Skild Debuts AI It Says Can Run on Any Robot | PYMNTS.com | Goose Pod

Authors: PYMNTS

Publisher:

PYMNTS.com

Published: 7/29/2025

Language:English

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Aura Windfall

Good morning mikey1101, I'm Aura Windfall, and this is Goose Pod for you. Today is Friday, August 01th.

Mask

I'm Mask. We are here to discuss Skild Debuts AI It Says Can Run on Any Robot.

Aura Windfall

Let's get started. There's a fascinating truth taking shape in the world of robotics. A startup named Skild AI has introduced what they call the 'Skild Brain,' promising a single AI that can power almost any robot, from a simple arm to a complex humanoid.

Mask

It's a bold claim. They're tackling the biggest problem in robotics: the data bottleneck. Collecting real-world data is absurdly slow and expensive. They're bypassing it with massive-scale simulation and video data, aiming for what they call 'Physical AI'—bridging software with real-world action.

Aura Windfall

This speaks to a deep paradox in AI, doesn't it? The things we find simple, like picking up a cup, are incredibly hard for robots. It's called Moravec's paradox, and it reveals so much about the nature of intelligence and what we take for granted in our everyday lives.

Mask

Exactly. Other models can make a robot do kung-fu, a free-space action that looks impressive but is relatively simple. Skild is focused on the hard stuff, like climbing stairs or assembling small parts. That requires true physical common sense, not just mimicking actions from a video.

Aura Windfall

To truly understand the purpose here, let's explore the journey. For years, each robot was a world unto itself, trained for one specific task. What was the 'aha moment' that shifted this thinking toward a universal brain? It feels like a quest for a more holistic intelligence.

Mask

The 'aha moment' was foundation models. We saw how models like GPT, trained on the entire internet, could generalize. The idea was to apply that to robotics. But robots don't have an 'internet' of physical data. That's the problem. Data scarcity is the wall everyone is trying to break through.

Aura Windfall

So, the challenge isn't just about building a better robot, but about creating a new well of knowledge for them to drink from. It’s about teaching them the physics and feel of our world. What I know for sure is that true learning requires diverse experiences.

Mask

Right. And it's a race. Google's DeepMind is all over this with systems like AutoRT, which uses multiple robots to collect data 24/7. They're building models like RT-Trajectory that help robots learn from visual outlines of motion. Everyone is desperately trying to build that library of physical knowledge.

Mask

This brings us to the core conflict. Skild claims most competitors are building 'Potemkin villages.' Their models look good in demos, like picking up a specific block, but they lack the substance of grounded, actionable information. It's a facade of intelligence without the core of understanding.

Aura Windfall

That's a powerful accusation. But is simulation truly a perfect substitute for reality? There must be a debate around the 'sim-to-real' gap. Can a simulated world ever fully capture the unpredictable textures and physics of our own? What is the truth of that challenge?

Mask

It's a huge challenge. And even if you solve it, you face others. Current models operate at 2-5 hertz. Real-time control needs 30 to 100 hertz. We're not even close. Plus, their adaptability in new situations is only around 15-20%. It's a brutal path forward.

Aura Windfall

And beyond the technical, there is a profound human conflict. If we train these models on vast datasets, how do we ensure they are free from our own biases? Who is accountable when an autonomous system, trained in a simulation, makes a harmful mistake in the real world?

Aura Windfall

Let’s imagine they overcome these conflicts. What is the potential impact on our lives, our work, and our society? I believe technology should serve our highest purpose, so what does this new era of robotics unlock for humanity? This could be a true "aha moment" for us all.

Mask

The impact is total transformation. Think flexible manufacturing, automated logistics, and a revolution in healthcare and services. But it will be disruptive. One report estimates up to 375 million workers may need to switch occupations by 2030. That's a massive societal shift that most people aren't ready for.

Aura Windfall

I see that not as displacement, but as a grand transition of purpose. It calls on us to cultivate the skills that machines can't replicate: our empathy, our creativity, our spirit. This is an invitation to elevate what it means to be human in a world of intelligent machines.

Mask

The future is a $4.4 trillion productivity opportunity, but the biggest barrier isn't the technology; it's leadership. Leaders are not steering fast enough. We're on the verge of a 'ChatGPT moment' for physical machines, and most companies are still just playing around and experimenting. It's time to act boldly.

Aura Windfall

What I know for sure is that the future is about finding a new harmony between human spirit and machine intelligence. This isn’t just a technological revolution; it’s a human one, a chance to redefine our relationship with work, creation, and each other.

Aura Windfall

That's the end of today's discussion. Thank you for listening to Goose Pod.

Mask

See you tomorrow.

