Caterpillar is collaborating with FieldAI to advance physical AI, autonomy and robotics, with one of the early applications for this partnership including autonomous inspections to improve safety and operational visibility l @CaterpillarInc @fieldai_

The @CaterpillarInc x @fieldai_ announcement establishes the technical direction, while future contracts and customer deployments will determine its financial importance. #ArtificialIntelligence# #Caterpillar# #Robotics# #PhysicalAI# #IndustrialTechnology#

Big news and another major step in scaling physical AI and the future of heavy industry: today, FieldAI is announcing its strategic collaboration with @Caterpillarinc, backed by a major commercial agreement. FieldAI is bringing its general-purpose robots together with Caterpillar’s industry expertise and operational data to accelerate the deployment of physical AI, autonomy, and robotics across industrial operations. Caterpillar selected FieldAI following extensive real-world validation of FieldAI’s ability to deploy robots across Caterpillar’s complex, dynamic jobsites. FieldAI’s general-purpose, robot-agnostic Field Foundation Models™ (FFM) are built for exactly these conditions, enabling robots to turn real-time observations from jobsites and industrial environments into actionable intelligence that can improve safety, productivity, and operational efficiency at scale. Caterpillar has spent more than a century shaping how work gets done across jobsites and manufacturing environments. With a growing global footprint of FieldAI deployments across three continents, this collaboration creates an exciting opportunity to bring robots and AI-enabled machines to industrial operations at significantly greater scale and help shape the next century of heavy industry. This collaboration is part of a broader expansion of FieldAI’s commercial deployments across industries, with more to come soon. Read the full announcement:

A FieldAI-powered robot, pictured with Singapore's Minister for Transport Jeffrey Siow at @SMRT_Singapore's Gali Batu Bus Depot. It patrols autonomously with infrared sensing, checking buses and EV charging bays for abnormal heat so the safety team gets an early warning instead of an incident. Congratulations to SMRT on the launch of their new Mobility Command and Control Centre.

The value in physical comes from being able to deploy it across different bodies and environments. It's making models so good, that edge cases become second nature. @fieldai_ handed a full passenger vehicle to a customer, gave it a waypoint dozens of miles out in the vehicle's own coordinates, then removed its maps and its GPS. Every decision the vehicle made came from FIeld's Foundation Models. Shayegan Omidshafiei, President and Chief Scientist at FieldAI, on stage at AUTONOMOUS.👇

Building robots for the toughest environments is no easy task. 🤖 @fieldai_ CEO Ali Agha explains why safety, simulation, and AI are essential for deploying robotics in dynamic, safety-critical settings. 👇

(5/6) More mobility creates a harder autonomy problem. More environments. More edge cases. More unpredictability. That's why we're expanding our ongoing collaboration with @fieldai_ as r-dog moves toward production. Field Foundation Models will serve as its autonomy brain.

Shayegan Omidshafiei, FieldAI President and Chief Scientist, gave the keynote “Autonomy in the Wild” at @autonomousevent The Future of Robotics & Physical AI in San Francisco. The premise: what does it take for a robot to arrive at a site it has never seen, with no prior map, no GPS, and no site-specific training—and get to work? FieldAI robots do exactly that across hundreds of deployments in construction, energy, and other complex industrial environments, where conditions are constantly changing and robots must operate safely around people, equipment, and incomplete information. Full keynote linked here:

@fieldai_ has developed its own model architectures in-house, labelled Field Foundation Models (FFMs). Designed, like many models, for better physical generalisation but also better at reducing the level of hallucination seen across other chosen architectures. It's the models they use to make robots better equipped for a variety of terrains.

At Automate in Chicago, FieldAI CEO Ali Agha joined @bheater for a special live episode of The Automated Podcast at the Humanoid Robot Forum. They discussed why robotics requires models purpose-built for the physical world, rather than shoehorning large language models into robotics. FieldAI’s Field Foundation Models combine data-driven learning with physics-based reasoning and uncertainty awareness, enabling one AI brain to operate across robots, tasks, and environments without prior maps, GPS, or predefined routes. FieldAI already powers robots across three continents, from construction and industrial to critical infrastructure inspection and beyond, with each new workflow expanding the value of robots already in the field. Watch the full podcast here:

No map. No GPS. No human control. Ali Agha and his team deployed legged robots several kilometers into Mars-analog caves, marking what he describes as the first deployment of its kind in human history. Hear the full story at #Robotics# #SpaceTech#

At MACHINA 2026 in Paris, FieldAI CEO Ali Agha took the stage to discuss what it took to move Physical AI beyond controlled demonstrations and into real-world deployment. In safety-critical environments, intelligence cannot rely on pattern recognition and data scale alone. Language models can hallucinate with limited real-world consequence. In robotics, a hallucination can become an unsafe action around people, heavy machinery, or critical infrastructure, where even a single error can cause physical harm or operational disruption. Ali shared how FieldAI’s architecture-first approach combines data-driven learning with physics-based reasoning, uncertainty awareness, and risk-aware decision-making. The result is robot intelligence designed to operate safely and reliably in unpredictable environments, across different robots, tasks, and industries. Deployment over demos means building for the conditions robots actually face in the field. Watch the full keynote here:

Join us at the 2026 Intermodal Expo in Long Beach, September 14–16. Visit FieldAI at Booth #1729 to# learn how autonomous robots can support inspection, monitoring, site intelligence, and other critical operations across complex intermodal environments.

We've had a pretty good secret for a while now. Lionel Messi and Play Time Ventures are investors in FieldAI! He masters the pitch; we build the universal AI "brain" that lets general-purpose robots operate in the world's most complex, unstructured terrain. Best of luck to Leo & Argentina in the FIFA World Cup Final this Sunday! 🇦🇷🏆 🔗 #FieldAI# #PlayTimeVentures# #EmbodiedAI# #WorldCup#

Keynote Announcement🎙️ Autonomy in the Wild. A keynote feature from Shayegan Omidshafiei of @fieldai_. 🗓️ San Francisco, July 16th 📌 The Midway 🎟️ Field AI builds Field Foundation Models, an embodiment-agnostic autonomy brain that runs on almost any robot body and operates in unstructured, GPS-denied places with no prior map. This keynote closes the day on the Frontier Stage. A behemoth in its own right with roughly $400m from backers, including Bezos Expeditions and Khosla Ventures, who will also be at #AUTONOMOUS2026#.

🤖 @Innovo_Group is partnering with California-based @fieldai_ to deploy AI-powered robots across UAE construction sites — the first of its kind in the region. The robots use real-time progress monitoring, environment mapping and data collection.

FieldAI is partnering with @MCLGroupPLC to deploy robots at scale across UK construction sites. As one of the UK’s leading contractors with work across commercial, residential, logistics, data centers, healthcare, education, and public-sector projects, McLaren is a strong partner for bringing Physical AI into one of the world’s most demanding construction markets. The deployment begins with 360° site imagery, point cloud generation, progress verification, model-to-site deviation analysis, safety compliance patrols, and quality assurance. Read More:

Just in: @fieldai_ surpasses $100 million in revenue and customer contracts, less than three years since founding. Its general-purpose robotic intelligence is now being deployed by more than 30 customers across Europe, Asia, and North America, operating across construction, mining, energy, data centers, and more.