Company

This move comes as we prepare for large-scale deployment of NEO, your friendly home humanoid. With the aim of having hundreds of NEO’s arrive in homes across the United States in 2025, followed by rapid expansion– Mustally will be instrumental in enabling our growth along the way.

“I am excited to welcome Mustally to the Executive Team at 1X,” said Bernt Børnich, CEO of 1X Technologies. “He will play a key role in helping us accelerate our growth plans from our global HQ in Palo Alto, California.”

Mustally brings a strong track record of leadership across Fortune 500 companies and high-growth startups. He has built finance organizations from the ground up, raised over $50 billion in capital through public and private markets, and led transformative commercial partnerships and M&A initiatives. Prior to joining 1X, Mustally served as Managing Director, Global Treasurer, and Head of Financial Services at Lucid Group, and held senior finance roles at Herc Holdings, Hyundai Capital, and National Grid, following a career in investment banking and management consulting.

“I’m thrilled to join the 1X team, which is well positioned to lead the physical AI and robotics sector,” said Mustally Hussain. “My focus will be on driving financial discipline and strategic growth as 1X scales its manufacturing and commercialization footprint in the U.S., followed by global expansion.”

Welcoming Mustally Hussain as CFO

 1X announces the acquisition of Kind Humanoid, uniting two robotics teams with aligned visions to advance humanoid technology.

“It’s rare to find someone who is not just a powerhouse engineer but also completely aligned philosophically and strategically on how humanoids as products should take shape,” said Bernt Bornich, CEO of 1X. “Having Christoph join the 1X team here in the Bay will accelerate our path to a world full of humanoid robots."

Kind Humanoid’s unique expertise and culture complement 1X’s mission to create an abundance of labor through safe and intelligent humanoids. The relationship between the two newly joined companies is built on the foundational belief that humanoids need to be developed alongside humans-- living and learning among us.

“Joining 1X feels like the perfect next chapter for Kind Humanoid,” said Christoph Kohstall, CEO of Kind Humanoid. “From starting out in a small garage to now becoming part of a team that shares our belief in humanoids living and learning among us, this acquisition brings our vision closer to reality. Together, we can create robots that truly connect with people and make a difference where it matters most.”

Kind Humanoid is a Palo Alto-based robotics startup founded by Christoph Kohstall, a former scientist at Stanford and member of Google's robotics team. The company developed Mona, a bipedal humanoid robot designed for home use and to bring additional labor to fields such as healthcare. Operating from a small garage, the team brought together a deeply bio-inspired robot body with advanced Al and large language models developing a robot that can interact with and assist everyday people.

1X is a leader in humanoid robotics, developing general-purpose robots designed to live and learn among humans in the home—an early step toward advancing physical intelligence. With a focus on safety, 1X is at the forefront of the next wave of robotics, offering products that are accessible and practical for everyday use. 1X’s mission is to create an abundance of labor through safe, intelligent humanoids that work alongside people

1X Acquires Kind Humanoid

San Francisco, CA, and Moss, Norway — July 22, 2024

 — 1X, an AI robotics company, is pleased to announce the appointments of three strategic hires. Jorge Milburn joins 1X as VP of Sales, Dar Sleeper as VP of Growth and Per Selvaag as VP of Design. These hires come as 1X prepares to bring its bipedal humanoid robot, NEO, to market, delivering on its mission to create an abundance of labor through safe, intelligent humanoids.

Backed by OpenAI, 1X has revolutionized humanoid robotics with NEO, a lightweight and soft bipedal robot capable of performing tasks through voice commands and natural language. To further progress on our mission, we are appointing 3 new hires.

 joins 1X as VP of Sales, bringing nearly 10 years of go-to-market experience at Tesla. He recently served as Global Head of Growth. He played a pivotal role in building the Supercharger network and led Tesla’s car business in EMEA, successfully introducing the Model 3 to Europe and establishing a Global Growth team. Originally from Uruguay, Jorge holds an MA in Economics. His responsibilities at Tesla included sales leadership, business planning, demand and supply optimization, delivery operations, and business analytics.



 joins 1X as VP of Design, bringing over 20 years of experience in design, user research, data analytics, and robotics. His career includes roles as Chief Designer at Automobiles Peugeot, lead designer at BMW, and establishing the Human-Centered Design discipline at Equinor Data Science. He also founded and led a successful consultancy in the Bay Area.



 joins as VP of Growth to build lead demand and brand in the Bay Area. Most recently, a product manager at Tesla, Dar, played a key role in launching the campaign for Cybertruck and created lead demand for electric vehicles.

