share improved in that specific segment, which was very crucial.

    5. Are there any other examples of ways that you see customer engagement data being able to shape marketing strategy in real time?
    When it comes to using the engagement data in real-time, we do quite a few things. In the recent past two, three years, we are using that for dynamic content personalization, adjusting the website content, email messaging, or ad creative based on real-time user behavior and preferences.
    We automate campaign optimization using specific AI-driven tools to continuously analyze performance metrics and automatically reallocate the budget to top-performing channels or ad segments.
    Then we also build responsive social media engagement platforms like monitoring social media sentiments and trending topics to quickly adapt the messaging and create timely and relevant content.

    With one-on-one personalization, we do a lot of A/B testing as part of the overall rapid testing and market elements like subject lines, CTAs, and building various successful variants of the campaigns.

    6. How are you doing the 1:1 personalization?
    We have advanced CDP systems, and we are tracking each customer’s behavior in real-time. So the moment they move to different channels, we know what the context is, what the relevance is, and the recent interaction points, so we can cater the right offer.
    So for example, if you looked at a certain offer on the website and you came from Google, and then the next day you walk into an in-person interaction, our agent will already know that you were looking at that offer.
    That gives our customer or potential customer more one-to-one personalization instead of just segment-based or bulk interaction kind of experience.

    We have a huge team of data scientists, data analysts, and AI model creators who help us to analyze big volumes of data and bring the right insights to our marketing and sales team so that they can provide the right experience to our customers.

    7. What role does customer engagement data play in influencing cross-functional decisions, such as with product development, sales, and customer service?
    Primarily with product development — we have different products, not just the financial products or products whichever organizations sell, but also various products like mobile apps or websites they use for transactions. So that kind of product development gets improved.
    The engagement data helps our sales and marketing teams create more targeted campaigns, optimize channel selection, and refine messaging to resonate with specific customer segments.

    Customer service also gets helped by anticipating common issues, personalizing support interactions over the phone or email or chat, and proactively addressing potential problems, leading to improved customer satisfaction and retention.

    So in general, cross-functional application of engagement improves the customer-centric approach throughout the organization.

    8. What do you think some of the main challenges marketers face when trying to translate customer engagement data into actionable business insights?
    I think the huge amount of data we are dealing with. As we are getting more digitally savvy and most of the customers are moving to digital channels, we are getting a lot of data, and that sheer volume of data can be overwhelming, making it very difficult to identify truly meaningful patterns and insights.

    Because of the huge data overload, we create data silos in this process, so information often exists in separate systems across different departments. We are not able to build a holistic view of customer engagement.

    Because of data silos and overload of data, data quality issues appear. There is inconsistency, and inaccurate data can lead to incorrect insights or poor decision-making. Quality issues could also be due to the wrong format of the data, or the data is stale and no longer relevant.
    As we are growing and adding more people to help us understand customer engagement, I’ve also noticed that technical folks, especially data scientists and data analysts, lack skills to properly interpret the data or apply data insights effectively.
    So there’s a lack of understanding of marketing and sales as domains.
    It’s a huge effort and can take a lot of investment.

    Not being able to calculate the ROI of your overall investment is a big challenge that many organizations are facing.

    9. Why do you think the analysts don’t have the business acumen to properly do more than analyze the data?
    If people do not have the right idea of why we are collecting this data, we collect a lot of noise, and that brings in huge volumes of data. If you cannot stop that from step one—not bringing noise into the data system—that cannot be done by just technical folks or people who do not have business knowledge.
    Business people do not know everything about what data is being collected from which source and what data they need. It’s a gap between business domain knowledge, specifically marketing and sales needs, and technical folks who don’t have a lot of exposure to that side.

    Similarly, marketing business people do not have much exposure to the technical side — what’s possible to do with data, how much effort it takes, what’s relevant versus not relevant, and how to prioritize which data sources will be most important.

    10. Do you have any suggestions for how this can be overcome, or have you seen it in action where it has been solved before?
    First, cross-functional training: training different roles to help them understand why we’re doing this and what the business goals are, giving technical people exposure to what marketing and sales teams do.
    And giving business folks exposure to the technology side through training on different tools, strategies, and the roadmap of data integrations.
    The second is helping teams work more collaboratively. So it’s not like the technology team works in a silo and comes back when their work is done, and then marketing and sales teams act upon it.

    Now we’re making it more like one team. You work together so that you can complement each other, and we have a better strategy from day one.

    11. How do you address skepticism or resistance from stakeholders when presenting data-driven recommendations?
    We present clear business cases where we demonstrate how data-driven recommendations can directly align with business objectives and potential ROI.
    We build compelling visualizations, easy-to-understand charts and graphs that clearly illustrate the insights and the implications for business goals.

    We also do a lot of POCs and pilot projects with small-scale implementations to showcase tangible results and build confidence in the data-driven approach throughout the organization.

    12. What technologies or tools have you found most effective for gathering and analyzing customer engagement data?
    I’ve found that Customer Data Platforms help us unify customer data from various sources, providing a comprehensive view of customer interactions across touch points.
    Having advanced analytics platforms — tools with AI and machine learning capabilities that can process large volumes of data and uncover complex patterns and insights — is a great value to us.
    We always use, or many organizations use, marketing automation systems to improve marketing team productivity, helping us track and analyze customer interactions across multiple channels.
    Another thing is social media listening tools, wherever your brand is mentioned or you want to measure customer sentiment over social media, or track the engagement of your campaigns across social media platforms.

    Last is web analytical tools, which provide detailed insights into your website visitors’ behaviors and engagement metrics, for browser apps, small browser apps, various devices, and mobile apps.

    13. How do you ensure data quality and consistency across multiple channels to make these informed decisions?
    We established clear guidelines for data collection, storage, and usage across all channels to maintain consistency. Then we use data integration platforms — tools that consolidate data from various sources into a single unified view, reducing discrepancies and inconsistencies.
    While we collect data from different sources, we clean the data so it becomes cleaner with every stage of processing.
    We also conduct regular data audits — performing periodic checks to identify and rectify data quality issues, ensuring accuracy and reliability of information. We also deploy standardized data formats.

    On top of that, we have various automated data cleansing tools, specific software to detect and correct data errors, redundancies, duplicates, and inconsistencies in data sets automatically.

    14. How do you see the role of customer engagement data evolving in shaping business strategies over the next five years?
    The first thing that’s been the biggest trend from the past two years is AI-driven decision making, which I think will become more prevalent, with advanced algorithms processing vast amounts of engagement data in real-time to inform strategic choices.
    Somewhat related to this is predictive analytics, which will play an even larger role, enabling businesses to anticipate customer needs and market trends with more accuracy and better predictive capabilities.
    We also touched upon hyper-personalization. We are all trying to strive toward more hyper-personalization at scale, which is more one-on-one personalization, as we are increasingly capturing more engagement data and have bigger systems and infrastructure to support processing those large volumes of data so we can achieve those hyper-personalization use cases.
    As the world is collecting more data, privacy concerns and regulations come into play.
    I believe in the next few years there will be more innovation toward how businesses can collect data ethically and what the usage practices are, leading to more transparent and consent-based engagement data strategies.
    And lastly, I think about the integration of engagement data, which is always a big challenge. I believe as we’re solving those integration challenges, we are adding more and more complex data sources to the picture.

    So I think there will need to be more innovation or sophistication brought into data integration strategies, which will help us take a truly customer-centric approach to strategy formulation.

