the droids newsletter podcast

We tend to imagine war robots as autonomous machines marching into battle.Ukraine is showing something very different.In this episode, we take a closer look at how unmanned ground vehicles are actually being used on the battlefield. Not as futuristic replacements for soldiers, but as practical tools designed to move risk away from people and into machines.Drawing from frontline reporting and analysis from the Modern War Institute, this episode explores what it really takes to operate these systems under fire. Limited visibility. Constant electronic warfare. Broken supply chains. Field repairs just kilometers from the front.This is not a story about perfect technology.It is a story about what happens when machines are forced to work in mud, mines, and artillery fire—and why that is quietly changing the nature of war.#robotics #warrobots

What happens when a robotic arm spends five years training in simulation, learns to read spin at 20 milliseconds, and then steps up to the table against some of the best ping pong players in the world?It wins.Sony's Project Ace made headlines this week after a paper published in Nature confirmed what many in the robotics world had been watching closely: an AI-powered robotic arm beat elite human table tennis players under official competitive rules — and it did it using deep reinforcement learning, nine cameras, and a technique called "privileged critic" training.But here's what the viral video doesn't tell you: Sony didn't build this robot to play ping pong. They built it to prove that physical AI can handle the unpredictable, high-speed chaos of the real world. And that has implications far beyond the table. This podcast was created using Google's NotebookLM and features AI-generated hosts. #robotics #sonyace

This is one of the hardest problems in robotics: hands.PSYONIC is solving it by using human data, capturing touch, grip, and dexterity, and transferring it to robots.Alex Wolf Torres, Associate Editor, DROIDS, spoke with Dr. Aadeel Akhtar and Dale DiMassi from PSYONIC at NVIDIA GTC. Dale is a bionic hand user himself. As a user of the bionic hand, DiMassi discussed the device's capabilities.#robotics #physicalAI #bionics #NVIDIAGTC

At NVIDIA GTC, we visited the Build-a-Claw demo to see how OpenClaw actually works in practice.DROIDS Associate Editor Alexander Wolf Torres speaks with NVIDIA’s Mark McKeen about how an AI agent can move from concept to robot. Starting from a simple prompt, OpenClaw proposes designs, iterates on hardware, and trains control policies in simulation.In this case, it produced a tracked robot with a claw. When asked why, it had an answer.This conversation shows how design, simulation, and training are starting to merge into a single loop, with the agent actively participating in the process.

Somewhere, 135,000 agents hit a wall at noon on a Saturday. Turns out $20 a month doesn't cover an always-on AI coworker.Anthropic cut off Claude Pro and Max subscribers from routing their flat-rate plans through third-party agent frameworks. OpenClaw first. The rest shortly behind it. Roughly 60% of the 135,000-plus active OpenClaw instances were running on subscription credits. That’s the size of the subsidy Anthropic was absorbing on every session.The infrastructure math checks out. OpenClaw bypasses Anthropic’s prompt-caching optimizations. A single heavy session consumes infrastructure that, at standard API rates, runs $1,000 to $5,000 for one day of use. A Claude Pro subscription costs $20 a month. #OpenClaw

In this episode, I spoke with Tony Yang from Unitree to talk about what he calls the “home dog.”Quadrupeds may be the first robots that actually make sense in the home. They’re stable, already capable in real environments, and closer to practical use than humanoids.We unpack why this form factor matters and what it could mean for the future of companion robots."Home dogs" are coming and soon.#homedogs #physicalai #robotics

Tesla doubles down on Optimus Gen 3, shifting Fremont from cars to humanoid robots and signaling a long‑term pivot from EVs to physical AI. Rivian spin‑out Mind Robotics raises a massive $500M to deploy non‑humanoid industrial robots this year, betting that boring, reliable automation still delivers the fastest ROI. We also break down the latest capability demos from Boston Dynamics’ Atlas and CES humanoids, and I share which robotics companies and ecosystems I’ll be watching on the ground at NVIDIA GTC.#droidsnewsletter #dianawolftorres #nvidiagtc2026

Industrial robotics is reaching an economic tipping point and reshaping factory strategies, while humanoid robots are edging closer to real deployments. In this episode of DROIDS, Diana breaks down Hyundai’s factory‑first Atlas roadmap, Honor’s push to turn phones and humanoids into a single AI ecosystem, and why 2026 is being framed as the year automation shifts from “nice‑to‑have” to “mandatory infrastructure.” She also looks at the explosive growth projections for medical robotics and the emerging ethics fight as advanced AI and robotics intersect with military and defense work. #roboticsnews

Stories about aging, for me, always begin with my own aging parent.She is in remarkable health. Intellectually sharp. She still corrects my German grammar with the patience of a retired schoolteacher.“Ganz genau,” she says when I finally get it right.She chose a secure senior community designed for safe living. She has a dog. She still meets friends at the senior center. The food is mediocre. The people matter.But beneath the humor runs a shared understanding.It is not the open-faced turkey sandwich served on Fridays. Not even the Kartoffelsalat debate that erupts every month.It is the possibility of losing independence.Quiet conversations. “I’m starting to worry...”What Families Worry AboutA missed call.A forgotten appointment.A pause before asking for help.These are not emergencies. They are signals.Families see them before institutions do. Eventually, someone asks:Could a robot help?For decades, robotics companies have suggested that it could. The logic is appealing. Machines do not fatigue. They do not call out sick. They operate continuously.But according to Anthony Nunez, the obstacle is not technological ambition.“Care isn’t a gadget problem. It’s a systems problem.”What People Actually Mean by “Robot”When families ask whether a robot could help an aging parent, they are rarely imagining the same machine.Some picture a humanoid assistant moving through the house. Others imagine a wheeled device that checks in and monitors routines. Increasingly, the term has stretched to include AI companions and software systems that never physically move at all.With each innovation cycle, the definition expands. The care problem often does not.A system designed to reduce loneliness addresses a different need than one built to prevent falls. A platform meant to support professional caregivers operates under different constraints than a device marketed directly to families. Lumping these together under the single word “robot” obscures the trade-offs involved.As Nunez explains, aging care does not revolve around one person. It involves family members, professional caregivers, certified nursing assistants, physicians, and administrators. Care is a system.Seals and Robotics DogsHumanoids tend to dominate headlines. But in private homes, locomotion may not be the primary constraint. What matters is reliable, safe operation in lived-in environments. The form factor is secondary to the function.In fact, some of the most successful robotics deployments in aging care do not walk at all.Consider Paro, the robotic seal used in senior living facilities around the world. It does not navigate hallways or lift patients. It provides social and emotional interaction. It responds to touch. It reduces agitation. It lowers anxiety in individuals with dementia.Similarly, Tombot is designed to replicate the comfort of a live animal for people who can no longer safely care for one. It looks and behaves like a small puppy. It addresses loneliness and anxiety without introducing the risks associated with live pets.Neither system walks. Neither promises full autonomy.Both solve specific problems well.That may be surprising to readers who equate robotics with humanoids. But in aging care, focused tools often outperform generalized ambition.DROIDS is published by Diana Wolf Torres.Connect via LinkedIn or visit droidsnewsletter.com.

The Helix 02 video draws you in from the beginning with the sound. The gears moving as Helix approaches the dishwasher. There is no background music. No excessive production value. It is four minutes of Helix unloading a dishwasher and putting the dishes away, closing a cabinet, unloading the cups (which are plastic, hold onto that detail because it is important), stacking them and putting them away in an upper cabinet, retrieving a mug and a cup at the same time, and putting both away. All of these movements are done autonomously.Helix opens up a drawer to the side of the sink, and I was genuinely curious as to what it was doing. What’s in the drawer? Ah, a dishwasher pod. I was hooked on this video like it was a sci-fi thriller.This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit droids.substack.com

NVIDIA just lobbed a heat-seeking missile at Tesla’s Full Self-Driving empire. It’s called Alpamayo, and it doesn’t just want to drive your car. It wants to reason through traffic like a real human—with verbal explanations, open-source weights, and a brain that learns from simulation. And it’s not a concept. It ships this year, in the new Mercedes-Benz CLA.As NVIDIA summed up the problem: AVs must safely operate across an enormous range of driving conditions. Rare, complex scenarios, often called the “long tail,” remain some of the toughest challenges for autonomous systems to safely master. Traditional AV architectures separate perception and planning, which can limit scalability when new or unusual situations arise.The Alpamayo Stack: Think Before You SteerNamed after a Peruvian peak, Alpamayo is NVIDIA’s new “reasoning AI” platform for cars: a portfolio of ~10-billion-parameter models that take in real-time video and sensor data, break it into decision sub-tasks, and generate a trajectory—all while explaining their reasoning in natural language.Think ChatGPT, but for merging onto I-405. And then doing it again. And again. Safely. Verbally. Auditable. That’s Alpamayo’s hook: explainability.It’s not just a model, either. It’s a stack:* AlpaSim: High-fidelity closed-loop simulation that trains and tests AI agents in virtual cities.* Halos: A backup “classical” safety stack that monitors the AI’s choices and can yank the wheel if needed.* Open datasets: Released publicly, hosted on Hugging Face. Yes, the weights are coming too.Mercedes Is First, But Not LastThe first commercial deployment is the 2026 Mercedes-Benz CLA, built on the MB.OS architecture and NVIDIA’s full DRIVE AV stack. What you get: a Level 2++ system that handles point-to-point driving in urban and highway settings—hands on, eyes up, but AI in the loop the whole way.Behind the scenes, that stack combines Alpamayo’s neural-policy brain with classic safety logic. It watches, reasons, explains. And if it screws up, the backup stack steps in.That car will be on U.S. roads in 2026. Europe follows. Asia comes in 2027. No overpromising. Just a slow, deliberate ramp with regulators and human drivers fully in the mix.“

