Matt Gilbert, AI and data director at Synapse, discusses the state and future of physical AI with Jonas on Tech First.
Gilbert says cheaper components are making physical AI deployments more practical. He cites LiDAR falling from about $75,000 ten years ago to below $1,000, while battery pack costs have declined roughly 85% over the same period.
Gilbert points to manufacturing and logistics as early areas where robotics has moved from pilots into broader use. He says Amazon reports more than a million facility robots and a 25% efficiency gain. Other examples include Gecko Robotics inspecting boilers and pipelines, and Ford using exoskeletons to reduce strain on workers.
Gilbert describes physical AI as a combination of hardware, software, sensors, and ongoing updates. He uses Tesla as an example of a fleet that gathers data, improves its AI, and receives software updates over the air. For processing, he expects a hybrid approach: fast, local decisions at the edge, with longer-running tasks handled in the cloud.
Gilbert describes Boston Dynamics as focused on agility, Figure AI on production scale and factory use, and Tesla on applying its AI capabilities to Optimus. He says the home remains especially difficult because its layout and obstacles change constantly; broad household autonomy may still be five to ten years away.
Gilbert says simulation and digital twins let robotics teams train systems through many scenarios before real-world deployment. He and Jonas stress layered safeguards, since a mistaken physical action can cause injury, and note that connected machines also create cybersecurity risks. Gilbert expects more service robots in places such as airports and restaurants, with consumer home uses arriving later.
Briefs summarise talks and interviews; timestamps open the video at that moment. Claims in a talk are the speaker's own.
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