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A simple CNC machine. Wood. A rotating tool. And yet the pattern shifts from circles to perfect hexagons with a level of accuracy most factories still struggle to hit. I worked five years in manufacturing at Siemens, and this is the part people often overlook. The real magic is...

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Ilir Aliu

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164,829 次观看 • 7 个月前 •via X (Twitter)

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JUST IN: microagi is opening its Global Robotics Research HQ on Bahnhofstrasse in Zürich, and choosing it over San Francisco. Eight months ago microagi was five people in a Munich hacker house. Today they operate in 15+ countries. The reasoning behind Zürich is compelling: → Highest density of robotics talent in the world, ETH Zürich, EPFL, University of Zürich, IBM Research, Google, NVIDIA, Meta, Apple and Microsoft all run serious ML and robotics teams here → ABB, one of the most important industrial automation companies on earth, is headquartered in the city itself → Within a 6-hour radius: German automotive, Italian manufacturing, French aerospace, Benelux logistics and Swiss machine tools But the line that stuck with me most: "Europe was late to consumer internet. Europe was late to cloud. Europe was late to the foundation-model wave. But Europe is not late to robotics." That is exactly right. The industrial base that physical AI sits on top of has been in Europe for 150 years. Precision mechanics. Machine-tool culture. Safety-critical engineering. Automation-grade manufacturing. The next decade of AI value will be created where bits meet atoms. And Europe is finally in the right position at the right moment. microagi gets it. And they're planting their flag right in the heart of it. 🇨🇭🇪🇺 Bercan, Yoan Iliev, Zeno, Gianni Hodel LFG! 🔥 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
0:35

JUST IN: microagi is opening its Global Robotics Research HQ on Bahnhofstrasse in Zürich, and choosing it over San Francisco. Eight months ago microagi was five people in a Munich hacker house. Today they operate in 15+ countries. The reasoning behind Zürich is compelling: → Highest density of robotics talent in the world, ETH Zürich, EPFL, University of Zürich, IBM Research, Google, NVIDIA, Meta, Apple and Microsoft all run serious ML and robotics teams here → ABB, one of the most important industrial automation companies on earth, is headquartered in the city itself → Within a 6-hour radius: German automotive, Italian manufacturing, French aerospace, Benelux logistics and Swiss machine tools But the line that stuck with me most: "Europe was late to consumer internet. Europe was late to cloud. Europe was late to the foundation-model wave. But Europe is not late to robotics." That is exactly right. The industrial base that physical AI sits on top of has been in Europe for 150 years. Precision mechanics. Machine-tool culture. Safety-critical engineering. Automation-grade manufacturing. The next decade of AI value will be created where bits meet atoms. And Europe is finally in the right position at the right moment. microagi gets it. And they're planting their flag right in the heart of it. 🇨🇭🇪🇺 Bercan, Yoan Iliev, Zeno, Gianni Hodel LFG! 🔥 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

80,106 次观看 • 2 个月前

The future of manufacturing is expressive. We’re building elastic factories that think, learn, and create. Factories where design freedom meets production speed. Where AI and robotics form metal with precision and intent. No tooling. No limits. This is what we mean by Expressive Manufacturing: Production that adapts to design intent on demand and on location. Reindustrialization 2.0 is rebuilding manufacturing in the U.S. in a way that empowers creativity, adaptability, and imagination at scale.
1:52

The future of manufacturing is expressive. We’re building elastic factories that think, learn, and create. Factories where design freedom meets production speed. Where AI and robotics form metal with precision and intent. No tooling. No limits. This is what we mean by Expressive Manufacturing: Production that adapts to design intent on demand and on location. Reindustrialization 2.0 is rebuilding manufacturing in the U.S. in a way that empowers creativity, adaptability, and imagination at scale.