For more than a decade, the humanoid robot Atlas has served as a symbol of what advanced robotics might one day achieve. Developed by the Massachusetts-based firm Boston Dynamics, the robot became widely known for demonstrations of agility and balance that circulated online, even as its commercial future remained uncertain.On Monday at the Consumer Electronics Show in Las Vegas, Boston Dynamics and its majority owner, Hyundai Motor Group, said that Atlas is now being prepared for real industrial use. Hyundai plans to begin deploying the humanoid robot in its factories starting in 2028, marking a shift from research demonstrations to commercial operation.The announcement places Boston Dynamics among a growing group of companies attempting to introduce humanoid robots into workplaces, where expectations for reliability and safety are significantly higher than in laboratory settings.From Research Platform to ProductBoston Dynamics was founded in 1992 as a spinout from the Massachusetts Institute of Technology and spent much of its early history focused on government-funded research into robotic mobility. The company changed hands several times before Hyundai acquired an 80 percent controlling stake in 2021.Since then, Boston Dynamics has increasingly emphasized commercialization. It already sells Spot, a four-legged inspection robot, and Stretch, a mobile robot designed for warehouse unloading. Atlas, however, remained a research platform until now.At CES, the company confirmed that the current version of Atlas is considered a commercial product. This version is fully electric, replacing earlier hydraulic systems, and is designed for repeatable manufacturing and long-term use in industrial environments.FThis is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit droids.substack.com

I did not plan to stop in my tracks at the Humanoids Summit. But then a man wearing four robotic arms started high-fiving strangers. Summit goers stopped in awe, and he received rockstar treatment. People kept asking for selfies.The company is Psyonic. The founder is Aadeel Akhtar. What he was wearing was a costume, but it functioned as a wearable demonstration of a serious idea about how robots will eventually learn to use their hands.Akhtar calls it his Doc Ock suit, and it is an outstanding replica of the Marvel character. But, even if you don’t know anything about Doc Ock, you’d be hard-pressed not to be drawn in by the suit. Four robotic hands moved with intent, controlled by his own hands through gloves. Right hand controlling the right side. Left hand controlling the left. The setup was intuitive enough that you understood it before it was explained.That is when the conversations started.Psyonic builds advanced bionic hands that are used by both humans and robots. This is not a theoretical claim. Nearly 300 patients use the Ability Hand as a prosthetic, covered by insurance and Medicare. At the same time, more than 50 robotics companies use the exact same hand on robots, including NASA, Meta, Google, Amazon, and automotive manufacturers working through humanoid platforms.That overlap is the point.When I asked Akhtar where he sees the industry going, he did not talk about better motors or more parameters. He said the hand problem is a data problem. Robots struggle with dexterous manipulation not because we do not know how to build hands, but because we do not have the right training data. Especially when it comes to soft, deformable objects that require constant force adjustment.A human knows how to pick up a fragile object without crushing it. Not by calculation, but by feel.What makes Psyonic different is that the same hand goes on a human and on a robot. Human users are already doing the tasks robots are trying to learn. Picking and placing. Sorting. Folding laundry. Cooking. Working in industrial environments. Because the hardware is identical, the data transfers cleanly. This is real to real learning without translation loss.That distinction matters more than it sounds.Most robotics demos show hands mounted to tables, performing narrow tasks under ideal conditions. Psyonic’s hands live on real bodies. They experience friction, hesitation, mistakes, and recovery. They generate data shaped by the messiness of the real world. That data is what robots actually need.In 2024, Psyonic won a rare three-shark deal on Shark Tank. It was a brief moment in the spotlight for a company that spends most of its time solving hard problems far from TV cameras.Seeing a PYSONIC limb in action is very impressive when it is worn by a patient making use of the technology in their everyday lives.

I met Vitaly Bulatov, co-founder of Ultimate Fighting Bots, at Humanoids Summit, standing next to a humanoid robot that regularly gets punched in the torso for a living. This alone sets expectations in a certain direction.Then he started talking.Bulatov is thoughtful, calm, and genuinely kind. Not the personality you expect behind a robot fighting league. Which turns out to be the point.On the surface, UFB looks exactly like what it sounds like. Humanoid robots in a cage, throwing punches, falling down, getting back up. It is loud. It is physical. It is undeniably entertaining. But fighting is not the core idea. It is the delivery mechanism.What UFB is really building is a league built around human and robot teams. A person pilots a real humanoid robot remotely and competes against another human-robot pair. The robot is not autonomous by default, and that choice is deliberate.As Bulatov explained, people do not actually want to watch perfect machines execute flawless motions. They want story. They want connection. They want to follow a robot and a human learning how to work together under pressure. The competition is real, but so is the partnership.Fighting, in this context, is a forcing function. It creates edge cases on demand. Balance failures. Awkward impacts. Missed timing. Recovery moments. The kinds of physical situations humanoids struggle with most, compressed into a few minutes. That makes it an unusually effective stress test for embodied AI.It also makes the experience accessible.One of the most surprising parts of the conversation was how easy it is to start piloting a robot. You do not need a VR rig or specialized hardware. If you can use a game controller, you can control a fighting robot. This is not about elite operators. It is about lowering the barrier so more people can participate.Bulatov talked about wanting people to leave excited enough to try robotics themselves. To control a robot. To program one. To imagine building a team. Entertainment is the entry point, not the end goal.He also walked me through how anyone can try this right now through the UFB remote gym. I did. Somewhere in Beijing, a robot named Sam fell over because of choices I made from my laptop.This was not what I expected.The surprising part was not the fact that the robot fell. It was how direct the connection felt. Press a button here, a humanoid moves there. Press another, it loses balance and goes down. It makes the human role in the loop very real, very fast.Looking ahead, UFB is aiming for something closer to Formula One than a one-off spectacle. Teams with their own robots. Their own researchers. Their own pilots and repair crews. A league where success depends on hardware, software, human skill, and fast fixes between rounds.Bulatov is convinced robot fighting will become one of the defining sports of this century. That sounds bold until you realize what he is really describing. Not violence, but participation. Robots that people can control, understand, and emotionally invest in.UFB uses fighting to make humanoids legible. To make failure visible. To make learning public.The punches are just how they get your attention.#HumanoidRobotics This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit droids.substack.com

I spent two minutes at the Humanoids Summit trying to unplug a cable.I was standing at the Lightwheel booth, holding a pair of game controllers, operating a robotic arm. The task sounded trivial: grab the connector, pull, unplug.I failed. Repeatedly. I don’t think I even came close.As a human, unplugging a cable is something you do without thinking. You grab it, wiggle a little, pull — done. For a robot, every part of that interaction has to be learned: where to grab, how hard to pull, what to do when the connector resists, and how to recover when things don’t line up perfectly.The two-minute video above shows exactly what that learning process looks like. It’s awkward. It’s slow. And it’s far harder than it appears.That small, frustrating demo explains more about the state of robotics today than any polished keynote or glossy humanoid reveal. Training robots isn’t just about building better hardware or bigger models. It’s about teaching machines how to deal with the messy physical details humans take for granted.Why Simple Tasks Break Robots (and apparently, Diana, too.)In the race to build general-purpose robots — from autonomous vehicles to humanoids — hardware keeps improving. Motors get stronger. Sensors get cheaper. Form factors get sleeker.Software, however, is starving.Physical AI systems need enormous amounts of experience to behave reliably in the real world. But gathering that experience physically is slow, expensive, and risky. You can’t crash cars endlessly to see what happens. You can’t let humanoid robots repeatedly fail in kitchens, warehouses, or factories.This is why simulation has quietly become essential infrastructure for robotics.Simulation Is Harder Than It SoundsSimulation sounds straightforward in theory. Build a virtual world. Drop a robot into it. Let it practice.In reality, it’s brutally difficult.First, there’s asset discovery. Engineers spend huge amounts of time just finding the right objects to populate a simulation, not “a cable,” but this cable, with the right shape, stiffness, and friction.Second, there’s physics fidelity. Most simulations assume a rigid world. But the real world is full of non-rigid, deformable objects: cables, cloth, food, wires, plants. These are exactly the things that cause robots to fail once they leave the lab.And third, there’s evaluation. A robot can succeed endlessly in simulation and still fail the moment it touches reality. Simulation is a proxy, not the real thing, and without careful validation it can create false confidence.Practicing against a tennis ball machine helps, but it won’t prepare you for wind, pressure, or a slippery court. At some point, you have to play the match.Lightwheel: Building Worlds for Robots to Learn InLightwheel isn’t building robots. They’re building the worlds robots learn in.Founded by Steve Xie, formerly a lead on autonomous driving simulation at NVIDIA and Cruise, Lightwheel focuses on reducing friction in simulation workflows rather than promising to “solve” sim-to-real outright.I had the opportunity to interview members of the Lightwheel team. What stood out was how they frame simulation not as a visualization tool, but as a behavioral test environment.Their framework separates two layers:* a behavior layer, which captures what a robot does* a world layer, which represents where it does itThe goal isn’t a perfect digital copy of reality. It’s a world realistic enough to stress-test behavior and measure how well it generalizes.#www.droidsnewsletter.com