"I am thrilled to welcome Jorge, Per and Dar," said Bernt Øivind Børnich, CEO of 1X. "Their expertise will be crucial as we prepare to bring NEO to market and enhance our products' design and user experience."


1X is a US-Norwegian AI robotics company specializing in developing robots with humanlike capabilities. With commercial deployments of the wheeled humanoid EVE and the ongoing production of their next product, a bipedal humanoid robot NEO, 1X builds their own models for embodied AI making robots capable of task manipulation and generalization. Our mission is to push the boundaries of AI and robotics to create a global abundance of labor through safe, intelligent humanoids.

1X Strengthens Leadership Team with New Hires

1X will be attending the NVIDIA GTC Conference on March 18th. Our involvement signifies 1X's dedication to advancing in the field of Embodied AI, showcasing our latest developments, and engaging with the global AI community.

The NVIDIA GTC Conference is renowned for being a pivotal event that gathers innovators, researchers, and industry leaders worldwide to explore the latest advancements in AI, machine learning, and related technologies. Attendees can look forward to a program full of insightful talks, dynamic workshops, and demonstrations.

For more information about the conference or to register:


We look forward to connecting with professionals to share our passion for AI and robotics at the event. See you at NVIDIA GTC.

1X Attends NVIDIA GTC

As of March 1st, 1X has expanded our operations with the establishment of dual headquarters in Sunnyvale, California, and Moss, Norway.

The Sunnyvale office will include a new branch of our 

 and support the expansion of our AI team. The new HQ will be staffed by the AI team, the customer success team, service technicians, and a significant fleet of NEO and EVE androids.

Opening new HQ in Sunnyvale

1X, an AI and robotics company producing androids to benefit society and meet the world’s labor demand, is pleased to announce it has raised $100 million in Series B funding with participation from EQT Ventures and other notable global investors.
‍

The company intends to utilize the new capital to bring to market its second generation android NEO. Designed as a bipedal humanoid, NEO is tailored for everyday home assistance, offering versatile support for a wide range of domestic tasks in the consumer market. The funds will also support 1X’s existing enterprise clients in logistics and guarding. With 1X offering an android safe to work among people and a new approach to embodied learning for data collection, the company stands at the forefront of AI robotics.

“We are thrilled that these leading investors are supporting 1X’s mission of safely deploying Androids with Smart Behavior into new markets. Our next milestone will be scaling our data collection strategy for Embodied AI and offering NEO to consumers,” says Bernt Øivind Børnich, CEO of 1X.

‍
After successfully completing a Series A funding round led by OpenAI and Tiger Global in March 2023, 1X has now raised over $125 million in less than 12 months. This funding will support their mission to produce safe and advanced androids at a commercial scale, aiming to meet global labor demands and build an abundant society. As part of the round, 1X also facilitated a significant secondary transaction in which existing investor Sandwater increased its stake with the third largest contribution to the round. Other secondary participants included new investor Samsung NEXT, and existing investors Skagerak Capital and the Nistad group.

“From Leonardo da Vinci, to today’s sci-fi, humans have dreamt of humanoid robots for more than 500 years. It’s a privilege to witness the enabling technologies form in front of our eyes, in real-time. The impact of androids joining our human workforce, on our terms will be transformative (to say the least). We’re convinced 1X with their NEO androids will play a crucial role in the pioneering steps towards the first forays of our technological and human future,” says Ted Persson, Partner, EQT Ventures.

Series B: 1X Secures $100M Funding

As part of an extensive rebranding initiative in 2023, Halodi Robotics unveils our new name.

