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Gadget Flow
thegadgetflow.com > blog > neura-robotics-physical-ai-is-heading-to-ifa-2026-and-i-have-one-demo-request-for-the-4ne1

NEURA Robotics Physical AI is heading to IFA 2026, and I have one demo request for the 4NE1

1+ hour, 58+ min ago   (258+ words) NEURA Robotics Physical AI hits IFA Berlin on NVIDIA and Amazon money, though the shoelace problem nobody has solved still worries me a lot....

PhotoViewer Online – View
photoviewer.online > 2026 > 09 > canva-photo-enhancer-tool-improve-image.html

Canva Photo Enhancer Tool: How to Improve Image Quality Easily

7+ hour, 8+ min ago   (103+ words) t.co Enhancing a picture in Canva is relatively straightforward. Visit Canva and create a new design or open an existing project. You can choose a template based on the type of content you are creating, such as an Instagram post,…...

Coursera
coursera.org > articles > business-intelligence-engineer

Business Intelligence Engineer: 2026 Career + Salary Guide

6+ day, 19+ hour ago   (951+ words) Labor Day starts with $70+ in savings on Coursera Plus. Save 40% for 3 months. A business intelligence (BI) engineer manages the processes and systems within a company for data collection and analysis. Some of the things a business intelligence engineer does include…...

AOL.com
aol.com > articles > zeroth-launches-bridge-world-first-105200000.html

Zeroth Launches Bridge, the World’s First AI-Native Embodied Robot, and OpenBridge Open-Source Ecosystem - AOL

12+ hour ago   (698+ words) Zeroth today launched Bridge, the world’s first AI-native embodied robot, alongside OpenBridge, a fully open-source ecosystem for embodied intelligence. The first batch of the Bridge Geek Edition is now available for purchase, while Zeroth has also launched the Bridge Builder…...

DEV Community
dev.to > vmodal_ai > building-synthetic-training-data-pipelines-for-robotics-542n

Building Synthetic Training Data Pipelines for Robotics

30+ min ago   (223+ words) Synthetic data pipelines are most valuable for: It's not a full replacement for real data — visual and dynamics gaps mean synthetic-only training rarely matches real-data performance for the hardest tasks — but as a large, cheap, well-labeled complement to a smaller…...

DEV Community
dev.to > vmodal_ai > using-vr-controllers-for-robot-teleoperation-54gh

Using VR Controllers for Robot Teleoperation

31+ min ago   (230+ words) Compared to a gamepad or keyboard, a VR controller gives you: If you're using Unity or Unreal for the VR side and streaming to a Python robot controller, this same pose data typically gets sent over a lightweight transport like…...

DEV Community
dev.to > vmodal_ai > building-an-imitation-learning-pipeline-for-robotic-manipulation-3fmm

Building an Imitation Learning Pipeline for Robotic Manipulation

31+ min ago   (290+ words) With a validated demonstration dataset in hand, the next step is building the actual training pipeline: turning (observation, action) pairs into a policy that can control the robot on its own. This tutorial covers the end-to-end pipeline — data loading, model…...

DEV Community
dev.to > vmodal_ai > integrating-perception-planning-and-control-in-autonomous-robots-28e6

Integrating Perception, Planning, and Control in Autonomous Robots

31+ min ago   (301+ words) Autonomous robots need to continuously answer three questions: These systems become powerful when integrated into a closed feedback loop. Planning should not consume isolated detections. It needs a coherent state. The state estimator should continuously update the robot's belief about…...

DEV Community
dev.to > vmodal_ai > building-and-testing-robot-policies-with-mujoco-1jaj

Building and Testing Robot Policies with MuJoCo

30+ min ago   (365+ words) Compared to more visually-oriented simulators like Isaac Sim, MuJoCo optimizes for: The modern mujoco Python package bundles the simulator itself — no separate license or binary download is required, unlike older MuJoCo versions. Verify the install: A minimal MJCF file describing…...

DEV Community
dev.to > vmodal_ai > domain-randomization-for-robust-robot-learning-396b

Domain Randomization for Robust Robot Learning

30+ min ago   (276+ words) A practical starting point is randomizing by a percentage range (e.g., ±20–30%) around your best system-identified estimate, rather than guessing an absolute range — this keeps the distribution centered on plausible reality instead of centered on an arbitrary default. For vision-based policies, visual…...