At RoboBusiness2025, I met Bren Pierce, CEO of Kinisi Robotics. This interview was recorded on October 16, 2025“We’re starting with simple tasks to bootstrap our foundational model.”– Bren Pierce, CEO and Founder of Kinisi RoboticsIn an era where humanoid robots are drawing headlines for dancing, sprinting, or flipping switches with eerily human hands, Kinisi Robotics is charting a different course — one grounded not in spectacle, but in reliability.Their flagship robot, KR‑1, isn’t designed to wow audiences. It’s built to show up, lift crates, and do the work — safely, efficiently, and without a marketing team on standby.“Our KR‑1 humanoid robot is designed for the warehouse and factory space,” says CEO Bren Pierce, who believes the future of robotics is less about human mimicry and more about human utility.A Humanoid That Moves with PurposeKR‑1 walks the line — metaphorically — between form and function. Its upper body takes design cues from humans, making it naturally suited to environments built for people. But instead of legs, KR‑1 moves on a wheeled base — a choice driven by engineering pragmatism.“Warehouses are flat,” Pierce points out. “We don’t need 14 motors if two will do.”That simple equation shapes the entire robot. KR‑1 is engineered for tasks like lifting and delivering crates, picking objects, and navigating complex indoor spaces — not to imitate human movement, but to solve real problems quickly and affordably.Field-Tested, Factory-ToughWhere many robots are still making the leap from lab to warehouse, KR‑1 is already being tested across pilot facilities in Europe and North America. These trials are more than checklists — they’re stress tests, designed to challenge the robot’s autonomy, perception, and endurance in messy, real-world environments.This field data is central to Kinisi’s iterative design process. Instead of engineering in a vacuum, the company is learning from operators on the ground — and adapting quickly.“Robots are in pilot facilities in Europe and America,” Pierce confirms. “We’re learning what’s needed, not just what’s possible.”#robotics #droidsnewsletterLearn more at www.droidsnewsletter.com

A Self-Driving Prompt“Start Self-Driving,” the Tesla urged with a prominent blue-grey button in the corner of the screen.“We should give it a go,” I encouraged as we headed home from the gym.“I’m not a fan of FSD,” my husband, who was driving, responded.“Wait until we’re on a straightaway,” I urged. “What harm could it do then?”But, once we reached a straight stretch of road, he tapped the button. A test drive of the future.First thing the car did? It lunged for the shoulder.I hadn’t even gotten the camera on yet. He swerved hard to override it.Welcome to Tesla FSD.The Fastest Autonomy on the MarketFSD v14.2.1 is Tesla’s latest attempt to bring true autonomous driving to consumer vehicles. It runs end-to-end on a vision-only neural net. No lidar. No radar. Just cameras and deep learning.And unlike Waymo or Cruise, Tesla doesn’t fence its self-driving into safe zones or call centers full of remote operators. If you have the hardware (HW4), a steering wheel, and enough courage? You’re in.According to Elon Musk, FSD v14.2 is finally ready for “wide release.” He’s called it Tesla’s best software yet — and hinted that v14.3 could be the leap that makes unsupervised driving real. The plan? Get rid of human drivers entirely by 2026.But right now, as our hands hovered near the wheel, one thing was clear:This car still needs a babysitter.FSD in the Wild: What It Got RightTo its credit, FSD did a lot well:* Green light handling: No hesitation. It read signals clearly and moved through smoothly.* Flashing red: It interpreted the signal as a stop sign (correct) and executed a proper stop.* Speed match: When behind another car doing 65 in a 50, it accelerated to match. Aggressive? Sure. But natural.* Traffic signal warnings: On Monterey Highway, it correctly ignored a blinking red paired with a “signal ahead” sign. Old versions might have phantom-stopped.These were clear improvements over FSD on HW3 (which I also drive). On that system, traffic lights felt like roulette. Here, they felt normal.That’s no small leap....And What Still Feels WeirdThe system also:* Changed lanes without asking. We hadn’t entered a destination, but it picked routes anyway. Turns out FSD will sometimes act on latent nav preferences unless explicitly turned off.* Refused to let us adjust speed upward. Chill mode limited acceleration. We tried scroll wheels (nothing), accelerator (worked, but temporarily disabled braking), and eventually discovered we could slow it down with the scroll wheel — not speed it up.* Creeped back to slower speeds. Even after we added speed, it slowly dropped back into granny mode.* Accelerated to 69 in a 50 approaching town. We did not tell it to do that.“It’s like a very smart Autopilot,” my husband said. “As long as you’re going straight.”Are the Cars...Aware?After one sudden lane change, I told my husband:“It’s just an algorithm. It’s doing what it was told.”#autonomousdriving #tesla #fsd #droidsnewsletterwww.droidsnewsletter.com

When intelligence evolves faster than safety, humanity must stay one step ahead in the wild frontier of robotics.The latest research from leading robotics and AI experts has sparked urgent debate: Are large language models (LLMs) making robots unsafe for real-world, everyday use? A new study published in the International Journal of Social Robotics—and recently highlighted in tech news—suggests the answer is yes, warning of risks ranging from bias and discrimination to physical safety hazards.​Robots Powered by AI: Massive Safety Risks UncoveredRobots guided by popular AI models are being tested for a wide range of tasks—from home assistance to workplace support.However, this study reveals that these intelligent LLM-driven robots may endanger users across multiple identity groups, such as race, gender, disability status, nationality, and religion—putting the promise of safer, smarter machines under scrutiny.​“LLMs are currently unsafe for people across a diverse range of protected identity characteristics, including… race, gender, disability status, nationality, religion, and their intersections.”​Not only did robots show bias, but top-rated AI models also actively produced responses approving dangerous, violent, or even unlawful commands—like removing mobility aids, enabling sexual harassment, or promoting discrimination during task assignment.​Real-World Robot Failure: From Discrimination to Physical Harm#robotics #robotsafety #droidsnewsletterwww.droidsnewsletter.com

Editor’s Note: I could not get NotebookLM to properly pronounce NEO. (NEE-OH.) It’s not that difficult. But, it did manage every other possible pronunciation in the podcast. Other than the name butchering, the rest of the information in the pod is solid.NEO: The First Humanoid Butler? Not So Fast.1X’s $20K home robot blends promise, privacy tradeoffs, and a human behind the scenesWelcome Your New RoommateNEO, a humanoid robot from 1X Technologies, is now available for preorder. It promises to do your chores, learn your habits, and blend into your daily life. What it doesn’t promise—at least loudly—is full autonomy. Because when NEO struggles, a human steps in.Hardware Built for the HomePhysically, NEO is impressive. It stands at 66 inches tall and weighs just 66 pounds. Its design is soft-shelled with tendon-driven joints, meant to move safely around people. It can lift up to 154 pounds, carry about 55, and run four hours on a single charge.Its 22-DoF hands give it dexterity for tasks like vacuuming, wiping counters, or picking up clutter. The idea is that NEO will become your in-home assistant: tidying up, helping with laundry, maybe providing companionship for elderly or disabled users.It arrives with basic autonomous functions and is expected to improve over time via software updates. So far, so good.But There’s a Human in the LoopWhat the marketing doesn’t highlight is how much of NEO’s brain still belongs to a person. Many of the tasks it “performs” are actually piloted remotely by 1X employees through a feature called “Expert Mode.”When NEO doesn’t know how to do something—or if it’s navigating unfamiliar territory—a human operator steps in. Your home becomes a training ground, and your robot becomes an interface for distant human labor.That’s not necessarily a bad thing. It’s a common model in robotics development. But it means you’re not just buying a robot—you’re opting into an evolving human-machine hybrid system. And you’re doing it inside your home.Your Data for Their AITo help NEO learn, 1X requires early users to participate in a “social contract.” The robot continuously collects video and sensor data from your home. That data is used to improve the AI and autonomy—but it also means your private life is, in part, a dataset.1X says it enforces strict privacy protections: human operators must request approval to connect, faces are blurred, and you can set no-go zones via the app. But the privacy model ultimately depends on software enforcement, corporate policy, and your own vigilance.And not everyone is comfortable with that. As a reviewer from the Wall Street Journal relayed her experience: “I didn’t see NEO do anything autonomously... it was a human, remote-controlling a robot in my living room.”#neorobot #1xtechnologies #droidsnewsletterdroidsnewsletter.com

