Archetype AI

AI goes into the real world 🌎 Today, we're starting a new chapter of Archetype as we celebrate our $35M Series A. The physical world generates vast amounts of sensor and video data every day but most of it goes unused. After years of AI living behind screens — in dashboards, apps, and digital abstractions — intelligence is finally stepping into the physical world. We're bringing the Archetype platform to more customers and evolving Newton from a powerful foundation model into an intelligence layer for the physical world—one that perceives, understands, and reasons across real-world systems, enabling hundreds of intelligent applications. And this is just the beginning. This funding round, led by IAG Capital Partners and Hitachi Ventures, with participation from Bezos Expeditions, Venrock, Amazon Industrial Innovation Fund, Samsung, E12, Systemiq Capital, HLV, and others, enables us to scale physical intelligence globally and continue advancing Newton as the premier foundation model for the real world. Thank you to our team, partners, investors, and all of you for following our journey to making the world truly intelligent. Onwards! 🚀

NEW OPEN POSITIONS 🚀 We’re growing and #hiring across multiple teams! At Archetype AI, we’re building the future of Physical AI. To get there, we’re looking for passionate people who want to make an impact. We currently have open roles for: 🔹 Evaluation Lead 🔹 Staff Backend Engineer - Distributed Systems 🔹 Staff Backend Software Engineer: Streaming 🔹 Backend Engineer - Distributed Systems 🔹 Backend Software Engineer: Inference 🔹 Customer Success Manager 🔹 AI Researcher 🔹 RevOps Manager 🔹 Visual, UI Designer 🔹 Design Engineer 🔹 Design Engineer 🔹 Software Engineer - Solutions 🔹 Staff Software Engineer, Edge AI Systems If you’re curious, driven, and ready to help shape what’s next, we’d love to hear from you. 👉 Explore all open positions here: careers.kula.ai/archetype-ai #careers #techjobs

This Friday our CEO & Co-Founder @ipoupyrev joins Jodi Forlizzi (CMU), Wendy Ju (Cornell Tech) and Max Kreminski (Cornell Tech) at the @UCBerkeley Master of Design Forum to discuss how to craft trustworthy, legible interactions for AI agents operating in the real world. 📅 Friday March 20 | 9am - 5:30pm PT 📍 Grimes Engineering Center, UC Berkeley Register here: eventbrite.com/e/from-interfa…

Big news! We’re announcing a new partnership with @TMobile and @nvidia to bring Physical AI to the edge. AI is starting to move beyond digital workflows into the physical systems that run factories, infrastructure, and cities. That shift needs a different kind of tech stack where intelligence runs close to where data is generated and decisions are made. With T-Mobile and NVIDIA, we’re deploying Newton, our Physical AI foundation model, on distributed edge infrastructure powered by RTX PRO 6000 Blackwell GPUs. This brings real-time understanding of sensor data directly to the source, whether that’s a production line or a city block. How it works: 🔹 T-Mobile is turning its network into a platform for distributed AI 🔹 NVIDIA provides the accelerated compute for real-time inference 🔹 @PhysicalAI is building the model that can interpret and reason over the physical world Together, this new stack enables AI to move beyond observation into real-world impact — shifting systems from reactive monitoring to real-time understanding and control. As intelligence becomes embedded across infrastructure and environments, the result is not just more intelligent systems, but a new class of systems that can continuously learn, improve, and act at global scale. We’re excited to be among the first deploying on this. Learn more here: blogs.nvidia.com/blog/telecom-a… Book a demo to explore Newton use cases at #NVIDIAGTC: archetypeai.io/put-physical-a…

Just wrapped up at the P&P Germany Summit in Munich — what a setting. 🏛️ The BMW Museum provided a stunning backdrop for conversations about Physical AI, Newton and physical agents in the real world. Grateful for the sharp questions and energy in the room. Munich delivered!

The physical world runs on sensor data — temperature, vibration, pressure, motion — not text. And while LLMs have transformed how we work with information, they were never designed to reason about what's actually happening on a factory floor, inside a vehicle, or across an industrial system. Bridging that gap is one of the hardest problems in AI. In our latest paper, our Chief Scientist and Co-Founder @_jaimelien_ and the team take a step toward solving it. By training a small mapping network that translates Newton's physical-signal embeddings into vectors an LLM can interpret, the result is a model that generates rich, context-aware descriptions of what sensors actually observe — in natural language, in real time. This is what bridging language and the physical world looks like in practice. Instead of a chatbot layered on top of a dashboard, we’re building a model that genuinely understands the signal.

🎉 Our Chief Scientist and Co-Founder @_jaimelien_ has been named to the @Inc's Female Founders 500. Jamie is one of the architects of Newton, our foundation model for the physical world. Her work sits at the intersection of signal processing, machine learning, and Physical AI, and it's redefining what machines can understand about reality. Congratulations, Jamie! #PhysicalAI #FoundationModel

Our Chief Scientist, Jaime Lien, is now on X! Welcome, @_jaimelien_ 💫

🎉 Today we are excited to be welcoming @DongLin_ML as the new Principal Research Engineer, leading Archetype's Foundation Model Team! Dong brings over a decade of experience in developing, shipping, and optimizing world-class production models at Google and Apple. Dong, welcome to the team!

