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In this episode, robotics expert Scott Walter (Humanoid Scott) breaks down Sunday’s debut, XPeng’s viral controversy, the big, yet strange, UBTech robot fleet, and more. 1:05 XPENG's New Robot, "Person in Suit" Debate 6:57 Actuation Strategy for the new XPENG IRON 17:18 Sunday Robotics Debut & Mobile Home Robot... show more

The Humanoid Hub

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New Episode: Humanoid Botangelist Dives Deep into Tesla's Optimus Scott breaks down Optimus Gen2, explores potential Gen3 design upgrades, the hands problem, actuator supply chain hurdles, Tesla’s shift away from teleoperation, and more. We shot a video at Tesla’s Fremont showroom of Scott analyzing a Gen2 bot in early summer, but due to poor audio, it wasn’t published. Scott revisits parts of that video here. 0:01 Meet Scott Walter, robotics expert 2:19 Gen2 refresher - wrist mechanism 2:45 Inside Gen2’s wrist parallel mechanism 8:28 Gen3 hand wrist redesign and packaging 5:20 Linear vs. rotary actuator supply chain 20:14 Tesla exploring dexterous hand designs 22:16 Hybrid actuation for hand precision 27:29 Tesla team consults hand surgeon 31:01 Shift to Gen3 production focus 34:04 Moving from teleoperation data 39:01 Autonomous demos via first-person videos 42:46 Gen3 hip and leg actuation upgrades 49:30 Optimus production scaling to 2026 53:36 Closing remarks Recorded on August 29

New Episode: Humanoid Botangelist Dives Deep into Tesla's Optimus Scott breaks down Optimus Gen2, explores potential Gen3 design upgrades, the hands problem, actuator supply chain hurdles, Tesla’s shift away from teleoperation, and more. We shot a video at Tesla’s Fremont showroom of Scott analyzing a Gen2 bot in early summer, but due to poor audio, it wasn’t published. Scott revisits parts of that video here. 0:01 Meet Scott Walter, robotics expert 2:19 Gen2 refresher - wrist mechanism 2:45 Inside Gen2’s wrist parallel mechanism 8:28 Gen3 hand wrist redesign and packaging 5:20 Linear vs. rotary actuator supply chain 20:14 Tesla exploring dexterous hand designs 22:16 Hybrid actuation for hand precision 27:29 Tesla team consults hand surgeon 31:01 Shift to Gen3 production focus 34:04 Moving from teleoperation data 39:01 Autonomous demos via first-person videos 42:46 Gen3 hip and leg actuation upgrades 49:30 Optimus production scaling to 2026 53:36 Closing remarks Recorded on August 29

The Humanoid Hub

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The Future of Tesla: AI, Robotaxis, and Embracing Technological Change This episode features a compelling conversation with Emmet Peppers from Good Soil Investment Management, who has been closely following Tesla's story for over a decade. We delve into the implications of Tesla's advancements in AI and autonomous driving, including the future of robotaxis and humanoid robots like Optimus. 0:00 Tesla's Vision: Beyond Cars to Sentient Robots 0:38 Introducing Emmett Peppers: A Decade of Tesla Insights 1:41 The Future of AI and Tesla's Role 2:20 The Simplicity of Investing in Tesla 4:26 Wall Street's Awakening to Tesla's Potential 6:28 The Road to Robotaxis and AI Embodiment 8:52 Challenges and Misconceptions About Tesla's Technology 12:10 The Investment Potential of Tesla's AI and Robotaxis 17:18 Tesla's Future: From Robotaxis to Humanoid Robots 23:06 The Paradigm Shift: Tesla's Impact on Society 26:04 The Economic Implications of Tesla's Innovations 31:11 The Road Ahead: Tesla's Market and Technological Advancements 41:46 High Valuation and Bull Case for Tesla 42:21 Elon's Compensation Plan and Stock Milestones 43:28 Humanoid Robots and Future Predictions 46:03 Economic Implications of AI and Robotics 53:50 Societal Impact and Universal Basic Income 01:00:37 Debate, Discourse, and Media Influence 01:15:22 Concluding Thoughts and Future Outlook

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37,219 Aufrufe • vor 9 Monaten

Here's my conversation with Marc Raibert, founder and long-time CEO of Boston Dynamics, and head of their new AI Institute, all about the history and future of robotics. It's here on X in full, and is up on YouTube, Spotify, and everywhere else. Links in comment. Timestamps: 0:00 - Introduction 1:43 - Early robots 6:47 - Legged robots 25:27 - Boston Dynamics 28:45 - BigDog 36:52 - Hydraulic actuation 38:44 - Natural movement 44:31 - Leg Lab 51:23 - AI Institute 54:41 - Athletic intelligence 1:02:35 - Building a team 1:05:37 - Videos 1:13:25 - Engineering 1:16:53 - Dancing robots 1:21:40 - Hiring 1:25:32 - Optimus robot 1:34:02 - Future of robotics 1:38:56 - Advice for young people

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The Humanoid Hub

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Molly O’Shea

732,250 Aufrufe • vor 2 Monaten

Today, we're joined by Nikita Rudin, co-founder and CEO of Flexion Robotics to discuss the gap between current robotic capabilities and what’s required to deploy fully autonomous robots in the real world. Nikita explains how reinforcement learning and simulation have driven rapid progress in robot locomotion—and why locomotion is still far from “solved.” We dig into the sim2real gap, and how adding visual inputs introduces noise and significantly complicates sim-to-real transfer. We also explore the debate between end-to-end models and modular approaches, and why separating locomotion, planning, and semantics remains a pragmatic approach today. Nikita also introduces the concept of "real-to-sim", which uses real-world data to refine simulation parameters for higher fidelity training, discusses how reinforcement learning, imitation learning, and teleoperation data are combined to train robust policies for both quadruped and humanoid robots, and introduces Flexion's hierarchical approach that utilizes pre-trained Vision-Language Models (VLMs) for high-level task orchestration with Vision-Language-Action (VLA) models and low-level whole-body trackers. Finally, Nikita shares the behind-the-scenes in humanoid robot demos, his take on reinforcement learning in simulation versus the real world, the nuances of reward tuning, and offers practical advice for researchers and practitioners looking to get started in robotics today. 🗒️ For the full list of resources for this episode, visit the show notes page: 📖 CHAPTERS =============================== 00:00 - Introduction 04:07 - Is robot locomotion solved? 06:04 - Sim-to-real gap 08:58 - Adding semantics to policies 09:42 - Modular vs end-to-end architectures 10:29 - Planner model 12:21 - Adapting RL techniques from quadrupeds to humanoids 15:39 - Behind robot demos 18:09 - Humanoid robots in home environments 22:03 - Training approach 23:56 - VLA models 27:59 - Closing the sim-to-real gap 32:55 - Task orchestration using VLMs 36:38 - Tool use 38:10 - Model hierarchy 43:37 - Simulator versus simulation environment 44:57 - Combining imitation learning and reinforcement learning 46:42 - RL in real world versus RL in simulation 52:58 - Reward tuning and value functions in robotics 56:38 - Predictions 1:00:10 - Humanoids, quadropeds, and wheeled platforms 1:02:45 - Advice, recommended robot kits, and community pla

