VisionAgent is the reasoning-driven object detection makes the human-like precision via text prompts without the overhead of custom training, made by Andrew Ng's Landing AI.

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Hi everyone! Super excited to share VisionAgent, featureing Agentic Object Detection from Andrew Ng's company, Landing AI! This is a completely new approach to object detection that's poised to change how we build computer vision applications. Forget labeling data and training custom models. With Agentic Object Detection, you simply describe what you want to detect in natural language, and the AI agent handles the rest. It uses advanced reasoning to understand object attributes, relationships, and even dynamic states. Think about the possibilities: Assembly Verification: "Detect missing capacitors" Agriculture: "Find unripe tomatoes" Workplace Safety: "Identify workers without helmets" Retail: "Locate unoccupied tables" And much more! Landing AI's internal benchmarks show it significantly outperforming traditional object detection systems. It's currently available via API, and processing takes 20-30 seconds per image (they're working on speed improvements!) You could try this demo.

The real-world use cases you mentioned, like assembly verification and workplace safety, highlight just how versatile this could be. Plus, with performance improvements on the horizon, this could redefine the speed and scalability of computer vision applications.

I’m excited to see how this technology evolves, using natural language for AI-driven tasks opens up endless possibilities for a wide range of industries!

Congrats on the launch and sending wins to the team :)

Unblocked AI Code Review — High-signal comments based on your team's context

High-signal comments based on your team's context

I’m excited to see how this technology evolves, using natural language for AI-driven tasks opens up endless possibilities for a wide range of industries!

Congrats on the launch and sending wins to the team :)

VisionAgent

Reasoning-Driven Agentic Object Detection

Reasoning-Driven Agentic Object Detection