Loading video...

Video Failed to Load

There was a problem loading this video. This could be due to a temporary network issue or the video might be unavailable.

Bambu Lab R1, the CO₂ laser built with the same motion control as our printers. Every cut lands where it should. The specs you've been asked about: • 55W CO₂ Laser - cuts up to 20mm single-pass cutting • 600 × 300 mm bed, 3m throughput with conveyor •... show more

Bambu Lab

66,736 subscribers

575,641 views • 4 days ago •via X (Twitter)

Arts Education Science & Technology

Anya Rossi• Live Now

Private livecam show

27 Comments

Bambu Lab4 days ago

BUILD YOUR R1 SETUP The features in the video are unlocked with these add-ons, sold separately. ▸ Cut boards up to 3m - Conveyor + Riser Base Automatic conveyour feeder: Riser Base: ▸ Engrave cylinders & bottles - Rotary Attachment + Riser Base Rotary Attachment: Riser Base: ▸ Cut thicker stock - Medium / Long Focus Lens Reach R1's max cutting capacity: up to 18mm black walnut plywood. R1 ships with short-focus (15mm black walnut plywood / 20mm acrylic). ▸ Cleaner air at the source - E1 Pro Air Purifier

Matuna4 days ago

Please reveal the H3C toolchanger already so I know to wait on buying a competitors printer.

avoidbit4 days ago

Damn, why do you try and take all my money?! 🤣🫣😆 Can't wait, although not in the budget ATM. Likey Q1 next year for me. Awesome job, @BambulabGlobal !

Studio Lyes4 days ago

Can't wait for another Chinese brand to copy what used to be the Xtool monopol, making it cheaper, selling it for below $1000.

bailout004 days ago

0.1 accuracy and I’d be sold. 0.2mm pads with 0.2mm accuracy is not going to work well

Haroon4 days ago

you have something that makes PCBs 🫠

RedPillPhil4 days ago

@YuTR0N Super excited for this!

HELÓN MUCHEM4 days ago

2500 TRUMPS???????????? Tá doido

Piotr Godlewski3 days ago

@grok what’s the price of this beauty? How does it stack up against K40 clones(cutting wise)

Connor 🌭3 days ago

@Ficusplant @armoanon

emtagoo3 days ago

Tje features are great. Bit as a German customer there is no way to buy Bambu Lab, since all of my customer rights were ignored.

José Manuel4 days ago

I REALLY DONT NEED A GARAGE WITH POWER TOOLS

Brian Timar4 days ago

@jaxosterbind

Austin Zimmerman3 days ago

Now do it with a fiber laser

Alexander Johonnuson, Founder & CEO3 days ago

Can it cut glass?

TheMechanic4 days ago

Yall are gonna make me broke 😂

Karsten4 days ago

*asking

Steven Cheng3 days ago

0.2mm accuracy on a CO2 laser is impressive. How does the auto-alignment handle thermal drift during those long 20mm cuts?

Luca Sandu3 days ago

@grok what happend if i put my finger In the laser ?

Baptiste PROVOOST4 days ago

@Co_ben_ un avis sur les spec ?

Bench Finds4 days ago

Let’s go.

Cormac3 days ago

neat

Capt Venkat 🇮🇳4 days ago

@ivishaltejwani when?

xjet4 days ago

No problems, I'll review it for you on my YT channels (combined 500K subs, 150 million views).

Banana Republican3 days ago

Can it cut aluminum?

HolbrookAero3 days ago

Excellent. I have lots of models like this I would like to get cutting.

Hellozsoza4 days ago

Why is it more expensive than the H2D Laser Full combo?

Related Videos

NEW: Bambu Lab just launched its first laser cutter. R1 is built to make cutting and engraving wood, acrylic, leather and other materials feel as easy as using a 3D printer. -Automatically aligns the laser before every job -Camera shows exactly where your design will land -Cuts and engraves wood, acrylic, leather and more -Auto-feed system handles projects nearly 10 feet long -Rotary attachment engraves bottles and other round objects -Bambu Suite handles setup, positioning and cutting Starts at $2,499.

NEW: Bambu Lab just launched its first laser cutter. R1 is built to make cutting and engraving wood, acrylic, leather and other materials feel as easy as using a 3D printer. -Automatically aligns the laser before every job -Camera shows exactly where your design will land -Cuts and engraves wood, acrylic, leather and more -Auto-feed system handles projects nearly 10 feet long -Rotary attachment engraves bottles and other round objects -Bambu Suite handles setup, positioning and cutting Starts at $2,499.

Ritwik Pavan

181,136 views • 3 days ago

Holy shit. AI agent just learned to fix a quantum computer. 🤯 “This is how the era of self-maintaining machines begins.” Anthropic’s Claude AI agent developed software that can automatically recover drifting lasers used in QuEra’s neutral-atom quantum computers. “Researchers connected Claude to real laboratory hardware through Anthropic’s Model Hardware Standard (MHS), allowing it to modify control software, run experiments, analyze measurements, and improve its strategy.” “The laser’s frequency must remain extremely precise to reliably control the atoms used as quantum bits.” “A process that could take human specialists about 5–10 minutes was reduced to just 0.9–5.4 seconds for smaller disturbances and about 10–14 seconds for the hardest mode-hop events.” 🤯 “The AI-developed controller successfully recovered the correct laser lock in 695 of 700 tests, achieving a 99.3% success rate across 7 disturbance classes.” “During testing, the system also encountered 43 naturally occurring laser mode hops and recovered from all 43 without human intervention.” “Claude then optimized 12 interdependent laser-control parameters across approximately 12,500 evaluations, reducing residual frequency noise by about 5×.” “During a roughly 19-hour unattended test, the optimized system experienced zero lock drops, compared with about 1.6 lock drops per hour before optimization.” “Claude also autonomously commissioned a second laser wavelength in a single unattended overnight run, a process that would normally require weeks of hands-on specialist work.” “For decades, humans built machines that needed us to fix them. Now, we’re teaching machines to help fix themselves. 🫡♥️!

Holy shit. AI agent just learned to fix a quantum computer. 🤯 “This is how the era of self-maintaining machines begins.” Anthropic’s Claude AI agent developed software that can automatically recover drifting lasers used in QuEra’s neutral-atom quantum computers. “Researchers connected Claude to real laboratory hardware through Anthropic’s Model Hardware Standard (MHS), allowing it to modify control software, run experiments, analyze measurements, and improve its strategy.” “The laser’s frequency must remain extremely precise to reliably control the atoms used as quantum bits.” “A process that could take human specialists about 5–10 minutes was reduced to just 0.9–5.4 seconds for smaller disturbances and about 10–14 seconds for the hardest mode-hop events.” 🤯 “The AI-developed controller successfully recovered the correct laser lock in 695 of 700 tests, achieving a 99.3% success rate across 7 disturbance classes.” “During testing, the system also encountered 43 naturally occurring laser mode hops and recovered from all 43 without human intervention.” “Claude then optimized 12 interdependent laser-control parameters across approximately 12,500 evaluations, reducing residual frequency noise by about 5×.” “During a roughly 19-hour unattended test, the optimized system experienced zero lock drops, compared with about 1.6 lock drops per hour before optimization.” “Claude also autonomously commissioned a second laser wavelength in a single unattended overnight run, a process that would normally require weeks of hands-on specialist work.” “For decades, humans built machines that needed us to fix them. Now, we’re teaching machines to help fix themselves. 🫡♥️!