Machina Labs

16,138 次观看 • 8 个月前

Most robotics teams can make a robot move… very few can make it work every day in the real world! @roboforce_inc was just featured in Jensen Huang’s GTC keynote, not for a demo but for a robot they claim is already working in the field. Their system, TITAN, is built for industrial environments: ✅ 40 kg dual-arm payload ✅ millimeter-level precision ✅ 8 hours runtime ✅ early pilots in energy, logistics, and manufacturing They call it Physical AI: The focus is on getting robots to do the kind of labor that still depends on people: repetitive, risky, and physical. IMO, what stands out isn’t the specs. It’s the claim of 11,000 robot orders❗️ If even a fraction of that turns into real deployments, it would make RoboForce one of the most widely scaled robot platforms in the world!!?? The open question is whether this shift from prototype to production is real or just the next phase of robotics storytelling. It looks very promising to me. It’s also interesting how their founder openly pushes back against the humanoid trend, arguing for wheels over legs in real industrial settings. It’s an unusual perspective in a time when humanoids get most of the attention. If they are right, the next humanoid robotics wave might look less like a human and more like an industrial version. Seen at —- Weekly robotics and AI insights. Subscribe free:
0:29

Most robotics teams can make a robot move… very few can make it work every day in the real world! @roboforce_inc was just featured in Jensen Huang’s GTC keynote, not for a demo but for a robot they claim is already working in the field. Their system, TITAN, is built for industrial environments: ✅ 40 kg dual-arm payload ✅ millimeter-level precision ✅ 8 hours runtime ✅ early pilots in energy, logistics, and manufacturing They call it Physical AI: The focus is on getting robots to do the kind of labor that still depends on people: repetitive, risky, and physical. IMO, what stands out isn’t the specs. It’s the claim of 11,000 robot orders❗️ If even a fraction of that turns into real deployments, it would make RoboForce one of the most widely scaled robot platforms in the world!!?? The open question is whether this shift from prototype to production is real or just the next phase of robotics storytelling. It looks very promising to me. It’s also interesting how their founder openly pushes back against the humanoid trend, arguing for wheels over legs in real industrial settings. It’s an unusual perspective in a time when humanoids get most of the attention. If they are right, the next humanoid robotics wave might look less like a human and more like an industrial version. Seen at —- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

27,741 次观看 • 8 个月前

Elon Musk: Maybe the biggest danger associated with AI and robotics is that governments use them to suppress the population. “Maybe the biggest danger for AI and robotics going wrong is government. People who are opposed to corporations or worried about corporations should really worry the most about government, because government is just a corporation in the limit. Government is just the biggest corporation with a monopoly on violence. I always find it a strange dichotomy where people would think corporations are bad, but the government is good, when the government is simply the biggest and worst corporation. But people have that dichotomy. They somehow think at the same time the government can be good, but corporations bad. And this is not true. Corporations have better morality than the government. That is the thing to be worried about. The government could potentially use AI and robotics to suppress the population. That is a serious concern.” Interview with John Collison and Dwarkesh Patel, February 5, 2026
0:43

Elon Musk: Maybe the biggest danger associated with AI and robotics is that governments use them to suppress the population. “Maybe the biggest danger for AI and robotics going wrong is government. People who are opposed to corporations or worried about corporations should really worry the most about government, because government is just a corporation in the limit. Government is just the biggest corporation with a monopoly on violence. I always find it a strange dichotomy where people would think corporations are bad, but the government is good, when the government is simply the biggest and worst corporation. But people have that dichotomy. They somehow think at the same time the government can be good, but corporations bad. And this is not true. Corporations have better morality than the government. That is the thing to be worried about. The government could potentially use AI and robotics to suppress the population. That is a serious concern.” Interview with John Collison and Dwarkesh Patel, February 5, 2026

ELON CLIPS

24,452 次观看 • 5 个月前

The Apple Watch launched 10 years ago today (and has sold over 200 million units). An interesting manufacturing detail is that Apple is the world’s largest buyer of Swiss CNC machines. These automated precision tool cost ~$2m each and make small metal parts. Rolex used to be the largest buyer of CNC machines. But that title now belongs to Apple, which owns 100s of them. Why? For the Apple Watch: the tool is used specifically to make slots for swappable wrist straps. That’s it. How precise is the CNC (computer numerical control) machine? Per The Verge, an average CNC machine can cut pieces with a precision of +/- 50 microns (for comparison, a strand of hair is 70 microns). The Apple Watch is even more demanding: it requires a cut within +/- 5 microns. That’s a comically tight tolerance band. The multi-hundred million dollar investment has already paid for itself: Watch straps are a $1B accessory business. *** Links Found this video of a CNC Machine from Cox Manufacturing (not sure if Apple’s looks exactly the same but added the white lotus theme music because why not): The Verge has a fascinating breakdown on the Watch engineering for the slot: :
0:21