Today, we're joined by Nikita Rudin, co-founder and CEO of Flexion Robotics to discuss the gap between current robotic capabilities and what’s required to deploy fully autonomous robots in the real world. Nikita explains how reinforcement learning and simulation have driven rapid progress in robot locomotion—and why locomotion is still far from “solved.” We dig into the sim2real gap, and how adding visual inputs introduces noise and significantly complicates sim-to-real transfer. We also explore the debate between end-to-end models and modular approaches, and why separating locomotion, planning, and semantics remains a pragmatic approach today. Nikita also introduces the concept of "real-to-sim", which uses real-world data to refine simulation parameters for higher fidelity training, discusses how reinforcement learning, imitation learning, and teleoperation data are combined to train robust policies for both quadruped and humanoid robots, and introduces Flexion's hierarchical approach that utilizes pre-trained Vision-Language Models (VLMs) for high-level task orchestration with Vision-Language-Action (VLA) models and low-level whole-body trackers. Finally, Nikita shares the behind-the-scenes in humanoid robot demos, his take on reinforcement learning in simulation versus the real world, the nuances of reward tuning, and offers practical advice for researchers and practitioners looking to get started in robotics today. 🗒️ For the full list of resources for this episode, visit the show notes page: 📖 CHAPTERS =============================== 00:00 - Introduction 04:07 - Is robot locomotion solved? 06:04 - Sim-to-real gap 08:58 - Adding semantics to policies 09:42 - Modular vs end-to-end architectures 10:29 - Planner model 12:21 - Adapting RL techniques from quadrupeds to humanoids 15:39 - Behind robot demos 18:09 - Humanoid robots in home environments 22:03 - Training approach 23:56 - VLA models 27:59 - Closing the sim-to-real gap 32:55 - Task orchestration using VLMs 36:38 - Tool use 38:10 - Model hierarchy 43:37 - Simulator versus simulation environment 44:57 - Combining imitation learning and reinforcement learning 46:42 - RL in real world versus RL in simulation 52:58 - Reward tuning and value functions in robotics 56:38 - Predictions 1:00:10 - Humanoids, quadropeds, and wheeled platforms 1:02:45 - Advice, recommended robot kits, and community pla

The TWIML AI Podcast

22,264 Aufrufe • vor 6 Monaten

Video: China firm to unveil world’s most ‘adorable’ humanoid robot for homes, schools | Christopher McFadden, Interesting Engineering Fourier’s latest humanoid robot, the GR‑3, is designed for domestic and educational environments. Fourier Robotics, the Shanghai-based robotics firm behind the GR-1 and GR-2 models, is preparing to launch its GR-3 humanoid robot on August 6. Early glimpses of the new robot, including a sneak-peek video, reveal a smaller, friendlier design, described as possibly the “most adorable humanoid robot yet.” Concrete information is scarce, but early reports suggest the robot will be smaller than its predecessors. According to some reports, the GR-3 will likely stand at around 4 feet 5 inches (134 cm). This makes it notably smaller than the earlier GR-1 (5.4 feet/165 cm) and GR-2 (5.74 feet/175 cm) models from Fourier. Most notable is its apparent “softer,” almost cuddly aesthetic.” The robot is likely intended for use in homes, schools, hospitals, and public spaces. It also features an integrated large language model (LLM) to enable natural speech engagement with users. To this end, the GR-3 will likely be marked as a companion‑style or caregiver bot (AKA a “Care‑bot”) aimed at friendly human interaction in personal or learning environments. GR-3: Fourier’s cutest robot yet “This softer aesthetic is a nice change compared to the usual designs we see with humanoid robots. The eyes are a much-needed touch,” comments a member on the Companian Robot Forums. “It’s so expressive and draws you in. Can’t wait to see what this looks like. Hopefully it is reasonably priced. Could definitely see myself owning one of these,” they added. The GR-3 is a natural progression of the company’s previous models. The first, the GR-1, was launched by Foureir in 2023 and was its first mass-targeted humanoid, featuring 44 joints and capable of walking at 3.1 mph (5 kph). Capable of carrying around 6.6. pounds (3 kg) of weight, it featured advanced perception via six RGB cameras that formed real-time 3D occupancy grids, an LLM-based emotional interaction system, and modular Fourier Smart Actuators (FSA) delivering around 230 N/m of torque. The GR-2 was debuted in 2024 and raised the bar with a taller frame (~175 cm, 63 kg), 53 degrees of freedom, enhanced 12 degrees of freedom (DoF) dexterous hands with tactile sensors, and power-dense FSA 2.0 actuators (around 380 N/m torque). Given this lineage, the GR-3 is likely to continue innovating in areas such as compact hardware design, featuring a shorter, lighter frame tailored to domestic spaces. It will also build on the company’s focus on friendly user interaction thanks to its softer aesthetic and approachable interface. The GR-3 will also likely feature use-case-specific actuation and sensing, likely simpler than the GR-2’s high-precision hands but optimized for social or light domestic tasks. Scheduled for release in August It will likely also feature an accessible software stack continuing Fourier’s support for developers via pre‑built APIs and possibly integration with LLMs and vision systems. Fourier has confirmed the robot’s official reveal is scheduled for early August, with teaser posts on X and robotics forums generating anticipation among fans and researchers. When formally revealed, the GR‑3 could represent Fourier’s first small-form social humanoid, bridging the gap between research platforms and home or classroom robots. Read more:

Video: China firm to unveil world’s most ‘adorable’ humanoid robot for homes, schools | Christopher McFadden, Interesting Engineering Fourier’s latest humanoid robot, the GR‑3, is designed for domestic and educational environments. Fourier Robotics, the Shanghai-based robotics firm behind the GR-1 and GR-2 models, is preparing to launch its GR-3 humanoid robot on August 6. Early glimpses of the new robot, including a sneak-peek video, reveal a smaller, friendlier design, described as possibly the “most adorable humanoid robot yet.” Concrete information is scarce, but early reports suggest the robot will be smaller than its predecessors. According to some reports, the GR-3 will likely stand at around 4 feet 5 inches (134 cm). This makes it notably smaller than the earlier GR-1 (5.4 feet/165 cm) and GR-2 (5.74 feet/175 cm) models from Fourier. Most notable is its apparent “softer,” almost cuddly aesthetic.” The robot is likely intended for use in homes, schools, hospitals, and public spaces. It also features an integrated large language model (LLM) to enable natural speech engagement with users. To this end, the GR-3 will likely be marked as a companion‑style or caregiver bot (AKA a “Care‑bot”) aimed at friendly human interaction in personal or learning environments. GR-3: Fourier’s cutest robot yet “This softer aesthetic is a nice change compared to the usual designs we see with humanoid robots. The eyes are a much-needed touch,” comments a member on the Companian Robot Forums. “It’s so expressive and draws you in. Can’t wait to see what this looks like. Hopefully it is reasonably priced. Could definitely see myself owning one of these,” they added. The GR-3 is a natural progression of the company’s previous models. The first, the GR-1, was launched by Foureir in 2023 and was its first mass-targeted humanoid, featuring 44 joints and capable of walking at 3.1 mph (5 kph). Capable of carrying around 6.6. pounds (3 kg) of weight, it featured advanced perception via six RGB cameras that formed real-time 3D occupancy grids, an LLM-based emotional interaction system, and modular Fourier Smart Actuators (FSA) delivering around 230 N/m of torque. The GR-2 was debuted in 2024 and raised the bar with a taller frame (~175 cm, 63 kg), 53 degrees of freedom, enhanced 12 degrees of freedom (DoF) dexterous hands with tactile sensors, and power-dense FSA 2.0 actuators (around 380 N/m torque). Given this lineage, the GR-3 is likely to continue innovating in areas such as compact hardware design, featuring a shorter, lighter frame tailored to domestic spaces. It will also build on the company’s focus on friendly user interaction thanks to its softer aesthetic and approachable interface. The GR-3 will also likely feature use-case-specific actuation and sensing, likely simpler than the GR-2’s high-precision hands but optimized for social or light domestic tasks. Scheduled for release in August It will likely also feature an accessible software stack continuing Fourier’s support for developers via pre‑built APIs and possibly integration with LLMs and vision systems. Fourier has confirmed the robot’s official reveal is scheduled for early August, with teaser posts on X and robotics forums generating anticipation among fans and researchers. When formally revealed, the GR‑3 could represent Fourier’s first small-form social humanoid, bridging the gap between research platforms and home or classroom robots. Read more:

