Use the vitals package with ellmer to evaluate and compare the accuracy of LLMs, including writing evals to test local models.
Dot Physics on MSN
Learn 3D object modeling and projectile motion with Python lesson 4
Dive into 3D object modeling and projectile motion with Python in Lesson 4! In this tutorial, we guide you step by step through creating 3D visualizations and simulating projectile motion using Python ...
New benchmark shows top LLMs achieve only 29% pass rate on OpenTelemetry instrumentation, exposing the gap between ...
Discover the best AI content detectors in 2026. Compare Winston AI, GPTZero, Originality.AI, and more for accuracy, trust, ...
Abstract: Modern diffusion-based image generative models have made significant progress and become promising to enrich training data for the object detection task. However, the generation quality and ...
At CES 2026, Nvidia launched Alpamayo, a new family of open source AI models, simulation tools, and datasets for training physical robots and vehicles that are designed to help autonomous vehicles ...
Astronomers have detected a massive object moving in a synchronized path behind Earth. Early measurements suggest it has been trailing the planet longer than previously assumed. Its trajectory does ...
Meta Platforms Inc. today is expanding its suite of open-source Segment Anything computer vision models with the release of SAM 3 and SAM 3D, introducing enhanced object recognition and ...
We’re introducing SAM 3 and SAM 3D, the newest additions to our Segment Anything Collection, which advance AI understanding of the visual world. SAM 3 enables detection and tracking of objects in ...
This project showcases a sophisticated pipeline for object detection and segmentation using a Vision-Language Model (VLM) and the Segment Anything Model 2 (SAM2). The core idea is to leverage the ...
Abstract: Small object detection is a significant and challenging research area in aerospace. Small objects often face issues like background interference and inter-class similarity due to their small ...
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