     
    This interview Q&A was hosted with Ankur Kothari, a previous Martech Executive, for Chapter 6 of The Customer Engagement Book: Adapt or Die.
    Download the PDF or request a physical copy of the book here.
    The post Ankur Kothari Q&A: Customer Engagement Book Interview appeared first on MoEngage.
    #ankur #kothari #qampampa #customer #engagement
    Ankur Kothari Q&A: Customer Engagement Book Interview
    Reading Time: 9 minutes In marketing, data isn’t a buzzword. It’s the lifeblood of all successful campaigns. But are you truly harnessing its power, or are you drowning in a sea of information? To answer this question, we sat down with Ankur Kothari, a seasoned Martech expert, to dive deep into this crucial topic. This interview, originally conducted for Chapter 6 of “The Customer Engagement Book: Adapt or Die” explores how businesses can translate raw data into actionable insights that drive real results. Ankur shares his wealth of knowledge on identifying valuable customer engagement data, distinguishing between signal and noise, and ultimately, shaping real-time strategies that keep companies ahead of the curve.   Ankur Kothari Q&A Interview 1. What types of customer engagement data are most valuable for making strategic business decisions? Primarily, there are four different buckets of customer engagement data. I would begin with behavioral data, encompassing website interaction, purchase history, and other app usage patterns. Second would be demographic information: age, location, income, and other relevant personal characteristics. Third would be sentiment analysis, where we derive information from social media interaction, customer feedback, or other customer reviews. Fourth would be the customer journey data. We track touchpoints across various channels of the customers to understand the customer journey path and conversion. Combining these four primary sources helps us understand the engagement data. 2. How do you distinguish between data that is actionable versus data that is just noise? First is keeping relevant to your business objectives, making actionable data that directly relates to your specific goals or KPIs, and then taking help from statistical significance. Actionable data shows clear patterns or trends that are statistically valid, whereas other data consists of random fluctuations or outliers, which may not be what you are interested in. You also want to make sure that there is consistency across sources. Actionable insights are typically corroborated by multiple data points or channels, while other data or noise can be more isolated and contradictory. Actionable data suggests clear opportunities for improvement or decision making, whereas noise does not lead to meaningful actions or changes in strategy. By applying these criteria, I can effectively filter out the noise and focus on data that delivers or drives valuable business decisions. 3. How can customer engagement data be used to identify and prioritize new business opportunities? First, it helps us to uncover unmet needs. By analyzing the customer feedback, touch points, support interactions, or usage patterns, we can identify the gaps in our current offerings or areas where customers are experiencing pain points. Second would be identifying emerging needs. Monitoring changes in customer behavior or preferences over time can reveal new market trends or shifts in demand, allowing my company to adapt their products or services accordingly. Third would be segmentation analysis. Detailed customer data analysis enables us to identify unserved or underserved segments or niche markets that may represent untapped opportunities for growth or expansion into newer areas and new geographies. Last is to build competitive differentiation. Engagement data can highlight where our companies outperform competitors, helping us to prioritize opportunities that leverage existing strengths and unique selling propositions. 4. Can you share an example of where data insights directly influenced a critical decision? I will share an example from my previous organization at one of the financial services where we were very data-driven, which made a major impact on our critical decision regarding our credit card offerings. We analyzed the customer engagement data, and we discovered that a large segment of our millennial customers were underutilizing our traditional credit cards but showed high engagement with mobile payment platforms. That insight led us to develop and launch our first digital credit card product with enhanced mobile features and rewards tailored to the millennial spending habits. Since we had access to a lot of transactional data as well, we were able to build a financial product which met that specific segment’s needs. That data-driven decision resulted in a 40% increase in our new credit card applications from this demographic within the first quarter of the launch. Subsequently, our market share improved in that specific segment, which was very crucial. 5. Are there any other examples of ways that you see customer engagement data being able to shape marketing strategy in real time? When it comes to using the engagement data in real-time, we do quite a few things. In the recent past two, three years, we are using that for dynamic content personalization, adjusting the website content, email messaging, or ad creative based on real-time user behavior and preferences. We automate campaign optimization using specific AI-driven tools to continuously analyze performance metrics and automatically reallocate the budget to top-performing channels or ad segments. Then we also build responsive social media engagement platforms like monitoring social media sentiments and trending topics to quickly adapt the messaging and create timely and relevant content. With one-on-one personalization, we do a lot of A/B testing as part of the overall rapid testing and market elements like subject lines, CTAs, and building various successful variants of the campaigns. 6. How are you doing the 1:1 personalization? We have advanced CDP systems, and we are tracking each customer’s behavior in real-time. So the moment they move to different channels, we know what the context is, what the relevance is, and the recent interaction points, so we can cater the right offer. So for example, if you looked at a certain offer on the website and you came from Google, and then the next day you walk into an in-person interaction, our agent will already know that you were looking at that offer. That gives our customer or potential customer more one-to-one personalization instead of just segment-based or bulk interaction kind of experience. We have a huge team of data scientists, data analysts, and AI model creators who help us to analyze big volumes of data and bring the right insights to our marketing and sales team so that they can provide the right experience to our customers. 7. What role does customer engagement data play in influencing cross-functional decisions, such as with product development, sales, and customer service? Primarily with product development — we have different products, not just the financial products or products whichever organizations sell, but also various products like mobile apps or websites they use for transactions. So that kind of product development gets improved. The engagement data helps our sales and marketing teams create more targeted campaigns, optimize channel selection, and refine messaging to resonate with specific customer segments. Customer service also gets helped by anticipating common issues, personalizing support interactions over the phone or email or chat, and proactively addressing potential problems, leading to improved customer satisfaction and retention. So in general, cross-functional application of engagement improves the customer-centric approach throughout the organization. 8. What do you think some of the main challenges marketers face when trying to translate customer engagement data into actionable business insights? I think the huge amount of data we are dealing with. As we are getting more digitally savvy and most of the customers are moving to digital channels, we are getting a lot of data, and that sheer volume of data can be overwhelming, making it very difficult to identify truly meaningful patterns and insights. Because of the huge data overload, we create data silos in this process, so information often exists in separate systems across different departments. We are not able to build a holistic view of customer engagement. Because of data silos and overload of data, data quality issues appear. There is inconsistency, and inaccurate data can lead to incorrect insights or poor decision-making. Quality issues could also be due to the wrong format of the data, or the data is stale and no longer relevant. As we are growing and adding more people to help us understand customer engagement, I’ve also noticed that technical folks, especially data scientists and data analysts, lack skills to properly interpret the data or apply data insights effectively. So there’s a lack of understanding of marketing and sales as domains. It’s a huge effort and can take a lot of investment. Not being able to calculate the ROI of your overall investment is a big challenge that many organizations are facing. 9. Why do you think the analysts don’t have the business acumen to properly do more than analyze the data? If people do not have the right idea of why we are collecting this data, we collect a lot of noise, and that brings in huge volumes of data. If you cannot stop that from step one—not bringing noise into the data system—that cannot be done by just technical folks or people who do not have business knowledge. Business people do not know everything about what data is being collected from which source and what data they need. It’s a gap between business domain knowledge, specifically marketing and sales needs, and technical folks who don’t have a lot of exposure to that side. Similarly, marketing business people do not have much exposure to the technical side — what’s possible to do with data, how much effort it takes, what’s relevant versus not relevant, and how to prioritize which data sources will be most important. 10. Do you have any suggestions for how this can be overcome, or have you seen it in action where it has been solved before? First, cross-functional training: training different roles to help them understand why we’re doing this and what the business goals are, giving technical people exposure to what marketing and sales teams do. And giving business folks exposure to the technology side through training on different tools, strategies, and the roadmap of data integrations. The second is helping teams work more collaboratively. So it’s not like the technology team works in a silo and comes back when their work is done, and then marketing and sales teams act upon it. Now we’re making it more like one team. You work together so that you can complement each other, and we have a better strategy from day one. 11. How do you address skepticism or resistance from stakeholders when presenting data-driven recommendations? We present clear business cases where we demonstrate how data-driven recommendations can directly align with business objectives and potential ROI. We build compelling visualizations, easy-to-understand charts and graphs that clearly illustrate the insights and the implications for business goals. We also do a lot of POCs and pilot projects with small-scale implementations to showcase tangible results and build confidence in the data-driven approach throughout the organization. 12. What technologies or tools have you found most effective for gathering and analyzing customer engagement data? I’ve found that Customer Data Platforms help us unify customer data from various sources, providing a comprehensive view of customer interactions across touch points. Having advanced analytics platforms — tools with AI and machine learning capabilities that can process large volumes of data and uncover complex patterns and insights — is a great value to us. We always use, or many organizations use, marketing automation systems to improve marketing team productivity, helping us track and analyze customer interactions across multiple channels. Another thing is social media listening tools, wherever your brand is mentioned or you want to measure customer sentiment over social media, or track the engagement of your campaigns across social media platforms. Last is web analytical tools, which provide detailed insights into your website visitors’ behaviors and engagement metrics, for browser apps, small browser apps, various devices, and mobile apps. 13. How do you ensure data quality and consistency across multiple channels to make these informed decisions? We established clear guidelines for data collection, storage, and usage across all channels to maintain consistency. Then we use data integration platforms — tools that consolidate data from various sources into a single unified view, reducing discrepancies and inconsistencies. While we collect data from different sources, we clean the data so it becomes cleaner with every stage of processing. We also conduct regular data audits — performing periodic checks to identify and rectify data quality issues, ensuring accuracy and reliability of information. We also deploy standardized data formats. On top of that, we have various automated data cleansing tools, specific software to detect and correct data errors, redundancies, duplicates, and inconsistencies in data sets automatically. 14. How do you see the role of customer engagement data evolving in shaping business strategies over the next five years? The first thing that’s been the biggest trend from the past two years is AI-driven decision making, which I think will become more prevalent, with advanced algorithms processing vast amounts of engagement data in real-time to inform strategic choices. Somewhat related to this is predictive analytics, which will play an even larger role, enabling businesses to anticipate customer needs and market trends with more accuracy and better predictive capabilities. We also touched upon hyper-personalization. We are all trying to strive toward more hyper-personalization at scale, which is more one-on-one personalization, as we are increasingly capturing more engagement data and have bigger systems and infrastructure to support processing those large volumes of data so we can achieve those hyper-personalization use cases. As the world is collecting more data, privacy concerns and regulations come into play. I believe in the next few years there will be more innovation toward how businesses can collect data ethically and what the usage practices are, leading to more transparent and consent-based engagement data strategies. And lastly, I think about the integration of engagement data, which is always a big challenge. I believe as we’re solving those integration challenges, we are adding more and more complex data sources to the picture. So I think there will need to be more innovation or sophistication brought into data integration strategies, which will help us take a truly customer-centric approach to strategy formulation.   This interview Q&A was hosted with Ankur Kothari, a previous Martech Executive, for Chapter 6 of The Customer Engagement Book: Adapt or Die. Download the PDF or request a physical copy of the book here. The post Ankur Kothari Q&A: Customer Engagement Book Interview appeared first on MoEngage. #ankur #kothari #qampampa #customer #engagement
    WWW.MOENGAGE.COM
    Ankur Kothari Q&A: Customer Engagement Book Interview
    Reading Time: 9 minutes In marketing, data isn’t a buzzword. It’s the lifeblood of all successful campaigns. But are you truly harnessing its power, or are you drowning in a sea of information? To answer this question (and many others), we sat down with Ankur Kothari, a seasoned Martech expert, to dive deep into this crucial topic. This interview, originally conducted for Chapter 6 of “The Customer Engagement Book: Adapt or Die” explores how businesses can translate raw data into actionable insights that drive real results. Ankur shares his wealth of knowledge on identifying valuable customer engagement data, distinguishing between signal and noise, and ultimately, shaping real-time strategies that keep companies ahead of the curve.   Ankur Kothari Q&A Interview 1. What types of customer engagement data are most valuable for making strategic business decisions? Primarily, there are four different buckets of customer engagement data. I would begin with behavioral data, encompassing website interaction, purchase history, and other app usage patterns. Second would be demographic information: age, location, income, and other relevant personal characteristics. Third would be sentiment analysis, where we derive information from social media interaction, customer feedback, or other customer reviews. Fourth would be the customer journey data. We track touchpoints across various channels of the customers to understand the customer journey path and conversion. Combining these four primary sources helps us understand the engagement data. 2. How do you distinguish between data that is actionable versus data that is just noise? First is keeping relevant to your business objectives, making actionable data that directly relates to your specific goals or KPIs, and then taking help from statistical significance. Actionable data shows clear patterns or trends that are statistically valid, whereas other data consists of random fluctuations or outliers, which may not be what you are interested in. You also want to make sure that there is consistency across sources. Actionable insights are typically corroborated by multiple data points or channels, while other data or noise can be more isolated and contradictory. Actionable data suggests clear opportunities for improvement or decision making, whereas noise does not lead to meaningful actions or changes in strategy. By applying these criteria, I can effectively filter out the noise and focus on data that delivers or drives valuable business decisions. 3. How can customer engagement data be used to identify and prioritize new business opportunities? First, it helps us to uncover unmet needs. By analyzing the customer feedback, touch points, support interactions, or usage patterns, we can identify the gaps in our current offerings or areas where customers are experiencing pain points. Second would be identifying emerging needs. Monitoring changes in customer behavior or preferences over time can reveal new market trends or shifts in demand, allowing my company to adapt their products or services accordingly. Third would be segmentation analysis. Detailed customer data analysis enables us to identify unserved or underserved segments or niche markets that may represent untapped opportunities for growth or expansion into newer areas and new geographies. Last is to build competitive differentiation. Engagement data can highlight where our companies outperform competitors, helping us to prioritize opportunities that leverage existing strengths and unique selling propositions. 4. Can you share an example of where data insights directly influenced a critical decision? I will share an example from my previous organization at one of the financial services where we were very data-driven, which made a major impact on our critical decision regarding our credit card offerings. We analyzed the customer engagement data, and we discovered that a large segment of our millennial customers were underutilizing our traditional credit cards but showed high engagement with mobile payment platforms. That insight led us to develop and launch our first digital credit card product with enhanced mobile features and rewards tailored to the millennial spending habits. Since we had access to a lot of transactional data as well, we were able to build a financial product which met that specific segment’s needs. That data-driven decision resulted in a 40% increase in our new credit card applications from this demographic within the first quarter of the launch. Subsequently, our market share improved in that specific segment, which was very crucial. 5. Are there any other examples of ways that you see customer engagement data being able to shape marketing strategy in real time? When it comes to using the engagement data in real-time, we do quite a few things. In the recent past two, three years, we are using that for dynamic content personalization, adjusting the website content, email messaging, or ad creative based on real-time user behavior and preferences. We automate campaign optimization using specific AI-driven tools to continuously analyze performance metrics and automatically reallocate the budget to top-performing channels or ad segments. Then we also build responsive social media engagement platforms like monitoring social media sentiments and trending topics to quickly adapt the messaging and create timely and relevant content. With one-on-one personalization, we do a lot of A/B testing as part of the overall rapid testing and market elements like subject lines, CTAs, and building various successful variants of the campaigns. 6. How are you doing the 1:1 personalization? We have advanced CDP systems, and we are tracking each customer’s behavior in real-time. So the moment they move to different channels, we know what the context is, what the relevance is, and the recent interaction points, so we can cater the right offer. So for example, if you looked at a certain offer on the website and you came from Google, and then the next day you walk into an in-person interaction, our agent will already know that you were looking at that offer. That gives our customer or potential customer more one-to-one personalization instead of just segment-based or bulk interaction kind of experience. We have a huge team of data scientists, data analysts, and AI model creators who help us to analyze big volumes of data and bring the right insights to our marketing and sales team so that they can provide the right experience to our customers. 7. What role does customer engagement data play in influencing cross-functional decisions, such as with product development, sales, and customer service? Primarily with product development — we have different products, not just the financial products or products whichever organizations sell, but also various products like mobile apps or websites they use for transactions. So that kind of product development gets improved. The engagement data helps our sales and marketing teams create more targeted campaigns, optimize channel selection, and refine messaging to resonate with specific customer segments. Customer service also gets helped by anticipating common issues, personalizing support interactions over the phone or email or chat, and proactively addressing potential problems, leading to improved customer satisfaction and retention. So in general, cross-functional application of engagement improves the customer-centric approach throughout the organization. 8. What do you think some of the main challenges marketers face when trying to translate customer engagement data into actionable business insights? I think the huge amount of data we are dealing with. As we are getting more digitally savvy and most of the customers are moving to digital channels, we are getting a lot of data, and that sheer volume of data can be overwhelming, making it very difficult to identify truly meaningful patterns and insights. Because of the huge data overload, we create data silos in this process, so information often exists in separate systems across different departments. We are not able to build a holistic view of customer engagement. Because of data silos and overload of data, data quality issues appear. There is inconsistency, and inaccurate data can lead to incorrect insights or poor decision-making. Quality issues could also be due to the wrong format of the data, or the data is stale and no longer relevant. As we are growing and adding more people to help us understand customer engagement, I’ve also noticed that technical folks, especially data scientists and data analysts, lack skills to properly interpret the data or apply data insights effectively. So there’s a lack of understanding of marketing and sales as domains. It’s a huge effort and can take a lot of investment. Not being able to calculate the ROI of your overall investment is a big challenge that many organizations are facing. 9. Why do you think the analysts don’t have the business acumen to properly do more than analyze the data? If people do not have the right idea of why we are collecting this data, we collect a lot of noise, and that brings in huge volumes of data. If you cannot stop that from step one—not bringing noise into the data system—that cannot be done by just technical folks or people who do not have business knowledge. Business people do not know everything about what data is being collected from which source and what data they need. It’s a gap between business domain knowledge, specifically marketing and sales needs, and technical folks who don’t have a lot of exposure to that side. Similarly, marketing business people do not have much exposure to the technical side — what’s possible to do with data, how much effort it takes, what’s relevant versus not relevant, and how to prioritize which data sources will be most important. 10. Do you have any suggestions for how this can be overcome, or have you seen it in action where it has been solved before? First, cross-functional training: training different roles to help them understand why we’re doing this and what the business goals are, giving technical people exposure to what marketing and sales teams do. And giving business folks exposure to the technology side through training on different tools, strategies, and the roadmap of data integrations. The second is helping teams work more collaboratively. So it’s not like the technology team works in a silo and comes back when their work is done, and then marketing and sales teams act upon it. Now we’re making it more like one team. You work together so that you can complement each other, and we have a better strategy from day one. 11. How do you address skepticism or resistance from stakeholders when presenting data-driven recommendations? We present clear business cases where we demonstrate how data-driven recommendations can directly align with business objectives and potential ROI. We build compelling visualizations, easy-to-understand charts and graphs that clearly illustrate the insights and the implications for business goals. We also do a lot of POCs and pilot projects with small-scale implementations to showcase tangible results and build confidence in the data-driven approach throughout the organization. 12. What technologies or tools have you found most effective for gathering and analyzing customer engagement data? I’ve found that Customer Data Platforms help us unify customer data from various sources, providing a comprehensive view of customer interactions across touch points. Having advanced analytics platforms — tools with AI and machine learning capabilities that can process large volumes of data and uncover complex patterns and insights — is a great value to us. We always use, or many organizations use, marketing automation systems to improve marketing team productivity, helping us track and analyze customer interactions across multiple channels. Another thing is social media listening tools, wherever your brand is mentioned or you want to measure customer sentiment over social media, or track the engagement of your campaigns across social media platforms. Last is web analytical tools, which provide detailed insights into your website visitors’ behaviors and engagement metrics, for browser apps, small browser apps, various devices, and mobile apps. 13. How do you ensure data quality and consistency across multiple channels to make these informed decisions? We established clear guidelines for data collection, storage, and usage across all channels to maintain consistency. Then we use data integration platforms — tools that consolidate data from various sources into a single unified view, reducing discrepancies and inconsistencies. While we collect data from different sources, we clean the data so it becomes cleaner with every stage of processing. We also conduct regular data audits — performing periodic checks to identify and rectify data quality issues, ensuring accuracy and reliability of information. We also deploy standardized data formats. On top of that, we have various automated data cleansing tools, specific software to detect and correct data errors, redundancies, duplicates, and inconsistencies in data sets automatically. 14. How do you see the role of customer engagement data evolving in shaping business strategies over the next five years? The first thing that’s been the biggest trend from the past two years is AI-driven decision making, which I think will become more prevalent, with advanced algorithms processing vast amounts of engagement data in real-time to inform strategic choices. Somewhat related to this is predictive analytics, which will play an even larger role, enabling businesses to anticipate customer needs and market trends with more accuracy and better predictive capabilities. We also touched upon hyper-personalization. We are all trying to strive toward more hyper-personalization at scale, which is more one-on-one personalization, as we are increasingly capturing more engagement data and have bigger systems and infrastructure to support processing those large volumes of data so we can achieve those hyper-personalization use cases. As the world is collecting more data, privacy concerns and regulations come into play. I believe in the next few years there will be more innovation toward how businesses can collect data ethically and what the usage practices are, leading to more transparent and consent-based engagement data strategies. And lastly, I think about the integration of engagement data, which is always a big challenge. I believe as we’re solving those integration challenges, we are adding more and more complex data sources to the picture. So I think there will need to be more innovation or sophistication brought into data integration strategies, which will help us take a truly customer-centric approach to strategy formulation.   This interview Q&A was hosted with Ankur Kothari, a previous Martech Executive, for Chapter 6 of The Customer Engagement Book: Adapt or Die. Download the PDF or request a physical copy of the book here. The post Ankur Kothari Q&A: Customer Engagement Book Interview appeared first on MoEngage.
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  • A routine test for fetal abnormalities could improve a mother’s health