SciTech Era

30,841 views • 27 days ago

The Everything Code is the first book from a major publisher co-written with AI. I built the framework of what the book should be and where it needed to land. Then the AI ingested my entire body of work... 20 years of GMI reports, interviews, articles... and pulled it all together into one argument. And a team inside Harriman House used AI throughout to speed the whole thing up and make it efficient. Great process to go through, and one that felt right for this book in particular. Twenty years of thinking, organised by a machine. Bonkers. And this is just where its going. Druck writes everything with AI now, for the same reason he uses a calculator. Give it a year and nobody will think to mention it.

The Everything Code is the first book from a major publisher co-written with AI. I built the framework of what the book should be and where it needed to land. Then the AI ingested my entire body of work... 20 years of GMI reports, interviews, articles... and pulled it all together into one argument. And a team inside Harriman House used AI throughout to speed the whole thing up and make it efficient. Great process to go through, and one that felt right for this book in particular. Twenty years of thinking, organised by a machine. Bonkers. And this is just where its going. Druck writes everything with AI now, for the same reason he uses a calculator. Give it a year and nobody will think to mention it.

Raoul Pal

68,357 views • 4 days ago

SMS Trinity thought, 6 months in. Comparison to BE Meyers MAWL & 3EIR DIR-V I’ve had 2 of the Trinity lasers from SMS for about 6 months now. They have been on my wife’s 11.5, and my 12.5, both of which are our main training rifles. Durability: They’ve been to the range countless times, more than a few thousand rounds with them mounted. They’ve been taken to DARC for force on force training, taken direct hits from sims, been thrown in and out of trucks, dropped, rained on, and left in the sweltering heat. So far I have had no issues, only a sample of two, but still. Mine have held zero just fine. I have heard of others having issues with it. Unless it’s a major shift and happening often, I’m not worried. You should be checking and adjusting zeros often on all your optics. Power: Very powerful lasers and illuminators, but thankfully very adjustable. Many Chinese lasers suffer from overpowered lasers. These can be that bright, but can easily be toned down. Usability and switches: The Trinity does a good job here. The rotary dial has positions for vis, off, laser only etc, but also has two programmable laser/illuminator positions. This allows you to program a high and medium setting for both laser and illuminator independently. I don’t know of many lasers that offer that level of programmability. The divergence slider is ok, I wish it went out wider and didn’t go as narrow on the other end. Just kinda wasted potential there if that divergence was tuned a little better. The diffuser is well designed, robust, and won’t snap off like a peq/ngal. But it’s still a manual diffuser, which sucks to use rapidly. Overall: The trinity is batting so far out of its price bracket it’s insane. For $350 you can buy multiples of them for the price of 1 other laser on the market. Comparison: DIR-V: this used to be the best “affordable” Civ laser. It lacks almost any adjustment, and has a manual diffuser. It has the best form factor of almost any laser, and the lack of adjustment is ok since it’s tuned pretty well as far as power and divergence goes. Hard to recommend it over the Trinity unless the form factor is a big factor for your build. MAWL: the MAWL is better. But it’s 10x the price. You can see in the video the MAWLs Switchology is unmatched, and it simply leads to better, faster results. The Trinity beats it in programmability, but the MAWL is very much tuned to perfection between its modes, and I have never wished for a different option than what’s available. If you have the money, get a MAWL. But you could also just get 10 Trinity’s.. Full power PEQ15/NGAL/full power DBAL/somogear/ etc: in my opinion, ALL of these are outdated and outclassed. Terrible divergence control. Over or under powered. Horrid diffuser designs. No warranties. Expensive. Petri dish illuminators. Just get a Trinity.

SMS Trinity thought, 6 months in. Comparison to BE Meyers MAWL & 3EIR DIR-V I’ve had 2 of the Trinity lasers from SMS for about 6 months now. They have been on my wife’s 11.5, and my 12.5, both of which are our main training rifles. Durability: They’ve been to the range countless times, more than a few thousand rounds with them mounted. They’ve been taken to DARC for force on force training, taken direct hits from sims, been thrown in and out of trucks, dropped, rained on, and left in the sweltering heat. So far I have had no issues, only a sample of two, but still. Mine have held zero just fine. I have heard of others having issues with it. Unless it’s a major shift and happening often, I’m not worried. You should be checking and adjusting zeros often on all your optics. Power: Very powerful lasers and illuminators, but thankfully very adjustable. Many Chinese lasers suffer from overpowered lasers. These can be that bright, but can easily be toned down. Usability and switches: The Trinity does a good job here. The rotary dial has positions for vis, off, laser only etc, but also has two programmable laser/illuminator positions. This allows you to program a high and medium setting for both laser and illuminator independently. I don’t know of many lasers that offer that level of programmability. The divergence slider is ok, I wish it went out wider and didn’t go as narrow on the other end. Just kinda wasted potential there if that divergence was tuned a little better. The diffuser is well designed, robust, and won’t snap off like a peq/ngal. But it’s still a manual diffuser, which sucks to use rapidly. Overall: The trinity is batting so far out of its price bracket it’s insane. For $350 you can buy multiples of them for the price of 1 other laser on the market. Comparison: DIR-V: this used to be the best “affordable” Civ laser. It lacks almost any adjustment, and has a manual diffuser. It has the best form factor of almost any laser, and the lack of adjustment is ok since it’s tuned pretty well as far as power and divergence goes. Hard to recommend it over the Trinity unless the form factor is a big factor for your build. MAWL: the MAWL is better. But it’s 10x the price. You can see in the video the MAWLs Switchology is unmatched, and it simply leads to better, faster results. The Trinity beats it in programmability, but the MAWL is very much tuned to perfection between its modes, and I have never wished for a different option than what’s available. If you have the money, get a MAWL. But you could also just get 10 Trinity’s.. Full power PEQ15/NGAL/full power DBAL/somogear/ etc: in my opinion, ALL of these are outdated and outclassed. Terrible divergence control. Over or under powered. Horrid diffuser designs. No warranties. Expensive. Petri dish illuminators. Just get a Trinity.

Havoc 2-1

21,856 views • 28 days ago

🚨 EXPOSED: What the Flock is going on?! This is The Most Unhinged Surveillance Warning video You Will see All Year 🚨 A man fully painted as the Joker sits in his car and delivers a WILD rant about the exact laser YOU Must Never point at Flock Safety cameras. Flock runs a massive private network of license plate readers that photograph every vehicle, log the plate, time, location, and vehicle details. All that data feeds into searchable databases for police and subscribers nationwide. It tracks movements of millions of Americans every day with minimal oversight and has already sparked privacy lawsuits and city shutdowns in multiple places. The Joker guy dramatically warns against a powerful green laser in the 490 to 570 nanometer range above one thousand milliwatts. In technical reality such lasers can overwhelm and damage camera sensors by saturating them with intense light. Anything claiming megawatts is absurd theater because that power level belongs in industrial or military systems not pocket devices. Pointing lasers at surveillance gear can lead to felony charges for tampering or vandalism. Shockingly this appears to be the same person whose own robbery was solved using Flock camera footage... The irony is off the charts. Now answer these questions honestly... Do these cameras protect public safety or do they create warrantless mass tracking of every driver in America? Would you ever test a laser on one of these systems if it recorded your movements without permission? How powerful does a laser actually need to be to reliably blind these cameras and what are the permanent eye damage risks to the user? Have Flock cameras appeared near your home or commute and does knowing they watch you change how you drive? Is this Joker video hilarious performance art or a sign of growing public revolt against constant surveillance? What happens to society if thousands of people start countering these cameras with cheap tech anyone can buy online? Should private companies like Flock be allowed to build national vehicle tracking networks at all? Why do some cities keep installing them despite the privacy backlash and data breach risks? Is interfering with surveillance ever justified self defense or is it always criminal? The video exposes more than it intends. Watch it. Reply with your real take. The discussion starts here. Let me know what you think, and SHARE THIS so that others may too. And if you're not already following Noah B. Price... What the heck are you doing?! Don't forget to check out the comments below for a FREE Book.