Owen Gregorian

64,074 Aufrufe • vor 11 Monaten

My conversation with Sergey Levine (Sergey Levine). Sergey is the co-founder of Physical Intelligence -- a company building foundation models that can control any robot to do any task in any environment. The company's thesis is that generality is more scalable than specialization, meaning that a model trained across many different robots and tasks will ultimately outperform any system built to do one thing well (eg, just wash dishes). Sergey is a researcher by background, but I think you will appreciate how practical and commercially grounded this conversation is. We discuss: - Why changing a diaper will be the last task a robot masters - The simulation v. real-world data debate - How multimodal LLMs give robots common sense - Moravec's Paradox + Robot Olympics - Why robots can do long-horizon tasks now - A realistic timeline for robots in our homes I should note that I am an investor in Physical Intelligence -- I made the investment because I believe it is one of the most important companies tackling the problem of robotics. Enjoy! Timestamps: 0:00 Intro 2:39 Defining Physical Intelligence 5:19 The Challenge of Building General Models 6:34 The Stakes and Future of General Purpose Robotics 8:15 Pros and Cons of Humanoid Robots 10:12 Historical Milestones in Robotics Research 15:31 Combining Generative AI and Deep RL 21:24 Moravec's Paradox 25:33 Kitchen Robots 29:30 Simulation vs. Real-World Data 30:48 The Robot Olympics 36:31 The Physiological Reality of Embodiment 38:56 Controversies in the Robotics Community 44:18 What Makes a Great Researcher 48:27 How Businesses Should Prepare for Robotics 54:09 Tracking Progress Through Research Papers 57:02 The Next Step: Mid-Level Reasoning 1:02:00 The Kindest Thing

My conversation with Sergey Levine (Sergey Levine). Sergey is the co-founder of Physical Intelligence -- a company building foundation models that can control any robot to do any task in any environment. The company's thesis is that generality is more scalable than specialization, meaning that a model trained across many different robots and tasks will ultimately outperform any system built to do one thing well (eg, just wash dishes). Sergey is a researcher by background, but I think you will appreciate how practical and commercially grounded this conversation is. We discuss: - Why changing a diaper will be the last task a robot masters - The simulation v. real-world data debate - How multimodal LLMs give robots common sense - Moravec's Paradox + Robot Olympics - Why robots can do long-horizon tasks now - A realistic timeline for robots in our homes I should note that I am an investor in Physical Intelligence -- I made the investment because I believe it is one of the most important companies tackling the problem of robotics. Enjoy! Timestamps: 0:00 Intro 2:39 Defining Physical Intelligence 5:19 The Challenge of Building General Models 6:34 The Stakes and Future of General Purpose Robotics 8:15 Pros and Cons of Humanoid Robots 10:12 Historical Milestones in Robotics Research 15:31 Combining Generative AI and Deep RL 21:24 Moravec's Paradox 25:33 Kitchen Robots 29:30 Simulation vs. Real-World Data 30:48 The Robot Olympics 36:31 The Physiological Reality of Embodiment 38:56 Controversies in the Robotics Community 44:18 What Makes a Great Researcher 48:27 How Businesses Should Prepare for Robotics 54:09 Tracking Progress Through Research Papers 57:02 The Next Step: Mid-Level Reasoning 1:02:00 The Kindest Thing

Patrick OShaughnessy

133,833 Aufrufe • vor 3 Monaten

i don't think people realize what's happening in Chinese robotics. this one manufacturer might be the most impressive AND most concerning company on Earth right now let me explain... Unitree Robotics sells a humanoid robot for $5,900. their robot dog costs $1,600 (Boston Dynamics charges $74,500 for theirs for context). you can literally buy these on Amazon today. so obviously the first question is: how is that even possible? the answer starts with a guy who couldn't pass his English exam. Wang Xingxing grew up in Zhejiang province. for his master's thesis, he decided to build a quadruped robot. budget: about $3,000. for context, $3,000 for this kinda robot is nothing. off-the-shelf servo motors alone would've eaten that twice over. so Wang did the only thing he could: he designed and machined every single component himself. motors, joints, controllers, the frame. all of it. the resulting robot was janky and imperfect. but it worked. and the video went viral globally. after graduating he joined DJI. but he quit after two months, and this is 2016, when DJI was arguably the hottest hardware company in China. walking away from that with no money to start a robotics company is a... specific kind of stubborn. he launches Unitree with $280K from a single angel investor. tiny office in Hangzhou. 50 square meters. but the money runs out fast. he can't make payroll for three years. the company almost dies in 2017. but emergency government funding arrives with days to spare. he survives, barely, and keeps building. this is where it gets really fascinating IMO. this founding constraint, building everything yourself because you literally cannot afford to buy parts, never went away. even after funding rounds started landing. even after revenue kicked in. it just became the company's permanent DNA. Unitree now manufactures 90%+ of its core components in-house. motors, reducers, controllers, encoders, LiDAR, etc the founder's $3,000 robot thesis ended up being an architectural decision that turned out to be structurally superior. think about what that means in practice. Boston Dynamics needs a better motor? they negotiate with a supplier, wait on lead times, qualify the part. but when Unitree needs one, they design theirs internally and have a new version in production within weeks. that gap compounds every cycle. Unitree shipped three separate humanoid platforms in 18 months. Figure AI has shipped one. Tesla has shipped zero commercially. the results are getting hard to dismiss. 23,700 robot dogs shipped in 2024 (roughly 70% of the entire global market). 7,000+ humanoids deployed. over 600 industrial sites running their quadrupeds. $140M+ revenue, profitable every year since 2020. for perspective: no Western humanoid competitor is profitable. not one. OK. now here's where the "most concerning" part of this starts... if you watched the DJI story unfold, you already recognize the shape. affordable Chinese hardware quietly saturates global markets. years later, the national security questions arrive, after the install base is already massive. drones, then EVs, then AI. now robots. Unitree is running this exact playbook in real time. in April 2025, researchers found an undocumented backdoor in their Go1 robot. a remote tunnel letting anyone control the robot and stream its camera feed. default password: pi/123. 1,919 vulnerable units exposed globally. including machines at MIT, Princeton, and Carnegie Mellon. but it gets worse. every Unitree robot shares the same hardcoded encryption key. encrypt the word "unitree" and you get root access to any of them. one compromised robot can spread to every Unitree robot in Bluetooth range automatically. a literal robot botnet. the G1 quietly transmits sensor data to Chinese servers every five minutes. audio, video, GPS, LiDAR spatial mapping, with no notification, no consent, no opt-out. PLA footage has shown Go2 robots with mounted weapons. Ukrainian forces literally deployed weaponized units on the actual frontline. and every member of the bipartisan House China Committee signed a letter calling for Unitree's military company designation. Wang signed a 2022 pledge alongside Boston Dynamics not to weaponize robots. but pledges don't survive contact with shipping hardware to open markets. and under China's 2025 rules restricting military-related speech, Unitree couldn't publicly confirm PLA use even if they wanted to. 50,000+ of these robots are now deployed globally. some at institutions that probably should've asked harder questions before connecting them to their networks. the security stuff is real and people should know about it. but i also think it's important not to let that overshadow what's actually been built here. a 35-year-old who failed his English exam created a robotics company that's outshipping and outpricing every Western competitor while being the only profitable humanoid maker on Earth. most impressive and most concerning company in the world right now.