    Science & technology | Hidden in plain sightA routine test for fetal abnormalities could improve a mother’s healthStudies show these can help detect pre-eclampsia and predict preterm births Illustration: Anna Kövecses Jun 11th 2025WHEN NON-INVASIVE prenatal testingarrived in 2011, it transformed pregnancy. With a simple blood test, scientists could now sweep a mother’s bloodstream for scraps of placental DNA, uncovering fetal genetic defects and shedding light on the health of the unborn baby. But the potential to monitor the mother’s health went largely unappreciated.Explore moreThis article appeared in the Science & technology section of the print edition under the headline “Testing time”From the June 14th 2025 editionDiscover stories from this section and more in the list of contents⇒Explore the editionReuse this content
    #routine #test #fetal #abnormalities #could
    A routine test for fetal abnormalities could improve a mother’s health
    Science & technology | Hidden in plain sightA routine test for fetal abnormalities could improve a mother’s healthStudies show these can help detect pre-eclampsia and predict preterm births Illustration: Anna Kövecses Jun 11th 2025WHEN NON-INVASIVE prenatal testingarrived in 2011, it transformed pregnancy. With a simple blood test, scientists could now sweep a mother’s bloodstream for scraps of placental DNA, uncovering fetal genetic defects and shedding light on the health of the unborn baby. But the potential to monitor the mother’s health went largely unappreciated.Explore moreThis article appeared in the Science & technology section of the print edition under the headline “Testing time”From the June 14th 2025 editionDiscover stories from this section and more in the list of contents⇒Explore the editionReuse this content #routine #test #fetal #abnormalities #could
    WWW.ECONOMIST.COM
    A routine test for fetal abnormalities could improve a mother’s health
    Science & technology | Hidden in plain sightA routine test for fetal abnormalities could improve a mother’s healthStudies show these can help detect pre-eclampsia and predict preterm births Illustration: Anna Kövecses Jun 11th 2025WHEN NON-INVASIVE prenatal testing (NIPT) arrived in 2011, it transformed pregnancy. With a simple blood test, scientists could now sweep a mother’s bloodstream for scraps of placental DNA, uncovering fetal genetic defects and shedding light on the health of the unborn baby. But the potential to monitor the mother’s health went largely unappreciated.Explore moreThis article appeared in the Science & technology section of the print edition under the headline “Testing time”From the June 14th 2025 editionDiscover stories from this section and more in the list of contents⇒Explore the editionReuse this content
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  • Four science-based rules that will make your conversations flow