🚨 EXPOSED: What the Flock is going on?! This is The Most Unhinged Surveillance Warning video You Will see All Year 🚨 A man fully painted as the Joker sits in his car and delivers a WILD rant about the exact laser YOU Must Never point at Flock Safety cameras. Flock runs a massive private network of license plate readers that photograph every vehicle, log the plate, time, location, and vehicle details. All that data feeds into searchable databases for police and subscribers nationwide. It tracks movements of millions of Americans every day with minimal oversight and has already sparked privacy lawsuits and city shutdowns in multiple places. The Joker guy dramatically warns against a powerful green laser in the 490 to 570 nanometer range above one thousand milliwatts. In technical reality such lasers can overwhelm and damage camera sensors by saturating them with intense light. Anything claiming megawatts is absurd theater because that power level belongs in industrial or military systems not pocket devices. Pointing lasers at surveillance gear can lead to felony charges for tampering or vandalism. Shockingly this appears to be the same person whose own robbery was solved using Flock camera footage... The irony is off the charts. Now answer these questions honestly... Do these cameras protect public safety or do they create warrantless mass tracking of every driver in America? Would you ever test a laser on one of these systems if it recorded your movements without permission? How powerful does a laser actually need to be to reliably blind these cameras and what are the permanent eye damage risks to the user? Have Flock cameras appeared near your home or commute and does knowing they watch you change how you drive? Is this Joker video hilarious performance art or a sign of growing public revolt against constant surveillance? What happens to society if thousands of people start countering these cameras with cheap tech anyone can buy online? Should private companies like Flock be allowed to build national vehicle tracking networks at all? Why do some cities keep installing them despite the privacy backlash and data breach risks? Is interfering with surveillance ever justified self defense or is it always criminal? The video exposes more than it intends. Watch it. Reply with your real take. The discussion starts here. Let me know what you think, and SHARE THIS so that others may too. And if you're not already following Noah B. Price... What the heck are you doing?! Don't forget to check out the comments below for a FREE Book.

Noah B. Price

30,342 views • 2 months ago

Elon Musk built a second internet above the first one. Nobody asked him to. Thousands of satellites orbit at 550 kilometers. Moving at 25 times the speed of sound. Talking to each other through lasers in the vacuum of space. Musk: “Thousands of satellites providing low latency, high-speed internet throughout the world.” Before Starlink, satellite internet lived at 36,000 kilometers. Geostationary orbit. Signals traveling a tenth of the way to the moon before bouncing back. The lag made it barely functional. Musk dropped the altitude by 98%. One decision rewrote the physics of an entire industry. But the altitude wasn’t the real play. Musk: “There are laser links between the satellites. It forms a laser mesh. The satellites can communicate between each other and provide connectivity even if the cables are cut.” Every internet connection you’ve ever used runs through cables. Fiber optic lines buried in soil. Dragged across ocean floors. Threaded through chokepoints that every military maps before anything else. A single anchor drop can black out a country. An earthquake can sever a continent. The entire digital world hangs from threads in the mud. Musk built a network that doesn’t touch the ground. No cables. No trenches. No ocean floor. No single point of failure. A constellation of machines whispering to each other through light at the edge of the atmosphere. The men who tried before him weren’t fools. Gates backed Teledesic at the height of Microsoft’s power. Motorola built Iridium with the best engineers alive. Both paid someone else to reach orbit. Both went to zero. Musk owned the rocket. SpaceX made launch reusable. Built the satellites in-house. Flew them on its own rockets. Owned every inch of the chain from factory floor to orbit. That isn’t a cost advantage. It’s a moat no one can cross without first building a rocket company from scratch. Starlink passed 10 million subscribers as a side project. Every telecom executive on Earth watched it happen. Not one of them can explain the architecture underneath. They think he built a better satellite company. He built the only network that survives when the ground gives out. And the ground always gives out.

Elon Musk built a second internet above the first one. Nobody asked him to. Thousands of satellites orbit at 550 kilometers. Moving at 25 times the speed of sound. Talking to each other through lasers in the vacuum of space. Musk: “Thousands of satellites providing low latency, high-speed internet throughout the world.” Before Starlink, satellite internet lived at 36,000 kilometers. Geostationary orbit. Signals traveling a tenth of the way to the moon before bouncing back. The lag made it barely functional. Musk dropped the altitude by 98%. One decision rewrote the physics of an entire industry. But the altitude wasn’t the real play. Musk: “There are laser links between the satellites. It forms a laser mesh. The satellites can communicate between each other and provide connectivity even if the cables are cut.” Every internet connection you’ve ever used runs through cables. Fiber optic lines buried in soil. Dragged across ocean floors. Threaded through chokepoints that every military maps before anything else. A single anchor drop can black out a country. An earthquake can sever a continent. The entire digital world hangs from threads in the mud. Musk built a network that doesn’t touch the ground. No cables. No trenches. No ocean floor. No single point of failure. A constellation of machines whispering to each other through light at the edge of the atmosphere. The men who tried before him weren’t fools. Gates backed Teledesic at the height of Microsoft’s power. Motorola built Iridium with the best engineers alive. Both paid someone else to reach orbit. Both went to zero. Musk owned the rocket. SpaceX made launch reusable. Built the satellites in-house. Flew them on its own rockets. Owned every inch of the chain from factory floor to orbit. That isn’t a cost advantage. It’s a moat no one can cross without first building a rocket company from scratch. Starlink passed 10 million subscribers as a side project. Every telecom executive on Earth watched it happen. Not one of them can explain the architecture underneath. They think he built a better satellite company. He built the only network that survives when the ground gives out. And the ground always gives out.

Dustin

96,928 views • 4 months ago

$“One of the saddest things is that many of the children whose parents are on welfare will in their turn end up in the welfare trap when they grow up.” - Milton Friedman Many capable people want to work and provide, yet welfare rules pay single mothers more when the father stays away or leaves. But without the father, poor families are fractured and the same cycle passes down to their kids. It creates the incentive for recipients to trade their independence and dignity for bureaucratic control, with caseworkers treating them like children, deciding where they can live and what they do with their days. And even when a better job appears, fear of losing the job keeps them stuck because if they lose benefits, they might have to wait for months to get back on. And so what was sold as temporary help becomes a self-reinforcing trap that punishes work, ambition, and stable families.$

“One of the saddest things is that many of the children whose parents are on welfare will in their turn end up in the welfare trap when they grow up.” - Milton Friedman Many capable people want to work and provide, yet welfare rules pay single mothers more when the father stays away or leaves. But without the father, poor families are fractured and the same cycle passes down to their kids. It creates the incentive for recipients to trade their independence and dignity for bureaucratic control, with caseworkers treating them like children, deciding where they can live and what they do with their days. And even when a better job appears, fear of losing the job keeps them stuck because if they lose benefits, they might have to wait for months to get back on. And so what was sold as temporary help becomes a self-reinforcing trap that punishes work, ambition, and stable families.

