To improve efficiency, Perceptron separated reasoning from world knowledge by integrating external tool calls, such as search and reverse image search. The system can also spawn parallel sub-agents to decompose complex tasks, such as identifying specific food items in a basket to check for allergies. This release is the first step in the company's plan to build agentic foundation models for real-time physical world applications.
Tuesday, October 20, 2026
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Perceptron’s Mk1.5 Model Beats Egocentric AI at 25x Lower Cost
AI25 days ago
A new intelligence layer for robots launched by Perceptron allows for the zero-shot control of quadrupeds and drones without requiring retraining for specific platforms. The model, known as Mk1.5, reduces latency by 2x to 5x compared to its predecessor and establishes a new state of the art in egocentric understanding, outperforming competing models at 25x lower cost. It incorporates audio as a primary modality, enabling capabilities such as predicting an object's proximity using the Doppler effect.
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