The name 1X alludes to the company’s growth and vision for the future and reflects the team’s unique competencies in robotics.

CEO Bernt Øivind Børnich expanded on that vision, saying, “Our androids will eventually work among people, one by one. And unlike other androids that have to slow down to be functional, 1X’s models work at 1x speed. We’re excited to embark on this new chapter, and we look forward to continuing to provide industry-leading products and services under our new brand.”

As 1X reaches many more milestones along with the name change, Børnich cites 2023 as an “important point in the evolution of 1X.” He continues, “We face this next phase of growth with excitement.”

With the goal to develop androids on a safe and capable platform, the company has deployed EVE, the first commercial android, at scale in the United States this year with a manufacturing capacity goal of 140 robots from Norway and Dallas, Texas.

Announcing rebranding: From Halodi Robotics to 1X

Humanoid robotics company 1X Technologies announces Series A2 fundraise led by OpenAI to pursue producing androids at commercial scale.

NORWAY, March 23rd, 2023. 1X, previously named Halodi Robotics, a manufacturer and inventor of androids, announced today the successful close of its Series A2 funding round, raising $23.5 million. This round was led by the OpenAI Startup Fund, with participation from Tiger Global and a consortium of Norway-based investors, including Sandwater, Alliance Ventures, and Skagerak Capital.

“1X is at the forefront of augmenting labor through the use of safe, advanced technologies in robotics,” said Brad Lightcap, OpenAI’s COO and manager of the OpenAI Startup Fund. “The OpenAI Startup Fund believes in the approach and impact that 1X can have on the future of work.”

Tiger Global partner Griffin Schroeder also expressed enthusiasm for 1X’s mission: “We believe 1X’s androids are revolutionizing the field of robotics and are excited to be investing alongside OpenAI to support their continued growth.”

The company intends to use the funds to increase the efforts of building its upcoming bipedal android model NEO, as well as scale manufacturing of its first commercially available android EVE in Norway and North America.

“1X is thrilled to have OpenAI lead this round because we’re aligned in our missions: thoughtfully integrating emerging technology into people’s daily lives. With the support of our investors, we will continue to make significant strides in the field of robotics and augment the global labor market,” says Bernt Øyvind Børnich, CEO and founder of 1X Technologies.

Børnich highlights the necessity of having androids deployed in the real world.

“Deploying our wheeled android EVE at an unprecedented commercial scale gives us a unique understanding of the challenges and opportunities the robotics community has yet to address. If androids are going to work in our world, they need to experience our world.”

Torkel Engeness, partner at Sandwater, sees tremendous value in 1X’s vision and next-generation model.“We are excited to support 1X as they launch their bipedal android NEO, while scaling their first-generation android EVE in Norway and North America. 1X is providing value now, and the potential for their androids looks limitless.”
‍
– TORKEL ENGENESS, PARTNER, SANDWATER

“Demographic changes will cause a labor shortage, and androids could help fill the gap. Goldman Sachs predicts a 150 BUSD market potential in 2035. Solving the right use cases is key to success, and we believe 1X Technologies is constructing a winning alliance.”
‍
– ARNE TONNING, PARTNER, ALLIANCE VENTURE

“1X now deploys Androids in North America before entering the global market while maintaining a “safety first” mindset, making product design and development even more challenging. It is exciting for Skagerak to support 1X with their disruptive technology now that they enter this ambitious commercialization phase.”
‍
– ESPEN KJELLSEN, PARTNER, SKAGERAK CAPITAL

1X Raises $23.5M in Series A2 Funding led by OpenAI

Opt in to receive updates. Unsubscribe anytime.

Experience NEO

Developing AI for humanoid robots involves tackling many open research challenges – in safety, dexterity, visual understanding, and much more. It helps to compare notes with other labs tackling similar challenges, in order to accelerate progress towards a future of NEOs doing all the tasks needed to keep your home in order autonomously.