The Apple Watch launched 10 years ago today (and has sold over 200 million units). An interesting manufacturing detail is that Apple is the world’s largest buyer of Swiss CNC machines. These automated precision tool cost ~$2m each and make small metal parts. Rolex used to be the largest buyer of CNC machines. But that title now belongs to Apple, which owns 100s of them. Why? For the Apple Watch: the tool is used specifically to make slots for swappable wrist straps. That’s it. How precise is the CNC (computer numerical control) machine? Per The Verge, an average CNC machine can cut pieces with a precision of +/- 50 microns (for comparison, a strand of hair is 70 microns). The Apple Watch is even more demanding: it requires a cut within +/- 5 microns. That’s a comically tight tolerance band. The multi-hundred million dollar investment has already paid for itself: Watch straps are a $1B accessory business. *** Links Found this video of a CNC Machine from Cox Manufacturing (not sure if Apple’s looks exactly the same but added the white lotus theme music because why not): The Verge has a fascinating breakdown on the Watch engineering for the slot: :

Trung Phan

276,100 次观看 • 1 年前

Walk me through a media optimization workflow "The best way to think about biologics manufacturing is to think about it as high precision manufacturing, closer to semiconductor manufacturing. That's really the reason why Samsung Biologics is in the position that they are — because they took what they learned in terms of process control and brought that over. The reason that Fujifilm is a large manufacturer is because they took chemical process engineering and brought it over. Now, these were not biological companies, right? They are industrial manufacturing companies."
7:40

Walk me through a media optimization workflow "The best way to think about biologics manufacturing is to think about it as high precision manufacturing, closer to semiconductor manufacturing. That's really the reason why Samsung Biologics is in the position that they are — because they took what they learned in terms of process control and brought that over. The reason that Fujifilm is a large manufacturer is because they took chemical process engineering and brought it over. Now, these were not biological companies, right? They are industrial manufacturing companies."

owl

12,103 次观看 • 2 个月前

An ultra compact, high precision industrial robot arm. This one stood out to me because it targets a part of automation that is usually glossed over. Extreme precision in very small spaces. According to Oleksandr Stepanenko, the arm is designed from the ground up with fully custom electronics, software, and calibration, paired with industrial components from Harmonic Drive and maxon. Reported specs are notable: • Repeatability better than 0.001 mm • Payload 250 g • Reach 250 mm • Total mass 1.5 kg This kind of form factor opens up use cases that traditional industrial arms struggle with. Think PCB assembly, micro soldering, precision pick and place of irregular parts, and medical or micro robotics components. ❗️What I find interesting is not just the numbers, but the direction… Smaller, lighter, highly precise systems could unlock automation in environments where space, inertia, and tolerance are the real constraints. Credit to Oleksandr Stepanenko for the original work and post. —- Weekly robotics and AI insights. Subscribe free:
0:43

An ultra compact, high precision industrial robot arm. This one stood out to me because it targets a part of automation that is usually glossed over. Extreme precision in very small spaces. According to Oleksandr Stepanenko, the arm is designed from the ground up with fully custom electronics, software, and calibration, paired with industrial components from Harmonic Drive and maxon. Reported specs are notable: • Repeatability better than 0.001 mm • Payload 250 g • Reach 250 mm • Total mass 1.5 kg This kind of form factor opens up use cases that traditional industrial arms struggle with. Think PCB assembly, micro soldering, precision pick and place of irregular parts, and medical or micro robotics components. ❗️What I find interesting is not just the numbers, but the direction… Smaller, lighter, highly precise systems could unlock automation in environments where space, inertia, and tolerance are the real constraints. Credit to Oleksandr Stepanenko for the original work and post. —- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

74,120 次观看 • 7 个月前

1/ The data parsing market for robotics is just emerging, and it’s already valued in the tens of billions. Data parsing to build data models and software for Robotics is a $20B market in 2024 and is expected to reach $150B+ by 2034 Cherry AI Robotics has built a data parsing tool for robotics, which goes live next week, and will effectively make this project one of the pioneers in data parsing for robotics.
0:25

1/ The data parsing market for robotics is just emerging, and it’s already valued in the tens of billions. Data parsing to build data models and software for Robotics is a $20B market in 2024 and is expected to reach $150B+ by 2034 Cherry AI Robotics has built a data parsing tool for robotics, which goes live next week, and will effectively make this project one of the pioneers in data parsing for robotics.