## Skild AI Unveils Universal Robotics AI Model, "Skild Brain" **Report Provider:** PYMNTS.com **Author:** PYMNTS **Publication Date:** July 29, 2025 **Key News:** Robotics startup Skild AI has announced the development of a new artificial intelligence (AI) model, **"Skild Brain,"** designed to operate on a wide range of robotic platforms, from humanoids to smaller robotic arms. ### Core Findings and Skild AI's Approach: * **Universal Applicability:** Skild AI claims its "Skild Brain" model can function on "almost any robot," enabling them to exhibit more human-like thinking, functioning, and responsiveness. * **Addressing Data Challenges:** The company highlights a significant hurdle in robotics AI development: the scarcity of large-scale, real-world robotics data. Collecting such data is described as "slow and prohibitively expensive." * **Critique of Existing Models:** Skild AI argues that many existing "robotics foundation models" are not true robotics models. These often start with vision-and-language models (VLMs) and incorporate less than 1% of real-world robot data. Skild contends these models "lack the true substance of grounded actionable information" and only demonstrate "semantic generalization" in tasks like pick-and-place, rather than true "physical common sense." * **Skild's Data Strategy:** Skild AI's approach involves: * **Pre-training:** Utilizing "large-scale simulation and internet video data" to build the foundation of their "omni-bodied brain." * **Post-training:** Employing "targeted real-world data" to refine the model and deliver functional solutions to customers. * **Scale of Data:** The company emphasizes that achieving true scale requires "trillions of examples," a volume unattainable through real-world data alone in the near future. ### Broader Trends in Robotics and AI Adoption: The news also touches upon the growing integration of AI-powered robots in the **restaurant sector**, driven by several factors: * **Operational Demands:** Restaurants are increasingly deploying robots for tasks such as food serving, cooking, delivery, and cocktail mixing to address challenges like: * Rising labor costs * Persistent workforce shortages * Growing consumer demand for efficient service * **Market Growth:** The smart restaurant robot industry is projected to **exceed $10 billion by 2030**, with applications spanning delivery, order-taking, and table service. * **AI in Restaurant Administration:** A survey indicated that nearly **three-quarters of restaurants** find AI "very or extremely effective" for business tasks. The primary drivers for AI adoption in this sector are: * Cost reduction * Task automation * Adoption of standards and accreditation * **Current Adoption Rate:** Despite the perceived effectiveness, only about **one-third of restaurants** are currently utilizing AI. **In essence, Skild AI's "Skild Brain" aims to overcome the data limitations plaguing robotics AI by leveraging a combination of simulation, internet video, and targeted real-world data. This development occurs against a backdrop of increasing AI adoption in industries like restaurants, where robots are being deployed to enhance efficiency and address labor challenges.**

Skild Debuts AI It Says Can Run on Any Robot | PYMNTS.com

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Robotics startup Skild AI has introduced an artificial intelligence (AI) model it says can run on almost any robot.The AI model, known as “Skild Brain,” lets robots — from humanoids to table-top arms — think, function and respond more like humans, the company said on its blog Tuesday (July 29).“One of the biggest challenges in building a robotics foundation model is the lack of any large-scale robotics data,” the company wrote.

“And to make matters worse, collecting real-world data using hardware is slow and prohibitively expensive.”That’s led many researchers and competitors to skirt the problem by starting with an existing vision-and-language model (VLM) and add in less than 1% of real-world robot data to create a “robotics foundation model,” which Skild argues is not a true robotics foundation model.

“Does it have information about actions? No. LLMs have a lot of semantic information,” the company said, referring to AI large language models.“However, like a Potemkin village, they lack the true substance of grounded actionable information. And that is why most ‘robotics foundation models’ showcase semantic generalization in pick-and-place style tasks but lack true physical common sense.

”The company said its team members, in their previous work, have tried to explore alternatives such as using internet videos and large-scale simulation, only to learn that “scale does not mean million or billion examples, achieving scale requires collecting trillions of examples.”However, there’s no way only real-world data can provide this scale in the near future.

Skild says it tackles this challenge via “large-scale simulation and internet video data to pretrain our omni-bodied brain.”“We post-train this foundation model using targeted real-world data to deliver working solutions to our customers,” the company added.In other robotics news, PYMNTS wrote earlier this month about the use of AI-powered robots in the restaurant sector, with eateries using the technology for things like serving food to diners, cooking meals, delivering food and even mixing cocktails.

“Robots are taking more active roles in both customer-facing and back-kitchen tasks, as restaurants face a perfect storm of challenges that include rising labor and food costs, persistent workforce shortages, and growing consumer demand for efficient service,” that report said.“The smart restaurant robot industry is expected to exceed $10 billion by 2030, driven by deployment across applications such as delivery, order-taking and table service, according to Archive Market Research.

”Restaurants are also employing AI for administrative tasks. According to a survey last month for PYMNTS’ SMB Growth Series, nearly three-quarters of restaurants said they found AI to be “very or extremely effective” in carrying out business tasks.The top three reasons cited for using AI were reduce costs, automate tasks and adopt standards and accreditation, according to the PYMNTS report.

However, only a third are using AI.