To that end, 1X AI and NVIDIA are pleased to announce our research collaboration effort. As a first step, the teams worked together to prepare an autonomy demo for Jensen Huang’s GTC 2025 Keynote, featuring NEO doing a dish loading task autonomously.

The following is a look into where, how and when we taught NEO to do the dishes with the NVIDIA team.



To make this collaboration possible, the 1X AI Team created a dataset API for NVIDIA to access data collected from 1X offices and employee homes, and an inference SDK to serve model predictions at a continuous 5Hz vision-action loop using an onboard NVIDIA GPU in NEO’s head or an offboard GPU.

A crucial step when onboarding a new learning codebase onto NEO is to verify correctness, i.e., overfitting a baseline model to a small amount of demonstration data and making sure that the time synchronization between images and actions is consistent all the way from data collection to training to runtime inference.

We demonstrate this by working with the NVIDIA GEAR team to train a single end-to-end neural network based on the 

 model to autonomously grasp a cup, hand it over to the other hand, and place it in a dishwasher to showcase how NEO fits compactly into the kitchen space while still having the kinematic reach to carry the cup from sink to dishwasher.

This is a good “first task” to learn because it checks for basic compatibility of an external research codebase with the logging and inference architecture. The obvious next step after verifying correctness is to feed thousands of hours of internally collected NEO data into the model.

Over the course of a week, our teams developed this model at a 1X employee’s home, swapped notes on action spaces, control frequencies, and other imitation learning tricks needed to get good performance on NEO Gamma. Moments like these – where friends are just hanging out in the home while a NEO does dishes in the background – will soon become an everyday occurrence.



When working in homes, the safety of NEO Gamma becomes particularly evident. NEO’s mechanically compliant and safe design allowed engineers to get in extremely close quarters with the robot while testing a variety of experimental architectures.


Our teams are both looking forward to continuing to learn from each other and push the industry forward. We hope that together we can accelerate our path to humanoids living and learning among us and providing a helping hand wherever one is needed.


 team and Jensen Huang for being gracious with their time and having us be a part of the NVIDIA experience at GTC. 

Additionally, thank you to 

 team for designing the jacket and capturing the moment.

1X & NVIDIA Research Collaboration 

NEO Gamma is the next generation of home humanoids designed and engineered by 1X Technologies. The Gamma series includes improvements across NEO’s hardware and AI, featuring a new design that is deeply considerate of life at home.


NEO Gamma's new design features Emotive Ear Rings to improve the communication and has a minimalist design aesthetic that fits into the home.




NEO can now walk with a natural human gait and arm swings, squat down to pick things up from the ground and sit in chairs.




NEO Gamma comes outfitted with soft covers to reduce impact on the surrounding environment and increase overall safety.




1X trained a visual manipulation model capable of picking up a large variety of objects in different scenarios, including environments not seen during training.




NEO Gamma’s Companion feature set integrates a new in-house language model that enables natural conversation and body language.

NEO Gamma’s design opens the door to start internal home testing—a first step in creating fully autonomous humanoids.

“There is a not-so-distant future where we all have our own robot helper at home, like Rosey the Robot or Baymax. But for humanoid robots to truly integrate into everyday life, they must be developed alongside humans, not in isolation.

The home provides real-world context and the diversity of data needed for humanoids to grow in intelligence and autonomy. It also teaches them the nuances of human life—how to open the door for the elderly, move carefully around pets, or adapt to the unpredictability of the surrounding world. Robots confined to industrial space or lab development miss out on this critical understanding.

With NEO Gamma, every engineering and design decision was made with one goal in mind: getting NEO into customers’ homes as quickly as possible… We’re close. We can’t wait to share more soon.”

NEO Gamma introduces a number of AI advancements, enhancing both autonomy and safe teleoperation in the home.




NEO now walks with a natural human gait and arm swings, squat down to pick things up from the ground and sit in chairs, all while maintaining balance. These dynamic control skills – running at 100Hz – are learned using Reinforcement Learning from human motion capture data. This range of motion allows NEO Gamma to experience household scenarios and tasks that would be otherwise inaccessible to other robot form factors.