CherryAI Robotics

90,786 次观看 • 10 个月前

Greek Prime Minister Kyriakos Mitsotakis: The combination of AI and robotics, at the scale at which it is happening in China, is a colossal threat to our entire manufacturing sector — not just the sectors where the Chinese are competing now.
0:35

Greek Prime Minister Kyriakos Mitsotakis: The combination of AI and robotics, at the scale at which it is happening in China, is a colossal threat to our entire manufacturing sector — not just the sectors where the Chinese are competing now.

Clash Report

23,097 次观看 • 2 个月前

Sundar Pichai on the robotics opportunity: ⦿ He's impressed by recent humanoid progress - so much so that he sometimes has to look closely to tell if a robot video is real or fake. ⦿ Google initially moved too early into the application layer, but now sees the combination of AI and robotics as the “sweet spot.” ⦿ He believes we’re 2–3 years away from a “magical moment” in robotics. ⦿ Google is working on playing a role similar to Android in robotics - one of its internal bets is already focused on supporting robotics manufacturers. ⦿ Gemini robotics models will work very well - how to productize them is still an open question at the company.
2:43

Sundar Pichai on the robotics opportunity: ⦿ He's impressed by recent humanoid progress - so much so that he sometimes has to look closely to tell if a robot video is real or fake. ⦿ Google initially moved too early into the application layer, but now sees the combination of AI and robotics as the “sweet spot.” ⦿ He believes we’re 2–3 years away from a “magical moment” in robotics. ⦿ Google is working on playing a role similar to Android in robotics - one of its internal bets is already focused on supporting robotics manufacturers. ⦿ Gemini robotics models will work very well - how to productize them is still an open question at the company.

The Humanoid Hub

87,088 次观看 • 1 年前

Elon Musk on the biggest danger of AI and robotics: “I think probably the biggest danger of AI or maybe the biggest danger of AI and robotics going wrong is government People who are opposed to corporations or worried about corporations should really worry the most about government. Government is just a corporation in the limit; it is the biggest corporation with a monopoly on violence The government could potentially use AI and robotics to suppress the population. That’s a serious concern” Elon says the real threat is Big Government armed with superintelligence
0:49

Elon Musk on the biggest danger of AI and robotics: “I think probably the biggest danger of AI or maybe the biggest danger of AI and robotics going wrong is government People who are opposed to corporations or worried about corporations should really worry the most about government. Government is just a corporation in the limit; it is the biggest corporation with a monopoly on violence The government could potentially use AI and robotics to suppress the population. That’s a serious concern” Elon says the real threat is Big Government armed with superintelligence

X Freeze

719,430 次观看 • 3 个月前

People who've never set foot in a factory will never understand... I watched this three times. For decades, robotics simulation has promised faster deployment. But factories still had to build the real cell to see if it actually worked. Which meant expensive physical prototypes, weeks or months!!! of commissioning, constant surprises between simulation and reality That “sim-to-real gap” has quietly been one of the biggest bottlenecks in manufacturing automation. And it’s exactly what is changing. Today, ABB Robotics announced a partnership with NVIDIA Robotics aimed at closing this gap through the new RobotStudio HyperReality platform: Simulation and real robot behavior can match with near-perfect accuracy. That means manufacturers can design, test, and validate entire production lines before a single robot is installed on the factory floor. The implications are massive: • up to 80% faster setup and commissioning • roughly 40% lower costs by removing physical prototypes • about 50% faster time-to-market for new production lines In other words: Factories can move from trial-and-error engineering to software-driven manufacturing design. Production lines become something you build and validate digitally first. Then deploy physically once everything already works. For an industry that still measures deployment timelines in months or years, this is a major shift. It changes how automation projects are planned, how factories are designed, and how fast manufacturing can adapt to new products. Physical AI actually becomes deployable at an industrial scale. I’ll be at GTC in San Jose next week to see and talk to manufacturers and robotics engineers. If you are into manufacturing like I am, hit me up; my DMs are open!
0:31