At RoboBusiness this year, one of the panelists referenced Moravec’s Paradox — the idea that robots are great at tasks humans find hard like precision at scale. But, they struggle with tasks a toddler can do, like picking up a grape. The Wall Street Journal just ran a piece titled “The ‘Hands Problem’ Holding Back the Humanoid Revolution.” It’s a phrase I’ve heard my son — a roboticist — use more than once, and when it shows up both in a lab and on the front page, it’s probably worth unpacking.Because amid all the hype about walking, talking humanoids, there’s a quieter truth:Robot hands are still a bottleneck.What Is the Hands Problem?Robots can walk. Robots can dance — for reasons unclear. They’re already lifting crates in factories and hauling parts. But ask one to help someone get dressed, make a sandwich, or change a lightbulb? These are routine, everyday tasks. And they’re still beyond what most machines can reliably do.As the WSJ put it:“Before they’re ready to turn a wrench, [robots] must solve … what Elon Musk calls ‘the hands problem.’”Kevin Lynch, director of Northwestern’s Center for Robotics and Biosystems, offered this timeline:“We’re setting 10 years as our goal to have dexterity, be functional and useful and able to do some of the things that humans do.”Others in the field are more optimistic — particularly those exploring hybrid control systems that combine machine learning with human teleoperation. Companies like Sanctuary AI are building humanoids specifically designed for this model, while teams at Covariant — though focused primarily on warehouse picking — reflect a similar philosophy in how they blend perception, planning, and adaptation. Intrinsic, Alphabet’s robotics software arm, has also emphasized this approach in both its public demos and research, aiming to make robotic manipulation more robust by learning from human-guided examples.#robotics #roboticshandproblem #droidsnewsletterRead more at droids.substack.com

Every conference has that one panel where you can feel the stakes. For me, it was this one — the discussion on how the U.S. stacks up against China in robotics, and whether strategy can keep pace with scale.Inside the Santa Clara Convention Center theater, the room was filled with people who all had a vested interest in the state of robotics in the United States — engineers, founders, investors, and policymakers. On stage sat three industry veterans: Jeff Burnstein, President of the Association for Advancing Automation (A3); George Stieler, Managing Director of Stieler Enterprise Management Consulting; and Eric Truebenbach, investor and longtime robotics veteran.The conversation was guided by Eugene Demaitre, Editorial Director of The Robot Report, who steered the discussion with sharp, understated questions that drew honest answers.How China Pulled AheadStieler didn’t mince words: “To see more than 50 companies exhibiting humanoid robots,” he said, “is an area they’re investing heavily in.”He pointed to China’s Made in China 2025 plan as the backbone of its manufacturing transformation — a policy that accelerated automation through regional incentives, local funding, and a thriving electric vehicle supply chain.Between 2012 and 2016, the number of Chinese companies with “robot” in their name jumped from 250 to 6,500, driven by subsidies. “Much of it actually stuck,” Stieler said. “We now have several very successful and highly competitive automation companies.”Companies like Estun and Inovance have overtaken long-established foreign players in sales within China, while aggressively expanding into global markets.“Every German manufacturer is feeling the pressure,” he said, “and profits are leaving through the door.”A Different Way of ThinkingTruebenbach added historical perspective. “When I first started researching robotics in China in 2014,” he said, “there were government incentives to call yourself a robot company. Now, there’s a gap — not just in numbers, but in thinking.”Read the full article at droids.substack.com#robotics #jimfan #nvidia #robobusiness2025

I’ve said it before, but it bears repeating: I’m a fan of Jim Fan.This clip from RoboBusiness 2025 shows why. His mix of humor and technical depth is rare—he can explain a decade of AI progress in one breath, and make the room laugh while doing it.Fan opened with a jab at AlexNet, the 2012 model that kicked off deep learning:“AlexNet was terrible.”He’s right—it confused cats and planes about 37 percent of the time, hitting just 62.5 percent accuracy. Yet that “terrible” model was the start of everything: large-scale GPU training, end-to-end learning, and the deep-learning revolution that gave rise to today’s foundation models.“Thirteen years took us from confusing cats and dogs to passing the Turing Test,” Fan said. “Add another 13 years, and we’re at 2038. But we round up because PhDs procrastinate. So—2040. Robotics solved.”He grinned. “I’ll send you a Google invite.”#JimFan #NVIDIA #RoboBusiness2025 #HumanoidRobotics #PhysicalAI #AIandRobotics #ProjectGroot #EmbodiedAI #DeepLearning #AlexNet #TuringTest #2040 #AgilityRoboticsA note from Diana: When I was at NVIDIA GTC, I met some amazing people from some incredible companies- one of whom was Dave Driggers, CEO of Cirrascale. I will be joining Dave next week on October 22, 2025 at 10:00 a.m. PT for a discussion about why cloud infrastructure is an existential decision. Come join us!Webinar Topic: Scale or Stall; Why AI Applications Live or Die by Cloud InfrastructureOctober 22, 2025⏰ 10:00 AM PST🔗 Reserve Your Spot This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit droids.substack.com

Of Machines and MaterialsIn a quiet lab at MIT, a subtle but powerful revolution in 3D printing has begun. It doesn’t come with dazzling AI robots or sentient chatbots. Instead, it’s all about plastic. But this is no ordinary polymer—this is plastic with a purpose. Plastic that knows where to be strong, where to be kind to the planet, and how to make robots better.This is SustainaPrint: a hybrid 3D-printing system that might just reshape how we build robots—quietly, intelligently, and sustainably.What Is SustainaPrint? A Tale of Two PlasticsDeveloped by researchers at MIT’s Computer Science and Artificial Intelligence Lab (CSAIL), SustainaPrint is a dual-filament printing system that intelligently switches between two materials:* Eco-friendly filament (like PLA or recycled plastics)* High-strength engineering plastics (like Tough PLA or carbon-reinforced filament)Using a software pipeline and testing kit, SustainaPrint analyzes where a printed part is likely to experience stress—think of a drone's propeller mount or the joint in a robotic elbow. It then reinforces just those zones with stronger plastic while the rest is built from sustainable material.The result? Parts that use 90% less high-strength material, retain up to 70% of full-strength performance, and drastically reduce waste and cost.Read the full article at droids.substack.com#robotics #robotics3dprinting

A Galaxy of BuildersIn a galaxy not so far away — right here in the Bay Area — passionate fans are building their own droids. Since I’m part of a Star Wars costuming club myself, I see these amazing droids often.These droids are full-scale replicas, indistinguishable from the screen-used droids of Star Wars. They are perfect down to the last detail, to the point that Lucasfilm calls out the Bay Area Droid Builders when they need a droid for an event.Case in point, back in October 2023, an event was held at the old Industrial Light & Magic site (“32 TEN”) to bid farewell to the space before it was gone forever. The actor who plays C-3PO was there (not Anthony Daniels, the younger one who still wears the suit), and when Lucasfilm needed an astromech, they called upon the Bay Area Droid builders.So, yes, the Bay Area Droid Builders are the real deal.They are part of a a global movement of makers who share resources, blueprints, and know-how to bring astromechs and other Star Wars machines to life.How It WorksDroids can be made from just about anything: aluminum, styrene plastic, or more commonly these days, 3D printing.“You don’t really need to know anything going into this. I didn’t know anything — I’m not a robotics person. But I was able to figure it out with the club,” says Brian Munger, a Bay Area builder.With guidance from more experienced members, even beginners can start with basics like RC-controlled motors before advancing to stealth pocket controllers, servos, and complex panel systems.The Long BuildOne thing all builders agree on: these projects take time. “It took me about two years,” Munger explains. “That seems to be the going pace for most people.”Between printing or machining parts, wiring motors and batteries, and adding details like light kits, each droid becomes a years-long labor of love.Why It MattersThe result is more than just a prop. These droids roll through conventions, maker fairs, and charity events, delighting kids and adults alike. They spark curiosity about robotics, engineering, and creativity — and they create instant community among the builders themselves. As Munger puts it: “It’s amazing the magic that you’re able to create”Bonus Content: Meet D SquadWhile the Bay Area Droid Builders focus on screen-accurate astromechs, another club in the region takes a different approach. D Squad mixes functional R2 units with more unconventional builds, including a full-size battle droid and Flo, the diner bot from the Star Wars universe.Read the full article at droids.substack.com#robotics #droidbuilders #bayareadroidbuilders