1X trained a visual manipulation model capable of picking up a large variety of objects in different scenarios, including environments not seen during training. NEO Gamma leverages neural networks trained to predict teleoperated actions directly from raw sensor data.




NEO Gamma’s Companion feature set integrates a conversational voice interface, allowing users to converse naturally with a 1X developed language model (LLM). These developments bring NEO closer to human-friendly user interaction, bridging the gap between humanoid robotics and daily life.

NEO Gamma is designed to be approachable, with all new features created to integrate seamlessly into people’s everyday lives. NEO’s new look aims to complement living spaces rather than disrupt them.




NEO Gamma’s Ear Rings provide real-time visual feedback for a more intuitive and interactive experience.




3D printed from durable and soft nylon using a Japanese Shimaseki machine, the suit utilizes a unique whole-garment seamless knitting process that allows the fabric to conform to NEO without impeding performance.




With safety as the top priority, NEO Gamma features 1X’s Tendon Drive for joint actuation, encased in soft covers to enhance passive safety.

NEO Gamma features significant hardware upgrades, making it quieter, more reliable, and well suited to deliver a consumer product experience.




NEO Gamma boasts a 10x increase in hardware reliability and a 10 dB decrease in noise, bringing NEO’s operating levels down to the level of a refrigerator.




NEO Gamma features four microphones (front, back, left, and right) with beamforming and echo cancellation, ensuring crystal-clear audio capture and A three-speaker system—one in the chest for AI voice interactions and two outward-facing speakers in the pelvis for bass, 360-degree sound effects, and music.

Media Inquiries: press@1x.tech

Introducing NEO Gamma

Our goal with this video was to create a fun and exciting glimpse into a not-so-distant future where humanoids cook delicious meals for us.

After connecting with Nick and his team, we brainstormed ideas for an engaging narrative. When Nick suggested a robot cook-off with NEO Beta as the “final boss,” we quickly set to work refining our cooking skills.

While cooking a steak dinner from start to finish was an impressive demonstration of NEO Beta's ability to navigate complex tasks, it is important to note that this showcase was done using teleoperation to ensure the successful execution of all tasks involved. That said, the only thing standing between NEO and a fully autonomous, medium-rare steak is the input data.

In the video, NEO Beta and Nick met up in Sunnyvale, California, near the 1X headquarters, for a home cooking showdown to see who could make the perfect medium-rare steak. The audience would ultimately decide the winner.

Nick generously brought NEO Beta a custom “Chef NEO” coat and stocked the fridges with more Wagyu beef than any humanoid could ever need.

: We (wrongly) assumed NEO Beta might mess up at least one steak since this was an entirely new skill. To be safe, we had multiple backup steaks on hand. Proving us wrong, NEO Beta nailed it on the first try, and the 1X team and Nick got to enjoy the extra steaks afterward.

The shoot was full of laughs, imperfections like knocking over the olive oil, and memorable moments like when NEO Beta pulled off butter basting—reminding everyone on set they were witnessing a landmark moment in the history of home robotics.

: Nick admitted that NEO Beta was a better chef than Gordon Ramsay and Uncle Roger. He asked us to keep it a secret, but we couldn’t resist sharing.

While videos like this are extremely fun and important for showing the masses that humanoid robots are here and the fun is just beginning– we find it equally important to be transparent about how we capture these shots to maintain trust in the robotics community and set the right expectations for our product.

All movements were powered by 1X’s VR Teleoperation App running on Meta Quest.

NEO Beta's lines were filmed using voice pass-through with a filter. Although NEO is equipped with real-time conversation capabilities via our GPT-4o voice integration, we opted for controlled dialogue to align with Nick’s vision for the video.

NEO Beta’s voice was designed in collaboration with Nick’s team to find a tone that was playful and appealing to both his audience and our vision of NEO as a friendly, home-assisting humanoid.

: Although NEO Beta successfully cooked a meal alongside Nick, cooking won’t be an immediate feature available to the first NEO users. We want to ensure NEO gains experience with safer tasks before handling sharp or hot objects.