    One of the four pillars of good conversation is levity. You needn’t be a comedian, you can but have some funTetra Images, LLC/Alamy
    Conversation lies at the heart of our relationships – yet many of us find it surprisingly hard to talk to others. We may feel anxious at the thought of making small talk with strangers and struggle to connect with the people who are closest to us. If that sounds familiar, Alison Wood Brooks hopes to help. She is a professor at Harvard Business School, where she teaches an oversubscribed course called “TALK: How to talk gooder in business and life”, and the author of a new book, Talk: The science of conversation and the art of being ourselves. Both offer four key principles for more meaningful exchanges. Conversations are inherently unpredictable, says Wood Brooks, but they follow certain rules – and knowing their architecture makes us more comfortable with what is outside of our control. New Scientist asked her about the best ways to apply this research to our own chats.
    David Robson: Talking about talking feels quite meta. Do you ever find yourself critiquing your own performance?
    Alison Wood Brooks: There are so many levels of “meta-ness”. I have often felt like I’m floating over the room, watching conversations unfold, even as I’m involved in them myself. I teach a course at Harvard, andall get to experience this feeling as well. There can be an uncomfortable period of hypervigilance, but I hope that dissipates over time as they develop better habits. There is a famous quote from Charlie Parker, who was a jazz saxophonist. He said something like, “Practise, practise, practise, and then when you get on stage, let it all go and just wail.” I think that’s my approach to conversation. Even when you’re hyper-aware of conversation dynamics, you have to remember the true delight of being with another human mind, and never lose the magic of being together. Think ahead, but once you’re talking, let it all go and just wail.

    Reading your book, I learned that a good way to enliven a conversation is to ask someone why they are passionate about what they do. So, where does your passion for conversation come from?
    I have two answers to this question. One is professional. Early in my professorship at Harvard, I had been studying emotions by exploring how people talk about their feelings and the balance between what we feel inside and how we express that to others. And I realised I just had this deep, profound interest in figuring out how people talk to each other about everything, not just their feelings. We now have scientific tools that allow us to capture conversations and analyse them at large scale. Natural language processing, machine learning, the advent of AI – all this allows us to take huge swathes of transcript data and process it much more efficiently.

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    Sign up to newsletter

    The personal answer is that I’m an identical twin, and I spent my whole life, from the moment I opened my newborn eyes, existing next to a person who’s an exact copy of myself. It was like observing myself at very close range, interacting with the world, interacting with other people. I could see when she said and did things well, and I could try to do that myself. And I saw when her jokes failed, or she stumbled over her words – I tried to avoid those mistakes. It was a very fortunate form of feedback that not a lot of people get. And then, as a twin, you’ve got this person sharing a bedroom, sharing all your clothes, going to all the same parties and playing on the same sports teams, so we were just constantly in conversation with each other. You reached this level of shared reality that is so incredible, and I’ve spent the rest of my life trying to help other people get there in their relationships, too.
    “TALK” cleverly captures your framework for better conversations: topics, asking, levity and kindness. Let’s start at the beginning. How should we decide what to talk about?
    My first piece of advice is to prepare. Some people do this naturally. They already think about the things that they should talk about with somebody before they see them. They should lean into this habit. Some of my students, however, think it’s crazy. They think preparation will make the conversation seem rigid and forced and overly scripted. But just because you’ve thought ahead about what you might talk about doesn’t mean you have to talk about those things once the conversation is underway. It does mean, however, that you always have an idea waiting for you when you’re not sure what to talk about next. Having just one topic in your back pocket can help you in those anxiety-ridden moments. It makes things more fluent, which is important for establishing a connection. Choosing a topic is not only important at the start of a conversation. We’re constantly making decisions about whether we should stay on one subject, drift to something else or totally shift gears and go somewhere wildly different.
    Sometimes the topic of conversation is obvious. Even then, knowing when to switch to a new one can be trickyMartin Parr/Magnum Photos
    What’s your advice when making these decisions?
    There are three very clear signs that suggest that it’s time to switch topics. The first is longer mutual pauses. The second is more uncomfortable laughter, which we use to fill the space that we would usually fill excitedly with good content. And the third sign is redundancy. Once you start repeating things that have already been said on the topic, it’s a sign that you should move to something else.
    After an average conversation, most people feel like they’ve covered the right number of topics. But if you ask people after conversations that didn’t go well, they’ll more often say that they didn’t talk about enough things, rather than that they talked about too many things. This suggests that a common mistake is lingering too long on a topic after you’ve squeezed all the juice out of it.
    The second element of TALK is asking questions. I think a lot of us have heard the advice to ask more questions, yet many people don’t apply it. Why do you think that is?
    Many years of research have shown that the human mind is remarkably egocentric. Often, we are so focused on our own perspective that we forget to even ask someone else to share what’s in their mind. Another reason is fear. You’re interested in the other person, and you know you should ask them questions, but you’re afraid of being too intrusive, or that you will reveal your own incompetence, because you feel you should know the answer already.

    What kinds of questions should we be asking – and avoiding?
    In the book, I talk about the power of follow-up questions that build on anything that your partner has just said. It shows that you heard them, that you care and that you want to know more. Even one follow-up question can springboard us away from shallow talk into something deeper and more meaningful.
    There are, however, some bad patterns of question asking, such as “boomerasking”. Michael Yeomansand I have a recent paper about this, and oh my gosh, it’s been such fun to study. It’s a play on the word boomerang: it comes back to the person who threw it. If I ask you what you had for breakfast, and you tell me you had Special K and banana, and then I say, “Well, let me tell you about my breakfast, because, boy, was it delicious” – that’s boomerasking. Sometimes it’s a thinly veiled way of bragging or complaining, but sometimes I think people are genuinely interested to hear from their partner, but then the partner’s answer reminds them so much of their own life that they can’t help but start sharing their perspective. In our research, we have found that this makes your partner feel like you weren’t interested in their perspective, so it seems very insincere. Sharing your own perspective is important. It’s okay at some point to bring the conversation back to yourself. But don’t do it so soon that it makes your partner feel like you didn’t hear their answer or care about it.
    Research by Alison Wood Brooks includes a recent study on “boomerasking”, a pitfall you should avoid to make conversations flowJanelle Bruno
    What are the benefits of levity?
    When we think of conversations that haven’t gone well, we often think of moments of hostility, anger or disagreement, but a quiet killer of conversation is boredom. Levity is the antidote. These small moments of sparkle or fizz can pull us back in and make us feel engaged with each other again.
    Our research has shown that we give status and respect to people who make us feel good, so much so that in a group of people, a person who can land even one appropriate joke is more likely to be voted as the leader. And the joke doesn’t even need to be very funny! It’s the fact that they were confident enough to try it and competent enough to read the room.
    Do you have any practical steps that people can apply to generate levity, even if they’re not a natural comedian?
    Levity is not just about being funny. In fact, aiming to be a comedian is not the right goal. When we watch stand-up on Netflix, comedians have rehearsed those jokes and honed them and practised them for a long time, and they’re delivering them in a monologue to an audience. It’s a completely different task from a live conversation. In real dialogue, what everybody is looking for is to feel engaged, and that doesn’t require particularly funny jokes or elaborate stories. When you see opportunities to make it fun or lighten the mood, that’s what you need to grab. It can come through a change to a new, fresh topic, or calling back to things that you talked about earlier in the conversation or earlier in your relationship. These callbacks – which sometimes do refer to something funny – are such a nice way of showing that you’ve listened and remembered. A levity move could also involve giving sincere compliments to other people. When you think nice things, when you admire someone, make sure you say it out loud.