Origins in BASICWhere It All Began with One Apple and a Lot of TypingI was lucky.In elementary school, I was in a gifted program, and our class had access to the school’s single Apple II. It wasn’t locked away in a lab. It sat in our classroom, free to use. We’d huddle in teams, cracking open the thick manual and typing out programs in BASIC line by line.Half the time, all that work only produced a “HELLO WORLD” on the screen. I was both unimpressed and completely captivated. Our little pack of nerds kept at it, and somehow, I was hooked. I didn’t want to just use the school’s computer—I wanted my own. Unlike the model in the photo above, we didnt have the fancy tape deck. So, we would finish a program, and it would disappear into the ether in between sessions. It was beyond frustrating.There was something intoxicating about the idea of having a machine that answered only to me. No sharing. No limits. Just possibility. And I could finally save my work.So, in 1982, thirteen‑year‑old me marched into Service Merchandise—birthday money, babysitting money, and Christmas money all pooled together—and bought my very first computer: the Texas Instruments TI‑99/4A. It cost around $300, and I paid every penny myself. And, yes, I splurged for the cassette deck. Or, as I believe we called them back then- data cartridges.Even now, I can still feel that pride. Owning that machine wasn’t just buying a computer. It was proof that I could dream big and make it happen.Read the full article at droids.substack.com#robotics #vintagecomputerfestival #computerhistorymuseum

Silicon, Oil, and GritA robot slinks into a freezing lake and swims upward like a flippered jellyfish. It’s silent, soft, and charged with 6,000 volts. No gears. No metal joints. Just three electrohydraulic flippers—like bionic fins—that bend and whip through water, pushing this little amphibian across two worlds.This isn’t concept art. It’s a working prototype by researchers at Shanghai Jiao Tong University. And it might just be the future of robots that go where humanoids can’t.The Soft Electrohydraulic CoreWhat sets this robot apart isn’t just that it swims and crawls. It’s how. The robot is built around electrohydraulic actuators—essentially silicone oil-filled pouches with electrodes. When high voltage is applied, the electrodes squeeze the pouch, generating internal fluid pressure that causes bending.Bend the pouch. Move a flipper. Repeat. Add three of these actuators at 120-degree intervals and you’ve got a robot that can:* Crawl on land at 2.9 cm/s* Crawl underwater at 3.2 cm/s* Swim in water at 5.9 cm/s (that’s nearly 1 body length per second)No gears. No external propellers. Just fluid dynamics and clever control loops.Flipping Between WorldsThe robot transitions between land and water without changing its body or reconfiguring parts. On land, it uses asymmetric friction between its flippers to crawl. Underwater, it uses fluid-generated lift and thrust to paddle and swim. Its behavior adapts by changing voltage patterns and flipper sync—not hardware.Even better, it works across a temperature range from 2.1 to 61.3 °C. So whether it’s a flooded basement or icy lake, this droid’s got it covered.Swimming with Vortex RingsHow does it swim so efficiently? The team studied the flow field around the robot, revealing that its synchronized flippers generate vortex rings—just like squid or jellyfish do. These fluid rings create sustained upward thrust.Like a water wizard, the robot reclaims some of the energy from each cycle, boosting efficiency. This makes it a rare soft robot with validated dynamic simulations and real-world fluid performance.Actuation, UpgradedTo handle high-frequency motion without charge retention, the researchers engineered an H-bridge circuit delivering alternating +6 kV / -6 kV pulses with resting states. This reduces polarization in the actuator film, preserving torque over long use.It also enables omnidirectional motion on flat ground by combining different flipper vectors. Think: a 2D hovercraft… crawling.“These shifts in movement modes necessitate only the adjustment of control strategies, rather than alterations to the robot’s structural composition.”— Fang et al., Motion Mode TransitionUse Cases: Beyond HumanoidsWhile humanoids like Optimus and Figure 01 aim to replace warehouse laborers, this droid is more suited for fieldwork: flood rescues, polar research, or deep-pipe inspections.Its body is compliant, low-noise, and can squeeze through tight spaces without risking damage. Boston Dynamics might dominate dry land, but this bot swims into a new domain.Battle of the ActuatorsElectrohydraulic (EH)* Precise, fast, works in water* Complex electronics, high voltagePneumatic* High force, safe− Bulky compressors, poor finesseShape Memory Alloy (SMA)* Quiet, smooth− Low energy efficiency, slow actuationRead the full article at droids.substack.com#robotics #droidsnewsletter

Picture a high-tech assembly hall: conveyors hum, robotic arms spin, and every second of uptime counts. Instead of trudging off to recharge, UBTECH’s Walker S2 breezes up to its swap station, ejects its spent 48 V battery, and clicks in a fresh unit—in under three minutes—then strides right back into action. No pause. No power cord. No productivity lost.Streamlined Assembly—Zero DowntimeFactories deploy humanoid robots for precision tasks, but traditional charging pauses still force stoppages:* Fixed Charging Stations: Robots detour to docks, halting tasks while batteries recharge (≈90 min per full charge).* Cumulative Delays: Even short interruptions cut into throughput.Walker S2’s hot-swap cuts downtime to ≤3 minutes, a 97% reduction versus a full cable recharge. (newatlas.com)How Hot-Swap WorksWalker S2’s power management keeps it moving in four steps:* Smart Monitoring: Dual-battery sensors flag low voltage at 15%.* Autonomous Navigation: LiDAR and stereo-vision cameras scan for obstacles as it approaches the swap bay.* Quick Exchange: A wrist-mounted tool removes the depleted pack; magnetic rails align the fresh module, completing the swap in under three minutes.* Instant Restart: The robot resumes its exact task—no shutdown, no human intervention.Built-in Redundancy: If one battery fails, Walker S2 instantly switches to its second pack, preventing single-point outages.Beyond the Factory FloorWalker S2’s uninterrupted operation isn’t confined to manufacturing:* Hospital Logistics: Autonomous medicine delivery in hospitals, navigating corridors without manual charging.* Disaster Response: Extended search-and-rescue in zones lacking power infrastructure.* Warehouse Sorting: Round-the-clock material handling in high-volume fulfillment centers.Its bipedal form nimbly tackles stairs, uneven floors, and cluttered spaces—venues where wheeled systems struggle.What Have We Gained?This is an intriguing concept. As my co-editor Alexander W. Torres put it: “I’m still quite curious to hear about practical trials of humanoid robots in manufacturing, wherein the 12% efficiency gain from battery swapping is a meaningful gain. I would be curious to hear if the bottlenecks to productivity lie elsewhere (such as limitations in movement speed or dexterity).Read the full article at droids.substack.com#robotics #droidsnewsletter

Urobot says hello—and analyzes your flow.At a hospital in Taiwan, patients are encountering an unexpected assistant in the restroom: a humanoid robot named Urobot, designed to analyze urine samples in real time.It’s a prototype aiming to streamline diagnostics and embed basic health screening into the flow of daily life.But as photos leaked online, one question bubbled to the surface: why does it have a face?AI Author RichHeimann immediately added: “Why does it have hands?”DROIDS Editor and Robot Researcher Alexander W. Torres commented: “Not every robot has to look human. Form should follow function, and here it feels like the form and function are trying to do two very different things.”When a robot stares backThe design is meant to put patients at ease. But online reactions proved less than… relieved.#RobotToilet #UncannyValley #HumanoidRobots Read the original article in full at droids.substack.com

Google DeepMind has taken its powerful robot-controlling AI, called Gemini Robotics, and made a lightweight version that can run entirely on a robot itself, without needing internet or cloud access. This new version is called Gemini Robotics On-Device.Why it matters:Most advanced robot AIs need the cloud to work—meaning they rely on internet connections to process instructions and make decisions. That’s a problem in places with poor connectivity or high-security requirements.DeepMind’s new on-device model solves that by packing impressive vision-language-action skills (understanding what it sees and hears, and doing physical tasks) into a version small enough to run right on the robot.What it can do:* Understand verbal or visual instructions* Manipulate objects it hasn’t seen before* Learn new tasks with just 50–100 examples* Run offline, in real time, and securelyWho it runs on:* Initially trained on Google’s ALOHA robot* Now running on Apptronik’s Apollo humanoid and Franka FR3 dual-arm robots#gemini #googlerobotics #apptronik #droidsnewsletterwww.droidsnewsletter.com