: While NEO Beta completed all tasks from seasoning the steak to flipping and removing it from the pan end to end, NEO Beta did require assistance to turn on the burner. Nick and his team felt that including this scene was important for their audience, so we agreed to create this article for transparency.

We’re incredibly excited that NEO Beta was able to cook a full steak dinner with minimal assistance. Sooner than you think, NEO will be cooking similar meals—and more—in your kitchen.

Huge thanks to Nick, Tim and Zach for putting this all together.

We hope you enjoyed the video. Share it with friends and family and let us know what you all think on 

Cooking With NEO Beta and Nick DiGiovanni

We see World Models as a grand challenge in robotics. They have the potential to solve general purpose simulation and evaluation, enabling robots that are safe, reliable, and intelligent.

 work on our robot world model which imagines possible futures given action proposals. We also announced our first challenge: compression, which focuses on minimizing training loss across a diverse robot dataset. The lower the loss, the better the model understands the training data. This challenge is still active, offering a $10k prize to the first submission that achieves a loss of 8.0 on our private test set. Our Github repo provides code and pretrained 

Today, we are announcing the next phase of the World Model Challenge: Sampling.

Sampling focuses on generating realistic future outcomes in video sequences by predicting the next frame given a sequence of prior frames. The goal is to produce coherent and plausible continuations of the video, accurately reflecting the dynamics of the scene. We encourage you to explore a variety of future prediction methods beyond traditional next-logit prediction. Techniques such as Generative Adversarial Networks, Diffusion Models, and MaskGIT are all welcome for generating the next frame. To be competitive, submissions should achieve a PSNR of around 26.5 or above. We will open our evaluation server for submissions and release our metric in March 2025.

To help accelerate research in this direction, we’re 

 of 100 hours of raw robot video alongside our robot state sequences which enable world model training. Our raw videos will be shared under the 

 license, and we will continue to share tokenized datasets under 

We’re also thrilled to announce that we’re partnering with NVIDIA’s World Models team to further tokenize our video sequences with their newly-announced 

. NVIDIA’s work in visual tokenization and quantization creates highly compressed, temporal representations of our robot data, optimized for such research. The Cosmos-tokenized dataset can be found 

On the horizon is our third challenge, Evaluation. This is our ultimate goal: can you predict how well a robot will perform before testing it in the real world? This challenge aims to assess the ability to evaluate and rank different robot policies using a world model, without the need for physical deployment.

The official details for the evaluation challenge have not been released yet—stay tuned for the announcement.

 - starter code, evals, baseline implementations


1X World Model: Sampling Challenge Update

 is a computer program that can imagine how the world evolves in response to an agent’s behavior. Building on advancements in 

, we have trained a world model that serves as a virtual simulator for our robots.

From the same starting image sequence, our world model can imagine multiple futures from different robot action proposals.

It can also predict non-trivial object interactions like rigid bodies, effects of dropping objects, partial observability, deformable objects (curtains, laundry), and articulated objects (doors, drawers, curtains, chairs).

In this post we’ll share why world models for robots are important, the capabilities and limitations of our current models, and a new dataset and public competition to encourage more research in this direction.

World models solve a very practical and yet often overlooked challenge when building general-purpose robots: evaluation. If you train a robot to perform 1000 unique tasks, it is very hard to know whether a new model has made the robot better at all 1000 tasks, compared to a prior model. Even the same model weights can experience a rapid degradation in performance in a matter of days due to subtle changes in the environment background or ambient lighting.

If the environment keeps changing over time, then old experiments performed in that environment are no longer reproducible because the old environment no longer exists! This problem gets worse if you are evaluating multi-task systems in a constantly-changing setting like the home or the office. This makes careful robotic science in the real world frustratingly hard.

Careful measurement of capabilities allows one to predict how capabilities will scale when one increases data, compute, and model size – these “

” defend the enormous investment that goes into general-purpose AI systems like ChatGPT. If robotics is to have its “ChatGPT moment”, we must first establish its “Scaling Laws”.