    This brings us to the last element of TALK: kindness. Why do we so often fail to be as kind as we would like?
    Wobbles in kindness often come back to our egocentrism. Research shows that we underestimate how much other people’s perspectives differ from our own, and we forget that we have the tools to ask other people directly in conversation for their perspective. Being a kinder conversationalist is about trying to focus on your partner’s perspective and then figuring what they need and helping them to get it.
    Finally, what is your number one tip for readers to have a better conversation the next time they speak to someone?
    Every conversation is surprisingly tricky and complex. When things don’t go perfectly, give yourself and others more grace. There will be trips and stumbles and then a little grace can go very, very far.
    Topics:
    #four #sciencebased #rules #that #will
    Four science-based rules that will make your conversations flow
    One of the four pillars of good conversation is levity. You needn’t be a comedian, you can but have some funTetra Images, LLC/Alamy Conversation lies at the heart of our relationships – yet many of us find it surprisingly hard to talk to others. We may feel anxious at the thought of making small talk with strangers and struggle to connect with the people who are closest to us. If that sounds familiar, Alison Wood Brooks hopes to help. She is a professor at Harvard Business School, where she teaches an oversubscribed course called “TALK: How to talk gooder in business and life”, and the author of a new book, Talk: The science of conversation and the art of being ourselves. Both offer four key principles for more meaningful exchanges. Conversations are inherently unpredictable, says Wood Brooks, but they follow certain rules – and knowing their architecture makes us more comfortable with what is outside of our control. New Scientist asked her about the best ways to apply this research to our own chats. David Robson: Talking about talking feels quite meta. Do you ever find yourself critiquing your own performance? Alison Wood Brooks: There are so many levels of “meta-ness”. I have often felt like I’m floating over the room, watching conversations unfold, even as I’m involved in them myself. I teach a course at Harvard, andall get to experience this feeling as well. There can be an uncomfortable period of hypervigilance, but I hope that dissipates over time as they develop better habits. There is a famous quote from Charlie Parker, who was a jazz saxophonist. He said something like, “Practise, practise, practise, and then when you get on stage, let it all go and just wail.” I think that’s my approach to conversation. Even when you’re hyper-aware of conversation dynamics, you have to remember the true delight of being with another human mind, and never lose the magic of being together. Think ahead, but once you’re talking, let it all go and just wail. Reading your book, I learned that a good way to enliven a conversation is to ask someone why they are passionate about what they do. So, where does your passion for conversation come from? I have two answers to this question. One is professional. Early in my professorship at Harvard, I had been studying emotions by exploring how people talk about their feelings and the balance between what we feel inside and how we express that to others. And I realised I just had this deep, profound interest in figuring out how people talk to each other about everything, not just their feelings. We now have scientific tools that allow us to capture conversations and analyse them at large scale. Natural language processing, machine learning, the advent of AI – all this allows us to take huge swathes of transcript data and process it much more efficiently. Receive a weekly dose of discovery in your inbox. Sign up to newsletter The personal answer is that I’m an identical twin, and I spent my whole life, from the moment I opened my newborn eyes, existing next to a person who’s an exact copy of myself. It was like observing myself at very close range, interacting with the world, interacting with other people. I could see when she said and did things well, and I could try to do that myself. And I saw when her jokes failed, or she stumbled over her words – I tried to avoid those mistakes. It was a very fortunate form of feedback that not a lot of people get. And then, as a twin, you’ve got this person sharing a bedroom, sharing all your clothes, going to all the same parties and playing on the same sports teams, so we were just constantly in conversation with each other. You reached this level of shared reality that is so incredible, and I’ve spent the rest of my life trying to help other people get there in their relationships, too. “TALK” cleverly captures your framework for better conversations: topics, asking, levity and kindness. Let’s start at the beginning. How should we decide what to talk about? My first piece of advice is to prepare. Some people do this naturally. They already think about the things that they should talk about with somebody before they see them. They should lean into this habit. Some of my students, however, think it’s crazy. They think preparation will make the conversation seem rigid and forced and overly scripted. But just because you’ve thought ahead about what you might talk about doesn’t mean you have to talk about those things once the conversation is underway. It does mean, however, that you always have an idea waiting for you when you’re not sure what to talk about next. Having just one topic in your back pocket can help you in those anxiety-ridden moments. It makes things more fluent, which is important for establishing a connection. Choosing a topic is not only important at the start of a conversation. We’re constantly making decisions about whether we should stay on one subject, drift to something else or totally shift gears and go somewhere wildly different. Sometimes the topic of conversation is obvious. Even then, knowing when to switch to a new one can be trickyMartin Parr/Magnum Photos What’s your advice when making these decisions? There are three very clear signs that suggest that it’s time to switch topics. The first is longer mutual pauses. The second is more uncomfortable laughter, which we use to fill the space that we would usually fill excitedly with good content. And the third sign is redundancy. Once you start repeating things that have already been said on the topic, it’s a sign that you should move to something else. After an average conversation, most people feel like they’ve covered the right number of topics. But if you ask people after conversations that didn’t go well, they’ll more often say that they didn’t talk about enough things, rather than that they talked about too many things. This suggests that a common mistake is lingering too long on a topic after you’ve squeezed all the juice out of it. The second element of TALK is asking questions. I think a lot of us have heard the advice to ask more questions, yet many people don’t apply it. Why do you think that is? Many years of research have shown that the human mind is remarkably egocentric. Often, we are so focused on our own perspective that we forget to even ask someone else to share what’s in their mind. Another reason is fear. You’re interested in the other person, and you know you should ask them questions, but you’re afraid of being too intrusive, or that you will reveal your own incompetence, because you feel you should know the answer already. What kinds of questions should we be asking – and avoiding? In the book, I talk about the power of follow-up questions that build on anything that your partner has just said. It shows that you heard them, that you care and that you want to know more. Even one follow-up question can springboard us away from shallow talk into something deeper and more meaningful. There are, however, some bad patterns of question asking, such as “boomerasking”. Michael Yeomansand I have a recent paper about this, and oh my gosh, it’s been such fun to study. It’s a play on the word boomerang: it comes back to the person who threw it. If I ask you what you had for breakfast, and you tell me you had Special K and banana, and then I say, “Well, let me tell you about my breakfast, because, boy, was it delicious” – that’s boomerasking. Sometimes it’s a thinly veiled way of bragging or complaining, but sometimes I think people are genuinely interested to hear from their partner, but then the partner’s answer reminds them so much of their own life that they can’t help but start sharing their perspective. In our research, we have found that this makes your partner feel like you weren’t interested in their perspective, so it seems very insincere. Sharing your own perspective is important. It’s okay at some point to bring the conversation back to yourself. But don’t do it so soon that it makes your partner feel like you didn’t hear their answer or care about it. Research by Alison Wood Brooks includes a recent study on “boomerasking”, a pitfall you should avoid to make conversations flowJanelle Bruno What are the benefits of levity? When we think of conversations that haven’t gone well, we often think of moments of hostility, anger or disagreement, but a quiet killer of conversation is boredom. Levity is the antidote. These small moments of sparkle or fizz can pull us back in and make us feel engaged with each other again. Our research has shown that we give status and respect to people who make us feel good, so much so that in a group of people, a person who can land even one appropriate joke is more likely to be voted as the leader. And the joke doesn’t even need to be very funny! It’s the fact that they were confident enough to try it and competent enough to read the room. Do you have any practical steps that people can apply to generate levity, even if they’re not a natural comedian? Levity is not just about being funny. In fact, aiming to be a comedian is not the right goal. When we watch stand-up on Netflix, comedians have rehearsed those jokes and honed them and practised them for a long time, and they’re delivering them in a monologue to an audience. It’s a completely different task from a live conversation. In real dialogue, what everybody is looking for is to feel engaged, and that doesn’t require particularly funny jokes or elaborate stories. When you see opportunities to make it fun or lighten the mood, that’s what you need to grab. It can come through a change to a new, fresh topic, or calling back to things that you talked about earlier in the conversation or earlier in your relationship. These callbacks – which sometimes do refer to something funny – are such a nice way of showing that you’ve listened and remembered. A levity move could also involve giving sincere compliments to other people. When you think nice things, when you admire someone, make sure you say it out loud. This brings us to the last element of TALK: kindness. Why do we so often fail to be as kind as we would like? Wobbles in kindness often come back to our egocentrism. Research shows that we underestimate how much other people’s perspectives differ from our own, and we forget that we have the tools to ask other people directly in conversation for their perspective. Being a kinder conversationalist is about trying to focus on your partner’s perspective and then figuring what they need and helping them to get it. Finally, what is your number one tip for readers to have a better conversation the next time they speak to someone? Every conversation is surprisingly tricky and complex. When things don’t go perfectly, give yourself and others more grace. There will be trips and stumbles and then a little grace can go very, very far. Topics: #four #sciencebased #rules #that #will
    WWW.NEWSCIENTIST.COM
    Four science-based rules that will make your conversations flow
    One of the four pillars of good conversation is levity. You needn’t be a comedian, you can but have some funTetra Images, LLC/Alamy Conversation lies at the heart of our relationships – yet many of us find it surprisingly hard to talk to others. We may feel anxious at the thought of making small talk with strangers and struggle to connect with the people who are closest to us. If that sounds familiar, Alison Wood Brooks hopes to help. She is a professor at Harvard Business School, where she teaches an oversubscribed course called “TALK: How to talk gooder in business and life”, and the author of a new book, Talk: The science of conversation and the art of being ourselves. Both offer four key principles for more meaningful exchanges. Conversations are inherently unpredictable, says Wood Brooks, but they follow certain rules – and knowing their architecture makes us more comfortable with what is outside of our control. New Scientist asked her about the best ways to apply this research to our own chats. David Robson: Talking about talking feels quite meta. Do you ever find yourself critiquing your own performance? Alison Wood Brooks: There are so many levels of “meta-ness”. I have often felt like I’m floating over the room, watching conversations unfold, even as I’m involved in them myself. I teach a course at Harvard, and [my students] all get to experience this feeling as well. There can be an uncomfortable period of hypervigilance, but I hope that dissipates over time as they develop better habits. There is a famous quote from Charlie Parker, who was a jazz saxophonist. He said something like, “Practise, practise, practise, and then when you get on stage, let it all go and just wail.” I think that’s my approach to conversation. Even when you’re hyper-aware of conversation dynamics, you have to remember the true delight of being with another human mind, and never lose the magic of being together. Think ahead, but once you’re talking, let it all go and just wail. Reading your book, I learned that a good way to enliven a conversation is to ask someone why they are passionate about what they do. So, where does your passion for conversation come from? I have two answers to this question. One is professional. Early in my professorship at Harvard, I had been studying emotions by exploring how people talk about their feelings and the balance between what we feel inside and how we express that to others. And I realised I just had this deep, profound interest in figuring out how people talk to each other about everything, not just their feelings. We now have scientific tools that allow us to capture conversations and analyse them at large scale. Natural language processing, machine learning, the advent of AI – all this allows us to take huge swathes of transcript data and process it much more efficiently. Receive a weekly dose of discovery in your inbox. Sign up to newsletter The personal answer is that I’m an identical twin, and I spent my whole life, from the moment I opened my newborn eyes, existing next to a person who’s an exact copy of myself. It was like observing myself at very close range, interacting with the world, interacting with other people. I could see when she said and did things well, and I could try to do that myself. And I saw when her jokes failed, or she stumbled over her words – I tried to avoid those mistakes. It was a very fortunate form of feedback that not a lot of people get. And then, as a twin, you’ve got this person sharing a bedroom, sharing all your clothes, going to all the same parties and playing on the same sports teams, so we were just constantly in conversation with each other. You reached this level of shared reality that is so incredible, and I’ve spent the rest of my life trying to help other people get there in their relationships, too. “TALK” cleverly captures your framework for better conversations: topics, asking, levity and kindness. Let’s start at the beginning. How should we decide what to talk about? My first piece of advice is to prepare. Some people do this naturally. They already think about the things that they should talk about with somebody before they see them. They should lean into this habit. Some of my students, however, think it’s crazy. They think preparation will make the conversation seem rigid and forced and overly scripted. But just because you’ve thought ahead about what you might talk about doesn’t mean you have to talk about those things once the conversation is underway. It does mean, however, that you always have an idea waiting for you when you’re not sure what to talk about next. Having just one topic in your back pocket can help you in those anxiety-ridden moments. It makes things more fluent, which is important for establishing a connection. Choosing a topic is not only important at the start of a conversation. We’re constantly making decisions about whether we should stay on one subject, drift to something else or totally shift gears and go somewhere wildly different. Sometimes the topic of conversation is obvious. Even then, knowing when to switch to a new one can be trickyMartin Parr/Magnum Photos What’s your advice when making these decisions? There are three very clear signs that suggest that it’s time to switch topics. The first is longer mutual pauses. The second is more uncomfortable laughter, which we use to fill the space that we would usually fill excitedly with good content. And the third sign is redundancy. Once you start repeating things that have already been said on the topic, it’s a sign that you should move to something else. After an average conversation, most people feel like they’ve covered the right number of topics. But if you ask people after conversations that didn’t go well, they’ll more often say that they didn’t talk about enough things, rather than that they talked about too many things. This suggests that a common mistake is lingering too long on a topic after you’ve squeezed all the juice out of it. The second element of TALK is asking questions. I think a lot of us have heard the advice to ask more questions, yet many people don’t apply it. Why do you think that is? Many years of research have shown that the human mind is remarkably egocentric. Often, we are so focused on our own perspective that we forget to even ask someone else to share what’s in their mind. Another reason is fear. You’re interested in the other person, and you know you should ask them questions, but you’re afraid of being too intrusive, or that you will reveal your own incompetence, because you feel you should know the answer already. What kinds of questions should we be asking – and avoiding? In the book, I talk about the power of follow-up questions that build on anything that your partner has just said. It shows that you heard them, that you care and that you want to know more. Even one follow-up question can springboard us away from shallow talk into something deeper and more meaningful. There are, however, some bad patterns of question asking, such as “boomerasking”. Michael Yeomans [at Imperial College London] and I have a recent paper about this, and oh my gosh, it’s been such fun to study. It’s a play on the word boomerang: it comes back to the person who threw it. If I ask you what you had for breakfast, and you tell me you had Special K and banana, and then I say, “Well, let me tell you about my breakfast, because, boy, was it delicious” – that’s boomerasking. Sometimes it’s a thinly veiled way of bragging or complaining, but sometimes I think people are genuinely interested to hear from their partner, but then the partner’s answer reminds them so much of their own life that they can’t help but start sharing their perspective. In our research, we have found that this makes your partner feel like you weren’t interested in their perspective, so it seems very insincere. Sharing your own perspective is important. It’s okay at some point to bring the conversation back to yourself. But don’t do it so soon that it makes your partner feel like you didn’t hear their answer or care about it. Research by Alison Wood Brooks includes a recent study on “boomerasking”, a pitfall you should avoid to make conversations flowJanelle Bruno What are the benefits of levity? When we think of conversations that haven’t gone well, we often think of moments of hostility, anger or disagreement, but a quiet killer of conversation is boredom. Levity is the antidote. These small moments of sparkle or fizz can pull us back in and make us feel engaged with each other again. Our research has shown that we give status and respect to people who make us feel good, so much so that in a group of people, a person who can land even one appropriate joke is more likely to be voted as the leader. And the joke doesn’t even need to be very funny! It’s the fact that they were confident enough to try it and competent enough to read the room. Do you have any practical steps that people can apply to generate levity, even if they’re not a natural comedian? Levity is not just about being funny. In fact, aiming to be a comedian is not the right goal. When we watch stand-up on Netflix, comedians have rehearsed those jokes and honed them and practised them for a long time, and they’re delivering them in a monologue to an audience. It’s a completely different task from a live conversation. In real dialogue, what everybody is looking for is to feel engaged, and that doesn’t require particularly funny jokes or elaborate stories. When you see opportunities to make it fun or lighten the mood, that’s what you need to grab. It can come through a change to a new, fresh topic, or calling back to things that you talked about earlier in the conversation or earlier in your relationship. These callbacks – which sometimes do refer to something funny – are such a nice way of showing that you’ve listened and remembered. A levity move could also involve giving sincere compliments to other people. When you think nice things, when you admire someone, make sure you say it out loud. This brings us to the last element of TALK: kindness. Why do we so often fail to be as kind as we would like? Wobbles in kindness often come back to our egocentrism. Research shows that we underestimate how much other people’s perspectives differ from our own, and we forget that we have the tools to ask other people directly in conversation for their perspective. Being a kinder conversationalist is about trying to focus on your partner’s perspective and then figuring what they need and helping them to get it. Finally, what is your number one tip for readers to have a better conversation the next time they speak to someone? Every conversation is surprisingly tricky and complex. When things don’t go perfectly, give yourself and others more grace. There will be trips and stumbles and then a little grace can go very, very far. Topics:
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  • Delightfully irreverent Underdogs isn’t your parents’ nature docuseries