i don't think people realize what's happening in Chinese robotics. this one manufacturer might be the most impressive AND most concerning company on Earth right now let me explain... Unitree Robotics sells a humanoid robot for $5,900. their robot dog costs $1,600 (Boston Dynamics charges $74,500 for theirs for context). you can literally buy these on Amazon today. so obviously the first question is: how is that even possible? the answer starts with a guy who couldn't pass his English exam. Wang Xingxing grew up in Zhejiang province. for his master's thesis, he decided to build a quadruped robot. budget: about $3,000. for context, $3,000 for this kinda robot is nothing. off-the-shelf servo motors alone would've eaten that twice over. so Wang did the only thing he could: he designed and machined every single component himself. motors, joints, controllers, the frame. all of it. the resulting robot was janky and imperfect. but it worked. and the video went viral globally. after graduating he joined DJI. but he quit after two months, and this is 2016, when DJI was arguably the hottest hardware company in China. walking away from that with no money to start a robotics company is a... specific kind of stubborn. he launches Unitree with $280K from a single angel investor. tiny office in Hangzhou. 50 square meters. but the money runs out fast. he can't make payroll for three years. the company almost dies in 2017. but emergency government funding arrives with days to spare. he survives, barely, and keeps building. this is where it gets really fascinating IMO. this founding constraint, building everything yourself because you literally cannot afford to buy parts, never went away. even after funding rounds started landing. even after revenue kicked in. it just became the company's permanent DNA. Unitree now manufactures 90%+ of its core components in-house. motors, reducers, controllers, encoders, LiDAR, etc the founder's $3,000 robot thesis ended up being an architectural decision that turned out to be structurally superior. think about what that means in practice. Boston Dynamics needs a better motor? they negotiate with a supplier, wait on lead times, qualify the part. but when Unitree needs one, they design theirs internally and have a new version in production within weeks. that gap compounds every cycle. Unitree shipped three separate humanoid platforms in 18 months. Figure AI has shipped one. Tesla has shipped zero commercially. the results are getting hard to dismiss. 23,700 robot dogs shipped in 2024 (roughly 70% of the entire global market). 7,000+ humanoids deployed. over 600 industrial sites running their quadrupeds. $140M+ revenue, profitable every year since 2020. for perspective: no Western humanoid competitor is profitable. not one. OK. now here's where the "most concerning" part of this starts... if you watched the DJI story unfold, you already recognize the shape. affordable Chinese hardware quietly saturates global markets. years later, the national security questions arrive, after the install base is already massive. drones, then EVs, then AI. now robots. Unitree is running this exact playbook in real time. in April 2025, researchers found an undocumented backdoor in their Go1 robot. a remote tunnel letting anyone control the robot and stream its camera feed. default password: pi/123. 1,919 vulnerable units exposed globally. including machines at MIT, Princeton, and Carnegie Mellon. but it gets worse. every Unitree robot shares the same hardcoded encryption key. encrypt the word "unitree" and you get root access to any of them. one compromised robot can spread to every Unitree robot in Bluetooth range automatically. a literal robot botnet. the G1 quietly transmits sensor data to Chinese servers every five minutes. audio, video, GPS, LiDAR spatial mapping, with no notification, no consent, no opt-out. PLA footage has shown Go2 robots with mounted weapons. Ukrainian forces literally deployed weaponized units on the actual frontline. and every member of the bipartisan House China Committee signed a letter calling for Unitree's military company designation. Wang signed a 2022 pledge alongside Boston Dynamics not to weaponize robots. but pledges don't survive contact with shipping hardware to open markets. and under China's 2025 rules restricting military-related speech, Unitree couldn't publicly confirm PLA use even if they wanted to. 50,000+ of these robots are now deployed globally. some at institutions that probably should've asked harder questions before connecting them to their networks. the security stuff is real and people should know about it. but i also think it's important not to let that overshadow what's actually been built here. a 35-year-old who failed his English exam created a robotics company that's outshipping and outpricing every Western competitor while being the only profitable humanoid maker on Earth. most impressive and most concerning company in the world right now.

Ole Lehmann

122,425 Aufrufe • vor 4 Monaten

🚨WATCH our latest episode with Anchorage Digital ⚓ CEO Nathan McCauley ⚓ as he breaks down the state of crypto custody, how it’s shifting under new leadership at the banking regulators and the SEC, and why all banks need a digital asset strategy. Plus Anchorage’s partnerships with BlackRock, Cantor Fitzgerald and much more. ⬇️ TIMESTAMPS: 00:23 - What Does Crypto In America Mean To Nathan? 02:18 - Nathan's Small Town Roots 04:30 - Becoming the first OCC-regulated crypto trust bank 07:01 - Understanding Custodial Regulations 16:49 - Securing Keys 21:00 - Custody Of Less Liquid Assets 21:15 - Token Generation In The U.S. 26:41 - Navigating the New Regulatory Environment 31:58 - Ending Operation Chokepoint and Removing Banking Hurdles 35:02 - Why All Banks Need A Digital Asset Strategy 39:11- Stablecoins in Traditional Finance 42:51 - State License vs. Federal Regulation in Crypto 46:00 - Next Regulatory Steps For Anchorage? 50:19 - The Role of Custodians in Preventing Collapses Like FTX 53:42 - Government Adoption of Crypto Assets

🚨WATCH our latest episode with Anchorage Digital ⚓ CEO Nathan McCauley ⚓ as he breaks down the state of crypto custody, how it’s shifting under new leadership at the banking regulators and the SEC, and why all banks need a digital asset strategy. Plus Anchorage’s partnerships with BlackRock, Cantor Fitzgerald and much more. ⬇️ TIMESTAMPS: 00:23 - What Does Crypto In America Mean To Nathan? 02:18 - Nathan's Small Town Roots 04:30 - Becoming the first OCC-regulated crypto trust bank 07:01 - Understanding Custodial Regulations 16:49 - Securing Keys 21:00 - Custody Of Less Liquid Assets 21:15 - Token Generation In The U.S. 26:41 - Navigating the New Regulatory Environment 31:58 - Ending Operation Chokepoint and Removing Banking Hurdles 35:02 - Why All Banks Need A Digital Asset Strategy 39:11- Stablecoins in Traditional Finance 42:51 - State License vs. Federal Regulation in Crypto 46:00 - Next Regulatory Steps For Anchorage? 50:19 - The Role of Custodians in Preventing Collapses Like FTX 53:42 - Government Adoption of Crypto Assets

