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Unsloth has emerged as a game-changer in the world of large language model (LLM) fine-tuning, addressing what has long been a resource-intensive and technically complex challenge. Adapting models like LLaMA,
Iterative Closest Point (ICP) is a widely used classical computer vision algorithm for 2D or 3D point cloud registration. As the name suggests it iteratively improves and minimizes the spatial
MedSAM2 brings “segment anything” power to healthcare, carving organs, tumours, and even moving heart chambers from CT, MRI, PET, and live ultrasound with a single prompt. Running in < 1
In Deep Learning, Batch Normalization (BatchNorm) and Dropout, as Regularizers, are two powerful techniques used to optimize model performance, prevent overfitting, and speed up convergence. While both have their individual
The field of computer vision is fueled by the remarkable progress in self-supervised learning. At the forefront of this revolution is DINOv2, a cutting-edge self-supervised vision transformer developed by Meta
As artificial intelligence continues to advance, Embedding Models have become fundamental to how machines interpret and interact with unstructured data. By translating inputs like text, images, audio, and video into
MASt3R-SLAM is a truly plug and play monocular dense SLAM pipeline that operates in-the-wild. It is first of its kind real-time SLAM system that leverages MASt3R’s 3D Reconstruction priors to
As AI systems become more specialized, getting them to work together without endless glue code is the next big challenge. That’s where Google’s A2A Protocol (Agent-to-Agent) steps in—a standardized messaging
The world of generative AI moves at a lightning speed, constantly pushing the boundaries of what is possible. In the vibrant field of text-to-image synthesis, generating stunningly detailed, high-resolution images
Object detection has come a long way, especially with the rise of transformer-based models. RF-DETR, developed by Roboflow, is one such model that offers both speed and accuracy. Using Roboflow’s
Qwen2.5-Omni is a groundbreaking end-to-end multimodal foundation model developed by Alibaba Qwen Group. In a unified and streaming manner, it’s designed to perceive and generate across multiple modalities – including
The advent of Generative AI, has fundamentally transformed robotic intelligence, enabling significant strides in how advanced humanoid robots “perceive, reason and act” in the physical world. This huge progress is