    show some love for the losers

    Delightfully irreverent Underdogs isn’t your parents’ nature docuseries

    Ryan Reynolds narrates NatGeo's new series highlighting nature's much less cool and majestic creatures

    Jennifer Ouellette



    Jun 15, 2025 3:11 pm

    |

    5

    The indestructible honey badger is just one of nature's "benchwarmers" featured in Underdogs

    Credit:

    National Geographic/Doug Parker

    The indestructible honey badger is just one of nature's "benchwarmers" featured in Underdogs

    Credit:

    National Geographic/Doug Parker

    Story text

    Size

    Small
    Standard
    Large

    Width
    *

    Standard
    Wide

    Links

    Standard
    Orange

    * Subscribers only
      Learn more

    Narrator Ryan Reynolds celebrates nature's outcasts in the new NatGeo docuseries Underdogs.

    Most of us have seen a nature documentary or twoat some point in our lives, so it's a familiar format: sweeping majestic footage of impressively regal animals accompanied by reverently high-toned narration. Underdogs, a new docuseries from National Geographic, takes a decidedly different and unconventional approach. Narrated by with hilarious irreverence by Ryan Reynolds, the five-part series highlights nature's less cool and majestic creatures: the outcasts and benchwarmers, more noteworthy for their "unconventional hygiene choices" and "unsavory courtship rituals." It's like The Suicide Squad or Thunderbolts*, except these creatures actually exist.
    Per the official premise, "Underdogs features a range of never-before-filmed scenes, including the first time a film crew has ever entered a special cave in New Zealand—a huge cavern that glows brighter than a bachelor pad under a black light thanks to the glowing butts of millions of mucus-coated grubs. All over the world, overlooked superstars like this are out there 24/7, giving it maximum effort and keeping the natural world in working order for all those showboating polar bears, sharks and gorillas." It's rated PG-13 thanks to the odd bit of scatalogical humor and shots of Nature Sexy Time
    Each of the five episodes is built around a specific genre. "Superheroes" highlights the surprising superpowers of the honey badger, pistol shrimp, and the invisible glass frog, among others, augmented with comic book graphics; "Sexy Beasts" focuses on bizarre mating habits and follows the format of a romantic advice column; "Terrible Parents" highlights nature's worst practices, following the outline of a parenting guide; "Total Grossout" is exactly what it sounds like; and "The Unusual Suspects" is a heist tale, documenting the supposed efforts of a macaque to put together the ultimate team of masters of deception and disguise.  Green Day even wrote and recorded a special theme song for the opening credits.
    Co-creators Mark Linfield and Vanessa Berlowitz of Wildstar Films are longtime producers of award-winning wildlife films, most notably Frozen Planet, Planet Earth and David Attenborough's Life of Mammals—you know, the kind of prestige nature documentaries that have become a mainstay for National Geographic and the BBC, among others. They're justly proud of that work, but this time around the duo wanted to try something different.

    Madagascar's aye-aye: "as if fear and panic had a baby and rolled it in dog hair"

    National Geographic/Eleanor Paish

    Madagascar's aye-aye: "as if fear and panic had a baby and rolled it in dog hair"

    National Geographic/Eleanor Paish

    An emerald jewel wasp emerges from a cockroach.

    National Geographic/Simon De Glanville

    An emerald jewel wasp emerges from a cockroach.

    National Geographic/Simon De Glanville

    A pack of African hunting dogs is no match for the honey badger's thick hide.

    National Geographic/Tom Walker

    A pack of African hunting dogs is no match for the honey badger's thick hide.

    National Geographic/Tom Walker

    An emerald jewel wasp emerges from a cockroach.

    National Geographic/Simon De Glanville

    A pack of African hunting dogs is no match for the honey badger's thick hide.

    National Geographic/Tom Walker

    A fireworm is hit by a cavitation bubble shot from the claw of a pistol shrimp defending its home.

    National Geographic/Hugh Miller

    As it grows and molts, the mad hatterpillar stacks old head casings on top of its head. Scientists think it is used as a decoy against would-be predators and parasites, and when needed, it can also be used as a weapon.

    National Geographic/Katherine Hannaford

    Worst parents ever? A young barnacle goose chick prepares t make the 800-foot jump from its nest to the ground.

    National Geographic

    An adult pearlfish reverses into a sea cucumber's butt to hide.

    National Geographic

    A vulture sticks its head inside an elephant carcass to eat.

    National Geographic

    A manatee releases flatulence while swimming to lose the buoyancy build up of gas inside its stomach, and descend down the water column.

    National Geographic/Karl Davies

    "There is a sense after awhile that you're playing the same animals to the same people, and the shows are starting to look the same and so is your audience," Linfield told Ars. "We thought, okay, how can we do something absolutely the opposite? We've gone through our careers collecting stories of these weird and crazy creatures that don't end up in the script because they're not big or sexy and they live under a rock. But they often have the best life histories and the craziest superpowers."
    Case in point: the velvet worm featured in the "Superheroes" episode, which creeps up on unsuspecting prey before squirting disgusting slime all over their food.Once Linfield and Berlowitz decided to focus on nature's underdogs and to take a more humorous approach, Ryan Reynolds became their top choice for a narrator—the anti-Richard Attenborough. As luck would have it, the pair shared an agent with the mega-star. So even though they thought there was no way Reynolds would agree to the project, they put together a sizzle reel, complete with a "fake Canadian Ryan Reynolds sound-alike" doing the narration. Reynolds was on set when he received the reel, and loved it so much he recoded his own narration for the footage and sent it back.
    "From that moment he was in," said Linfield, and Wildstar Films worked closely with Reynolds and his company to develop the final series. "We've never worked that way on a series before, a joint collaboration from day one," Berlowitz admitted. But it worked: the end result strikes the perfect balance between scientific revelation and accurate natural history, and an edgy comic tone.
    That tone is quintessential Reynolds, and while he did mostly follow the script, Linfield and Berlowitz admit there was also a fair amount of improvisation—not all of it PG-13.  "What we hadn't appreciated is that he's an incredible improv performer," said Berlowitz. "He can't help himself. He gets into character and starts riffing off. There are some takes that we definitely couldn't use, that potentially would fit a slightly more Hulu audience."  Some of the ad-libs made it into the final episodes, however—like Reynolds describing an Aye-Aye as "if fear and panic had a baby and rolled it in dog hair"—even though it meant going back and doing a bit of recutting to get the new lines to fit.

    Cinematographer Tom Beldam films a long-tailed macaque who stole his smart phone minutes later.

    National Geographic/Laura Pennafort

    Cinematographer Tom Beldam films a long-tailed macaque who stole his smart phone minutes later.

    National Geographic/Laura Pennafort

    The macaque agrees to trade ithe stolen phone for a piece of food.

    National Geographic

    The macaque agrees to trade ithe stolen phone for a piece of food.

    National Geographic

    A family of tortoise beetles defend themselves from a carnivorous ant by wafting baby poop in its direction.

    National Geographic

    A family of tortoise beetles defend themselves from a carnivorous ant by wafting baby poop in its direction.

    National Geographic

    The macaque agrees to trade ithe stolen phone for a piece of food.

