Researchers have developed a high-density, ultra-flexible electrode array that maintains signal integrity for over 550 days by minimizing mechanical friction with neural tissue.
The co-author of the Transformer architecture moves to OpenAI after a brief tenure at Google, signaling a shift in the development of efficient large language models.
Researchers in Sweden have developed a machine-learning framework that integrates electromagnetic laws to speed up the design of optical components.
The ATLAS navigation system utilizes synthetic data and probabilistic filtering to enable uncrewed ground vehicles to operate in contested environments without satellite signals.
A new diagnostic metric provides real-time monitoring of vision-language models by quantifying the grounding of generated text in visual inputs.
The automaker is cutting its development timeline to 36 months by integrating machine learning and virtual testing into its engineering pipeline.
Researchers have adapted computer vision techniques to solve the challenge of missing hydrogen atoms in crystal lattices with high accuracy.
A new machine learning framework utilizes the Mori-Zwanzig formalism to model chaotic particle trajectories in turbulent flows, overcoming traditional computational barriers.
A new edge-computing system utilizes high-performance neural processing to monitor wildfire risks directly at the grid level.
The coffee giant has ended its nine-month pilot of an automated inventory system, citing significant technical limitations in real-world retail environments.
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