We have a new HQ! #PhysicalAI

🌍 At MWC 2026 this week, conversations about AI focused heavily on connectivity and infrastructure. One dimension that is often overlooked is the physical world itself. At Archetype AI, we are building a Physical AI model that represents a missing layer into the conversation and turning raw sensor data into real-time understanding of what’s happening across industrial systems. 🔹 First, at the @GSMA stage, our COO and co-founder @BrandonBarbello presented our vision for the future of manufacturing and industrial operations, and why Physical AI requires going beyond large language models. The physical world speaks in vibration, torque, pressure, and hundreds of continuous signals. Newton is designed to understand them organize them semantically so that anyone can interpret what's happening across their operations in real time. 🔹 Second, at the @NTTDATA panel, Brandon spoke about the power of combining Physical AI, Edge Compute and Private Networks for the future of smart cities with Paul Bloudoff and Jorge Cardenas. Big thanks to Jo Gilbert, Vijay Taylor, our team on the ground and to our partners for making today possible. More to come from Barcelona this week. #MWC26 #PhysicalAI #Manufacturing

Latest from @PhysicalAI demo land: This is Newton distinguishing between two people using the same phone. But how? Everyone has a slightly different way of typing. Newton understands the micro-differences in motion, which are mapped clearly in the embedded space (on the right). We never explicitly trained Newton to do this. Our Physical AI foundation model is capable of detecting emergent behaviors — so instead of multiple vertical AI solutions, organizations can leverage Newton to generalize across hundreds of sensor types and support a broad range of use cases. #PhysicalAI #FoundationModel

Demo team at @NTTDATA booth looking 🔥 Thank you all for stopping by and checking out Newton's Task Verification Physical Agent in real time. See you tomorrow at #MWC26 for Day 2!

👋In a few minutes, our COO @BrandonBarbello will join executives at the @nttdata_inc @NTTDATA booth for the "Accelerating Industrial Automation: How the Intersection of Physical AI, Edge Compute, and Private Networks are Powering Real-Time Decisions". For those of you joining #MWC2026 we hope to see you there ! #PhysicalAI

Is Physical AI just a fancy word for robotics? 🤖Our CEO @ipoupyrev recently sat down with @richierocks from @DataCamp to dive into AI applications for real-world environments. 👇

Over the last couple of years, AI models got really good at reasoning over text and images. Meanwhile, factories, fleets, and infrastructure generate continuous streams of vibration, motion, temperature, and current and these signals rarely make it into the conversation in a usable way. What if we bridge between these sensor signals and language? Today at @PhysicalAI we share new research demonstrating that meaningful integration between physical signals and language can be achieved with minimal additional computation. To do so, we built a lightweight 3.3M-parameter alignment network that connects our Newton physical world encoder to a frozen LLM (Llama-2-7B-Chat) in under 30 minutes on a single modern GPU. All of this is possible because Newton, our Physical AI foundation model, clusters together signals that mean similar things without being trained to do so. That emergent structure is what makes alignment with language practical and easy. This matters beyond the lab. The physical world generates more sensor data than any team of experts can interpret. The companies that win in manufacturing, infrastructure, transportation are those that can use existing infrastructure and turn raw signals into insights. --- Paper by Hasan Doğan, Jaime Lien, Laura I. Galindez Olascoaga, Muhammed Selman Artıran and O. Serdar Gedik 🔗👇 archetypeai.io/blog/language-…

We are #hiring across multiple teams! If you’re curious, driven, and ready to help shape what’s next, we’d love to hear from you. 👉 Explore & apply here: careers.kula.ai/archetype-ai

In 2026, Physical AI in manufacturing is moving past the pilot stage. AI agents are capable of interpreting sensor data and turning it into insights — for example, detect defects or provide safety alerts. Tomorrow, Raleigh Murch (Managing Director, Physical AI at @NTTDATA) and our Head of Solutions Engineering Sisinio Baldis will break down what's actually working, where manufacturers are investing, and the practical lessons from deploying Physical AI in production environments. 📅 Thursday, Feb 19 | 9:00 AM PST Save your spot: luma.com/1v9n9r0n

This April, our CEO & co-founder @ipoupyrev will join leaders at @Semafor World Economy  — the leading modern platform for global CEOs and executives — to discuss critical issues facing the new world economy. We hope to see you there!

We're rolling with "Windows of Reality" ty to @JSosadiaz

Time series data + language = TimeFusion. In our latest demo, TimeFusion, the first general sensor-language fusion model, processes raw IMU data from a smartphone, and identifies activities (shaking, raising your hand) without explicit training. Then, when queried in natural language, it generates a control signal: 0 for no motion-of-interest, 1 when detected. A big step for Physical AI and autonomous systems of any scale, anywhere. 🚀 #AI #MachineLearning #SensorFusion #PhysicalAI