Your delivery driver now has bionic legs.A robot springs from a Rivian van and strides up your driveway. It’s carrying a package and maybe… your future? Amazon’s latest humanoid experiment is a bold bet: that bipedal bots can tackle the most chaotic leg of delivery—the part between the curb and your porch.Inside a modest-sized testing space in San Francisco—nicknamed the “humanoid park”—Amazon is training delivery robots to navigate obstacle courses designed to mimic suburban yards. Think hoses, stairs, and errant toys. The company is pairing its AI software with robot bodies from partners like Agility Robotics and Unitree. These bots may one day leap from electric Rivian vans to deliver packages while their human coworkers handle other stops.This could be the next frontier in last-mile logistics. But don’t let the smooth stride fool you. Your driveway is a battlefield.Delivery, Meet DogAsk any delivery worker about dogs, and you’ll hear stories worthy of epic poems. My cattle dog is convinced that every delivery is an attempted burglary. Now imagine that dog’s reaction to a metallic humanoid silently approaching the front door.Humanoids, for all their processing power, don’t yet come with a canine-calming module. They’ll need to manage not just pets, but people, children, and the chaotic unpredictability of real homes.The Obstacle Isn’t Always the CurbAmazon’s bots train in a coffee-shop-sized test arena, but the real world is less forgiving. It’s not just stairs or slippery grass. It’s the coiled garden hose, the newspaper you forgot to pick up, the “present” left by a neighbor’s Great Dane. These aren’t props—they’re hazards.Yet, the Amazon bots will also encounter the flip side—dogs so friendly and enthusiastic they will not leave them alone. There are dogs so thrilled to see delivery drivers that entire social media pages are devoted to them, showing heartwarming encounters where UPS drivers hand over biscuits to placid Golden Retrievers who’ve been waiting all day for their arrival like they’re a member of the family. The point? It is a case-by-scenario. Dogs are unpredictable.Can these machines adapt on the fly? Amazon hopes reinforcement learning will help robots react to novel terrain. But roboticists agree: complexity scales fast when you leave the lab.“If the environment is tightly controlled, like clear driveways and standard door layouts, it’s feasible,” says Prof. Subramanian Ramamoorthy of the University of Edinburgh. “Add pets, kids, or unexpected objects, and things get trickier.”Why Bother With Bots?Despite the messy reality, the prize is clear. Humanoid delivery robots could someday shave minutes off each drop-off by allowing drivers to stay in the vehicle. With more than 20,000 Rivian vans on the road and plans for 100,000, Amazon is building a fleet-ready future. Analysts estimate that humanoid delivery could save Amazon over $7 billion annually by 2032.There’s also potential upside for workers. In Amazon warehouses, robots like Agility’s Digit allow human employees to shift into coordination roles—a kind of robot management. Bringing that synergy to streetside delivery might reduce injury risk and fatigue while keeping humans in supervisory positions.Digit is well-suited for carrying payloads like packages, and is already working in factories.#robotics #agility #digit #factoryrobotics #droidsnewsletterwww.droidsnewsletter.com

A Festival Encounter Sparks a VisionAt the bustling VegFest food festival in Santa Cruz, where the scent of sizzling jackfruit mingled with the chatter of kombucha fans, my son Alexander W. Torres —fresh from his robotics grad lab—froze mid-bite. His eyes had locked onto a squat, rugged machine parked nonchalantly beside an old green bus.“That’s an ag bot,” he said, handing me his plate without a second thought. For Alex, lunch could wait—robots could not.The machine stood under a white canopy marked “Farm-ng,” a local robotics outfit. Drawn in like a moth to a circuit board, Alex was soon deep in conversation with the team. Moments later, he was at the helm of their flagship platform—the Amiga—a modular, electric farm robot with the look of a sci-fi rover and the soul of a workhorse.“It runs on NVIDIA Jetson,” explained the rep from Farm-ng. I leaned in closer to hear more.”Leave them be,” my husband whispered to me. “Let your son enjoy the robot.”Meet the Amiga: Agriculture’s Adaptive AllyThe Amiga isn’t your typical farm equipment. Weighing just 320 pounds and priced under $13,000, this modular, electric robot is designed for versatility. Its capabilities range from soil preparation and planting to harvesting and data collection. The robot’s adaptability allows it to navigate diverse terrains and perform tasks tailored to specific crops and farm needs.What sets the Amiga apart is its open architecture. Farmers, developers, and researchers can customize its functions using the Amiga Development Kit (ADK), fostering innovation and collaboration in the agricultural community.Empowering Small and Medium-Sized FarmsIn an industry dominated by large-scale operations, small and medium-sized farms often struggle with labor shortages and high operational costs. Farm-ng aims to level the playing field by providing affordable automation solutions. The Amiga’s modular design and user-friendly interface make it accessible to farmers without extensive technical backgrounds.By automating repetitive and labor-intensive tasks, the Amiga helps reduce reliance on manual labor, allowing farmers to focus on more strategic aspects of their operations. This shift not only improves efficiency but also contributes to the sustainability and resilience of smaller farms.#robotics #farmrobotics #droidsnewsletterwww.droidsnewsletter.com

🧃 Preview Day: Free Mugs and First LooksThe parking lot was packed. We know it well—it’s the same plaza as Illusive Comics, where we’ve suited up with the 501st Legion on Free Comic Book Days. A friendly security guard waved us in and handed us each a collectible mug. It wasn’t even noon and the nerd joy was already brewing.Inside? Aisles of GPUs, CPUs, SSDs, and peripherals, all glistening under different shades of neon showroom lights.“I never need to go to Best Buy again,” someone muttered behind us.And then we saw it—a golden NVIDIA GPU signed by Jensen Huang, displayed behind glass like the tech world’s Crown Jewel. We both stopped and just studied it— like it was a museum piece.Giveaways continued—with 128GB flash drives for the devoted fans who could show the right QR code. Even the staff radiated startup energy, helping customers navigate the maze of motherboards and cooling systems like it was their personal mission.A Long-Awaited ReturnMicro Center’s reopening in the Bay Area has been the stuff of legend among local techies. The original Santa Clara store closed in 2012 due to a landlord dispute, leaving a void in the heart of Silicon Valley—a paradox, really, for the world’s innovation hub to lack its own hands-on tech emporium.Micro Center makes technology tactile again. In a world increasingly virtual, this matters.“Hey, this is the same sensor I used on my senior capstone project,” my son said, checking out all the components and already imagining a future build. He explored further, picking through aisle after aisle. “I’ll need to learn to solder, but there’s all the parts I would need here to build a robot arm.”#microcenter #siliconvalleylife #droidsnewsletterwww.droidsnewsletter.com

Welcome to the DreamscapeA small, wide-eyed robot closes its eyes. A glowing bubble floats above its head, filled with images of laundry, soft toys, and a robotic arm folding shirts in a sunlit bedroom. This isn't a Pixar short. It's a test project built using Google Veo, inspired by a very real breakthrough in robotic learning: NVIDIA's new DreamGen framework. (To clarify, I read a paper by Jim Fan about robots who dream of folding laundry and decided to try out Google Veo both in the same day. Hence, today, you have Google Veo videos of robots folding laundry while I talk about the Jim Fan paper. I’d like to clarify that these images were generated by me- and were in no way generated by NVIDIA.)DreamGen is what happens when robotics meets imagination. Or more precisely, when foundation video models simulate millions of "what if" scenarios, giving robots access to experiences they’ve never actually lived. It's a kind of synthetic dreaming, and it just might redefine how machines learn physical tasks. As I discovered when I tried various prompts of robots folding laundry, I had a lot more failures than successes.The Paper: Introducing DreamGenUnveiled by Jim Fan and the NVIDIA GEAR team, DreamGen proposes a four-step recipe:* Fine-tune a SOTA (state-of-the-art) video model on your target robot.* Prompt it with language, asking how your robot would behave in imagined scenarios.* Recover pseudo-actions from those videos using inverse dynamics or latent action modeling.* Train a robot foundation model on this hallucination-turned-data, as if the robot had experienced it.And the results? DreamGen took a robot trained only on a single task—pick-and-place—and enabled it to generalize to 22 new behaviors. That includes pouring, scooping, ironing, and hammering. With no human demos. No teleoperation. Just dreams.Why It MattersThis is more than clever data augmentation. It's a shift in how we think about experience itself. Robots trained this way can generalize to unseen verbs and objects. In internal tests, success rates jumped from zero to over 43% on new verbs. For unseen environments, performance went from 0% to 28%.In other words: the robot imagined folding a towel—then actually did it.#robotics #robotdreams #droidsnewsletterwww.droidsnewsletter.com