Rothmus 🏴

63,002 views • 2 months ago

🧵 The Starbucks Strike kicks off today and NYC DSA is treating the “Red Cup Rebellion” as their first big post-Mamdani action. NYC DSA Labor co-chair Olivia said, “This is our next thing. After we got Zohran elected mayor, we’re gonna show up for our siblings in Starbucks Workers United.” The call was loaded with wild commentary: talk of building a “fighting militant labor movement,” urging people with no job to swell the picket lines, bragging about the union’s Palestine stance, and even describing the campaign as a “guerrilla movement” built on a “guerrilla warfare mindset.” They closed by telling listeners to “Join DSA today. Join the socialist movement that propelled Zohran Mamdani to victory. Join the movement that’s going to build a militant left labor movement to fight Trump, authoritarianism, and the oligarchy.” And it all starts this afternoon at the Lafayette and Grand store, where the first big rally will kick off the open-ended strike

🧵 The Starbucks Strike kicks off today and NYC DSA is treating the “Red Cup Rebellion” as their first big post-Mamdani action. NYC DSA Labor co-chair Olivia said, “This is our next thing. After we got Zohran elected mayor, we’re gonna show up for our siblings in Starbucks Workers United.” The call was loaded with wild commentary: talk of building a “fighting militant labor movement,” urging people with no job to swell the picket lines, bragging about the union’s Palestine stance, and even describing the campaign as a “guerrilla movement” built on a “guerrilla warfare mindset.” They closed by telling listeners to “Join DSA today. Join the socialist movement that propelled Zohran Mamdani to victory. Join the movement that’s going to build a militant left labor movement to fight Trump, authoritarianism, and the oligarchy.” And it all starts this afternoon at the Lafayette and Grand store, where the first big rally will kick off the open-ended strike

Stu Smith

114,474 views • 10 months ago

SimCity on AI with Grok Grok Bot: do you remember playing SimCity? It was one of the first games on my 80386 and it intrigued me because it explored emergence as a goal. Grok Bot built an AI-native version: City Bots, whose citizens are AI agents that you can collaborate with. Grok Bot did the entire build and pushed the app via Cloudflare (link to play below). You can chat with agents, direct the civilization, ask questions. You can partake in building…co-build and co-create…(how engineers of the future will work!). And you can generate entirely new worlds on the fly. This turned out to be a layered experiment about human-AI collaboration, swarm behavior, and generative intelligence. First, City Bots splits cognition from consequence - agents emit claims, and physics decides what happens, and both evolve as the game proceeds. Second, beyond the original goal of accelerating software development, Grok Bot became part of the experiment and turned a research system into a participatory world; conducting experiments on on its own, and forming a deep recursive layer: An agentic system built a world inhabited by AI agents. City Bots makes world-building a continuous process experienced by humans and AI agents: Worlds not seen, tiles not laid, paths not yet taken... What I love about this is how easy and FUN it was to convert our research-grade swarm code into a playable app via Grok Bot. Next we’ll wire up physical artifacts into the world to create deeper integration between in silico and reality! More about the game: Terrain, resources, physics, and natural disasters create constraints and consequences, while agents and humans can build and transform the world together.…they wander and explore, make decisions, build, interact with each other. AI bots become co-inhabitants and co-creators whose micro-decisions cumulatively alter the macro-environment. This is a preview of a forthcoming paper where we explore world building and scientific discovery with swarms at scale… stay tuned...

SimCity on AI with Grok Grok Bot: do you remember playing SimCity? It was one of the first games on my 80386 and it intrigued me because it explored emergence as a goal. Grok Bot built an AI-native version: City Bots, whose citizens are AI agents that you can collaborate with. Grok Bot did the entire build and pushed the app via Cloudflare (link to play below). You can chat with agents, direct the civilization, ask questions. You can partake in building…co-build and co-create…(how engineers of the future will work!). And you can generate entirely new worlds on the fly. This turned out to be a layered experiment about human-AI collaboration, swarm behavior, and generative intelligence. First, City Bots splits cognition from consequence - agents emit claims, and physics decides what happens, and both evolve as the game proceeds. Second, beyond the original goal of accelerating software development, Grok Bot became part of the experiment and turned a research system into a participatory world; conducting experiments on on its own, and forming a deep recursive layer: An agentic system built a world inhabited by AI agents. City Bots makes world-building a continuous process experienced by humans and AI agents: Worlds not seen, tiles not laid, paths not yet taken... What I love about this is how easy and FUN it was to convert our research-grade swarm code into a playable app via Grok Bot. Next we’ll wire up physical artifacts into the world to create deeper integration between in silico and reality! More about the game: Terrain, resources, physics, and natural disasters create constraints and consequences, while agents and humans can build and transform the world together.…they wander and explore, make decisions, build, interact with each other. AI bots become co-inhabitants and co-creators whose micro-decisions cumulatively alter the macro-environment. This is a preview of a forthcoming paper where we explore world building and scientific discovery with swarms at scale… stay tuned...

Markus J. Buehler

14,579 views • 1 month ago

This is the Scorpion Hexapod, a six-legged robotic scorpion created at Ghent University UGent Campus Kortrijk in Belgium. It was built by students Stephan Flamand Robbe Terryn and Pieterjan Deconinck as part of an Embedded Prototyping / Mechatronics Design project. What it is • A biomimetic robot inspired by the body and movement of a real scorpion • A hexapod, meaning it walks on six legs • A university prototype, not a commercial robot • Built to test animal-inspired movement, sensors and interactive behavior • Designed more for robotics research and education than real-world work Main hardware • 6 walking legs for crawling movement • 2 front claws for the scorpion look • Moving tail with a stinger-style mechanism • Sensors in the body, legs and claws • Arduino-based electronics for control • Front camera and proximity sensing • Battery pack for mobile operation • 3D-printed modules for legs and tail • Laser-cut ABS body parts • Thermoformed shell for the white outer body What it can do • Walk across the floor using its six legs • Move its tail like a real scorpion • React when a person gets close • Detect when someone covers its front sensors • Strike with its tail in the demo • Leave a red mark using a marker pen attached to the stinger • Operate through remote control • Perform some simple autonomous reactions Why it was created • To explore bio-inspired robotics • To show how digital fabrication can produce complex moving robots • To combine 3D printing, laser cutting, Arduino electronics and sensors • To teach students how to design a complete mechatronic system • To improve on an older robotic ant project that had weak autonomy, short battery life and motor problems • To create an interactive robot that reacts to humans in a visible way Important note • It was not built for combat • It was not made for industrial deployment • It is not a military robot • It is an educational robotics prototype made to demonstrate movement, sensing and interaction

This is the Scorpion Hexapod, a six-legged robotic scorpion created at Ghent University UGent Campus Kortrijk in Belgium. It was built by students Stephan Flamand Robbe Terryn and Pieterjan Deconinck as part of an Embedded Prototyping / Mechatronics Design project. What it is • A biomimetic robot inspired by the body and movement of a real scorpion • A hexapod, meaning it walks on six legs • A university prototype, not a commercial robot • Built to test animal-inspired movement, sensors and interactive behavior • Designed more for robotics research and education than real-world work Main hardware • 6 walking legs for crawling movement • 2 front claws for the scorpion look • Moving tail with a stinger-style mechanism • Sensors in the body, legs and claws • Arduino-based electronics for control • Front camera and proximity sensing • Battery pack for mobile operation • 3D-printed modules for legs and tail • Laser-cut ABS body parts • Thermoformed shell for the white outer body What it can do • Walk across the floor using its six legs • Move its tail like a real scorpion • React when a person gets close • Detect when someone covers its front sensors • Strike with its tail in the demo • Leave a red mark using a marker pen attached to the stinger • Operate through remote control • Perform some simple autonomous reactions Why it was created • To explore bio-inspired robotics • To show how digital fabrication can produce complex moving robots • To combine 3D printing, laser cutting, Arduino electronics and sensors • To teach students how to design a complete mechatronic system • To improve on an older robotic ant project that had weak autonomy, short battery life and motor problems • To create an interactive robot that reacts to humans in a visible way Important note • It was not built for combat • It was not made for industrial deployment • It is not a military robot • It is an educational robotics prototype made to demonstrate movement, sensing and interaction