    National Geographic

    A family of tortoise beetles defend themselves from a carnivorous ant by wafting baby poop in its direction.

    National Geographic

    A male hippo sprays his feces at another male who is threatening to take over his patch.

    National Geographic

    A male proboscis monkey flaunts his large nose. The noses of these males are used to amplify their calls in the vast forest.

    National Geographic

    Dream girl: A blood-soaked female hyena looks across the African savanna.

    National Geographic

    A male bowerbird presents one of the finest items in his collection to a female in his bower.

    National Geographic

    The male nursery web spider presents his nuptial gift to the female.

    National Geographic

    Cue the Barry White mood music: Two leopard slugs suspend themselves on a rope of mucus as they entwine their bodies to mate with one another.

    National Geographic

    Despite their years of collective experience, Linfield and Berlowitz were initially skeptical when the crew told them about the pearl fish, which hides from predators in a sea cucumber's butt. "It had never been filmed so we said, 'You're going to have to prove it to us,'" said Berlowitz. "They came back with this fantastic, hilarious sequence of a pearl fish reverse parking [in a sea cucumber's anus)."
    The film crew experienced a few heart-pounding moments, most notably while filming the cliffside nests of barnacle geese for the "Terrible Parents" episode. A melting glacier caused a watery avalanche while the crew was filming the geese, and they had to quickly grab a few shots and run to safety. Less dramatic: cinematographer Tom Beldam had his smartphone stolen by a long-tailed macaque mere minutes after he finished capturing the animal on film.
    If all goes well and Underdogs finds its target audience, we may even get a follow-up. "We are slightly plowing new territory but the science is as true as it's ever been and the stories are good. That aspect of the natural history is still there," said Linfield. "I think what we really hope for is that people who don't normally watch natural history will watch it. If people have as much fun watching it as we had making it, then the metrics should be good enough for another season."
    Verdict: Underdogs is positively addictive; I binged all five episodes in a single day.Underdogs premieres June 15, 2025, at 9 PM/8 PM Central on National Geographicand will be available for streaming on Disney+ and Hulu the following day.  You should watch it, if only to get that second season.

    Jennifer Ouellette
    Senior Writer

    Jennifer Ouellette
    Senior Writer

    Jennifer is a senior writer at Ars Technica with a particular focus on where science meets culture, covering everything from physics and related interdisciplinary topics to her favorite films and TV series. Jennifer lives in Baltimore with her spouse, physicist Sean M. Carroll, and their two cats, Ariel and Caliban.