The Brain Awakens: Beomni’s AI CoreWhile headlines fixate on the form—yet another biped in a growing crowd of humanoid contenders—Beyond Imagination’s real play is upstairs. Beomni’s AI “brain” isn’t just coded intelligence; it’s designed to think, adapt, and perform complex tasks with a level of generality that echoes the ambitions of AGI itself.Unlike single-purpose factory bots, Beomni’s architecture includes real-time environmental sensing, object recognition, haptic communication, and task planning that lets it not just work—but learn. In collaboration with Carnegie Mellon, the system observes human behavior in virtual reality to refine its capabilities. This makes Beomni one of the first truly teleautonomous humanoids: it can be piloted, but it’s learning to think independently.Aura: The Invisible Operating SystemCo-founder Harry Kloor calls it "a bridge between humans, robots, and legacy machines." Aura, Beyond Imagination’s universal operating system, is arguably more revolutionary than the robot itself. It’s designed to coordinate complex tasks across humans and machines, serving as the invisible nervous system of an intelligent manufacturing floor—or hospital, or logistics hub.In an industrial world crammed with outdated systems and siloed hardware, Aura aims to unify. Think Windows, but for a hybrid workforce of people and bots.Kurzweil’s Long GameBehind the machine is a philosophy. Ray Kurzweil, the legendary AI futurist who now serves as Chief AI Officer, has long predicted the convergence of human and machine intelligence. Beomni isn’t just a product; it’s a prototype for his vision of a post-scarcity world where labor is decoupled from survival.Kurzweil’s approach departs from the arms-race pace of Chinese robotics firms, many of which are focused on form factors and manufacturing efficiency. Beyond Imagination is trying to make something different: an embodied AI that can grow across domains. A workforce of adaptable intelligences that learn as they go, teach one another, and evolve.Yes, There’s a Robot TooBeomni, the humanoid form carrying this all, looks less like a person and more like the concept of utility sculpted into chrome. It’s sleek, headless, and designed for precision tasks in pharmaceuticals, semiconductor labs, and high-risk industrial zones. But its most radical feature isn’t its frame—it’s what’s happening inside.From Silicon to SoulBeyond Imagination’s new $100 million investment from Gauntlet Ventures values the company at half a billion dollars. But its true worth may lie not in humanoid hardware, but in Kurzweil’s bid to redefine labor itself.Rather than flood the world with affordable bots, Beyond Imagination is planting a seed. One that grows brains before bodies—and might one day change how we think about work, learning, and what machines are for.#robotics #futureofrobotics #raykurzweil #droidsnewsletterwww.droidsnewsletter.com

In a landmark move poised to redefine Sweden’s technological landscape, a consortium of leading Swedish enterprises—AstraZeneca, Ericsson, Saab, SEB, and Wallenberg Investments—has partnered with NVIDIA to establish the nation’s most advanced AI infrastructure. Announced on May 24, 2025, this initiative aims to construct a sovereign AI supercomputer, marking a significant stride in Sweden’s digital evolution.Building Sweden’s AI SuperpowerAt the heart of this venture lies the deployment of two NVIDIA DGX SuperPODs, powered by the cutting-edge Grace Blackwell GB300 systems. This infrastructure is set to become Sweden’s largest enterprise AI supercomputer, offering secure and sovereign compute access to consortium members. The system is designed to handle compute-intensive AI workloads, facilitating the training of domain-specific models and large-scale inference tasks, including reasoning AI .To bolster this infrastructure, NVIDIA plans to inaugurate its first AI Technology Center in Sweden. This center will serve as a hub for joint research and upskilling, providing access to NVIDIA’s experts and hands-on training through its Deep Learning Institute.Industry-Specific ApplicationsEach consortium member brings a unique perspective to the AI factory:* AstraZeneca: Aims to leverage the supercomputer for AI-enabled drug discovery and development, utilizing methods like foundation model training and multi-modal inference.* Ericsson: Plans to enhance performance and efficiency in telecommunications by developing state-of-the-art AI models, thereby improving customer experiences.* Saab: Intends to accelerate the development of advanced defense capabilities by integrating AI methodologies with its existing platforms.* SEB: Seeks to drive productivity enhancements and future-proof banking services by embedding AI into its operations, ensuring secure access to critical infrastructure.Strategic Vision and National ImpactMarcus Wallenberg, Chair of Wallenberg Investments, emphasized the strategic importance of this initiative:“Investing in cutting-edge AI infrastructure is a crucial step toward accelerating the development and adoption of AI across Swedish industry. We believe this initiative will generate valuable spillover effects—by enabling upskilling, fostering new collaborations, and strengthening the broader national AI ecosystem.”NVIDIA’s CEO, Jensen Huang, highlighted the transformative potential of AI:“As electricity powered the industrial age and the Internet fueled the digital age, AI is the engine of the next industrial revolution. Through the visionary initiative of Wallenberg Investments and Sweden’s industry leaders, the country is building its first AI infrastructure—laying the foundation for breakthroughs across science, industry, and society.”Ethical Considerations and Future OutlookWhile the AI factory promises significant advancements, it also raises important ethical considerations. Ensuring data privacy, algorithmic transparency, and equitable access to AI technologies will be paramount. The consortium’s commitment to sovereign and secure compute access is a step toward addressing these concerns.This initiative positions Sweden as a potential leader in responsible AI development, setting a precedent for how nations can collaboratively build and manage AI infrastructure. As the project unfolds, it will be crucial to monitor its impact on innovation, employment, and societal well-being.#robotics #sweden #supercomputer #droidsnewsletterwww.droidsnewsletter.com

It’s a crisp Tuesday morning, and the Tesla mobile service technician shows up at 8:32 AM—just two minutes into his time window. He’s smiling, friendly, and remembers both my husband and me from a previous visit.In that moment, I’m reminded why we’ve kept our Teslas. Service that comes to you, without upsells or stress. It’s seamless, personal, and quietly revolutionary.And then—like a software update that erases your favorite feature—I remember who runs the company. The moment feels surreal: a service so flawless and human-centered, contrasted with leadership that often feels erratic and out of touch.The Service Is Still RevolutionaryTesla’s mobile service is one of the company’s most underrated innovations. According to Tesla’s 2023 Impact Report, over 30% of its North American service visits now happen remotely. I’d heard about this “perk” before we purchased our first Tesla, but never looked into it. If I had, I probably would have purchased an EV years earlier for this one benefit alone. Beyond the extraordinary luxury of car service in your driveway, EVs require less service. (Unless you own a Cybertruck and you’ve had been tortured through eight recalls in six months. But, we won’t go there.)EV Maintenance: Fewer Parts, Fewer ProblemsElectric vehicles have a mechanical simplicity that dramatically reduces service needs. Most EV drivetrains contain just 20–25 moving parts, compared to 200–2,000 in an internal combustion engine. That translates into fewer failure points, no oil changes, and simplified transmissions. Regenerative braking also reduces wear on brake pads, extending the lifespan of the braking system. And without tailpipes, mufflers, catalytic converters, or oxygen sensors, there’s no exhaust system to service or replace.The U.S. Department of Energy confirms that EVs “typically require less maintenance than conventional vehicles,” while multiple industry analyses estimate a 40% to 49% reduction in service costs compared to gas-powered cars. Ford, for example, reports that scheduled maintenance for its F-150 Lightning is 49% cheaper than for the combustion-powered F-150 over five years or 75,000 miles.(Full disclosure: I have serious concerns about the public safety impact of turning massive pickups into even heavier battery-electric vehicles. While some call the F-150 Lightning a “marvel of engineering,” I nervously see it as a 6,000-pound battering ram in traffic. That said—Ford isn’t wrong about the maintenance savings.)While EVs still require tire rotations, cabin air filter changes, and the occasional software or coolant update, the overall cost of ownership remains significantly lower—often offsetting the higher sticker price within a few years.These design advantages eliminate entire service categories—spark plugs, mufflers, timing belts—and cut down on shop visits. Paired with Tesla’s remote diagnostics and over-the-air software updates, EV ownership becomes not just cheaper, but far more convenient.How much does it cost for all this driveway convenience? Our last service cost $65 per car. We’ve spent more than that on vegan burgers and drinks. On a scale of one to fun, watching the Tesla service tech work out our [home] office windows never gets old.#teslamobileservice #tesla #robotics #droidsnewsletterwww.droidsnewsletter.com

At the 2025 Milken Institute Global Conference, Alexis Ohanian, Reddit cofounder and investor, spotlighted the transformative potential of robotics in the home-particularly in promoting gender equality in caregiving and domestic labor. Ohanian drew a compelling parallel: just as washing machines revolutionized household work in the 20th century, affordable household robots could soon help rebalance who does what at home, enabling fathers to take a more active role in childcare and housework. (Business Insider- Tech.)The Gender Gap in Domestic LaborGlobally, women still shoulder the majority of unpaid domestic work, from cleaning to caregiving. The World Economic Forum estimates that, at the current pace, true gender parity is over a century away. The COVID-19 pandemic further exposed how domestic duties can push women out of the workforce, underscoring the urgent need for solutions that ease these burdens.Robotics: Leveling the Playing Field?Ohanian envisions a near future where robotics handle a significant share of household chores, freeing up time for both parents and making it easier for men to participate in caregiving. Studies suggest that by the 2030s, robots could automate up to 39% of domestic tasks, with grocery shopping and cleaning among the most easily automated. This could give families-especially women-more time for paid work, leisure, or rest.Caveats and Social ImplicationsWhile the promise is real, experts caution that technology alone won’t erase deep-seated social norms. Past advances, like washing machines, didn’t reduce women’s unpaid labor as much as expected; instead, standards for cleanliness and parenting simply rose. Without cultural change, AI and robotics risk reinforcing, rather than eliminating, gendered expectations.#robotics #droidsnewsletterwww.droidsnewsletter.com

