1587 Use Cases

See How People Use AI at Work

Real examples of how people are using AI — not hype, not marketing fluff

🧠 Curated discussions from researchers, builders, and domain experts
🎯 Focused on how people use AI to get work done
🗂️ Organized by industry, job, and capability
🌱 Updated daily at the edge of what’s next

Use case "Train Robotic Tasks Using..." and related

5 use cases

🔌 Electronics & Hardware

Train Robotic Tasks Using Human-in-the-Loop Learning

Sources: 🐦 Tweet by @ClementDelangue 🐦 Tweet by @AdilZtn 🌐 huggingface.co +3 more

Helps: Robotics Engineers Robotics Techs Software Developers +2 more

AI Features: Image Generation Personal Planning +1 more

1 week ago

🔌 Electronics & Hardware

Enhance Smart Glasses For Hands-Free Communication and Navigation

Sources: 🐦 Tweet by @SpirosMargaris 🌐 www.pymnts.com

Helps: Software Engineers Data Scientists Systems Engineers +2 more

AI Features: Question Answering Language Translation +2 more

4 weeks ago

🔌 Electronics & Hardware

Build Advanced Robotic Projects with 16-DoF Robotic Arm

Sources: 🐦 Tweet by @ClementDelangue 🐦 Tweet by @AlokkJain

Helps: Robotics Engineers EM Technicians Bioinformatics Specialists

AI Features: Tool-use & Integration Agentic Reasoning

1 week ago

🔌 Electronics & Hardware

Generate Pose-Controllable Grasps From Point Cloud Data

Sources: 🐦 Tweet by @Scobleizer 🐦 Tweet by @salimazak 🌐 nus-lins-lab.github.io

Helps: Data Scientists Ops Research Analysts Systems Engineers +2 more

AI Features: Mathematical Reasoning Image Generation +2 more

3 weeks ago

🔌 Electronics & Hardware

Prototype and Program Robotics Kits with Hugging Face AI

Sources: 🐦 Tweet by @ClementDelangue 🐦 Tweet by @burhansebin 🌐 lu.ma

Helps: Robotics Engineers Robotics Techs EM Techs +1 more

AI Features: Question Answering Tool-use & Integration

3 weeks ago

🔌 Electronics & Hardware

Train Robotic Tasks Using Human-in-the-Loop Learning

Robotics engineers use a human-in-the-loop reinforcement learning system (HIL-SERL by Hugging Face) to train robot policies, achieving faster training times and near-perfect success rates for tasks like precision assembly and bimanual coordination. The system combines human interventions, demonstrations, and a distributed actor-learner architecture to improve sample efficiency.

Helps: Robotics Engineers Robotics Techs Software Developers Data Analysts Data Architects

AI Features: Image Generation Personal Planning Agentic Reasoning

Jun 13, 2025