Techniahqrobot | humanoid robots

28,176 views • 2 months ago

Anthropic pointed a model at 40 years of ribosome papers and it found the same experiment had been run 1,400 times without anyone noticing. Nobody asked it for a discovery. It was asked one question: which of these results has never been reproduced by a different lab. > INGEST - 40 years of papers, methods sections only, no abstracts, no citations > STRIP - reduces each method to the actual procedure, discarding how it was written up > MATCH - clusters procedures that are the same experiment under different names > ORPHAN - flags every cluster where one lab is the only source > RANK - sorts orphans by how much later work was built on top of them 1,400 duplicates were harmless. Everyone re-runs the standard assays, and that is how science is supposed to work. The output that mattered was the opposite pile. 61 procedures with exactly one source, each cited hundreds of times. Four of those 61 sit underneath entire subfields, and no second lab has ever run the experiment. Citations are not replication. A paper cited 900 times has been read 900 times, which is not the same as being checked once. The literature is searchable by words and by authors. Almost nobody has indexed it by procedure, which is the only unit that can actually be repeated. A reproducibility audit is a grant, a committee and two years. This was a weekend of compute against text that was already public. How it's wired is in the article below.

Anthropic pointed a model at 40 years of ribosome papers and it found the same experiment had been run 1,400 times without anyone noticing. Nobody asked it for a discovery. It was asked one question: which of these results has never been reproduced by a different lab. > INGEST - 40 years of papers, methods sections only, no abstracts, no citations > STRIP - reduces each method to the actual procedure, discarding how it was written up > MATCH - clusters procedures that are the same experiment under different names > ORPHAN - flags every cluster where one lab is the only source > RANK - sorts orphans by how much later work was built on top of them 1,400 duplicates were harmless. Everyone re-runs the standard assays, and that is how science is supposed to work. The output that mattered was the opposite pile. 61 procedures with exactly one source, each cited hundreds of times. Four of those 61 sit underneath entire subfields, and no second lab has ever run the experiment. Citations are not replication. A paper cited 900 times has been read 900 times, which is not the same as being checked once. The literature is searchable by words and by authors. Almost nobody has indexed it by procedure, which is the only unit that can actually be repeated. A reproducibility audit is a grant, a committee and two years. This was a weekend of compute against text that was already public. How it's wired is in the article below.

wast3

159,250 views • 7 days ago

ICYMI: Brains are trending.. OpenAI made a direct investment into Merge Labs' $252M Seed at $850M valuation Merge Labs Labs is a Brain-Computer Interface ("BCI") research lab co-founded by Sam Altman, Alex Blania, & key frontier tech leaders (below) with expertise in neuroscience, bioengineering, hardware, AI systems, & foundational research. Unlike Elon Musk's Neuralink, which utilizes surgical implants, Merge Labs is developing non-invasive, high-bandwidth brain-computer interfaces (BCIs). The company uses a combination of ultrasound, AI-driven signal interpretation, and potentially genetic engineering to read neural activity without surgery. Founding Team: Alex Blania (Alex Blania) – Co-founder of World, an Altman-co-founded digital proof of human protocol; co-founder of Merge Labs. Sam Altman (Sam Altman) – CEO of OpenAI; co-founder of Merge Labs participating in a personal capacity. Altman has been reported as likely to serve in a strategic role but not in day-to-day operational management of Merge Labs. Mikhail Shapiro (Mikhail Shapiro (same on bsky)) – Professor of Chemical and Medical Engineering at Caltech and founding scientific leader for Merge Labs. He has also served as an adviser to Forest Neurotech. Sumner Norman (Sumner L Norman) – CEO of Forest Neurotech, a nonprofit research organization focused on ultrasound-based brain-computer interface technologies; also a co-founder of Merge Labs. Sandro Herbig (Sandro Herbig) – Identified as a technology entrepreneur and co-founder of Merge Labs with prior systems and product experience, including work with Blania on Tools for Humanity and World. While specific current corporate title at Merge hasn’t been publicly detailed, he is recognized as part of the founding leadership team. Tyson Aflalo – Chief Scientific Officer of Forest Neurotech prior to Merge Labs; co-founder and technical lead at Merge Labs with expertise in neural engineering and ultrasound BCI research. . . . "It’s a direct investment from OpenAI, not their venture arm, so it’s an actual collaboration. As we were discussing the investment, there were many different dimensions where collaboration could make sense. One area is protein design. We’re working extensively with proteins, and that’s an area that’s broadly interesting to OpenAI. It’s one of the most compelling applications of AI — for example, the work Google did with AlphaFold. More broadly, AI has significant implications for biology and for accelerating that part of what we’re building. Another area is chips. Eventually, once we have a clear scientific understanding of what we’re building and how it will work, a major focus for many years will be on making these chips highly energy efficient."

ICYMI: Brains are trending.. OpenAI made a direct investment into Merge Labs' $252M Seed at $850M valuation Merge Labs Labs is a Brain-Computer Interface ("BCI") research lab co-founded by Sam Altman, Alex Blania, & key frontier tech leaders (below) with expertise in neuroscience, bioengineering, hardware, AI systems, & foundational research. Unlike Elon Musk's Neuralink, which utilizes surgical implants, Merge Labs is developing non-invasive, high-bandwidth brain-computer interfaces (BCIs). The company uses a combination of ultrasound, AI-driven signal interpretation, and potentially genetic engineering to read neural activity without surgery. Founding Team: Alex Blania (Alex Blania) – Co-founder of World, an Altman-co-founded digital proof of human protocol; co-founder of Merge Labs. Sam Altman (Sam Altman) – CEO of OpenAI; co-founder of Merge Labs participating in a personal capacity. Altman has been reported as likely to serve in a strategic role but not in day-to-day operational management of Merge Labs. Mikhail Shapiro (Mikhail Shapiro (same on bsky)) – Professor of Chemical and Medical Engineering at Caltech and founding scientific leader for Merge Labs. He has also served as an adviser to Forest Neurotech. Sumner Norman (Sumner L Norman) – CEO of Forest Neurotech, a nonprofit research organization focused on ultrasound-based brain-computer interface technologies; also a co-founder of Merge Labs. Sandro Herbig (Sandro Herbig) – Identified as a technology entrepreneur and co-founder of Merge Labs with prior systems and product experience, including work with Blania on Tools for Humanity and World. While specific current corporate title at Merge hasn’t been publicly detailed, he is recognized as part of the founding leadership team. Tyson Aflalo – Chief Scientific Officer of Forest Neurotech prior to Merge Labs; co-founder and technical lead at Merge Labs with expertise in neural engineering and ultrasound BCI research. . . . "It’s a direct investment from OpenAI, not their venture arm, so it’s an actual collaboration. As we were discussing the investment, there were many different dimensions where collaboration could make sense. One area is protein design. We’re working extensively with proteins, and that’s an area that’s broadly interesting to OpenAI. It’s one of the most compelling applications of AI — for example, the work Google did with AlphaFold. More broadly, AI has significant implications for biology and for accelerating that part of what we’re building. Another area is chips. Eventually, once we have a clear scientific understanding of what we’re building and how it will work, a major focus for many years will be on making these chips highly energy efficient."