Crypto In America

81,808 Aufrufe • vor 1 Jahr

NEW POD | EP 74 🎙️ Trade War & The Markets Timestamps: 0:46 Eric Trump 1:59 Movement Labs 4:37 Regulation in Crypto 8:34 Benefits of Going Public 9:25 OpenAI Tried to Buy Windsurf 12:48 OpenAI as a Super App 14:24 Investment in AI Companies 15:57 AI vs Crypto Startups 17:18 Impact of Crypto's Speculative Nature 19:03 Trade War 25:01 Trade War Strategy Discussion 28:18 Impact of Trade War on Global Relations 30:30 Impact of Trade War on Startups 31:57 Impact of Military Conflict on AI Progress 32:34 China's Dominance in Robotics 36:01 China's Advancements in Solar Energy 38:18 Zora Launch & "Base is for everyone" Token 41:07 What's New in AI? 48:35 OpenAI o3 49:54 Competitive Nature of AI Models 53:50 AI Memory Feature 56:37 Market Discussion 59:34 Market Predictions 1:02:02 Exciting Startups in AI and Crypto 1:03:19 Poof 1:03:38 slop.club 1:05:10 o1.exchange Link ↓

NEW POD | EP 74 🎙️ Trade War & The Markets Timestamps: 0:46 Eric Trump 1:59 Movement Labs 4:37 Regulation in Crypto 8:34 Benefits of Going Public 9:25 OpenAI Tried to Buy Windsurf 12:48 OpenAI as a Super App 14:24 Investment in AI Companies 15:57 AI vs Crypto Startups 17:18 Impact of Crypto's Speculative Nature 19:03 Trade War 25:01 Trade War Strategy Discussion 28:18 Impact of Trade War on Global Relations 30:30 Impact of Trade War on Startups 31:57 Impact of Military Conflict on AI Progress 32:34 China's Dominance in Robotics 36:01 China's Advancements in Solar Energy 38:18 Zora Launch & "Base is for everyone" Token 41:07 What's New in AI? 48:35 OpenAI o3 49:54 Competitive Nature of AI Models 53:50 AI Memory Feature 56:37 Market Discussion 59:34 Market Predictions 1:02:02 Exciting Startups in AI and Crypto 1:03:19 Poof 1:03:38 slop.club 1:05:10 o1.exchange Link ↓

Good Game

38,552 Aufrufe • vor 1 Jahr

DROPS E4: redactedcoin : From NFT craze to Web3 Top Accelerator In this 4th episode of DROPS, our podcast series for upcoming crypto founders, I sit down with shan , the CoFounder & CEO of redactedcoin , PG and Jirasan 🔴 Right on time for the $RDAC TGE day! Timestamps 0:00 Introduction 1:25 Welcome to DROPS 2:02 City Living Trade-Offs 4:13 FUD is Fun in Web3 5:09 Dealing With Online Hate 5:55 Turning FUD into Fun 7:00 The 24 Hour Rule 9:36 Who is Shan? 10:33 Growing up in India 12:27 Studying Abroad 14:17 Working for Tesla 16:30 The Humanoid Robot Race 18:40 Hedging Big Tech Bets 20:21 Investing With the Right Circle 21:52 Building Something That Matters 24:37 Building in Web2.5 27:10 Becoming a Crypto Founder 31:17 From Advisor to Co-Founder 33:22 Managing NFT Treasury Funds 36:58 From NFTs to Consulting 41:57 Lessons Learned from Consulting 44:38 Launching PG Capital 48:29 What is Redacted? 51:44 Where Redacted Got Its Name 52:50 Why would and Accelerator launch a Token? 55:26 When a Product Fails 57:27 Aligning Investor & Founder Interest 59:27 No Unlock Without Market Cap 1:01:55 Founder Funds and Belief 1:05:22 Future of Redacted 1:08:13 Judge Teams By Actions 1:10:45 Concluding Remarks

DROPS E4: redactedcoin : From NFT craze to Web3 Top Accelerator In this 4th episode of DROPS, our podcast series for upcoming crypto founders, I sit down with shan , the CoFounder & CEO of redactedcoin , PG and Jirasan 🔴 Right on time for the $RDAC TGE day! Timestamps 0:00 Introduction 1:25 Welcome to DROPS 2:02 City Living Trade-Offs 4:13 FUD is Fun in Web3 5:09 Dealing With Online Hate 5:55 Turning FUD into Fun 7:00 The 24 Hour Rule 9:36 Who is Shan? 10:33 Growing up in India 12:27 Studying Abroad 14:17 Working for Tesla 16:30 The Humanoid Robot Race 18:40 Hedging Big Tech Bets 20:21 Investing With the Right Circle 21:52 Building Something That Matters 24:37 Building in Web2.5 27:10 Becoming a Crypto Founder 31:17 From Advisor to Co-Founder 33:22 Managing NFT Treasury Funds 36:58 From NFTs to Consulting 41:57 Lessons Learned from Consulting 44:38 Launching PG Capital 48:29 What is Redacted? 51:44 Where Redacted Got Its Name 52:50 Why would and Accelerator launch a Token? 55:26 When a Product Fails 57:27 Aligning Investor & Founder Interest 59:27 No Unlock Without Market Cap 1:01:55 Founder Funds and Belief 1:05:22 Future of Redacted 1:08:13 Judge Teams By Actions 1:10:45 Concluding Remarks

MR SHIFT 🦁

89,716 Aufrufe • vor 1 Jahr

Dan Wang (Dan Wang) says that America should become 20% more engineering-minded to fix its broken infrastructure, while China needs to be 50% more lawyerly so the Communist Party will stop strangling individual rights and the creative impulses of its people. But would a more lawyerly China constrain state power, or just create new tools for oppression? And, asks tylercowen insouciantly, aren’t the American suburbs actually sterling achievements where the infrastructure works quite well? 0:00:00 - American infrastructure and suburban life 0:05:18 - American vs. Chinese infrastructure buildouts... 0:12:25 - And health care investment 0:17:52 - Chinese suburbs 0:20:10 - The existing lawyerly influence in East Asia 0:25:12 - China’s lack of a liberal tradition 0:29:35 - Why China’s won’t democratize 0:33:49 - China’s economic disfunction 0:38:44 - China’s expansionism 0:41:55 - Chinese pragmatism and bureaucratic incentives 0:46:50 - Chinese cities and regional culture 0:59:44 - James C. Scott, Zomia, and elite culture 1:06:27 - A 10-day Yunnan itinerary 1:11:57 - On Chinese arts, literature, and cultural expression 1:18:23 - The Dan Wang production function 1:30:34 - Tyler’s grand strategy, or lack thereof

Dan Wang (Dan Wang) says that America should become 20% more engineering-minded to fix its broken infrastructure, while China needs to be 50% more lawyerly so the Communist Party will stop strangling individual rights and the creative impulses of its people. But would a more lawyerly China constrain state power, or just create new tools for oppression? And, asks tylercowen insouciantly, aren’t the American suburbs actually sterling achievements where the infrastructure works quite well? 0:00:00 - American infrastructure and suburban life 0:05:18 - American vs. Chinese infrastructure buildouts... 0:12:25 - And health care investment 0:17:52 - Chinese suburbs 0:20:10 - The existing lawyerly influence in East Asia 0:25:12 - China’s lack of a liberal tradition 0:29:35 - Why China’s won’t democratize 0:33:49 - China’s economic disfunction 0:38:44 - China’s expansionism 0:41:55 - Chinese pragmatism and bureaucratic incentives 0:46:50 - Chinese cities and regional culture 0:59:44 - James C. Scott, Zomia, and elite culture 1:06:27 - A 10-day Yunnan itinerary 1:11:57 - On Chinese arts, literature, and cultural expression 1:18:23 - The Dan Wang production function 1:30:34 - Tyler’s grand strategy, or lack thereof