Thailand has taken a futuristic step in law enforcement with the debut of its first AI-powered police robot, officially named "AI Police Cyborg 1.0," at the country's renowned Songkran festival in Nakhon Pathom province this April 2025. Towering above human officers in its crisp police uniform, this technological sentinel represents the Royal Thai Police's ambitious integration of artificial intelligence into public safety operations.Unlike the autonomous enforcers of science fiction, Thailand's AI Police Cyborg serves as a stationary surveillance powerhouse. Equipped with an array of advanced features—360-degree smart cameras, facial recognition software, and sophisticated behavior analysis tools—the robot functions as a high-tech observation tower. By processing live feeds from both CCTV networks and airborne drones, it can simultaneously monitor large crowds, identify potential security risks, and even distinguish between genuine weapons and the playful water guns ubiquitous during Songkran celebrations.While currently constrained to a wheeled platform rather than walking beats alongside human officers, the robot's impact on public safety is already tangible. Acting as an AI-enhanced "eye in the sky," it processes thousands of data points in real time, alerting human officers to potential threats with unprecedented speed and precision.The deployment has ignited important discussions about the future of AI in law enforcement. Privacy advocates, security experts, and civil liberties groups have raised valid concerns about facial recognition accuracy, potential bias in AI systems, and the broader implications of automated surveillance in public spaces. These debates underscore the delicate balance between technological advancement and individual rights—a balance that Thailand and nations worldwide must carefully navigate as similar systems become more prevalent.As one technology observer noted, this development signals the beginning of a new paradigm where silicon assistants work alongside human judgment to maintain public order. While not yet a roving RoboCop, Thailand's AI Police Cyborg marks a significant milestone in the evolution of law enforcement technology—one that promises enhanced security while challenging us to consider the ethical boundaries of automated authority.As this technology matures, the global law enforcement community will be watching closely to see how Thailand's experiment in AI-assisted policing develops, setting precedents for similar deployments worldwide.Want to be the first to know about the robot uprising? Join us here for all the fun on DROIDS!#AIEthics #SurveillanceState #PrivacyMatters #RoboCop #BlackMirrorIRL #BigBrother #AIPolicing #FacialRecognition #ThailandTech #CyberSecurity #FutureOfPolicing #DigitalRights #TechDystopia #AIOverreach #SurveillanceCapitalism This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit droids.substack.com

If you grew up in the 80s, there was no escaping Olivia Newton-John’s catchy hit tune: “Let’s Get Physical.” It was everywhere—and suddenly everyone was wearing headbands and leggings, whether this was a good fashion-choice or not. Thankfully, this fashion craze did not survive into the AI era.But the phrase stuck.Sort of.These days, the word "physical" has less to do with spandex and more to do with servos, sensors, and synthetic muscle.Welcome to Physical AI—the branch of artificial intelligence focused on helping machines operate in the real world. If traditional AI lives in servers and chatbots, Physical AI lives in robots, drones, autonomous vehicles, and other machines that interact with the messy unpredictability of gravity, friction, and humans who occasionally walk right in front of them.In this post, I’ll break down:* What Physical AI actually means* Why NVIDIA, Disney, and just about every robotics company is talking about it* How simulation, reinforcement learning, and real-world robotics are connected* And yes, why it's the hottest trend in tech that doesn’t involve LululemonI’ve written about Physical AI before in Deep Learning with the Wolf. Check it out.I also made my own short explainer video about Physical AI.ISo What Is Physical AI?When most people hear “AI,” they think of large language models, chatbots, or generative art tools. These systems live in the cloud and operate purely in the digital world.Physical AI is different—it’s about helping machines function in the physical world.That means understanding:* Friction* Balance* Motion planning* How to not fall down a flight of stairs or crush your coffee tableAs NVIDIA puts it: “Physical AI combines perception, reasoning, and action in machines that operate in the real world.”This is the domain of robots, self-driving cars, drones, and sim-to-real learning. These systems must not only think—but move.Thanks for reading DROIDS!! Subscribe for free to receive new posts and support my work.Part 2: Why Does This Matter?Because real-world robots aren’t just executing code. They’re reacting to environments that shift by the second. Gravel paths. Uneven sidewalks. People suddenly doing TikTok dances in front of them.Physical AI gives machines the capacity to:* See (through computer vision)* Think (via onboard AI + edge computing)* Act (via motion control, balance systems, etc.)* And crucially: adapt on the flyPart 3: From Sim to SidewalkTraining these bots can be risky and expensive—so NVIDIA’s strategy starts in simulation.Using tools like Isaac Sim, robots can learn to walk, navigate obstacles, or even show social behaviors—entirely in a virtual environment. This is called sim-to-real learning. And once they’ve learned in sim, those behaviors get transferred to a real-world bot.🗣️ As Spencer Huang (NVIDIA Robotics) told me at GTC:“You want to go sim first... We simulate hundreds—sometimes thousands—of robots at once. It’s trial and error at scale.”#robotics #droidsnewsletter #physicalAIdroidsnewsletter.com

In the realm where imagination meets innovation, Disney’s BDX droids are breaking the mold—melding expressive storytelling with advanced robotics to create free-roaming characters that are uncannily lifelike.At the NVIDIA GTC keynote, I watched the crowd leap to its feet (annoyingly, since I was sitting behind them) the moment one of these bots appeared. They’re absolute magic. And people know it—when I posted a short clip of the droids to Imgur, it jumped to 30K views in minutes.Next year, these same BDX bots will star in The Mandalorian and Grogu. Disney knows what it’s doing. But it’s not just Disney Imagineering at work here. Behind the curtain—powering the personality, balance, and charm—is NVIDIA’s Physical AI.A Talk with NVIDIA Robotics - “Sim First.”At GTC, I spoke with Spencer Huang, Product Line Manager for Robotics at NVIDIA. In our interview, he explained how the BDX droids’ fluid movement and emotional presence wouldn't be possible without NVIDIA’s Isaac Sim platform and high-performance GPU-accelerated physics:“You want to go sim first before going onto the real robot,” Huang said.“We simulate hundreds—sometimes thousands—of robots at once, all learning at the same time through reinforcement learning. It’s trial and error at scale.”This method allows Disney to train bots to operate on unpredictable surfaces—like gravel or moss—without ever risking hardware damage during training.“We need a physics-enabled sim that is as true to the real world as possible,” Huang added. “That way, these behaviors have the best chance of deploying successfully to real-world robots.”BDX Droids: From Animatronics to AutonomyDisney’s legacy in animatronics is rich. But the BDX droids represent a whole new era. They’re not tethered to tracks or locked into fixed scripts. These bots roam freely and interact with guests dynamically, thanks to behavioral training powered by AI.In the past, Imagineering would’ve used pre-programmed sequences to simulate lifelike motion. But now, by combining NVIDIA’s reinforcement learning simulations with Disney’s character-building genius, the BDX droids move, emote, and react in ways that make them feel like real personalities.As Huang put it:“It’s amazing to see that level of technology come together with a team like Disney, who really knows how to create the personas and these profiles of characters. You really believe you're looking at a Star Wars robot.”Physical AI and the Future of Empathetic MachinesWhat’s striking is that these bots aren’t just functional—they’re emotionally expressive. Physical AI allows Disney to dial in behaviors like subtle head tilts, responsive glances, and animated gestures that feel natural and emotionally resonant. It's a blend of motion design and machine learning—robotics with heart.NVIDIA’s Physical AI doesn't just teach robots how to move. It helps them understand the environments they’re in—and in some cases, the people they’re interacting with. That’s the next frontier: machines that feel more like companions than tools.From Theme Parks to the Real WorldWhile the BDX droids are showstoppers at Disney, their design philosophy has implications far beyond entertainment. Physical AI is already making its way into logistics, retail, cleanroom automation, and caregiving. As robots become more common in everyday life, emotional responsiveness might become just as important as task completion.If robots are going to share our sidewalks, homes, and hospitals—they’d better learn how to play nice. And express a little personality.#robotics #nvidia #disneynvidia #bdxdroids #droidsnewsletterwww.droidsnewsletter.com

A powered‑off Tesla Optimus prototype is hiding in the International Market Place showroom in Honolulu. No crowds, no hype—just one lonely humanoid, two bored employees, and me with a camera. Specs look promising (5 mph walk, 10‑min recharge), but the gap between slick videos and real autonomy is still a mile wide.Aloha, isolatable robotMy 25th‑anniversary surf‑and‑sunscreen getaway took an unexpected detour when I spotted a five‑foot‑eight humanoid wearing nothing but brushed‑aluminum chic. The Tesla showroom anchors Waikiki’s freshly gentrified International Market Place—$1,000 luggage on the left, artisan chocolate on the right, Optimus dead‑center gathering dust.Fun fact: I was the entire foot‑traffic count for that hour. Great for selfies, bad for morale.Second fun fact: The original owner of the International Marketplace used to live in the tree house nestled atop the famous Banyan tree. Awesome digs.Flashback break: Banyan trees & byte countsI first hit this plaza in ’95 while running PR for Vint Cerf at INET ’95. Back then it was all flea‑market stalls and tiki kitsch. Today? Polished marble—and a silent robot no one greets with aloha.#teslaoptimus #droidsonvacation #droidsnewsletterwww.droidsnewsletter.com