New AI tool predicts airport traffic to avert devastating collisions

In managing airport traffic, small errors can cause catastrophe. A group from the CMU Robotics Institute’s AirLab used the Pittsburgh Supercomputing Center’s Bridges-2 supercomputer to create World2Rules, an AI that draws from airport data and historical crash reports to help human controllers spot collisions before they happen. Their paper is published on the arXiv preprint …

Had to keep it going

Continuing the music video u/optimisoprimeo posted: https://www.reddit.com/r/StableDiffusion/comments/1t64gni/so_far_this_is_my_favorite_usecase_for_ltx/ submitted by /u/hidden2u [link] [comments]

What Matters in Practical Learned Image Compression

One of the major differentiators unlocked by learned codecs relative to their hard-coded traditional counterparts is their ability to be optimized directly to appeal to the human visual system. Despite this potential, a perceptual yet practical image codec is yet to be proposed. In this work, we aim to close this gap. We conduct a …

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Secure short-term GPU capacity for ML workloads with EC2 Capacity Blocks for ML and SageMaker training plans

As companies of various sizes adopt graphic processing units (GPU)-based machine learning (ML) training, fine-tuning and inference workloads, the demand for GPU capacity has outpaced industry-wide supply. This imbalance has made GPUs a scarce resource, creating a challenge for customers who need reliable access to GPU compute resources for their ML workloads. When you encounter …

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Gemini 3.1 Flash-Lite is now generally available on Gemini Enterprise Agent Platform

Today, we’re thrilled to announce that Gemini 3.1 Flash-Lite, our fastest and most cost-efficient Gemini 3 series model yet, is now generally available.  Designed for ultra-low latency, high-volume tasks, and unmatched cost-efficiency, Flash-Lite is already transforming how applications are built at scale. Fast, iterative, and scalable, it joins our comprehensive suite of Pro and Flash …

Inspired by the brain, researchers build smarter and more efficient computer hardware

As traditional computer chips reach their physical limits and artificial intelligence demands more energy than ever, University of Missouri researchers are rethinking how computers work by taking cues from the human brain. The timing is critical. Energy use from AI data centers is projected to double by the end of the decade, raising urgent questions …