    5 Comments
    #delightfully #irreverent #underdogs #isnt #your
    Delightfully irreverent Underdogs isn’t your parents’ nature docuseries
    show some love for the losers Delightfully irreverent Underdogs isn’t your parents’ nature docuseries Ryan Reynolds narrates NatGeo's new series highlighting nature's much less cool and majestic creatures Jennifer Ouellette – Jun 15, 2025 3:11 pm | 5 The indestructible honey badger is just one of nature's "benchwarmers" featured in Underdogs Credit: National Geographic/Doug Parker The indestructible honey badger is just one of nature's "benchwarmers" featured in Underdogs Credit: National Geographic/Doug Parker Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only   Learn more Narrator Ryan Reynolds celebrates nature's outcasts in the new NatGeo docuseries Underdogs. Most of us have seen a nature documentary or twoat some point in our lives, so it's a familiar format: sweeping majestic footage of impressively regal animals accompanied by reverently high-toned narration. Underdogs, a new docuseries from National Geographic, takes a decidedly different and unconventional approach. Narrated by with hilarious irreverence by Ryan Reynolds, the five-part series highlights nature's less cool and majestic creatures: the outcasts and benchwarmers, more noteworthy for their "unconventional hygiene choices" and "unsavory courtship rituals." It's like The Suicide Squad or Thunderbolts*, except these creatures actually exist. Per the official premise, "Underdogs features a range of never-before-filmed scenes, including the first time a film crew has ever entered a special cave in New Zealand—a huge cavern that glows brighter than a bachelor pad under a black light thanks to the glowing butts of millions of mucus-coated grubs. All over the world, overlooked superstars like this are out there 24/7, giving it maximum effort and keeping the natural world in working order for all those showboating polar bears, sharks and gorillas." It's rated PG-13 thanks to the odd bit of scatalogical humor and shots of Nature Sexy Time Each of the five episodes is built around a specific genre. "Superheroes" highlights the surprising superpowers of the honey badger, pistol shrimp, and the invisible glass frog, among others, augmented with comic book graphics; "Sexy Beasts" focuses on bizarre mating habits and follows the format of a romantic advice column; "Terrible Parents" highlights nature's worst practices, following the outline of a parenting guide; "Total Grossout" is exactly what it sounds like; and "The Unusual Suspects" is a heist tale, documenting the supposed efforts of a macaque to put together the ultimate team of masters of deception and disguise.  Green Day even wrote and recorded a special theme song for the opening credits. Co-creators Mark Linfield and Vanessa Berlowitz of Wildstar Films are longtime producers of award-winning wildlife films, most notably Frozen Planet, Planet Earth and David Attenborough's Life of Mammals—you know, the kind of prestige nature documentaries that have become a mainstay for National Geographic and the BBC, among others. They're justly proud of that work, but this time around the duo wanted to try something different. Madagascar's aye-aye: "as if fear and panic had a baby and rolled it in dog hair" National Geographic/Eleanor Paish Madagascar's aye-aye: "as if fear and panic had a baby and rolled it in dog hair" National Geographic/Eleanor Paish An emerald jewel wasp emerges from a cockroach. National Geographic/Simon De Glanville An emerald jewel wasp emerges from a cockroach. National Geographic/Simon De Glanville A pack of African hunting dogs is no match for the honey badger's thick hide. National Geographic/Tom Walker A pack of African hunting dogs is no match for the honey badger's thick hide. National Geographic/Tom Walker An emerald jewel wasp emerges from a cockroach. National Geographic/Simon De Glanville A pack of African hunting dogs is no match for the honey badger's thick hide. National Geographic/Tom Walker A fireworm is hit by a cavitation bubble shot from the claw of a pistol shrimp defending its home. National Geographic/Hugh Miller As it grows and molts, the mad hatterpillar stacks old head casings on top of its head. Scientists think it is used as a decoy against would-be predators and parasites, and when needed, it can also be used as a weapon. National Geographic/Katherine Hannaford Worst parents ever? A young barnacle goose chick prepares t make the 800-foot jump from its nest to the ground. National Geographic An adult pearlfish reverses into a sea cucumber's butt to hide. National Geographic A vulture sticks its head inside an elephant carcass to eat. National Geographic A manatee releases flatulence while swimming to lose the buoyancy build up of gas inside its stomach, and descend down the water column. National Geographic/Karl Davies "There is a sense after awhile that you're playing the same animals to the same people, and the shows are starting to look the same and so is your audience," Linfield told Ars. "We thought, okay, how can we do something absolutely the opposite? We've gone through our careers collecting stories of these weird and crazy creatures that don't end up in the script because they're not big or sexy and they live under a rock. But they often have the best life histories and the craziest superpowers." Case in point: the velvet worm featured in the "Superheroes" episode, which creeps up on unsuspecting prey before squirting disgusting slime all over their food.Once Linfield and Berlowitz decided to focus on nature's underdogs and to take a more humorous approach, Ryan Reynolds became their top choice for a narrator—the anti-Richard Attenborough. As luck would have it, the pair shared an agent with the mega-star. So even though they thought there was no way Reynolds would agree to the project, they put together a sizzle reel, complete with a "fake Canadian Ryan Reynolds sound-alike" doing the narration. Reynolds was on set when he received the reel, and loved it so much he recoded his own narration for the footage and sent it back. "From that moment he was in," said Linfield, and Wildstar Films worked closely with Reynolds and his company to develop the final series. "We've never worked that way on a series before, a joint collaboration from day one," Berlowitz admitted. But it worked: the end result strikes the perfect balance between scientific revelation and accurate natural history, and an edgy comic tone. That tone is quintessential Reynolds, and while he did mostly follow the script, Linfield and Berlowitz admit there was also a fair amount of improvisation—not all of it PG-13.  "What we hadn't appreciated is that he's an incredible improv performer," said Berlowitz. "He can't help himself. He gets into character and starts riffing off. There are some takes that we definitely couldn't use, that potentially would fit a slightly more Hulu audience."  Some of the ad-libs made it into the final episodes, however—like Reynolds describing an Aye-Aye as "if fear and panic had a baby and rolled it in dog hair"—even though it meant going back and doing a bit of recutting to get the new lines to fit. Cinematographer Tom Beldam films a long-tailed macaque who stole his smart phone minutes later. National Geographic/Laura Pennafort Cinematographer Tom Beldam films a long-tailed macaque who stole his smart phone minutes later. National Geographic/Laura Pennafort The macaque agrees to trade ithe stolen phone for a piece of food. National Geographic The macaque agrees to trade ithe stolen phone for a piece of food. National Geographic A family of tortoise beetles defend themselves from a carnivorous ant by wafting baby poop in its direction. National Geographic A family of tortoise beetles defend themselves from a carnivorous ant by wafting baby poop in its direction. National Geographic The macaque agrees to trade ithe stolen phone for a piece of food. National Geographic A family of tortoise beetles defend themselves from a carnivorous ant by wafting baby poop in its direction. National Geographic A male hippo sprays his feces at another male who is threatening to take over his patch. National Geographic A male proboscis monkey flaunts his large nose. The noses of these males are used to amplify their calls in the vast forest. National Geographic Dream girl: A blood-soaked female hyena looks across the African savanna. National Geographic A male bowerbird presents one of the finest items in his collection to a female in his bower. National Geographic The male nursery web spider presents his nuptial gift to the female. National Geographic Cue the Barry White mood music: Two leopard slugs suspend themselves on a rope of mucus as they entwine their bodies to mate with one another. National Geographic Despite their years of collective experience, Linfield and Berlowitz were initially skeptical when the crew told them about the pearl fish, which hides from predators in a sea cucumber's butt. "It had never been filmed so we said, 'You're going to have to prove it to us,'" said Berlowitz. "They came back with this fantastic, hilarious sequence of a pearl fish reverse parking [in a sea cucumber's anus)." The film crew experienced a few heart-pounding moments, most notably while filming the cliffside nests of barnacle geese for the "Terrible Parents" episode. A melting glacier caused a watery avalanche while the crew was filming the geese, and they had to quickly grab a few shots and run to safety. Less dramatic: cinematographer Tom Beldam had his smartphone stolen by a long-tailed macaque mere minutes after he finished capturing the animal on film. If all goes well and Underdogs finds its target audience, we may even get a follow-up. "We are slightly plowing new territory but the science is as true as it's ever been and the stories are good. That aspect of the natural history is still there," said Linfield. "I think what we really hope for is that people who don't normally watch natural history will watch it. If people have as much fun watching it as we had making it, then the metrics should be good enough for another season." Verdict: Underdogs is positively addictive; I binged all five episodes in a single day.Underdogs premieres June 15, 2025, at 9 PM/8 PM Central on National Geographicand will be available for streaming on Disney+ and Hulu the following day.  You should watch it, if only to get that second season. Jennifer Ouellette Senior Writer Jennifer Ouellette Senior Writer Jennifer is a senior writer at Ars Technica with a particular focus on where science meets culture, covering everything from physics and related interdisciplinary topics to her favorite films and TV series. Jennifer lives in Baltimore with her spouse, physicist Sean M. Carroll, and their two cats, Ariel and Caliban. 5 Comments #delightfully #irreverent #underdogs #isnt #your
    ARSTECHNICA.COM
    Delightfully irreverent Underdogs isn’t your parents’ nature docuseries
    show some love for the losers Delightfully irreverent Underdogs isn’t your parents’ nature docuseries Ryan Reynolds narrates NatGeo's new series highlighting nature's much less cool and majestic creatures Jennifer Ouellette – Jun 15, 2025 3:11 pm | 5 The indestructible honey badger is just one of nature's "benchwarmers" featured in Underdogs Credit: National Geographic/Doug Parker The indestructible honey badger is just one of nature's "benchwarmers" featured in Underdogs Credit: National Geographic/Doug Parker Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only   Learn more Narrator Ryan Reynolds celebrates nature's outcasts in the new NatGeo docuseries Underdogs. Most of us have seen a nature documentary or two (or three) at some point in our lives, so it's a familiar format: sweeping majestic footage of impressively regal animals accompanied by reverently high-toned narration (preferably with a tony British accent). Underdogs, a new docuseries from National Geographic, takes a decidedly different and unconventional approach. Narrated by with hilarious irreverence by Ryan Reynolds, the five-part series highlights nature's less cool and majestic creatures: the outcasts and benchwarmers, more noteworthy for their "unconventional hygiene choices" and "unsavory courtship rituals." It's like The Suicide Squad or Thunderbolts*, except these creatures actually exist. Per the official premise, "Underdogs features a range of never-before-filmed scenes, including the first time a film crew has ever entered a special cave in New Zealand—a huge cavern that glows brighter than a bachelor pad under a black light thanks to the glowing butts of millions of mucus-coated grubs. All over the world, overlooked superstars like this are out there 24/7, giving it maximum effort and keeping the natural world in working order for all those showboating polar bears, sharks and gorillas." It's rated PG-13 thanks to the odd bit of scatalogical humor and shots of Nature Sexy Time Each of the five episodes is built around a specific genre. "Superheroes" highlights the surprising superpowers of the honey badger, pistol shrimp, and the invisible glass frog, among others, augmented with comic book graphics; "Sexy Beasts" focuses on bizarre mating habits and follows the format of a romantic advice column; "Terrible Parents" highlights nature's worst practices, following the outline of a parenting guide; "Total Grossout" is exactly what it sounds like; and "The Unusual Suspects" is a heist tale, documenting the supposed efforts of a macaque to put together the ultimate team of masters of deception and disguise (an inside man, a decoy, a fall guy, etc.).  Green Day even wrote and recorded a special theme song for the opening credits. Co-creators Mark Linfield and Vanessa Berlowitz of Wildstar Films are longtime producers of award-winning wildlife films, most notably Frozen Planet, Planet Earth and David Attenborough's Life of Mammals—you know, the kind of prestige nature documentaries that have become a mainstay for National Geographic and the BBC, among others. They're justly proud of that work, but this time around the duo wanted to try something different. Madagascar's aye-aye: "as if fear and panic had a baby and rolled it in dog hair" National Geographic/Eleanor Paish Madagascar's aye-aye: "as if fear and panic had a baby and rolled it in dog hair" National Geographic/Eleanor Paish An emerald jewel wasp emerges from a cockroach. National Geographic/Simon De Glanville An emerald jewel wasp emerges from a cockroach. National Geographic/Simon De Glanville A pack of African hunting dogs is no match for the honey badger's thick hide. National Geographic/Tom Walker A pack of African hunting dogs is no match for the honey badger's thick hide. National Geographic/Tom Walker An emerald jewel wasp emerges from a cockroach. National Geographic/Simon De Glanville A pack of African hunting dogs is no match for the honey badger's thick hide. National Geographic/Tom Walker A fireworm is hit by a cavitation bubble shot from the claw of a pistol shrimp defending its home. National Geographic/Hugh Miller As it grows and molts, the mad hatterpillar stacks old head casings on top of its head. Scientists think it is used as a decoy against would-be predators and parasites, and when needed, it can also be used as a weapon. National Geographic/Katherine Hannaford Worst parents ever? A young barnacle goose chick prepares t make the 800-foot jump from its nest to the ground. National Geographic An adult pearlfish reverses into a sea cucumber's butt to hide. National Geographic A vulture sticks its head inside an elephant carcass to eat. National Geographic A manatee releases flatulence while swimming to lose the buoyancy build up of gas inside its stomach, and descend down the water column. National Geographic/Karl Davies "There is a sense after awhile that you're playing the same animals to the same people, and the shows are starting to look the same and so is your audience," Linfield told Ars. "We thought, okay, how can we do something absolutely the opposite? We've gone through our careers collecting stories of these weird and crazy creatures that don't end up in the script because they're not big or sexy and they live under a rock. But they often have the best life histories and the craziest superpowers." Case in point: the velvet worm featured in the "Superheroes" episode, which creeps up on unsuspecting prey before squirting disgusting slime all over their food. (It's a handy defense mechanism, too, against predators like the wolf spider.) Once Linfield and Berlowitz decided to focus on nature's underdogs and to take a more humorous approach, Ryan Reynolds became their top choice for a narrator—the anti-Richard Attenborough. As luck would have it, the pair shared an agent with the mega-star. So even though they thought there was no way Reynolds would agree to the project, they put together a sizzle reel, complete with a "fake Canadian Ryan Reynolds sound-alike" doing the narration. Reynolds was on set when he received the reel, and loved it so much he recoded his own narration for the footage and sent it back. "From that moment he was in," said Linfield, and Wildstar Films worked closely with Reynolds and his company to develop the final series. "We've never worked that way on a series before, a joint collaboration from day one," Berlowitz admitted. But it worked: the end result strikes the perfect balance between scientific revelation and accurate natural history, and an edgy comic tone. That tone is quintessential Reynolds, and while he did mostly follow the script (which his team helped write), Linfield and Berlowitz admit there was also a fair amount of improvisation—not all of it PG-13.  "What we hadn't appreciated is that he's an incredible improv performer," said Berlowitz. "He can't help himself. He gets into character and starts riffing off [the footage]. There are some takes that we definitely couldn't use, that potentially would fit a slightly more Hulu audience."  Some of the ad-libs made it into the final episodes, however—like Reynolds describing an Aye-Aye as "if fear and panic had a baby and rolled it in dog hair"—even though it meant going back and doing a bit of recutting to get the new lines to fit. Cinematographer Tom Beldam films a long-tailed macaque who stole his smart phone minutes later. National Geographic/Laura Pennafort Cinematographer Tom Beldam films a long-tailed macaque who stole his smart phone minutes later. National Geographic/Laura Pennafort The macaque agrees to trade ithe stolen phone for a piece of food. National Geographic The macaque agrees to trade ithe stolen phone for a piece of food. National Geographic A family of tortoise beetles defend themselves from a carnivorous ant by wafting baby poop in its direction. National Geographic A family of tortoise beetles defend themselves from a carnivorous ant by wafting baby poop in its direction. National Geographic The macaque agrees to trade ithe stolen phone for a piece of food. National Geographic A family of tortoise beetles defend themselves from a carnivorous ant by wafting baby poop in its direction. National Geographic A male hippo sprays his feces at another male who is threatening to take over his patch. National Geographic A male proboscis monkey flaunts his large nose. The noses of these males are used to amplify their calls in the vast forest. National Geographic Dream girl: A blood-soaked female hyena looks across the African savanna. National Geographic A male bowerbird presents one of the finest items in his collection to a female in his bower. National Geographic The male nursery web spider presents his nuptial gift to the female. National Geographic Cue the Barry White mood music: Two leopard slugs suspend themselves on a rope of mucus as they entwine their bodies to mate with one another. National Geographic Despite their years of collective experience, Linfield and Berlowitz were initially skeptical when the crew told them about the pearl fish, which hides from predators in a sea cucumber's butt (along with many other species). "It had never been filmed so we said, 'You're going to have to prove it to us,'" said Berlowitz. "They came back with this fantastic, hilarious sequence of a pearl fish reverse parking [in a sea cucumber's anus)." The film crew experienced a few heart-pounding moments, most notably while filming the cliffside nests of barnacle geese for the "Terrible Parents" episode. A melting glacier caused a watery avalanche while the crew was filming the geese, and they had to quickly grab a few shots and run to safety. Less dramatic: cinematographer Tom Beldam had his smartphone stolen by a long-tailed macaque mere minutes after he finished capturing the animal on film. If all goes well and Underdogs finds its target audience, we may even get a follow-up. "We are slightly plowing new territory but the science is as true as it's ever been and the stories are good. That aspect of the natural history is still there," said Linfield. "I think what we really hope for is that people who don't normally watch natural history will watch it. If people have as much fun watching it as we had making it, then the metrics should be good enough for another season." Verdict: Underdogs is positively addictive; I binged all five episodes in a single day. (For his part, Reynolds said in a statement that he was thrilled to "finally watch a project of ours with my children. Technically they saw Deadpool and Wolverine but I don't think they absorbed much while covering their eyes and ears and screaming for two hours.") Underdogs premieres June 15, 2025, at 9 PM/8 PM Central on National Geographic (simulcast on ABC) and will be available for streaming on Disney+ and Hulu the following day.  You should watch it, if only to get that second season. Jennifer Ouellette Senior Writer Jennifer Ouellette Senior Writer Jennifer is a senior writer at Ars Technica with a particular focus on where science meets culture, covering everything from physics and related interdisciplinary topics to her favorite films and TV series. Jennifer lives in Baltimore with her spouse, physicist Sean M. Carroll, and their two cats, Ariel and Caliban. 5 Comments
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