
Carnegie Mellon advances autonomous metallurgy with self-driving lab
The Materials Innovation Cloud Lab integrates agentic AI and robotics to accelerate alloy discovery for aerospace and industrial applications.

The Materials Innovation Cloud Lab integrates agentic AI and robotics to accelerate alloy discovery for aerospace and industrial applications.

The new toolkit enables high-fidelity synthetic data generation for surgical robotics, addressing critical data gaps in clinical AI training.

The new Touch Surgery Aide platform integrates NVIDIA hardware to enable low-latency computer vision applications within the operating room.

The company is integrating heavy foundation models as a semantic safety net to help delivery robots interpret complex, high-stakes urban environments.

A new architectural framework enables mobile robots to store and retrieve semantic information about their environment using natural language queries.

A new robotic system utilizes deep reinforcement learning and tactile sensing to automate the delicate task of slicing and serving salmon.

The ATLAS navigation system utilizes synthetic data and probabilistic filtering to enable uncrewed ground vehicles to operate in contested environments without satellite signals.
Concordia University researchers utilized generative AI synthetic data to train a deep reinforcement learning agent capable of executing complex cardiac imaging without manual guidance.

Boston Dynamics’ Spot robot, powered by Google DeepMind’s Gemini AI, makes a pivotal leap, moving beyond data collection to truly autonomous interpretation and intelligent decision-making in complex industrial environments.
Applied machine learning, filed daily.
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