ARCHETYPE AI

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2024: The Year of Physical AI

Archetype AI Team
  • 5 min
  • December 23, 2024

2024 was the year Physical AI moved from concept to reality. Whether in robotics, world models, materials discovery, physical simulations, smart homes, or industrial automation, the potential of modern AI foundation models to solve critical real-world problems became clear and entered the mainstream. It was also a transformative year for Archetype AI. Starting with our operational launch in January to pursue the Physical AI vision, we built the initial version of Newton — the first general-purpose physical AI foundation model for the physical world. We initiated collaborations and completed large-scale projects for our customers, shared our vision at TED AI and conferences worldwide, released our first research paper, and grew awareness about the importance of Physical AI. We are proud to be at the forefront of this movement. Let's look at some of the key moments from Archetype AI this year.

Beyond Chatbots: The Untapped Potential of Sensors

At the start of the year, Archetype AI closed a seed round led by Venrock and joined by Hitachi Ventures and the Amazon Industrial Innovation Fund.

The investment enabled us to advance the development of a foundation model for the physical world that we call Newton, moving from concept to reality in our mission to use AI to solve real-world problems across diverse customer use cases and industries.

The timing couldn't have been better. The proliferation of sensors from the IoT era, massive adoption of cloud computing infrastructure, and the shift from machine learning to generative AI architectures provided the foundation for Newton, our large behavior model. It is designed to perceive and reason about the physical world in real time by fusing multimodal sensor data and natural language.

Read on:

An AI Model that Learns Physics from Raw Data

Our research paper, "A Phenomenological AI Foundation Model for Physical Signals," showed Newton's ability to understand and predict real world behaviors without being explicitly trained with underlying principles, i.e., laws of physics.

The research demonstrated how Newton can forecast complex real-world processes it has never encountered before, which unlocks applications of foundation models in a variety of industries and use cases. From predicting power grid demand to understanding oil temperature variations in electrical transformers, our model demonstrated an unprecedented ability to generalize across different physical systems.

Read on:

Can AI Learn Physics from Sensor Data?

Unveiling the Future of Physical AI at TEDAI San Francisco

Venture Beat: Archetype AI’s Newton Model Learns Physics From Raw Data — Without Any Help From Humans

Solving Real World Problems with Physical AI

We demonstrated Newton's potential to solve critical real-world challenges by putting it to work. Our partner Soarchain integrated Newton into their decentralized connectivity platform to create an intelligent road safety system that processes real-time camera data and interprets complex road situations.

With Khasm Labs, we ran Newton on a single edge GPU to process real time traffic data in an intersection and urban data streamed from drones over a 5G network. Our partnerships with Infineon and several Fortune Global 500 customers—spanning automotive, consumer electronics, and construction sectors—validated our vision of using Physical AI to solve real world problems. We were also thrilled to be selected for the AWS Gen AI accelerator to speed up development of real-world applications with Newton.

Read on:

How Soarchain Is Making Roads Safer With Physical AI

Bringing AI to Sensor Data: Newton On-Prem and Real-Time

Infineon to Pilot New AI Developer Model by Archetype AI to Anhance AI Sensor Solution Innovation

Washington Post: Startups Shaping the Future of Generative AI

AI for Physical Awareness

AI working in the physical world cannot rely just on one kind of sensor. A factory, vehicle, or smart home cannot run just on a camera, but needs hundreds of different sensors working together to capture critical processes and events happening in real time. Working in collaboration with Infineon, we demonstrated how Newton could integrate high-level contextual information with real-time data from simple sensors — just a microphone and radar — to understand and describe complex real-world events.

By fusing basic sensor data with context, we demonstrate that AI can achieve human-like understanding of fluid physical situations. This marks a step toward a future where Physical AI will seamlessly understand and respond to complex real-world events—much like humans do. Whether it's improving home safety, enhancing manufacturing efficiency, or designing autonomous vehicles, the ability to connect different types of sensor data opens up endless possibilities.

Read on:

How AI Can Make Sense of the Real World

As we head toward 2025, we're looking forward to continuing to push the boundaries of what's possible with Physical AI. We are thankful to everyone who supported us on our journey this year, shared excitement, advice, and insights. We thank you all! From all of us at Archetype AI, we wish you a great holiday season and a fantastic new year filled with discovery!

Recommended posts

Last week, we made waves at TEDAI San Francisco — on Day 1, we premiered our feature video,  "A Phenomenological AI Foundation Model for Physical Signals” and on Day 2, our co-founder, CEO, and CTO, Ivan Poupyrev, took the stage for a panel discussion on the future of embodied AI.

October 30, 2024

Humans can instantly connect scattered signals—a child on a bike means school drop-off; breaking glass at night signals trouble. Despite billions of sensors, smart devices haven’t matched this basic human skill.  Archetype AI’s Newton combines simple sensor data with contextual awareness to understand events in the physical world, just like humans do.  Learn how it’s transforming electronics, manufacturing, and automotive experiences.

December 12, 2024

Imagine a world where your car responds not just to what you see but to what every vehicle, traffic light, and smartphone detects. Soarchain is making this a reality by combining their decentralized platform with Archetype AI’s developer API, Newton. Together, we will give drivers and autonomous vehicles a rich real time understanding of what’s happening on the roads around them.

August 13, 2024

Implementing AI in industrial settings comes with significant challenges like ensuring employee safety, estimating productivity, and monitoring hazards—all requiring real-time processing. However, sending sensor data to the cloud for analysis introduces latency and security concerns, driving up costs. The solution? Eliminate the cloud. With Archetype AI’s Newton foundation model, AI can run on local machines using a single off-the-shelf GPU, delivering low latency, high security, and reduced costs in environments like manufacturing, logistics, transportation, and construction.

September 5, 2024

On October 17, 2024, Infineon and Archetype AI introduced the first-ever foundation model capable of understanding real time sensor data. They presented a demo at OktoberTech™ Silicon Valley, Infineon's annual technology forum. Read on to learn more about the event and our approach to building a large behavior model that can reason about events in the physical world.

October 24, 2024

We’re building the first AI foundation model that learns about the physical world directly from sensor data, with the goal of helping humanity understand the complex behavior patterns of the world around us all.

November 1, 2023

The renowned tech journalist Steven Levy featured Archetype AI in an exclusive article on WIRED. In his piece, Levy explores how our advanced AI models serve as a crucial translation layer between humans and complex sensors, enabling seamless interactions with houses, cars, factories, and more.

April 8, 2024

We are excited to share a milestone in our journey toward developing a physical AI foundation model. In a recent paper by the Archetype AI team, "A Phenomenological AI Foundation Model for Physical Signals," we demonstrate how an AI foundation model can effectively encode and predict physical behaviors and processes it has never encountered before, without being explicitly taught underlying physical principles. Read on to explore our key findings.

October 17, 2024

Imagine a world where technology could help us make sense of the world's hidden patterns, understand the root causes of problems, and identify solutions.

At Archetype AI, we believe such a world is possible. We’re unveiling a new form of artificial intelligence that takes us a step closer to this reality.

April 5, 2024

Infineon will be the first company to utilize the Newton AI developer platform, offering device makers a combined package of sensor hardware and sensor AI.

October 24, 2023