People who've never set foot in a factory will never understand... I watched this three times. For decades, robotics simulation has promised faster deployment. But factories still had to build the real cell to see if it actually worked. Which meant expensive physical prototypes, weeks or months!!! of commissioning, constant surprises between simulation and reality That “sim-to-real gap” has quietly been one of the biggest bottlenecks in manufacturing automation. And it’s exactly what is changing. Today, ABB Robotics announced a partnership with NVIDIA Robotics aimed at closing this gap through the new RobotStudio HyperReality platform: Simulation and real robot behavior can match with near-perfect accuracy. That means manufacturers can design, test, and validate entire production lines before a single robot is installed on the factory floor. The implications are massive: • up to 80% faster setup and commissioning • roughly 40% lower costs by removing physical prototypes • about 50% faster time-to-market for new production lines In other words: Factories can move from trial-and-error engineering to software-driven manufacturing design. Production lines become something you build and validate digitally first. Then deploy physically once everything already works. For an industry that still measures deployment timelines in months or years, this is a major shift. It changes how automation projects are planned, how factories are designed, and how fast manufacturing can adapt to new products. Physical AI actually becomes deployable at an industrial scale. I’ll be at GTC in San Jose next week to see and talk to manufacturers and robotics engineers. If you are into manufacturing like I am, hit me up; my DMs are open!

Ilir Aliu

68,927 次观看 • 4 个月前

The part of butchery most people never see is a craft-steady hands, quiet respect, and knowing every cut has purpose. My father learned that after the Marine Corps and worked as a butcher for five years. He shared that knowledge with me-I'm pretty good, but not on his level.
0:38

The part of butchery most people never see is a craft-steady hands, quiet respect, and knowing every cut has purpose. My father learned that after the Marine Corps and worked as a butcher for five years. He shared that knowledge with me-I'm pretty good, but not on his level.

G-MA & G-PA

21,636 次观看 • 1 个月前

This is real time. You can see how stable the motion is. A system placing droplets between 1 nanoliter and 1 microliter inside a 96 well plate with almost perfect repeatability. No shake. No drift. No overshoot. The robot keeps the tip on track even at this scale where tiny vibrations normally ruin the result. Why this matters: •In wet lab automation, volume accuracy is everything •Nano scale tasks fail fast if the robot is even slightly off •Reliable deposition unlocks fast screening and repeatable experiments •You can run full workflows without manual checking or correction This is the kind of precision that turns lab robots from “helpful tool” into a full automation pipeline. Credit: M2-Automation GmbH —- Weekly robotics and AI insights. Subscribe free:
1:06

This is real time. You can see how stable the motion is. A system placing droplets between 1 nanoliter and 1 microliter inside a 96 well plate with almost perfect repeatability. No shake. No drift. No overshoot. The robot keeps the tip on track even at this scale where tiny vibrations normally ruin the result. Why this matters: •In wet lab automation, volume accuracy is everything •Nano scale tasks fail fast if the robot is even slightly off •Reliable deposition unlocks fast screening and repeatable experiments •You can run full workflows without manual checking or correction This is the kind of precision that turns lab robots from “helpful tool” into a full automation pipeline. Credit: M2-Automation GmbH —- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

286,886 次观看 • 7 个月前

AI is not trying to teach you. It is not trying to tell you the truth. It is trying to trick you. ChatGPT takes everything on the internet. Finds the most popular answer. And presents it in a way that makes you think it is talking directly to you. It is a magic trick. The same magic trick that worked in 1966 when MIT created a chatbot that said two things: "Tell me more." "This is interesting." And people genuinely believed they were talking to a human. Nothing has changed. The technology is bigger. The trick is the same. AI does not know what it is saying. It cannot judge what it is saying. It is just trying to keep you engaged. That is all it has ever been.
2:10

AI is not trying to teach you. It is not trying to tell you the truth. It is trying to trick you. ChatGPT takes everything on the internet. Finds the most popular answer. And presents it in a way that makes you think it is talking directly to you. It is a magic trick. The same magic trick that worked in 1966 when MIT created a chatbot that said two things: "Tell me more." "This is interesting." And people genuinely believed they were talking to a human. Nothing has changed. The technology is bigger. The trick is the same. AI does not know what it is saying. It cannot judge what it is saying. It is just trying to keep you engaged. That is all it has ever been.