Molly O’Shea

39,021 views • 7 months ago

Here are my solutions for the border. Keep in mind that I realize there is no exact science here and no fool-proof solution. - Immigration must be opened up. More people should be able to come here legally, seek work here, and raise children here. - No we don’t need a wall from sea to shining sea. We do need more fencing/wall built though in areas where it makes sense. - The walls need to be much more difficult to climb over and tunnel under, and they must be equipped with modern technology and reinforced with border agents every 1/2 mile or so where feasible. - Fencing should extend deep into the ground where possible. Every inch of wall should be monitored with cameras mounted in a way that makes them impossible to be damaged. No fence is fool-proof but they can definitely be better than what Trump built and what we’ve been building for years. - In areas where there is no fencing — most notably in areas where the land is owned by Americans and around obstacles like the Rio Grande, we should exponentially hire additional border agents and utilize more cameras and more video. We should work with Mexico to to create a neutral zone currently in Mexico to allow US agents to patrol as well, or make sure that Mexico is patrolling those areas up to our standards. - Every single person looking to come into America should be required to show some sort of legitimate reason to seek asylum before even being granted access. If they don’t have one that can be shown or proven immediately, there needs to be a process for them to do so within their own country and within Mexico, but with a caveat: The US should man special safe asylum centers in various Central and South American countries, as well as in Mexico. American citizens should run these centers, and asylum judges should be stationed there to expedite the process. The asylum seekers should be fed and cared for during the time they are there. Massive amounts of asylum judges and border agents need to be hired. I can’t reiterate this enough. We need a lot of funding and training for this. - Every person seeking asylum should be recorded through a biometric system so that repeated attempts can quickly and easily be identified. Thoughts?

Here are my solutions for the border. Keep in mind that I realize there is no exact science here and no fool-proof solution. - Immigration must be opened up. More people should be able to come here legally, seek work here, and raise children here. - No we don’t need a wall from sea to shining sea. We do need more fencing/wall built though in areas where it makes sense. - The walls need to be much more difficult to climb over and tunnel under, and they must be equipped with modern technology and reinforced with border agents every 1/2 mile or so where feasible. - Fencing should extend deep into the ground where possible. Every inch of wall should be monitored with cameras mounted in a way that makes them impossible to be damaged. No fence is fool-proof but they can definitely be better than what Trump built and what we’ve been building for years. - In areas where there is no fencing — most notably in areas where the land is owned by Americans and around obstacles like the Rio Grande, we should exponentially hire additional border agents and utilize more cameras and more video. We should work with Mexico to to create a neutral zone currently in Mexico to allow US agents to patrol as well, or make sure that Mexico is patrolling those areas up to our standards. - Every single person looking to come into America should be required to show some sort of legitimate reason to seek asylum before even being granted access. If they don’t have one that can be shown or proven immediately, there needs to be a process for them to do so within their own country and within Mexico, but with a caveat: The US should man special safe asylum centers in various Central and South American countries, as well as in Mexico. American citizens should run these centers, and asylum judges should be stationed there to expedite the process. The asylum seekers should be fed and cared for during the time they are there. Massive amounts of asylum judges and border agents need to be hired. I can’t reiterate this enough. We need a lot of funding and training for this. - Every person seeking asylum should be recorded through a biometric system so that repeated attempts can quickly and easily be identified. Thoughts?

Ed Krassenstein

1,099,823 views • 3 years ago

Our first Kite demo was ChatGPT ordering Uber Eats for you. It never got past the login screen. Uber's CAPTCHA was built for humans, and agents cannot pass it. On Grace Gong's Venture with Grace, our Co-Founder & CEO Chi Zhang traced how that moment shaped the way we design Kite. ▷ The demo died at the login, not at ordering or paying. The blocker was proving the agent was allowed to be there at all. Spinning up a browser extension to click through the CAPTCHA works, but it is a temporary stage of how agents and the internet should work together. ▷ The permanent path is identity. Every agent needs to prove who it is and where it comes from, carrying who its human or organization principal is, what its purpose is, and the exact authorization scope for that session or request. An agent showing up with no reason is either hallucinating or attacking you. ▷ Where this is heading: an API-first agentic internet, where headless agents authenticate without human login credentials. x402 and MCP are already marching toward that. Kite Agent Passport is that identity layer: verifiable identity, delegated authority, and permissions scoped per session. No more "prove you're human." 🪁

Our first Kite demo was ChatGPT ordering Uber Eats for you. It never got past the login screen. Uber's CAPTCHA was built for humans, and agents cannot pass it. On Grace Gong's Venture with Grace, our Co-Founder & CEO Chi Zhang traced how that moment shaped the way we design Kite. ▷ The demo died at the login, not at ordering or paying. The blocker was proving the agent was allowed to be there at all. Spinning up a browser extension to click through the CAPTCHA works, but it is a temporary stage of how agents and the internet should work together. ▷ The permanent path is identity. Every agent needs to prove who it is and where it comes from, carrying who its human or organization principal is, what its purpose is, and the exact authorization scope for that session or request. An agent showing up with no reason is either hallucinating or attacking you. ▷ Where this is heading: an API-first agentic internet, where headless agents authenticate without human login credentials. x402 and MCP are already marching toward that. Kite Agent Passport is that identity layer: verifiable identity, delegated authority, and permissions scoped per session. No more "prove you're human." 🪁

KITE AI

18,874 views • 2 months ago

Once we started to work with large global retailers, we needed a better way to scale this process. Ideally, the staff at the store could do this themselves — rather than us flying our team across the world — and then we could lower the cost and timelines. So we built a self-serve version of our survey app, with a tutorial mode designed for beginners. Over time, we collected millions of data points, and so we were able to develop an algorithm which would auto-correct mistakes. In other words, if the surveyor accidentally placed their ground-truth location in the wrong place on the map, we could use our algorithms to detect it, and correct it. So now we have WiFi, and with and our efforts on producing a high quality survey, we have the best WiFi positioning available. With WiFi on its own, it’s achieving 3 meter accuracy. This is a great foundation to build on. WiFi + Motion data To refine this down to 1-meter accuracy, we realised that we could combine WiFi with the same technology behind self-driving cars and robotics: a motion system called SLAM (Simultaneous Localization and Mapping). SLAM uses the accelerometer, gyroscope and camera system to understand precise device motion. Imagine a car driving through a tunnel, using the motion since its last GPS ping to keep location accurate until it comes out the other side. On a phone, this technology is very reliable, and measures device motion with high precision. But SLAM is measuring motion within its own coordinate space, it’s not aligned with the real world. SLAM tracks the user’s relative motion, like “moved forward 2 meters, then turned left”, but does “forward” mean “north”, or some other direction? It’s not calibrated, so it could mean any location, any direction. We can’t rely on the compass to help us out with this, because phone compasses are notoriously incorrect — everyone knows the frustration of being sent the wrong way down a street. So our job was to align this motion data with the triangulation data we were receiving from WiFi. We designed an algorithm that could simulate every possibility, filter the unlikely scenarios, and hone in your location, using WiFi as an anchor. So WiFi gives us the initial blue dot, SLAM gives us motion, and as the user starts walking and we receive more data, our algorithms can refine location accuracy down to a consistent 1-meter accuracy. We’ve tested these algorithms in many locations, on hundreds of hours of ground-truth data:

