# SpatioTemporal


## Posts

- [Building the infrastructure for trusted robotics: The Robot Benchmark and The Robot Range](https://spatiotemporal.ai/news/building-the-infrastructure-for-trusted-robotics-the-robot-benchmark-and-the-robot-range/): SpatioTemporal is proud to be a Founding Partner of two new initiatives designed to help solve one of the biggest problems facing robotics and Physical AI: proving what robots can actually do in the real world.
- [The Robot Brain Is Splitting by Time](https://spatiotemporal.ai/research/the-robot-brain-is-splitting-by-time/): Léo Morillon, who writes about the emerging robotics stack, described a robot brain being divided by latency: “Rent the plan, not the reflex.” The premise is straightforward. Some parts of a robot’s intelligence can move to the cloud. Others physically cannot.
- [SpatioTemporal Named Runner-Up in Propel-AIR 2.0](https://spatiotemporal.ai/news/spatiotemporal-named-runner-up-in-propel-air-2-0/): SpatioTemporal was named runner-up in Propel-AIR 2.0, Australia’s AI and robotics commercialisation program led by ARM Hub and designed to help Australian technology companies build pathways into international markets.
- [THANK YOU FOR YOUR ATTENTION](https://spatiotemporal.ai/research/thank-you-for-your-attention/): Trust, selective cognition and the reflexive intelligence robots need around humans
- [The Ultimate Bottleneck for Robotics: Trust](https://spatiotemporal.ai/research/the-ultimate-bottleneck-for-robotics-trust/): Robots can already see, navigate and plan. So why aren’t they everywhere?
- [State Is All You Need](https://spatiotemporal.ai/research/state-is-all-you-need/): Introducing World State Vectors for Physical AI.
- [SpatioTemporal featured on SME AI's 'ROI from AI' Podcast](https://spatiotemporal.ai/news/spatiotemporal-featured-on-sme-ais-roi-from-ai-podcast/): SpatioTemporal founder Andrew Ballard recently joined Andrew Lai and Amir Nissen from  ⁠SMEC AI for a conversation about Motion Intelligence, foundation models and a different approach to building AI for the physical world.
- [The Data Wire: Physical AI Needs Better Signals, Not Bigger Data Pipelines](https://spatiotemporal.ai/news/the-data-wire-physical-ai-needs-better-signals-not-bigger-data-pipelines/): SpatioTemporal founder Andrew Ballard has been interviewed by The Data Wire for a feature exploring a growing challenge for Physical AI: how to extract the signals that matter without carrying the enormous computational burden of continuous video.
- [Melbourne’s 'Let's Get Physical AI' Meetup Brought the Emerging Ecosystem Together](https://spatiotemporal.ai/news/melbournes-lets-get-physical-ai-meetup-brought-the-emerging-ecosystem-together/): Melbourne’s inaugural Physical AI Meetup brought together researchers, engineers, founders, operators and technologists at Natural Velocity in Docklands for an evening focused on what comes after the current generation of AI.
- [Robots that read the room.](https://spatiotemporal.ai/research/robots-that-read-the-room/): A controlled experiment using NVIDIA Cosmos suggests that explicit behavioural state can materially change how a robot acts around people. In a controlled crossing experiment using NVIDIA Cosmos-Reason2-8B, the proportion of encounters entering a defined collision envelope fell from 24% to 2% when Motion Intelligence-derived behavioural information was available to the planner.
- [Motion Intelligence announced at the Melbourne Foundational Models Meetup](https://spatiotemporal.ai/news/motion-intelligence-announced-at-the-melbourne-foundational-models-meetup/): Humans are remarkably good at not walking into each other. We rarely think about it, but every busy footpath, station and pedestrian crossing is a continuous exercise in prediction.

## Pages

- [Motion Lab](https://spatiotemporal.ai/motion-lab/)
- [](https://spatiotemporal.ai/about/): SpatioTemporal [Adjective] Relating to both space and time. SpatioTemporal is an Australian research company building foundation models for Physical AI. Founded in Melbourne, we develop compact foundation models and operating systems for robotics – with research spanning motion, intent, human-robot interactions and consequence modelling. Our first foundation model, LSTM-01, established Motion Intelligence as the first Large SpatioTemporal Model. We are now expanding the technical programme through simulation, benchmarking, multi-agent research and collaboration with robotics and Physical AI partners. Physical AI is moving from controlled environments into a world shaped by people. Machines can increasingly perceive that world and plan actions within it. […]
- [Motion Tokens](https://spatiotemporal.ai/motion-tokens/)
- [Motion Intelligence](https://spatiotemporal.ai/motion-intelligence/): Movement reveals intent. Before someone crosses a road, they shift their weight.Before a cyclist turns, their trajectory begins to change.Before two people collide, their movements begin to converge. Movement contains information about what is happening now, what may happen next, and how others should respond. Motion Intelligence is the ability to read that information. Seeing is not understanding. Modern perception systems are remarkably good at identifying what surrounds a machine. A person. A bicycle. A vehicle. A doorway. Planning systems can then determine a path or action. But real environments are dynamic. The important question is often not simply what is there, […]
- [](https://spatiotemporal.ai/): Robots can see. Robots can plan.But can they read the room? SpatioTemporal is building the trust layer for Physical AI, starting with Motion Intelligence – a foundation model that understands movement and intent. Movement is a language all humans understand.We call it Motion Intelligence. Movement carries information: a pedestrian hesitates. A cyclist begins to turn. A vehicle drifts towards a lane. Long before an action is complete, motion reveals our intent, and our intent colours what may happen next. SpatioTemporal models these patterns directly, giving machines another source of intelligence for understanding the dynamic world around them. Explore Motion Intelligence → […]

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