Physics-based simulation (Bullet, Mujoco, Isaac Sim, Drake) are a reasonable way to quickly test robot policies. They are resettable and reproducible, allowing researchers to carefully compare different control algorithms. However, these simulators are mostly designed for rigid body dynamics and require a lot of manual asset authoring. How to simulate robot hands opening a cardboard box of coffee filters, cutting fruit with a knife, unscrewing a frozen jar of preserves, or interacting with other intelligent agents like humans? Everyday objects and animals encountered in home environments are notoriously difficult to simulate, so simulation environments used in robotics tend to be visually sterile and lack the diversity of the real world use case. Small-scale evaluation on a limited number of tasks in real or sim is not predictive of large-scale evaluation in the real world.

We’re taking a radically new approach to evaluation of general-purpose robots: learning a simulator directly from raw sensor data and using it to evaluate our policies across millions of scenarios. By learning a simulator directly from real data, you can absorb the full complexity of the real world without manual asset creation.

Over the last year, we’ve gathered thousands of hours of data on EVE humanoids doing diverse mobile manipulation tasks in homes and offices and interacting with people. We combined the video and action data to train a world model that can anticipate future video from observations and actions.

Our world model is capable of generating diverse outcomes based on different action commands. Below we show various generations conditioning the world model on four different trajectories, each of which start from the same initial frames. As before, the examples shown are not included during training.

The main value of the world model comes from simulating object interactions. In the following generations, we provide the model the same initial frames and three different sets of actions to grasp boxes. In each scenario, the box(es) grasped are lifted and moved in accordance with the motion of the gripper, while the other boxes remain undisturbed.

We can also generate long-horizon videos. The example below simulates a complete t-shirt folding demonstration. T-shirts and deformable objects tend to be difficult to implement in rigid body simulators.

Our model can fail to maintain the shape and color of objects during interaction, and at times, objects may completely disappear. Additionally, when objects are occluded or displayed at unfavorable angles, their appearance can become distorted throughout the generation.

The generation on the left demonstrates that our model has an emergent understanding of physical properties, as evidenced by the spoon falling to the table when released by the gripper. However, there are many instances where generations fail to adhere to physical laws, such as on the right where the plate remains suspended in the air.

We placed EVE in front of a mirror to see if generations would result in mirrored actions, but we did not see successful recognition or “self-understanding"

As shown by the examples above, there is still much work to be done. World models have the potential to solve general purpose simulation and evaluation, enabling robots that are safe, reliable, and intelligent in a wide variety of scenarios. As such, we see this effort as a grand challenge in robotics that the community can work on solving together. To help accelerate progress towards solving world models for robotics, we are 

releasing over 100 hours of vector-quantized video

 (Apache 2.0), pretrained baseline models, and the 

, a three-stage challenge with cash prizes.

Compression Challenge | Prize: $10,000 USD

The first challenge, compression, is about how well one can minimize training loss on an extremely diverse robot dataset. The lower the loss, the better the model understands the training data. Even though there are many different ways to implement a world model, optimizing loss well is a general objective that underpins nearly all large-scale deep learning tasks. A $10k prize is awarded to the first submission that achieves a loss of 8.0 on our private test set. The Github repo provides code and pretrained 

The second challenge, sampling, is about how well and how quickly a model can generate videos of the future. Details of the Sampling Challenge will be announced soon, based on lessons learned from running the Stage 1 Challenge.

The third challenge, evaluation, is our holy grail: can you predict how well a robot performs before you test it in the real world? Details of the Evaluation Challenge will be announced after we’ve learned lessons from Stage 1 and Stage 2 Challenges.

If you’re excited about these directions, we have 

 on the 1X AI team. Internally, we have a large dataset of high resolution robot data across even more diverse scenarios. Our ambitions for world models go beyond just solving the general evaluation problem; once you can step an agent in this world model and perform evaluation, you can follow on with 

Welcoming Mustally Hussain as CFO

1X Acquires Kind Humanoid

1X Strengthens Leadership Team with New Hires

1X Attends NVIDIA GTC

Opening new HQ in Sunnyvale

ExperienceNEO