Conversations with Tyler

85,048 Aufrufe • vor 7 Monaten

NEW! vitalik.eth joins the greenpill.network podcast today to talk about Web3 Public Goods Funding in 2025. This episode is part 1 of a 2 part series. In ep 1 we discuss: TIMESTAMPS 00:00 - Intro 2:18 - Why Public Goods? 03:17- Private vs. Public Goods 05:20 - Challenges of Funding Public Goods 06:13 - Intrinsic Motivation and Public Goods 07:16 - Funding Models for Public Goods 09:18 - Digital Ecosystem and Public Goods 10:12 - Revenue Curve and Public Goods 11:36 - Decentralization vs. Domination 13:05 - Competitive Advantage of Public Goods 15:01 - Resilience Through Public Goods 17:07 - Broader Impact of Ethereum 19:18 - Escape Velocity Theory 19:51 - Importance of Public Goods 21:31 - Diversity in Funding Entities 23:44 - Challenges in Funding Public Goods 26:02 - Scaling Funding Needs 27:04 - Hybrid Funding Models 29:09 - Institutionalizing Funding 31:00 - Layer Two Solutions 31:59 - Importance of Scaling Funding 34:00 - Moralism in Ecosystem Dynamics 36:22 - Quality Allocation of Funding 37:26 - Diversity of Funding Mechanisms 39:34 - Stability in Funding Mechanisms 41:09 - Prediction Markets for Public Goods 42:27 - Info Finance Concept 44:36 - Distilled Human Judgment Mechanism 46:52 - Governance as a Lego Concept 47:58 - Forking Protocol Guild 50:54 - Discussion on Ethereum Critique 51:57 - Auto Public Goods Funding 53:11 - Tokenization and Open Source Funding 53:49 - Evaluating Funding Mechanisms 54:48 - Finding High Leverage Projects 56:19 - Challenges in Distribution 57:32 - Public Goods Funding in 2025 59:36 - Outro

NEW! vitalik.eth joins the greenpill.network podcast today to talk about Web3 Public Goods Funding in 2025. This episode is part 1 of a 2 part series. In ep 1 we discuss: TIMESTAMPS 00:00 - Intro 2:18 - Why Public Goods? 03:17- Private vs. Public Goods 05:20 - Challenges of Funding Public Goods 06:13 - Intrinsic Motivation and Public Goods 07:16 - Funding Models for Public Goods 09:18 - Digital Ecosystem and Public Goods 10:12 - Revenue Curve and Public Goods 11:36 - Decentralization vs. Domination 13:05 - Competitive Advantage of Public Goods 15:01 - Resilience Through Public Goods 17:07 - Broader Impact of Ethereum 19:18 - Escape Velocity Theory 19:51 - Importance of Public Goods 21:31 - Diversity in Funding Entities 23:44 - Challenges in Funding Public Goods 26:02 - Scaling Funding Needs 27:04 - Hybrid Funding Models 29:09 - Institutionalizing Funding 31:00 - Layer Two Solutions 31:59 - Importance of Scaling Funding 34:00 - Moralism in Ecosystem Dynamics 36:22 - Quality Allocation of Funding 37:26 - Diversity of Funding Mechanisms 39:34 - Stability in Funding Mechanisms 41:09 - Prediction Markets for Public Goods 42:27 - Info Finance Concept 44:36 - Distilled Human Judgment Mechanism 46:52 - Governance as a Lego Concept 47:58 - Forking Protocol Guild 50:54 - Discussion on Ethereum Critique 51:57 - Auto Public Goods Funding 53:11 - Tokenization and Open Source Funding 53:49 - Evaluating Funding Mechanisms 54:48 - Finding High Leverage Projects 56:19 - Challenges in Distribution 57:32 - Public Goods Funding in 2025 59:36 - Outro

owockai

213,967 Aufrufe • vor 1 Jahr

🚨ZHERKA x CLAVICULAR FULL CALL PT. 2 👀🔥 Topics: (0:00) Opening + Airport Call + Fake Drug Story (0:27) Cocaine Risks + Heart Attack Talk (0:58) BDO, Alcohol, and Lethal Dose (1:26) Ketamine, BDNF, and Cognitive Effects (2:25) Therapeutic Use vs Abuse (4:02) Why He Says Not to Do Drugs (4:31) Using Stimulants for Streaming (5:00) Addiction, Willpower, and Audience Influence (6:03) Adderall Era + Building Content (6:29) Daily Use vs Going Hard (7:32) Dopamine from Clips vs Real Life (8:06) Content vs Girls (8:36) Lifestyle, Girls, and Routine (9:28) Grace, Age, and Learning Experience (10:38) Intentions from the Start (11:22) Situation with Girls + Setup (11:49) Genetics, Attraction, and “Genetics Pill” (12:18) Why His Life Doesn’t Apply to Most People (13:04) Clip Farming Strategy (13:30) OnlyFans, Genetics, and Concerns (14:13) Kids, Legacy, and Future Planning (14:42) Building an Empire Through Family (15:22) IGF-1, Growth, and Planning Kids (16:04) Height, Frame, and Physical Traits (16:30) Genetics vs Luck Between Siblings (16:57) Parenting for Optimization (17:24) Gym at a Young Age Debate (17:54) Testosterone Use + Cycles (18:21) Compounds, Confidence, and Behavior (18:52) Yohimbine and Anxiety (19:31) Pre-workout and Supplements (20:00) Testosterone vs DHT (20:33) Estrogen, Collagen, and Skin (21:01) Looks, Models, and Face Optimization (21:32) TRT vs Higher Doses (22:02) DHT Blockers and Aging (22:35) What Actually Ages You (UV, Alcohol, Stress) (23:12) Stress vs Physical Aging Debate (23:46) Hair Loss Prevention + New Tech (24:12) Looksmaxing in 2026 (24:40) Status, Money, and Looks (25:20) Ascending Through Looks (25:36) Bottom Tier Reality (26:06) Money Maxing vs Attraction (26:38) Coming Out to Miami + Linking Up (27:09) Taking Over the Stream + Episode Plans (27:46) Rating Girls + “Trying to Help” (28:42) Watching His Content + Strategy (29:14) Running Streams While Working (29:50) Viral Content vs Personal Fulfillment