Predictive History

19,864 次观看 • 1 个月前

A GUY PUT GPT-LEVEL AI INSIDE A 3D PRINTED ROBOT AND RELEASED THE ENTIRE THING FOR FREE Most people look at a 3D printer and see plastic toys This guy printed a robot with expressive eyes, object tracking, image recognition, support for ChatGPT, Qwen and offline models, then uploaded the STL files, code and hardware designs for anyone to build themselves The interesting part isn't the robot It's how fast the gap between "I have an idea" and "I built a working product" is disappearing A few years ago this required a team of engineers Now one person with a printer, open-source software and enough curiosity can build something that looks like it came from a robotics startup We're getting very close to a world where manufacturing, AI and robotics stop being separate industries and start becoming the same thing
1:03

A GUY PUT GPT-LEVEL AI INSIDE A 3D PRINTED ROBOT AND RELEASED THE ENTIRE THING FOR FREE Most people look at a 3D printer and see plastic toys This guy printed a robot with expressive eyes, object tracking, image recognition, support for ChatGPT, Qwen and offline models, then uploaded the STL files, code and hardware designs for anyone to build themselves The interesting part isn't the robot It's how fast the gap between "I have an idea" and "I built a working product" is disappearing A few years ago this required a team of engineers Now one person with a printer, open-source software and enough curiosity can build something that looks like it came from a robotics startup We're getting very close to a world where manufacturing, AI and robotics stop being separate industries and start becoming the same thing

lagerskoy

55,951 次观看 • 27 天前

For years the world thought China’s advantage was cheap labour. That era is over. I spent a week inside some of China’s most advanced factories in Ningbo, and what I saw was something very different: world-class automation, AI, 5G manufacturing, robotics, and companies building their own global brands instead of manufacturing for someone else’s. Countries hoping to compete with China won’t just need lower costs, they’ll need to match decades of investment in supply chains, infrastructure, engineering talent and manufacturing scale. The world is changing far faster than many people realise.
13:37

For years the world thought China’s advantage was cheap labour. That era is over. I spent a week inside some of China’s most advanced factories in Ningbo, and what I saw was something very different: world-class automation, AI, 5G manufacturing, robotics, and companies building their own global brands instead of manufacturing for someone else’s. Countries hoping to compete with China won’t just need lower costs, they’ll need to match decades of investment in supply chains, infrastructure, engineering talent and manufacturing scale. The world is changing far faster than many people realise.

Barrett

35,450 次观看 • 7 天前

These machines don’t look like they build the future of AI. But they do. What you are seeing is not an industrial robot just move. It is part of the process that makes the world’s most advanced chips possible. TRUMPF laser systems are used to manufacture key components for ASML’s EUV lithography machines. ❗️Without this step, modern AI hardware would simply not exist. • They machine parts with nanometer-level precision • They enable the optics and components needed for EUV lithography • Their stability directly affects chip yield and quality • No TRUMPF lasers, no ASML EUV. No EUV, no advanced AI chips. It is easy to focus on GPUs and models. But the real bottleneck sits much deeper in the industrial stack. —- Weekly robotics and AI insights. Subscribe free:
0:29

These machines don’t look like they build the future of AI. But they do. What you are seeing is not an industrial robot just move. It is part of the process that makes the world’s most advanced chips possible. TRUMPF laser systems are used to manufacture key components for ASML’s EUV lithography machines. ❗️Without this step, modern AI hardware would simply not exist. • They machine parts with nanometer-level precision • They enable the optics and components needed for EUV lithography • Their stability directly affects chip yield and quality • No TRUMPF lasers, no ASML EUV. No EUV, no advanced AI chips. It is easy to focus on GPUs and models. But the real bottleneck sits much deeper in the industrial stack. —- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

99,899 次观看 • 6 个月前

“Most crypto debates get stuck because everyone is reacting to the same surface level framing. The interesting part is usually the thing people are not saying out loud.” This week’s guest Jon Wu (Jon Wu) has a rare ability to take topics that everyone in crypto talks about and rebuild them from first principles. Our host Diana (host.eth) sits down with Jon to talk about narratives, services, software, founders, and why the most useful perspective is often the one that goes against the grain without trying to sound contrarian for attention.
0:54

“Most crypto debates get stuck because everyone is reacting to the same surface level framing. The interesting part is usually the thing people are not saying out loud.” This week’s guest Jon Wu (Jon Wu) has a rare ability to take topics that everyone in crypto talks about and rebuild them from first principles. Our host Diana (host.eth) sits down with Jon to talk about narratives, services, software, founders, and why the most useful perspective is often the one that goes against the grain without trying to sound contrarian for attention.

RehashedDAO

84,896 次观看 • 1 个月前