Computer vision has become a cornerstone of enterprise innovation, powering applications ranging from medical imaging and autonomous…Continue reading on Medium »
Computer Vision remains one of the most commercially valuable areas in AI. Powering applications from autonomous driving to medical imaging and generative systems. But breaking into the field requires more than just theory! A strong portfolio of practi…
Google DeepMind research team introduced Gemini Robotics-ER 1.6, a significant upgrade to its embodied reasoning model designed to serve as the ‘cognitive brain’ of robots operating in real-world environments. The model specializes in reasoning capabilities critical for robotics, including visual and spatial understanding, task planning, and success detection — acting as the high-level reasoning model […]
The post Google DeepMind Releases Gemini Robotics-ER 1.6: Bringing Enhanced Embodied Reasoning and Instrument Reading to Physical AI appeared first on MarkTechPost.
I still remember the exact moment I hit the wall…What DETR is really doing here is treating object detection as a set prediction problem…Continue reading on Medium »
In this tutorial, we walk through MolmoAct step by step and build a practical understanding of how action-reasoning models can reason in space from visual observations. We set up the environment, load the model, prepare multi-view image inputs, and explore how MolmoAct produces depth-aware reasoning, visual traces, and actionable robot outputs from natural language instructions. […]
The post A Coding Implementation of MolmoAct for Depth-Aware Spatial Reasoning, Visual Trajectory Tracing, and Robotic Action Prediction appeared first on MarkTechPost.
A $50 experiment on a single GPU proved that training data quality isn’t a nice-to-have. It’s the difference between a model that sees and…Continue reading on Medium »
Liquid AI just released LFM2.5-VL-450M, an updated version of its earlier LFM2-VL-450M vision-language model. The new release introduces bounding box prediction, improved instruction following, expanded multilingual understanding, and function calling support — all within a 450M-parameter footprint designed to run directly on edge hardware ranging from embedded AI modules like NVIDIA Jetson Orin, to mini-PC […]
The post Liquid AI Releases LFM2.5-VL-450M: a 450M-Parameter Vision-Language Model with Bounding Box Prediction, Multilingual Support, and Sub-250ms Edge Inference appeared first on MarkTechPost.
Yapay zeka dünyasında bir görseli “görmek” ile “anlamak” arasındaki o devasa köprüyü kuran teknolojiye hoş geldiniz. Eğer telefonunuz…Continue reading on Medium »
In this tutorial, we build and run a complete Pose2Sim pipeline on Colab to understand how markerless 3D kinematics works in practice. We begin with environment setup, configure the project for Colab’s headless runtime, and then walk through calibration, 2D pose estimation, synchronization, person association, triangulation, filtering, marker augmentation, and OpenSim-based kinematics. As we progress, […]
The post A Coding Guide to Markerless 3D Human Kinematics with Pose2Sim, RTMPose, and OpenSim appeared first on MarkTechPost.
RGB was designed for screens, not for human perception. If your fashion AI pipeline uses RGB to compare, cluster or search by color, it’s…Continue reading on Medium »