🚨ZHERKA x CLAVICULAR FULL CALL PT. 2 👀🔥 Topics: (0:00) Opening + Airport Call + Fake Drug Story (0:27) Cocaine Risks + Heart Attack Talk (0:58) BDO, Alcohol, and Lethal Dose (1:26) Ketamine, BDNF, and Cognitive Effects (2:25) Therapeutic Use vs Abuse (4:02) Why He Says Not to Do Drugs (4:31) Using Stimulants for Streaming (5:00) Addiction, Willpower, and Audience Influence (6:03) Adderall Era + Building Content (6:29) Daily Use vs Going Hard (7:32) Dopamine from Clips vs Real Life (8:06) Content vs Girls (8:36) Lifestyle, Girls, and Routine (9:28) Grace, Age, and Learning Experience (10:38) Intentions from the Start (11:22) Situation with Girls + Setup (11:49) Genetics, Attraction, and “Genetics Pill” (12:18) Why His Life Doesn’t Apply to Most People (13:04) Clip Farming Strategy (13:30) OnlyFans, Genetics, and Concerns (14:13) Kids, Legacy, and Future Planning (14:42) Building an Empire Through Family (15:22) IGF-1, Growth, and Planning Kids (16:04) Height, Frame, and Physical Traits (16:30) Genetics vs Luck Between Siblings (16:57) Parenting for Optimization (17:24) Gym at a Young Age Debate (17:54) Testosterone Use + Cycles (18:21) Compounds, Confidence, and Behavior (18:52) Yohimbine and Anxiety (19:31) Pre-workout and Supplements (20:00) Testosterone vs DHT (20:33) Estrogen, Collagen, and Skin (21:01) Looks, Models, and Face Optimization (21:32) TRT vs Higher Doses (22:02) DHT Blockers and Aging (22:35) What Actually Ages You (UV, Alcohol, Stress) (23:12) Stress vs Physical Aging Debate (23:46) Hair Loss Prevention + New Tech (24:12) Looksmaxing in 2026 (24:40) Status, Money, and Looks (25:20) Ascending Through Looks (25:36) Bottom Tier Reality (26:06) Money Maxing vs Attraction (26:38) Coming Out to Miami + Linking Up (27:09) Taking Over the Stream + Episode Plans (27:46) Rating Girls + “Trying to Help” (28:42) Watching His Content + Strategy (29:14) Running Streams While Working (29:50) Viral Content vs Personal Fulfillment

ZHERKA DAILY

30,495 Aufrufe • vor 2 Monaten

Episode #123: Inside All-In with @jason - Lessons from Elon, Oprah, Trump, Travis Kalanick We go inside the origins of The All-In Podcast, how they decide what to talk about each week, and if Jason thinks they helped swing the election. We also talk lessons from starting 7 media companies over the past three decades, what he's learned from studying the world's best interviewers, joining Sequoia’s first scout program, his investing strategy at Launch, the story of being the 3rd or 4th investor in Uber, what people underestimate about Elon, and what it was like inside the Twitter buyout in 2022. Thanks to Numeral for supporting this episode and austin petersmith for help on topics. Timestamps: 3:34 Interviewing lessons from Oprah, Charlie Rose 6:48 How to ask good questions 12:20 Jason’s favorite upcoming podcasters 17:57 Starting 7 media companies 22:50 How he'd start a new media company today 27:56 In-person experiences, “Bang Bang” in Japan 32:44 Vinyl bars, smartphones, mental health 38:41 Origin of the All-In Podcast 42:58 All-In’s influence on the 2024 Election 46:58 Why All-In got so political 52:35 Media lessons from Trump 55:01 Joining Sequoia’s very first scout program 57:55 Jason’s VC investing strategy 1:03:55 How Launch competes with other accelerators 1:08:46 Fundraising is a numbers game 1:13:06 Investing in Uber and Robinhood Seed rounds 1:18:31 Origin of “3rd or 4th investor in Uber” meme 1:20:57 How Jason got the first Model S 1:26:19 What people underestimate about Elon 1:27:37 Inside the Twitter takeover 1:31:44 Career advice for young people 1:35:22 Jason’s experience taking GLP-1’s 1:40:05 How All-in picks topics each week

Episode #123: Inside All-In with @jason - Lessons from Elon, Oprah, Trump, Travis Kalanick We go inside the origins of The All-In Podcast, how they decide what to talk about each week, and if Jason thinks they helped swing the election. We also talk lessons from starting 7 media companies over the past three decades, what he's learned from studying the world's best interviewers, joining Sequoia’s first scout program, his investing strategy at Launch, the story of being the 3rd or 4th investor in Uber, what people underestimate about Elon, and what it was like inside the Twitter buyout in 2022. Thanks to Numeral for supporting this episode and austin petersmith for help on topics. Timestamps: 3:34 Interviewing lessons from Oprah, Charlie Rose 6:48 How to ask good questions 12:20 Jason’s favorite upcoming podcasters 17:57 Starting 7 media companies 22:50 How he'd start a new media company today 27:56 In-person experiences, “Bang Bang” in Japan 32:44 Vinyl bars, smartphones, mental health 38:41 Origin of the All-In Podcast 42:58 All-In’s influence on the 2024 Election 46:58 Why All-In got so political 52:35 Media lessons from Trump 55:01 Joining Sequoia’s very first scout program 57:55 Jason’s VC investing strategy 1:03:55 How Launch competes with other accelerators 1:08:46 Fundraising is a numbers game 1:13:06 Investing in Uber and Robinhood Seed rounds 1:18:31 Origin of “3rd or 4th investor in Uber” meme 1:20:57 How Jason got the first Model S 1:26:19 What people underestimate about Elon 1:27:37 Inside the Twitter takeover 1:31:44 Career advice for young people 1:35:22 Jason’s experience taking GLP-1’s 1:40:05 How All-in picks topics each week

The Peel

92,577 Aufrufe • vor 6 Monaten

Tata Curvv EV: Pros & Cons, Quality Insights & Competition Analysis! Timestamps 0:00 - Real-time sound output 0:22 - Brake test 0:41 - Build, safety, and feel 1:04 - Curvv EV Empowered: Basic info 2:00 - Dual-tone color looks 2:23 - Fog lamps still present 2:30 - Ugly welding spots 2:48 - Paint quality 3:00 - Panel gaps 3:28 - No rear wiper 3:37 - Rearview glass and rear camera on the go 4:20 - ADAS while driving 5:10 - Glossy wheel cladding 5:28 - Insulation material and rubber beading 5:38 - Raised stance 6:07 - Aero twin wipers 6:18 - Flush door handles 6:54 - Frunk 7:06 - Fast AC wall charger with the car 7:17 - V2V and V2L 7:40 - Electric tailgate and boot space 8:17 - Alloys with aero inserts and full inner wheel arch cladding 8:54 - Front seat space and comfort 9:50 - Rear seat comfort and space 12:08 - Powered front driver seat 12:30 - AVAS 12:46 - Bottle holder style 12:57 - Similarities with Nexon 13:31 - No door pockets at the rear 13:41 - Auto hold 14:01 - Clean mechanism of the panoramic sunroof 14:16 - Digital cockpit and infotainment screen brightness 14:46 - Slippery floor mats 15:12 - Thick plastic panel gap in the glovebox 15:22 - Dashboard plastic design 15:49 - Had to stretch for ORVM buttons 16:00 - All power windows should have one-touch up/down 16:09 - Center console with piano finish 16:56 - No telescopic steering adjustment 17:07 - Screw covers not neat and no flaps/mirror for the sun visor 17:33 - Two 45W chargers available in the cabin 17:52 - Storage box and old-fashioned charging pad 18:16 - AC touch panel and knobs 19:17 - Range I got during the drive 20:13 - Can the Curvv EV sell in big numbers? 21:36 - COUPE styling: A gamble by TATA 23:06 - Why is there more buzz for Curvv EV compared to Nexon EV? 24:17 - IRA EV app 25:27 - Competition against ZS EV and Creta/Seltos in ICE