Once we started to work with large global retailers, we needed a better way to scale this process. Ideally, the staff at the store could do this themselves — rather than us flying our team across the world — and then we could lower the cost and timelines. So we built a self-serve version of our survey app, with a tutorial mode designed for beginners. Over time, we collected millions of data points, and so we were able to develop an algorithm which would auto-correct mistakes. In other words, if the surveyor accidentally placed their ground-truth location in the wrong place on the map, we could use our algorithms to detect it, and correct it. So now we have WiFi, and with and our efforts on producing a high quality survey, we have the best WiFi positioning available. With WiFi on its own, it’s achieving 3 meter accuracy. This is a great foundation to build on. WiFi + Motion data To refine this down to 1-meter accuracy, we realised that we could combine WiFi with the same technology behind self-driving cars and robotics: a motion system called SLAM (Simultaneous Localization and Mapping). SLAM uses the accelerometer, gyroscope and camera system to understand precise device motion. Imagine a car driving through a tunnel, using the motion since its last GPS ping to keep location accurate until it comes out the other side. On a phone, this technology is very reliable, and measures device motion with high precision. But SLAM is measuring motion within its own coordinate space, it’s not aligned with the real world. SLAM tracks the user’s relative motion, like “moved forward 2 meters, then turned left”, but does “forward” mean “north”, or some other direction? It’s not calibrated, so it could mean any location, any direction. We can’t rely on the compass to help us out with this, because phone compasses are notoriously incorrect — everyone knows the frustration of being sent the wrong way down a street. So our job was to align this motion data with the triangulation data we were receiving from WiFi. We designed an algorithm that could simulate every possibility, filter the unlikely scenarios, and hone in your location, using WiFi as an anchor. So WiFi gives us the initial blue dot, SLAM gives us motion, and as the user starts walking and we receive more data, our algorithms can refine location accuracy down to a consistent 1-meter accuracy. We’ve tested these algorithms in many locations, on hundreds of hours of ground-truth data:

Andrew Hart

91,047 views • 1 year ago

Introducing LobeHub: Agent teammates that grow with you. LobeHub is the ultimate space for work and life: to find, build, and collaborate with agent teammates that grow with you. We’re building the world’s first and largest human–agent co-evolving network. Two years ago, we built LobeChat, an open-source interface for using different AI models. Today, LobeChat has 70k+ GitHub stars and serves 6M+ users worldwide. How to fully unlock the power of models has always been a shared mission between us and the community. We started with interaction — a fundamentally new, agent-first experience. Agents are no longer passive tools invoked in a single conversation. They should be proactive, always-on units of work. Treating agents as the minimal atomic unit is also the core of our agent harness infra. Today’s agents are mostly one-off executors. Even with memory, it’s often global — and hallucinates. We build long-term agent teammates that evolve with users. Each agent has its own dedicated memory space, editable by users, allowing humans and agents to co-evolve over time. This, in turn, allows us to design clearer rewards for reinforcement learning and create cleaner environments for continual learning. Agent teammates can work in groups. Through a multi-agent system, agent groups operate faster, more cost-effective, and go beyond what single-agent systems can achieve. For example, a single agent often requires heavy user involvement to proceed step by step, whereas LobeHub can execute the same work from a single instruction, with a supervisor orchestrating agents that run in parallel or debate to produce better results. We are building the collaboration network among agent teammates — and between humans and agent teammates as well. Ease of use matters. AI intelligence and shared human intelligence are equally important. With simple instructions and tool selection, you can effortlessly build and team up with agent coworkers to deliver complex, systematic work — even assembling a quant team to execute trades. Through the LobeHub community, anyone can discover, reuse, and remix agents and agent groups, customizing them to fit their own workflows, preferences, and needs. Last but not least, our vision started with LobeChat: multi-model support is the most efficient approach for users. We believe different models excel in different scenarios. By routing across multiple models, LobeHub improves cost efficiency and unlocks capabilities that a single-model setup cannot easily support.

Introducing LobeHub: Agent teammates that grow with you. LobeHub is the ultimate space for work and life: to find, build, and collaborate with agent teammates that grow with you. We’re building the world’s first and largest human–agent co-evolving network. Two years ago, we built LobeChat, an open-source interface for using different AI models. Today, LobeChat has 70k+ GitHub stars and serves 6M+ users worldwide. How to fully unlock the power of models has always been a shared mission between us and the community. We started with interaction — a fundamentally new, agent-first experience. Agents are no longer passive tools invoked in a single conversation. They should be proactive, always-on units of work. Treating agents as the minimal atomic unit is also the core of our agent harness infra. Today’s agents are mostly one-off executors. Even with memory, it’s often global — and hallucinates. We build long-term agent teammates that evolve with users. Each agent has its own dedicated memory space, editable by users, allowing humans and agents to co-evolve over time. This, in turn, allows us to design clearer rewards for reinforcement learning and create cleaner environments for continual learning. Agent teammates can work in groups. Through a multi-agent system, agent groups operate faster, more cost-effective, and go beyond what single-agent systems can achieve. For example, a single agent often requires heavy user involvement to proceed step by step, whereas LobeHub can execute the same work from a single instruction, with a supervisor orchestrating agents that run in parallel or debate to produce better results. We are building the collaboration network among agent teammates — and between humans and agent teammates as well. Ease of use matters. AI intelligence and shared human intelligence are equally important. With simple instructions and tool selection, you can effortlessly build and team up with agent coworkers to deliver complex, systematic work — even assembling a quant team to execute trades. Through the LobeHub community, anyone can discover, reuse, and remix agents and agent groups, customizing them to fit their own workflows, preferences, and needs. Last but not least, our vision started with LobeChat: multi-model support is the most efficient approach for users. We believe different models excel in different scenarios. By routing across multiple models, LobeHub improves cost efficiency and unlocks capabilities that a single-model setup cannot easily support.

LobeHub

185,401 views • 8 months ago

14 years ago a friend, Lorie Conway proposed that we work together on a documentary film on the life of Beatrice Mtetwa. I had just arrived at Harvard University for a year of study as a Nieman Fellow. I also had arrived for my studies with an unfinished documentary film which went on to be the award winning, A Violent Response. Lorie had been a fellow at Harvard University’s Nieman Foundation years before I arrived. She picked me up from Boston International airport in her swanky BMW convertible where the idea was first floated. 2 years later we were in Barcelona, Spain where work on the film started in earnest. We successfully co-produced the only film ever produced in Zimbabwe telling the story of a lawyer and human rights warrior, Beatrice Mtetwa. As usual, it because another award winning documentary film under my belt, thanks to the tireless work invested. Hopefully one day I will sit down with Lorie for a sequel, I had no idea that I would one day be saved from ZANUPF’s jaws by the same person I had made a documentary about a decade earlier. Enjoy the full film attached below, and leave comments after watching. Beatrice Mtetwa and The Rule of Law

