NEO Gamma 1.0 Pilots Redwood AI Controller: 5 Next Gen Humanoid Robot Skills

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Summary

➡ The company 1X has introduced new features in its Neo Gamma humanoid robot using the Redwood AI system. The robot can now walk, sit, kneel, and stand with realistic movements, and can even move in all directions, including sidestepping and pivoting. It can navigate stairs using vision-based technology and perform floor-level tasks like cleaning and packing. The robot’s AI can interpret high-level commands and translate them into precise movements, demonstrating advanced autonomy.

Transcript

Alright, so 1X just revealed several new mobility milestones with its newest Redwood AI system for its Neo Gamma humanoid robot. So what can it do now, and how smart is it as a result? Today I’ll explain 5 new Android Intelligence Advances, plus more as we explore what this means for robot companions, and what it means for you. Starting with Advancement number 5, its Unified Mobility Toolkit. So Neo’s new Reinforcement Learning Controller is a game changer as it brings together a complete set of mobility skills for the first time ever. And these include walking naturally in any direction, sitting, kneeling, plus standing, and it’s all with next level realism.

And this is thanks to 1X’s new Redwood AI, which processes high level commands and translates them into precise movements via the robot’s unified controller. And to do this, it’s trained in simulation with randomized physics parameters like friction and mass, with the controller being robust enough to handle real-world unpredictability, resulting in some of the most human-like movements yet for robots. With part of this performance stemming from an even more important advancement, it’s Omnidirectional Gate. And this is clever because Neo’s controller achieves an even more natural human-like gate by simply being able to move in all directions now.

Meaning it moves not only forward and backward, but now the robot can also sidestep through potentially tight spaces, and it can even pivot itself 180 degrees while walking full speed to go backwards, plus it can even now sprint from a complete standstill on rough terrain. And part of 1X’s secret is that unlike earlier RL models that relied on hand-tuned shaping rewards for each motion, Neo now uses human motion capture data that’s retargeted to all of its joints. Basically, this approach trains the reinforcement learning controller to track the robot’s trajectories for more fluid movements, all without needing to sacrifice any stability.

But what’s even more important is advancement number 3, its vision-based navigation. So stairs are a common hurdle in homes, but Neo’s newest feature is called Vision-Based Stair Mode, and it’s using stereo RGB cameras to let the robot predict depth directly from its visual data, which eliminates the need for bulky lidar or time-of-flight sensors. And what’s even more impressive is that the new RL controller anticipates the robot’s step heights in advance, and this gives Neo the ability to easily handle uneven or even mix-height stairs and even sidestep when needed. But this next upgrade may be even more important with advancement number 2 for floor-level tasks, as many home tours require working at floor levels, like cleaning carpets, sorting laundry, or packing suitcases.

And to do this, Neo’s new Redwood AI-powered controller now supports fast transitions to sitting, kneeling, lying down, and even getting back up, all while maintaining contact-ware interactions with its environment. But the heart of the Neo robot is actually in its Redwood AI action interface, and this provides a steerable action interface for both teleoperation and autonomous tasks. And to demonstrate it all working together, 1X even fine-tuned its Redwood AI to dribble a soccer ball using its vision inputs, and this allowed Redwood to predict whole-body joint targets as well as its walking velocities, which the RL controller then translated into precise leg forces to guide the ball, and this shows off just how much Neo can now interpret high-level AI commands down into complex, contact-rich interactions for next-generation autonomy.

Plus, we’ll take a look at two new humanoid robots, but first, a message from today’s sponsor. If you’re someone trying to grow in a fast-moving, competitive space like tech or AI, then listen up, because whether you’re trying to land a higher-paying role, make a career pivot into emerging industries, or just feel stuck in a job that isn’t evolving with you. Today’s sponsor, Strawberry.me Career Coaching, helps you move forward with clarity and a plan. They even match you with a professional career coach who’s trained to help you identify your goals, sharpen how you present your value, and build a step-by-step strategy that actually works.

It’s not therapy, but it’s like therapy for your career. It’s structured, action-oriented, and totally focused on helping you grow. Sessions are virtual, flexible, and built around your schedule, so if you’re ready to land your dream job, switch careers, or level up in your industry, get the right coach and make it happen by heading to Strawberry.me slash AI News to claim your $50 credit and get started today. That’s Strawberry.me slash AI News. Meanwhile, Lumos Robotics is breaking through barriers of raw speed, as its LUS2 humanoid robot is now able to stand up in less than one second.

And beyond this, not many specifications are known, other than that the company is currently working on a high-resolution advanced tactile sensing gripper for dexterity. But there’s another humanoid from the global robotics leader Estun, having just launched its Codroid 2, a second-generation humanoid robot built to transform industrial manufacturing. Powered by electrical drive and fully self-developed components, the robot uses advanced actuators for stable, precise motion, and it’s equipped with a Vision Language Action Large Language model to support teamwork with other robots while adapting to complex factory settings. Plus, it can pick up components, handle materials, fasten screws, and even perform quality checks while reducing the workload for its human coworkers.

With Estun Codroid’s expertise in collaborative robots shining in Codroid 2, serving as a practical, general-purpose humanoid robot. Meanwhile, Robot Era’s Star1 humanoid used chopsticks to pick up delicate items, proving that it’s ready to take on household tasks. And this 171-centimeter-tall robot weighs 63 kilograms, and it features 55 degrees of freedom to move with next-level agility. Plus, it packs a unique 3 degree of freedom waist to let it walk and move with more fluidity. And the robot can even sprint at speeds of 13 kilometers per hour, making it one of the fastest two-legged robots around, having already run in multiple marathons.

And to add to this power, Star1’s 7 degree of freedom bionic arms can handle payloads of over 20 kilograms. Plus, the robot’s X1 hands feature 12 degrees of freedom with high-resolution tactile sensors. And the robot’s brains are powered by its Intel processors as well as its NVIDIA Oran platform, with Star1 boasting 275 tera operations per second of AI computation, letting it learn new tasks on the fly while using reinforcement learning and imitation learning. And generative AI also just saw a breakthrough as ByteDance, the tech giant behind TikTok, just unveiled SeedDance 1.0, its powerful AI video generation model that’s making waves in the industry.

And according to ByteDance, SeedDance 1.0 outperforms its competitors, including Google’s V03, QuiShow’s Cling 2.0, and OpenAI’s Sora, claiming the top spot on artificial analysis for both text-to-video and image-to-video tasks. And the model excels in prompt adherence, motion quality, and image sharpness, offering a new standard for AI-driven video creation. In fact, SeedDance 1.0 transforms simple text or image prompts into complex, high-quality videos, with it generating extended sequences with consistent characters, varied camera angles, and precise visual styles, sticking closely to users’ instructions. This capability stems from its training on a vast dataset of video clips sourced from both public and licensed content, with ByteDance rigorously filtering this data to remove logos, subtitles, and violent material, then enriching it with detailed annotations to describe movement, appearance, and style.

And finally, mid-journey is getting an overhaul to its video generation model, but make sure to tell us in the comments what you think about this compared to OpenAI’s Sora and Google’s V03, as some people on Reddit have said that the transitions don’t look like previous AI models, as it’s much smoother, with much greater fluidity in between different frames, and better continuity between characters. Anyways, if you want to know more about the latest in AI news, make sure to like and subscribe, and thank you strawberry.me career coaching for sponsoring this video.

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