Tata Curvv EV: Pros & Cons, Quality Insights & Competition Analysis! Timestamps 0:00 - Real-time sound output 0:22 - Brake test 0:41 - Build, safety, and feel 1:04 - Curvv EV Empowered: Basic info 2:00 - Dual-tone color looks 2:23 - Fog lamps still present 2:30 - Ugly welding spots 2:48 - Paint quality 3:00 - Panel gaps 3:28 - No rear wiper 3:37 - Rearview glass and rear camera on the go 4:20 - ADAS while driving 5:10 - Glossy wheel cladding 5:28 - Insulation material and rubber beading 5:38 - Raised stance 6:07 - Aero twin wipers 6:18 - Flush door handles 6:54 - Frunk 7:06 - Fast AC wall charger with the car 7:17 - V2V and V2L 7:40 - Electric tailgate and boot space 8:17 - Alloys with aero inserts and full inner wheel arch cladding 8:54 - Front seat space and comfort 9:50 - Rear seat comfort and space 12:08 - Powered front driver seat 12:30 - AVAS 12:46 - Bottle holder style 12:57 - Similarities with Nexon 13:31 - No door pockets at the rear 13:41 - Auto hold 14:01 - Clean mechanism of the panoramic sunroof 14:16 - Digital cockpit and infotainment screen brightness 14:46 - Slippery floor mats 15:12 - Thick plastic panel gap in the glovebox 15:22 - Dashboard plastic design 15:49 - Had to stretch for ORVM buttons 16:00 - All power windows should have one-touch up/down 16:09 - Center console with piano finish 16:56 - No telescopic steering adjustment 17:07 - Screw covers not neat and no flaps/mirror for the sun visor 17:33 - Two 45W chargers available in the cabin 17:52 - Storage box and old-fashioned charging pad 18:16 - AC touch panel and knobs 19:17 - Range I got during the drive 20:13 - Can the Curvv EV sell in big numbers? 21:36 - COUPE styling: A gamble by TATA 23:06 - Why is there more buzz for Curvv EV compared to Nexon EV? 24:17 - IRA EV app 25:27 - Competition against ZS EV and Creta/Seltos in ICE

Sunderdeep - Volklub

28,298 Aufrufe • vor 1 Jahr

64 Arguments Against Democratic Socialism Timestamps: 0:00 Definitions 2:28 Hyper-individualism 5:44 Universality 9:30 He Who Pays the Piper, Calls the Tune 12:37 Welfare State Turns Humans From Assets to Liabilities 15:18 Against Me 16:25 Trump Test 18:29 Zero Sum Thinking 21:05 Forcible Depravation 22:46 Monopoly Contradiction 25:27 Vilifying Producers 28:03 Competition Protects People 32:03 The Secret to Mass Consumption = Mass Production 34:30 Decreasing Prices in the Private Sector & Potential Competition 39:35 The Myth of the Rational Voter: Fake Power vs. Real Power 50:02 Social Contract Myth 53:29 "Which Happens First?" 58:45 Static Thinking Fallacy 1:03:20 Metrics for Standard of Living & Time Prices 1:07:58 Humans Are Inherently Self Interested 1:12:53 Recognizing Rights as Reciprocal 1:14:49 We Are Not the Government 1:17:29 More Power = Better Outcome Assumption 1:21:19 The Myth of "Free" 1:23:50 Iron Law of Oligarchy 1:26:50 Praxeology 1:37:55 Inequality & Trickle Down Economics 1:44:41 Domestic Imperialism 1:48:56 Regulatory Capture 1:50:48 Abolish the Police 1:53:02 The Empirical Case 1:54:08 "Me Being X Doesn't Affect You" 1:56:01 Material Mindset 1:59:16 Capital Financing Shift 2:00:30 The Value of the Capitalist 2:03:47 Opposition to Voluntary Solutions 2:07:45 Apartheid Entitlement 2:14:36 Democracy and Delegating Rights 2:17:02 The Expert Problem 2:23:45 Capitalist Time Preference 2:31:41 Capitalist Productivity 2:34:15 Self-Ownership 2:38:15 Who Defines What "Service X" is? 2:41:57 Inevitability of Scarcity 2:46:35 The Angel Argument 2:49:04 The Crimes of the 99% 2:51:09 "Poverty Causes Crime" 2:53:04 Intentions Over Results 2:57:41 Free Association = The Ultimate "Check and Balance" 3:00:31 Surplus Value 3:04:39 Firms Reduce Transaction Costs 3:08:21 Collective Action Problem 3:10:09 Empiricism, the High Cost of Experimentation, and the Difficulty in Isolating Variables 3:12:46 Each According to Their Ability? Need? 3:15:51 Disparities Prove Discrimination 3:23:58 Comparing Theory to Reality 3:31:42 Nirvana Fallacy 3:34:41 Which Collective? 3:39:20 Argument From Tolerance 3:39:50 Prices: Signal & Incentive 3:42:58 Catastrophizing 3:46:43 Stock Diversification 3:48:17 Press Conference Bias 3:50:20 Divorce and Discrimination 3:53:38 Discouraging Savings

64 Arguments Against Democratic Socialism Timestamps: 0:00 Definitions 2:28 Hyper-individualism 5:44 Universality 9:30 He Who Pays the Piper, Calls the Tune 12:37 Welfare State Turns Humans From Assets to Liabilities 15:18 Against Me 16:25 Trump Test 18:29 Zero Sum Thinking 21:05 Forcible Depravation 22:46 Monopoly Contradiction 25:27 Vilifying Producers 28:03 Competition Protects People 32:03 The Secret to Mass Consumption = Mass Production 34:30 Decreasing Prices in the Private Sector & Potential Competition 39:35 The Myth of the Rational Voter: Fake Power vs. Real Power 50:02 Social Contract Myth 53:29 "Which Happens First?" 58:45 Static Thinking Fallacy 1:03:20 Metrics for Standard of Living & Time Prices 1:07:58 Humans Are Inherently Self Interested 1:12:53 Recognizing Rights as Reciprocal 1:14:49 We Are Not the Government 1:17:29 More Power = Better Outcome Assumption 1:21:19 The Myth of "Free" 1:23:50 Iron Law of Oligarchy 1:26:50 Praxeology 1:37:55 Inequality & Trickle Down Economics 1:44:41 Domestic Imperialism 1:48:56 Regulatory Capture 1:50:48 Abolish the Police 1:53:02 The Empirical Case 1:54:08 "Me Being X Doesn't Affect You" 1:56:01 Material Mindset 1:59:16 Capital Financing Shift 2:00:30 The Value of the Capitalist 2:03:47 Opposition to Voluntary Solutions 2:07:45 Apartheid Entitlement 2:14:36 Democracy and Delegating Rights 2:17:02 The Expert Problem 2:23:45 Capitalist Time Preference 2:31:41 Capitalist Productivity 2:34:15 Self-Ownership 2:38:15 Who Defines What "Service X" is? 2:41:57 Inevitability of Scarcity 2:46:35 The Angel Argument 2:49:04 The Crimes of the 99% 2:51:09 "Poverty Causes Crime" 2:53:04 Intentions Over Results 2:57:41 Free Association = The Ultimate "Check and Balance" 3:00:31 Surplus Value 3:04:39 Firms Reduce Transaction Costs 3:08:21 Collective Action Problem 3:10:09 Empiricism, the High Cost of Experimentation, and the Difficulty in Isolating Variables 3:12:46 Each According to Their Ability? Need? 3:15:51 Disparities Prove Discrimination 3:23:58 Comparing Theory to Reality 3:31:42 Nirvana Fallacy 3:34:41 Which Collective? 3:39:20 Argument From Tolerance 3:39:50 Prices: Signal & Incentive 3:42:58 Catastrophizing 3:46:43 Stock Diversification 3:48:17 Press Conference Bias 3:50:20 Divorce and Discrimination 3:53:38 Discouraging Savings

Voluntaryist Keith

315,532 Aufrufe • vor 17 Tagen