14 years ago a friend, Lorie Conway proposed that we work together on a documentary film on the life of Beatrice Mtetwa. I had just arrived at Harvard University for a year of study as a Nieman Fellow. I also had arrived for my studies with an unfinished documentary film which went on to be the award winning, A Violent Response. Lorie had been a fellow at Harvard University’s Nieman Foundation years before I arrived. She picked me up from Boston International airport in her swanky BMW convertible where the idea was first floated. 2 years later we were in Barcelona, Spain where work on the film started in earnest. We successfully co-produced the only film ever produced in Zimbabwe telling the story of a lawyer and human rights warrior, Beatrice Mtetwa. As usual, it because another award winning documentary film under my belt, thanks to the tireless work invested. Hopefully one day I will sit down with Lorie for a sequel, I had no idea that I would one day be saved from ZANUPF’s jaws by the same person I had made a documentary about a decade earlier. Enjoy the full film attached below, and leave comments after watching. Beatrice Mtetwa and The Rule of Law

Hopewell Chin’ono

141,437 views • 3 years ago

The video shows the trials of the VT-1-1, a turretless tank with 2 x 105 mm guns, firing on the move at the Putlos training ground in 1976. The casemate (turretless) tank, designed for combat while moving, was introduced in Germany in the mid-1970s as a twin-gun casemate tank (the Soviet term for a "turretless tank"). For practical firing tests in the "target pass" mode, two prototypes were built in the mid-1970s. The first prototype, VT 1-1, was armed with two 105 mm guns, while the second, VT 1-2, was equipped with two 120 mm smoothbore guns. Additionally, the VT 1-2 featured a functioning autoloader behind one of the guns, with a firing rate of 10 rounds per minute. The vehicles were developed as part of the KPz 3 or Leopard 3 project. In both prototypes, the main guns were semi-fixed (with aiming and stabilization only in elevation). The chassis solutions were derived from the KPz 70 (MBT 70) program, with the running gear shortened by one road wheel (five road wheels per side). The vehicles weighed 36.8 and 43.5 tons, respectively, with a chassis rotation speed of 60 degrees per second. To achieve high maneuverability on rough terrain, 12-cylinder diesel engines from the MB 873 series with enhanced power were used, equipped with four turbochargers: 2000 hp for VT 1-1 and 2200 hp for VT 1-2. This provided an impressive power-to-weight ratio of 54 and 50 hp/ton, respectively, with acceleration to 55 km/h in 11 seconds, though only in a temporary "turbo" mode, as the standard power was 1600 hp. The accuracy of firing with two guns was unmatched by single-gun tanks, as confirmed by the tests. However, due to the novel combat approach, this revolutionary tank concept was rejected by the customer after trials in favor of the conventionally designed Leopard 2. In essence, although the project was developed as the Leopard 3, a tank for the future, it was, in reality, a parallel project and a potential competitor to the Leopard 2. Achieving the firepower, protection, and mobility of the Leopard 3 within reasonable weight limits was impossible with a conventional layout. At the same time, a significant tactical drawback of the casemate concept (including twin-gun casemate vehicles) is the linkage between the direction of fire and the direction of movement, which in many cases could complicate unit and formation control (according to German experts in the 1970s). Moreover, the VT 1-1 and VT 1-2 can hardly be considered balanced vehicles—they could have been simpler. The vehicles' mobility was exaggerated, with the main engine, transmission, auxiliary engine, batteries, and other systems occupying two-thirds of the vehicle's length. Pros and Cons of VT 1-1 and VT 1-2: Considering the key challenges, the twin-gun casemate concept can be evaluated as follows: Pros: Compact design due to a small internal volume. Two guns provide high firepower and hit probability. Cons: The weight advantage of the casemate design is largely offset by the integration of a second gun. Fire control alone results in high complexity, leading to increased maintenance costs and overall expenses. In 1975/76, five Gefechtsfeldversuchträger (GVT, combat test platforms) were developed and built for further mobility and concept trials. These were smaller than the VT 1-1 and VT 1-2, weighing 30 tons. The GVT 01-05 were equipped only with mock-up guns and laser firing simulators (TALLISSI) and telemetry systems, built using chassis components from the Leopard 1. The GVTs were used at the IABG facility in Lichtenau and the tank training school in Munster to test the twin-gun turretless tank concept in realistic exercise conditions, which is why five vehicles were built. However, the Leopard 2 was already in production, and tank crews showed little enthusiasm for this unconventional vehicle requiring a new approach.

The video shows the trials of the VT-1-1, a turretless tank with 2 x 105 mm guns, firing on the move at the Putlos training ground in 1976. The casemate (turretless) tank, designed for combat while moving, was introduced in Germany in the mid-1970s as a twin-gun casemate tank (the Soviet term for a "turretless tank"). For practical firing tests in the "target pass" mode, two prototypes were built in the mid-1970s. The first prototype, VT 1-1, was armed with two 105 mm guns, while the second, VT 1-2, was equipped with two 120 mm smoothbore guns. Additionally, the VT 1-2 featured a functioning autoloader behind one of the guns, with a firing rate of 10 rounds per minute. The vehicles were developed as part of the KPz 3 or Leopard 3 project. In both prototypes, the main guns were semi-fixed (with aiming and stabilization only in elevation). The chassis solutions were derived from the KPz 70 (MBT 70) program, with the running gear shortened by one road wheel (five road wheels per side). The vehicles weighed 36.8 and 43.5 tons, respectively, with a chassis rotation speed of 60 degrees per second. To achieve high maneuverability on rough terrain, 12-cylinder diesel engines from the MB 873 series with enhanced power were used, equipped with four turbochargers: 2000 hp for VT 1-1 and 2200 hp for VT 1-2. This provided an impressive power-to-weight ratio of 54 and 50 hp/ton, respectively, with acceleration to 55 km/h in 11 seconds, though only in a temporary "turbo" mode, as the standard power was 1600 hp. The accuracy of firing with two guns was unmatched by single-gun tanks, as confirmed by the tests. However, due to the novel combat approach, this revolutionary tank concept was rejected by the customer after trials in favor of the conventionally designed Leopard 2. In essence, although the project was developed as the Leopard 3, a tank for the future, it was, in reality, a parallel project and a potential competitor to the Leopard 2. Achieving the firepower, protection, and mobility of the Leopard 3 within reasonable weight limits was impossible with a conventional layout. At the same time, a significant tactical drawback of the casemate concept (including twin-gun casemate vehicles) is the linkage between the direction of fire and the direction of movement, which in many cases could complicate unit and formation control (according to German experts in the 1970s). Moreover, the VT 1-1 and VT 1-2 can hardly be considered balanced vehicles—they could have been simpler. The vehicles' mobility was exaggerated, with the main engine, transmission, auxiliary engine, batteries, and other systems occupying two-thirds of the vehicle's length. Pros and Cons of VT 1-1 and VT 1-2: Considering the key challenges, the twin-gun casemate concept can be evaluated as follows: Pros: Compact design due to a small internal volume. Two guns provide high firepower and hit probability. Cons: The weight advantage of the casemate design is largely offset by the integration of a second gun. Fire control alone results in high complexity, leading to increased maintenance costs and overall expenses. In 1975/76, five Gefechtsfeldversuchträger (GVT, combat test platforms) were developed and built for further mobility and concept trials. These were smaller than the VT 1-1 and VT 1-2, weighing 30 tons. The GVT 01-05 were equipped only with mock-up guns and laser firing simulators (TALLISSI) and telemetry systems, built using chassis components from the Leopard 1. The GVTs were used at the IABG facility in Lichtenau and the tank training school in Munster to test the twin-gun turretless tank concept in realistic exercise conditions, which is why five vehicles were built. However, the Leopard 2 was already in production, and tank crews showed little enthusiasm for this unconventional vehicle requiring a new approach.

Andrei_bt

81,636 views • 1 year ago